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This thesis is composed of my original work, and contains no material previously published or written

by another person except where due reference has been made in the text. I have clearly stated the

contribution by others to jointly-authored works that I have included in my thesis.

I have clearly stated the contribution of others to my thesis as a whole, including statistical assistance,

survey design, data analysis, significant technical procedures, professional editorial advice, and any

other original research work used or reported in my thesis. The content of my thesis is the result of

work I have carried out since the commencement of my research higher degree candidature and does

not include a substantial part of work that has been submitted to qualify for the award of any other

degree or diploma in any university or other tertiary institution. I have clearly stated which parts of

my thesis, if any, have been submitted to qualify for another award.

I acknowledge that an electronic copy of my thesis must be lodged with the University Library and,

subject to the General Award Rules of The University of Queensland, immediately made available for

research and study in accordance with the Copyright Act 1968.

I acknowledge that copyright of all material contained in my thesis resides with the copyright

holder(s) of that material.

?).)"4"&)(,-(@,&)0$<*)$,&#(),(A,$&)%=(B*)>,0"+(C,0:#(@,&).$&"+($&()>"(D>"#$#(

No jointly-authored works.

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Kenneth R. N. Anthony, Ove Hoegh-Guldberg, contributed to the development of concepts and

discussion of ideas and provided comment on written material for all chapters. In Chapter 3, Kenneth

R.N. Anthony contributed to assisting with the ecological modelling methods, technical advice on

programming code, and graphical analysis using MATLAB. In the same chapter, Jeffrey A. Maynard

contributed the sampling design of reef benthic community assessments. In Chapter 4, Joshua Cinner

provided advices on questionnaire design. In the same chapter, Nadine Marshall provided assistance

in the interpretation of social survey results and providing comments on written material. However, in

all chapters significant part of the analysis and interpretation of results was provided by myself.

?).)"4"&)(,-(9.0)#(,-()>"(D>"#$#(?*<4$))"+(),(F*.%$-=(-,0()>"(B7.0+(,-(B&,)>"0(;"30""(

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Maynard, JA, Anthony, KRN, Afatta, S, Anggraini, LF, Haryanti, D & Ambariyanto 2008, 'Rock

anchoring in Karimun Jawa, Indonesia: Ecological impacts and management implications ', Pacific

Conservation Biology, vol. 14, p. 2.

Maynard, J, Anthony, K, Afatta, S, Dahl-Tacconi, N & Hoegh-Guldberg, O 2010, 'Making a Model

Meaningful to Coral Reef Managers in a Developing Nation: a Case Study of Overfishing and Rock

Anchoring in Indonesia', Conservation Biology, vol. 24, no. 5, p. 11.

B':&,7%"+3"4"&)#(

First, it is a pleasure to thank the many people who made this research and thesis possible.

I would like to express my gratitude to my two supervisors: Prof. Ove Hoegh-Guldberg and

Dr. Ken Anthony for their guidance, support, and encouragement during the course of my research.

This research would not be impossible without their patience and positive attitude, for giving me the

opportunity to have a tremendous share of their immense knowledge and experience. I would also like

to thank Prof. Ambariyanto for his assistance and advices for making the collaborative nature of the

research project possible.

I am also indebted to the Karimunjawa project team members: Dwi Haryanti, Lely F.

Anggraini, Jeffery A. Maynard, Adhitya K. Wardana, Achmad Mustofa, Dewi Sri and Arif F.

Setyawan, for their continuous support and contribution throughout numerous discussions and field

work tasks in Indonesia and Australia.

My sincere thanks also go to the inspiring people of Karimunjawa islands, of thousands whom

I cannot mention them all, for their hospitality and helpfulness throughout many visits I have made to

the islands particularly those who have assisted the team in the marine surveys and participants of the

social survey.

I am also grateful to all researchers and staffs at the Centre for Marine Studies and Global

Change Institute for the knowledge and support they have shared to me, for having the chance of

working within an exceptionally dynamic and fun group of international researchers.

I wish to thank to the support of institutions: the Australian Agency for International

Development for giving me full-time scholarship for my postgraduate research, the David and Lucille

Packard Foundation for financially supporting my research, the Diponegoro University for their

cooperation and providing institutional working platform, and staffs at Karimunjawa National Park

Agency: Bapak M.G. Nababan, Bapak Sutris Haryanta, Bapak Mualim, Ibu Puji Prihatiningsih and

others; for their collaborative support to the research project.

Special thanks to my parents: Betty and Kemal Taruc, my siblings: Ipang and Wawa, for their

unconditional support through all my walks of life. Finally, another special thanks also to my wife,

Shofi, for her outstanding moral support and love; for putting up with me disappearing into the study

and especially during the final stages of the study during which our beautiful daughter Zia was born.

To them I dedicate this thesis.

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The global impact of climate change is threatening the resilience of coral reef ecosystems; yet,

human-associated local scale disturbances are still driving the decline of reefs around the world.

Tropical reefs are largely located in less-developing regions such as Indonesia that is within the center

for coral biodiversity known as the Coral Triangle region. Coastal and islands communities of

Indonesia are characteristically dependent to reef resources in terms of their livelihood, which

requires local managers to be capable of identifying key information of the response of reef

ecosystems to local disturbances and the subsequent impact on the livelihoods of the associated

people. As local reef stressors is yet linked to the livelihood regime, managing reef also means

finding socially adaptable solutions to reduce key social drivers that are giving potentially negative

feedbacks to the ecosystem.

The aim of this thesis was to incorporate the concept of social and ecological resilience in

developing tools and providing options for marine protected area management in Karimunjawa

islands. Karimunjawa National Park (KNP) was used as a study site to represent a conservation area

where natural resources are subject to intense utilization and extractive human activities. Outcomes of

this research were to address critical science gaps relevant to management resource imitations in KNP

that has resulted in the inattention to the key local reef issues and critical indicators of socioeconomic

vulnerability. Firstly, this research used ecological modelling as an approach to facilitate exploration

in habitat response to scenarios of local disturbance, as local reef ecosystem data are low and sparse,

along with limited resource to conduct rigorous biophysical measurements. Secondly, I used social

assessments in the local community to evaluate relative resilience of resource user in terms of the

social consequence of both future resource change and different marine reserve policy options.

I used model projections to explore response of benthic reef habitat to various intensities and

combination of local disturbances at a decadal basis. I found that gradual reduction of grazer reef fish

and stochastic but frequent events of rock anchoring could potentially diminish recoverability of the

majority of disrupted reef sites. Simulation results suggested that reef sites in ‘good’ category would

benefit from priority of management investment in protection, given by their low sensitivity for any

possibilities of grazing reduction in 30-year timeframe. On the other hand, the recoverability of

‘moderate’ to ‘poor’ reefs that were more sensitive to grazing loss, can be maintained of improved if

the exploitation and management herbivorous reef species is not adequately addressed in the long-

term. Despite the relatively patchy and stochastic impact of anchoring, the impact can potentially

decelerate the recovery of reef site, regardless of any categories within a shorter 10-year timeframe

simulated, This result suggested that immediate efforts is needed to stop or reduce local anchoring

methods that are damaging to coral reef. In overall, the model study suggests that local management

efforts to control herbivorous reef fish extraction and minimize anchor damage associated with

fishing are vital to facilitate regeneration of unprotected reef sites in Karimunjawa National Park.

The vulnerability and adaptation of resource user was also assessed by using indicators such as

capacity to learn, flexibility and adaptation in livelihood and regulation, capacity to organize and

asset. Key social findings showed that alternative livelihood portfolio is an essential development

aspect of the local community to allow suspension or withdrawal extractive activities and

establishment local conservation ethic. In regard of compliance to regulation, investing in

communication may bring more benefit than improving resources for surveillance as this could

indirectly result in reducing costs in enforcement by bridging collective action in resource

management. Livelihood diversification strategy was a dominant choice for individuals to adapt to

both current and future depletion of marine resources, both current and future. In response to resource

change, facilitation by an external institution may be required to build platforms for community

interaction to develop adaptive capacity and promote knowledge sharing and decision-making.

Findings of local ecological knowledge suggested that there were a latent demand in the community

to conserve resources, as individuals learned once the resources they depend on are limited or

depleting. Findings of assets suggest that efforts to diversify physical assets that could generate less

natural-resource-dependent occupation are critical parallel with the resource management framework.

In general, this thesis demonstrates that model-based tool can function as adaptable tool for

particular local management situation where scientific units and biophysical data are limited.

Correspondingly, underpinning key characteristic of the resource user can facilitate local managers to

develop community-driven resource management policies and regulation to reduce the apparent

socioeconomic-related social resistance to regulation in KNP.

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socio-ecological resilience, Indonesia, Karimunjawa, developing region, human impacts, ecological

modelling, socio-economic assessment, coral reef management, marine protected area

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050209 Natural Resource Management 40%, 050199 Ecological Applications not elsewhere classified

30%, 160802 Environmental Sociology 30%

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1.1.! Historical relationships between people, the country and the marine resources ...... 1!1.2.! Human threats to reef ecosystems in Indonesia ........................................................ 2!1.3.! Brief on the obstacles in the management of coral reef resources ............................ 4!

1.3.1.! Past influences in politic and governance on coastal resource management ............................................................................................... 4!

1.3.2.! The influence of economy on reef management and coastal livelihoods .. 5!1.3.3.! Obstacles in the management of Marine Protected Areas ......................... 6!

1.4.! Closing remarks ........................................................................................................ 6!@>.G)"0(Q! D>"(&""+(-,0(.(&"7(.GG0,.'>1(R*$%+$&3(#,'$.%(.#(7"%%(.#("',%,3$'.%(0"#$%$"&'"(NNNN(S!

2.1.! The value of the whole: seamless relationships between reef ecosystems and social systems. ......................................................................................................... 8!

2.2.! Local reefs susceptible to future resilience loss: Case study in Karimunjawa National Park. ........................................................................................................ 10!2.2.1! Reef resource, community and management. .......................................... 10 2.2.2! Synergies of Local scale reef stressors .................................................... 13!

2.2.2.1.! Fishing Pressure: Past and Current ............................................ 15!2.2.2.2.! Physical disturbances to coral reefs ........................................... 15

2.2.2.3.! Increasing demand for fish from tourism .................................. 16!2.2.2.4.! Degrading Water Quality .......................................................... 17!

2.3.! Synthesizing social and ecological perspectives in managing reef resources in KNP. ...................................................................................................................... 18!

2.4.! Thesis Aims ............................................................................................................ 19!@>.G)"0(T! 2UG%,0$&3(',0.%(0""-(0"#$%$"&'"($&(5.0$4*&6.7.(8.)$,&.%(9.0:1(?"4$VW*.&)$).)$H"(

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3.1.! Background and Objectives .................................................................................... 20!3.2.! Study Area Biophysical Assessments ..................................................................... 21!

3.2.1! Survey Design and Methodology ............................................................ 21!3.2.2! Preliminary Biophysical Survey Results ................................................. 23!

3.3.! Ecological Modelling Approach and Conceptual Design ...................................... 28!3.4.! Model Parameterization .......................................................................................... 30!3.5.! Sensitivity Analysis: Method and results. .............................................................. 35!

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3.6.! Graphical analysis: Method and results .................................................................. 37!3.7.! Discussion: Model implication for management and end-users. ............................ 43!

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4.1.! Background and Objectives .................................................................................... 48!4.2.! Methodology ........................................................................................................... 49!

4.2.1! Theoretical framework ............................................................................ 49!4.2.2! Survey and analysis method .................................................................... 50!

4.3.! Survey Results and Discussions ............................................................................. 52!4.3.1! Response profile and possibilities of response bias ................................. 52!4.3.2! Livelihood flexibility and adaptation ...................................................... 55!4.3.3! Flexibility and adaptation to resource regulation .................................... 59!4.3.4! Local capacity to learn about changes in the environment ...................... 62!4.3.5! Organizational capacity, experience in decision-making and migration . 69!4.3.6! Household and community assets ............................................................ 73!

4.4.! Conclusions ............................................................................................................. 77!@>.G)"0(Z! !"',44"&+.)$,&#(.&+(',&'%*#$,&#(NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN([\!

5.1.! Thesis conclusions .................................................................................................. 79!5.1.1! General conclusions ................................................................................. 79!5.1.2! Specific conclusions related to the ecological study. .............................. 80!5.1.3! Specific conclusions related to the social study. ..................................... 81!5.1.4! Research implication to the general context of natural resource

management. ............................................................................................ 83!5.2.! Thesis limitation ..................................................................................................... 83!5.3.! Directions of future research .................................................................................. 84!5.4.! Recommendations for reef ecosystem management in KNP ................................. 85!

5.4.5! Evaluations and directions related to ecosystem management ................ 86!5.4.6! Socioeconomic-related evaluation and direction ..................................... 87!5.4.7! Stewarding institutional linkage for integrated resilience management in

Karimunjawa ........................................................................................... 88!!2I2!28@2?(NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNNN(\X!

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M$#)(,-(D.<%"#( Table 3.1. Descriptions of benthic substrate categories visually sampled in each quadrant

transect photo. ......................................................................................................... 23 Table 3.2. Benthic state category settings used for simulation input and output based on a

range of percentage of cover proportion data, part of the biophysical assessment in Karimunjawa in August 2008 (see Figure 3.4, Appendix 2). ............................. 31

Table 3.3. Categories of substratum and the conceptual behaviour applied in the simulation. .............................................................................................................. 31

Table 3.4. Options of initial set of parameter values adjusted from the literature of other selected regions. ...................................................................................................... 33

Table 3.5. Summary of parameter sensitivity assessment showing mean relative abundance output using base value and adjusted values. ......................................................... 36

Table 4.1. Summary of types of information gathered through questions developed from social resilience indicators assessed in the survey research ................................... 52

Table 4.2. Responses to questions related to livelihood flexibility and adaptation to hypothetical decline in reef resource conditions. ................................................... 55

Table 4.3. Response to questions related to perception and adaptation to zoning regulations in Karimunjawa National Park. .............................................................................. 59

Table 4.4. Test of associations between responses of perceived resource conditions (Table 4.3) and the related influential causal factors (Table 4.4.). .................................... 64

Table 4.5. Response to questions about past and future changes of fishery and coral reef conditions. All response categories were based on answers given limited to one (n=209). .................................................................................................................. 64

Table 4.6. Response to questions about the dominant activity that influence changes in fishery and coral reef conditions. ............................................................................ 65

Table 4.7. Degree of association between respondents’ level of formal education (No. 2, Table 4.6) and knowledge of key local reef issues (No. 1.b, Table 4.6) where both variables are treated as ordinals ..................................................................... 69

Table 4.8. Response to questions related to three putative local scale reef related issues and level of education. ................................................................................................... 69

Table 4.9. Reponses to questions related to social capacity to organize including involvement in organization, participation in decision-making, and migration status and intention.. ............................................................................................... 70

Table 4.10. Response distribution related to assets such as style of living based household appliances, housing materials, sanitation and individual assets such as approximate monthly income and age group. ......................................................... 76

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Figure 1.1. The Coral Triangle region consists of 6 countries, which are home to some of the most species rich marine habitats in the world. Photo credit: WWF. ....................... 3

Figure 2.1. A conceptual model of reef habitat state trajectory responding to human disturbances over time. ............................................................................................. 9

Figure 2.2. Diagram depicting the relationship between social and ecological arrangements. 10

Figure 2.3. Map of islands and the coral reef areas within Karimunjawa National Park boundaries. (Figure modified from map courtesy of Karimunjawa National Park Agency, Wildlife Conservation Society). ............................................................... 11

Figure 2.4. Conceptual depiction of identified key reef stressors (red boxes) in Karimunjawa that are influencing reef ecosystem processes. ....................................................... 14

Figure 2.5. Undersized reef fishes caught on Karimunjawan reefs. A: Small Parrotfishes (Scarridae) sold at the street market at Karimunjawa village, B: Young Groupers and Parrotfish caught in a protected zone and served as lunch to tourists, C: Young Rabbitfish (Siganidae) served as regular meals in a homestay (guesthouse) in Karimunjawa. ..................................................................................................... 17

Figure 2.6. Direct disposal (A) and untreated (B) domestic waste polluting coastal waters in Karimunjawa. .......................................................................................................... 17

Figure 3.1. Fourteen reef sites surveyed in Karimunjawa and Kemujan island inshore reefs. . 22 Figure 3.2. Mean fish abundance of herbivorous and predatory reef fish for each size-length

categories in sampling sites during preliminary assessments in Karimunjawa, August 2008 ............................................................................................................ 25

Figure 3.3. Mean percentage cover composition of each benthic category per site based on preliminary biophysical assessments in Karimunjawa, August 2008. ................... 26

Figure 3.4. Selection of photos documenting preliminary key findings taken during the baseline survey in August 2008 .............................................................................. 27

Figure 3.5. Conceptual diagram depicting the layout of the benthic community dynamics model and key stressor functions influencing each community group. .................. 28

Figure 3.6. Conceptual diagram of benthic space occupation by living substrate groups assumed in the model. ............................................................................................. 29

Figure 3.7. P1-A timeline projections of three starting point compositions of reef habitat: Good (10% M, 70% C), Moderate (50% M, 30% C) and Poor (70% M, 10% C). 38

Figure 3.8. P1-B timeline projections of three starting point compositions of reef habitats: Good (10% M, 70% C), Moderate (50% M, 30% C) and Poor (70% M, 10% C). 39

Figure 3.9. P2-A colour plot projection of three reef habitats with starting point compositions of: Good (10% M (X-axis), 70% C (Y-axis)), Moderate (50% M, 30% C) and Poor (60% M, 20% C), each marked with white cross-hairs. ................................. 41

Figure 3.10. P2-B projection result of three reef habitats with starting point compositions of: Good (10% M, 70% C), Moderate (50% M, 30% C) and Poor (60% M, 20% C), each marked with white cross-hairs ........................................................................ 42

Figure 4.1. Map of area surveyed in residential areas of Karimunjawa, Kemujan and Parang villages (in colours). ............................................................................................... 51

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Figure 4.2. Pie diagram showing distribution of respondents’ main occupation (n= 209) grouped by relation to reef resources, both directly (A) and (B) and indirectly (C); as well as those not related to marine resource utilisation (D). .............................. 54

Figure 4.3. Photos showing semi-dry red soil ground characteristic in Parang island (A), allowing much tropical fruit to grow like pomegranates, for example (B,C), whereas seaweed drying was visually more common in Kemujan and Karimunjawa area (D,E,F). ..................................................................................... 57

Figure 4.4. Photos showing logging activities, some conducted by ex-fishing families (A,B), including rock breaking to supply construction material (D). These supplementary income strategies could be found in combination for some households (C,E). ..... 58

Figure 4.5. Photos taken in the Karimunjawa Kota area showing a makeshift garbage dumping site (A), unmanaged garbage (B,C), and collected plastic bottles (D). ... 67

Figure 4.6. Photos showing the typical structure of village roads. Main roads constructed with asphalt layering connect Karimunjawa and Kemujan villages (A), a brick pavement road in Parang village (B), whereas in the sub-village areas mostly soil roads still predominate. ........................................................................................... 74

Figure 4.7. Photo showing a gasoline-based generator used by a household to supply an additional period of electricity, however, this was visually uncommon during the survey. ..................................................................................................................... 75

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The Indonesian archipelago is one of the world’s greatest centres of biodiversity in both

terrestrial and marine ecosystems (Brown 1997; Veron, J 2000). Historically, resource richness in the

region has attracted international trade as early as two centuries BC (Taylor 2004). Trade was one of

the reasons for the establishment of small naval kingdoms in the 7th to 15th century followed with

three centuries of European colonialism. This has brought many cultural influences (e.g. mainly

Indian, Arabic, Chinese, Malay, and European) that shape around 300 ethnic groups nowadays. Due

to its economical as well as political importance, (e.g. sea-ports as a gateway to trade and the centre of

governance), for centuries, the coastal perimeter has been the frontier of both cultural and

demographic expansion in Indonesia (Taylor 2004).

Historical trends in the coastal population growth of Indonesia are largely unknown. Early

demographic records made since the Dutch colonisation (between 16th– 18th century) are scarce and

clustered particularly in the Java region (Gooszen 1999). Initially, demographic census was

intentionally for Dutch labour control in the agriculture, forestry and mineral resource extraction that

took place particularly in western Indonesia (e.g. Java, Sumatra, Kalimantan) (Nitisastro 2006).

Between the end of the 18th century to early in the 19th century, there was a cluster of population

growth in areas of Java and Sumatra due to the spice and rice trade run by the East Indies Company,

(Gooszen 1999)). On the other hand, in the eastern archipelago (e.g. Sulawesi, Flores, Papua), the

socio-economic history was much more influenced by social dependence on maritime resources. One

example is the endangered Bajau culture (sea-nomads, also known as ‘orang laut’), which, with its

unique mobile dwellings in coastal shallows has more than two hundred years of microeconomic

reliance on the fish and sea-cucumber trade (Tomascik, T. et al. 1997). Before the early nineteenth

century, it was likely that coastal resource extraction (e.g. fishing) in Indonesia was still a

subsistence-level activity, where most coastal dwellings in Southeast Asia (SEA) were village

dominated at that time (Osborne 2004; Taylor 2004). In the same period, fishing in the SEA region

itself was light in resource exploitation, due to the quality and abundance of fish stocks and the simple

methods of fishing described in several contemporary records of the region (Butcher 2004).

After the World War II era, fishing in the SEA region began to become industrialized.

Technical advances in the design of fishing vessels allowed an increase in extraction capacity and

ability to access new, more remote fishing grounds (Butcher 2004; Morgan & Staples 2006). Around

the end of the 20th century, as nations began to identify a decline in abundance of many fish stocks,

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control of fishing activities between territorial waters was initiated (e.g. UN Conventions on the Law

of the Sea, UNCLOS, (Bardach & Matsuda 1980)). Throughout the years in which nations developed

the treaty, Indonesia was constantly increasing its marine capture and, together with Thailand, was the

top fish producing nation in SEA (Sugiyama, Staples & Funge-Smith 2004). During the same period,

overfishing because of from industrialized practices in SEA began to become rampant (Pauly, D &

Thia-Eng 1988). At some local sites, its effect of generating declining catches also began to impact

artisanal fishers, including in Indonesia; which triggered them to resort to more catch-efficient

methods that were destructive (Pauly, D & Thia-Eng 1988).

After the mid 20th century, towards the early 1990s, the national planning policy in Indonesia

was still oriented towards terrestrial resources (e.g. Pembangunan Jangka Panjang / Long Term

Development 1 (PJP 1) (Sloan & Sugandhy 1994). It was not until the PJP II, which ran from 1993 to

1998, that a national development plan about coastal and marine resource exploration was initiated.

However, its objectives were more to do with exploitation since measures of sustainable resource use

were hindered by weak constitutional governance, poor use of government resources and a centralized

bureaucracy (Bengen, Knight & Dutton 2006). The end of the Suharto presidential era in 1998

marked the beginning of a national initiative in marine conservation when the elected president

Abdurrahman Wahid established a ministry related to fisheries and coastal resource. Since then, there

has not been much reform in the national fisheries policy, until in 2002 the statement to “conserve

resources for sustainable utilization” was included in the national guidelines of fisheries (MMAF

2002). However, the early 2000s was a transitional era for Indonesia after economic and political

crises (Aswicahyono, Bird & Hill 2009). During that period, there were multifaceted obstacles in

managing natural resources, including the fisheries, due to the condition of the regulatory regime

(Thorburn, C 2002), which included overestimating fish management approach, ineffective

surveillance and regulation, and a lack of knowledge, implementation, inter-departmental

coordination, and background ecological data that impeded decision-making processes (Mous, P et al.

2005; White et al. 2005).

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Indonesia is one of six countries within the Coral Reef Triangle - the area with the highest

species diversity of coral reef organisms: about 590 of the world’s 793 known reef-building coral

species (Veron, J 2000; Wilkinson, Clive 2008). The coastal ecosystems in the region provide

resources and livelihoods for millions of people in the coastal and island communities of Indonesia.

Their dependency on reef resources places pressure on reef systems (Cesar, H 1996). These reef

ecosystems support the core of subsistence fishing in Indonesia, as well as other socio-economic

assets such as natural coastal protection, tourism revenue, and aesthetic and cultural values.

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Unfortunately, the condition of coral reefs in Indonesia is in a declining state with almost half of the

reefs now highly threatened (Wilkinson, Clive 2008). Human impacts on coral reefs have altered

these ecosystems through both long-term stresses such as overfishing, domestic, industrial and

agricultural pollution, eutrophication and sedimentation (Dixon 1997; Edinger, EN et al. 1998;

Holmes et al. 2000; Tomascik, T, Suharsono & Mah 1993). Short-term (often acute) threats such as

destructive fishing practices include blast fishing, poison fishing and anchor damage (Pet-Soede, L &

Erdmann 1998).

Figure 1.1. The Coral Triangle region consists of 6 countries, which are home to some of the most species rich marine habitats in the world. Photo credit: WWF.

Similar to other countries in Southeast Asia, these impacts have been correlated with over-

exploitation associated with rapid human population growth in Indonesia in the past 30 years

(Edinger, EN, Kolasa & Risk 2000; Mous, PJ et al. 2000; Wilkinson, Clive 2008). External influences

exist, such as foreign commercial fishing vessels that extract pelagic and demersal fishes at higher

capacity (‘fishing roving bandits’ (Berkes, F. et al. 2006)) outcompeting local subsistence fishers or

pushing them to resort to more destructive reef fishing practices in coastal areas (Jackson, J. 2001;

McClanahan, T 2002; McManus, J. W. 1997). Moreover, terrestrial development is historically

detrimental to coral reefs, threatening reefs even more through intense pollution and sea floor

dredging in major cities - e.g. Jakarta. Sedimentation and land run-off result from deforestation and

coastal conversion (for example, more than 60% of Indonesian mangroves have been converted into

!'!!

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wood pulp, aquaculture ponds, tidal agriculture, and plantations (Hodgson & Dixon 1992; Tomascik,

T. et al. 1997).

At the global scale, anthropogenic greenhouse gas emissions pose another threat to coral reef

ecosystems, leading to more frequent and severe coral bleaching events, and this is projected to lead

to intensified reef damage due to a higher frequency of severe storms and ocean acidification (Hoegh-

Guldberg et al. 2007). Sea level rise is another serious global threat that may leave millions in low-

lying coastal areas without homes by the mid-to late 21st century (Marfai & King 2008). In addition to

the loss of coastal ecosystem resources, there are growing risks to the community associated with

vulnerability, which is when the loss of entitlements such as food security makes society more

unstable and susceptible to harm (Adger, WN 2006; Allison et al. 2005). Management and mitigation

of the impact of the more direct local human activities is critical in order to avoid further degradation

in combination with climate change threats that are uncertain in the immediate future. Failure to do so

is costly in all aspects: socially, economically and ecologically.

ONTN R0$"-(,&()>"(,<#).'%"#($&()>"(4.&.3"4"&)(,-(',0.%(0""-(0"#,*0'"#(

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In the past five decades, the development process in Indonesia has not properly accounted for

the loss in the value of coastal reef resources and services resulting from over-exploitation and

degradation (Dahuri & Dutton 2000). This is partly a consequence of policy makers, reef users and

the general public being ill informed of both the use and non-use bioeconomic value of reef resources

and the long-term economic consequences of the coastal reef reduction due to unsustainable practices

(Cesar, H 1996; Pet-Soede, C, Cesar & Pet 1999). Furthermore, the geopolitical situation and

economic development in the years of New Order (Vickers 2005) have not given much strategic

attention to coastal and marine resources, where emphasis is still on terrestrial ones (e.g. oil, gas,

mining, and timber) (BAPENNAS/CIDA 1987; Dahuri & Dutton 2000).

In the years following the fall of President Soeharto [in 1998 (Vickers 2005)], the government

of Indonesia established a long-term national program in coral reef management [e.g. COREMAP in

Moosa and Ahmed (2004)] as a response to the critical condition of Indonesian reefs (Edinger, EN et

al. 1998; Suharsono 1998). However, such a program was still confronted by fragmented jurisdictions

within and across departments and prevalent corruption which is still apparent within the transitioning

government (post-1998, “reformation” era) (Patlis 2005). Specifically, the transition towards

decentralisation of natural resource management was partial. Suppression of accountability across

governmental levels was apparent resulting in an inappropriate legal framework, a lack of integration

among environmental management initiatives and weak enforcement (e.g. fisheries, reef management,

and logging (Dirhamsyah 2006; Lebel et al. 2006)). At the local scale, this governmental intricacy has

!(!!

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brought in attention to societal considerations in resource management (e.g. alternative livelihood

provision, and traditional management (Pomeroy, RS et al. 2006; Satria, Arif, Matsuda & Sano 2006).

As a consequence, much of the regulatory framework was centred on biological goals where social

issues such as poverty alleviation for the larger segment of coastal communities has been overlooked;

thus bringing about more social aversion to resource management regulations (Christie 2004).

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As in most developing tropical nations, coral reef valuations came many years behind the

process of reef degradation. However, the significance of environmental valuation as a tool to

influence political decisions have likely been inconsistent, making Indonesia a low bio-prospecting

governance where the national conservation investments delivered were mostly transitory (Ahmed,

Mahfuzuddin, Chong & Cesar 2005). During the end of the 90s, there was significant research into

the economic value of coral reef ecosystems in most tropical countries with rich coral-reef resources,

including Indonesia (Cesar, H 1996; Dixon 1997; Pet-Soede, C, Cesar & Pet 1999). One rationale for

placing a dollar value on coral reefs is to gain political interest in preserving reefs; specifically by

identifying, measuring and quantifying the economic cost of inaction and unsustainable practices

(Cesar, H. & Chong 2004). However, measuring the values of ‘non-use’ (e.g. future biodiversity, and

aesthetic values) and ‘indirect use’ (e.g. natural coastal protection) benefits of reef ecosystems has

only been ‘virtual’ or ‘hypothetical’ as described by Cesar and Chong (2004). Thus, ‘direct use’ (e.g.

fishing and tourism investments) is a factor that involves actual cash transactions; thereby it is often

financially more realistic for policy makers to use this as the benchmark for resource sustainability

(Ahmed, M, Chong & Balasubramanian 2004).

Direct coastal resource users, particularly the traditional fishermen, have been predominantly

ineffective in participating in the coastal economy (Moosa & Ahmed 2004). This is despite their

contribution amounting to more than 99% of Indonesia’s national fishing vessel fleet, which is

dominated by small-scale vessels (< 30 gross tonnes) with almost half of them non-powered boats

(traditional) and most of the extractions occurring near-shore (FAO 2009). Thus, the vast majority of

the fishing community does not determine the nature of the fishing market. The regional fishing

economy surplus is derived from a production and marketing system that flows mainly to roving

buyers and vessel owners rather than fishermen. Artisanal fishermen are highly dependent on

intermediary brokers (‘middlemen’) who control the fish prices. These brokers are often unavoidable

since the acquisition of legitimate harvesting permits, certification and tax and rent avoidance

prevents many traditional fishermen from joining the regional market, which is also often too

complex for the mostly illiterate fisher folk. In addition, the Indonesian region is also subject to the

operation of thousands of illegal, unmonitored and unregulated international commercial fishing

!)!!

!

vessels, according to an analysis by Sodik (2009). The author also mentioned some of these vessels

conducting illegal trans-shipment, where they land, collect and process fishes directly offshore from

traditional fishers (Sodik 2009). The subsistence fishers who are also marginalized by the market have

experienced the bottom effect of this intense resource competition. Accordingly, at some poverty

threshold, subsistence fishers have resorted to short-term economic remedies in the form of

unsustainable resource extraction such as destructive fishing.

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The Indonesian Government has been adopting marine protected areas (MPA) predominantly

as an approach to facilitate recovery of fisheries and regulate associated activities that destabilize reef

ecosystem. However, upon establishing MPAs, most efforts in enforcing MPA regulations in

Indonesia have been deficient or ineffective (Christie 2004; McClanahan, T et al. 2006). As part of

the Integrated Coastal Management (ICM) tools, marine national parks (MPAs) were established as a

means to decentralizing governance where promulgate policies still inherit past centralized legislation

(Christie 2005). A critical review by Dirhamsyah (2006) demonstrated some of the major defects in

Indonesia’s legal framework in coastal and reef resource management that impede enforcement of

unsustainable practices. For instance, fishing activities that damage fish habitats (e.g. muro ami) and

which are prohibited under the national law in by the Fisheries Act, were seen as a ‘tolerable’ act

under the regional governmental laws.

Moreover, most of the MPAs in Indonesia have been less socially accepted as tools to limit

users access to resources and were not effectively coupled by livelihood-based management measures

(McClanahan, T et al. 2006). Several MPAs have reinvigorated either community-based or co-

management frameworks as adaptive measures to gain trust, collaboration, and a sense of ownership

by reef users; however, only few have been viable [e.g. local tenure at Gili Indah Marine Tourism

Park, and community participation in Wakatobi National Park (Fitzgerald 2007; Satria, Arif, Matsuda

& Sano 2006)]. Despite the ecological imperative to scale up current MPA requirements to protect the

vast reef areas of Indonesia; efforts in both spatial and temporal scaling of MPAs should not neglect

consistency in adapting to the specificity of social issues [lessons from the Philippines (Lowry, White

& Christie 2009)]. Moreover, as part of multi-national initiatives (e.g. the Coral Triangle), local

initiatives to manage Indonesian reefs (via the community and the national government) need to be

imposed upward in order to ensure internationally driven top-down targets are realistic for both

resource users as well as local managers in the field (Agardy et al. 2003; World Bank 2006).

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Improving how ecosystem conservation can be integrated with and adapted to the socio-

economic system is crucial for the sustainability of Indonesia’s coral reefs. Ignoring the demands of

!*!!

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poverty reduction, for example, can cause failure in efforts to conserve biodiversity as coastal or

island communities often reside within the protected areas (Adams 2004). Regarding reef

management, wealth can be a major factor that influences how people perceive, behave, and develop

the need to conserve reef resources (Cinner, JE & Pollnac 2004). The Indonesian community is,

therefore, challenged to ensure long-term societal development whilst conserving the ecosystem’s

assets via sustainable development (Bell et al. 2006). To achieve this, a more adaptive governance is

needed, which means structures of a social, economic, legal, and political nature related to natural

resources should recognize not only how the human dimension is shaping the ecosystem processes

and functions but also that their behaviour and interaction will respond to and influence the ecological

structure and its dynamics (Folke et al. 2005).

Despite global political commitments to reduce greenhouse gas emissions, the impacts of

current climate change on the ecosystem are results of past emissions (Hoegh-Guldberg et al. 2007;

IPCC 2007). Future reduction in global emissions is uncertain and Indonesia is susceptible to the risks

of multiple consequences on its communities and its reef resources (Hoegh-Guldberg et al. 2009;

Veron, JEN et al. 2009). Managing local anthropogenic impacts on reefs are therefore a high priority

for Indonesia.

Focusing on the conservation of biodiversity has likely been leading to conflicts, such as those

between fishermen and the government (Agardy et al. 2003; Nielsen & Vedsmand 1999; Pomeroy, R

et al. 2007). This implies that goals set for reef conservation need to include both goals for resource

recovery and livelihood sustainability. Furthermore, external driving forces of conservation such as

academic and non-government conservation organizations often serve as entry points, whereas

governments are the key drivers through legal and institutional instruments (Christie & White 2007;

Dahuri & Dutton 2000). Institutional support is often required to identify potential social instruments

and livelihood criteria that may have been disregarded by the ecological or biological goals set by

resource state agencies (Christie 2004). Nonetheless, the corresponding biological aspects themselves

may not yet be sufficiently addressed due to limitations on scientific methods in the national park

management units. In some situations it is more realistic to ask the right management questions than

conducting more research (Johannes 1998). These conditions have been distinguished in marine

reserve areas in Indonesia such as in Karimunjawa National Park, which is discussed at a length in the

next chapter.

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Anthropogenic stresses in many ecosystems have caused dramatic change in species

composition, which are often almost irreversible (Scheffer, M. 2003; Scheffer, M. et al. 2001). For

coral reefs, strong influence from human activities at local, regional and global scales has reduced the

ecosystem’s capacity to re-establish after disturbances (Hughes et al. 2003; Mora 2008; Pandolfi, JM

2005). In many reef areas, disturbances have caused transition in community compositions from

corals to algae, known as ‘phase shifts’ (Hughes et al. 2003; Hughes, Rodrigues, et al. 2007; Pandolfi,

J 2003). The occurrence of an undesirable phase shifts (Fig. 2.1), where the coral reef system

gravitates irreversibly to a degraded system (Done 1992; Scheffer, M. et al. 2001), has given rise to

studies that address the importance of managing for coral reef resilience (Hughes et al. 2003; Hughes,

Rodrigues, et al. 2007; Mumby, P., Hastings & Edwards 2007; Nyström, Folke & Moberg 2000; West

& Salm 2003).

The definition of ‘resilience’ is often specific to the scientific disciplines in which it is used

(Brand & Jax 2007). As in most coastal and marine ecosystem, humans and coral reef are part of an

socio-ecological system (SES) (Hughes et al. 2005). In this context Walker et al. (2004) described

resilience as “the capacity of a system to absorb disturbance and reorganize while undergoing change

so as to still retain essentially the same function, structure, identity, and feedbacks”. The link between

social and ecosystem resilience is closely linked with the dependency of people on reef resources

(Adger, W. 2000; Folke et al. 2002). As human societies utilize resources from reef systems, it is in

their interest to help sustain the reef’s regenerative capacity to continuously deliver resources and

services that are important for their livelihood (Folke et al. 2004). However, individuals and

institutions within the social systems can differ in their vulnerability to both natural or human-induced

ecological surprises (Adger, WN et al. 2005; Holling 1996). Thus, the social adaptability to maintain

ecological resilience is also affected (Walker, B et al. 2004)

! ,

Figure 2.1. A conceptual model of reef habitat state trajectory responding to human disturbances over time. If severity and frequency of disturbances to some extent impaired reef ecosystem functions, incomplete recovery can occur (brown line). In this case, the reef system is losing its regenerating capacity to human-related stressors such as habitats that are losing its structural complexity (from coral dominated to coral-depauperate state). Managing reef resilience, in this case, is to maintain key ecosystem process so that reef system dynamics are remaining in the ‘desirable’ domain (blue line). This includes managing human-made disturbances in a level where impacts still allow for successful or, at least, prolonged reorganization of reefs. (Figure modified from Palumbi et al. (2008)).

People interact with coral reefs predominantly through fishing (McManus, J. W. 1997; Roberts

1995). Unfortunately, over-harvesting is nearly universal (Jackson, J. 2001; Myers & Worm 2003;

Pauly, D. et al. 2002), partly due to fisheries management treating ecosystem resources as static rather

than dynamic systems (Pauly, D. et al. 2002). Moreover, at local to regional scale, much of planning

of protected areas and actions associated with coral reef fisheries provide inadequate consideration of

the socio-economic context (Christie 2004; Christie et al. 2005; McClanahan, T et al. 2006). Thus,

most reef management policies and regulation that were economically detrimental could be socially

less adaptable and develop negative feedbacks from the community (McClanahan, T.R. et al. 2008;

Mora 2008). Therefore, managing reef resilience requires the perspective of socio-ecological system

(SES) that develops dual positive feedbacks of both maintaining ecosystem functions and processes,

but also the capacity social that are responding and adapting to environmental changes and

management intervention (Folke 2006; Hughes et al. 2005; Mumby, PJ & Steneck 2008) (See Fig.

2.2).

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Figure 2.2. Diagram depicting the relationship between social and ecological arrangements. The coral reef ecosystem provides benefits for the people that are linked to it, such as in fisheries and tourism (1). Concurrently, reef use by people impact on reef ecosystem processes (6), such as modification of reef habitats or reduction in fish population sizes (2). The response of the reef system includes recoverability and resistance to man-made stressors yet ecosystem information received by reef user is partial through reinterpretations such as science or traditional knowledge (3). Collective decisions and actions from the social system, subsequently, generates feedbacks or controls, such as in managing fishing or, protecting and govern reef resource (4); or amplification of an effect, such as further exploitation that could generate detrimental effects to ecosystem, such as overfishing and destructive fishing. In this case, reef resource management is required to be responsive to both ecological changes (3) as well as the socioeconomic aspect that influence decisions and actions of resource user (5). Synthesizing science with the common knowledge of resource users (e.g. the community) could be essential to influence decision whether to intensify, reduce, or stop resource use (1,2,4). Yet, scientific tools to assess biophysical and ecological variables in the context of resilience and appropriate management actions are a challenge (3,4,6). (Figure modified from Nyström (2006)).

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The Indonesian government has established fifty National Parks (Dephut 2008) - nine of

which cover an area of 41,129 km2 gazetted as marine national parks (Clifton 2003). Karimunjawa

Islands is one of the nine National Marine Parks in Indonesia (Dephut 2008). KNP (5' 40"-5' 57" S

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and 110' 4"-110' 40" W) lies in the Java Sea, approximately ± 45 nautical miles from Jepara, on the

north coast of Central Java, Indonesia (Fig. 2.3). The park includes 111.625 Ha, which consists of

7.033 Ha of terrestrial and 104.592 Ha of marine areas. Karimunjawa consists of 27 islands that

include 5 inhabited islands of Karimunjawa, Kemujan, Parang, Nyamuk, and Genting. The marine

zonings within the KNP boundaries are buffer, rehabilitation, traditional fishing, aquaculture, tourist,

and a no-take zone. The purpose of the zoning plan was to regulate park utilization mainly for

research, science, education, resource sustainability, tourism and recreation (BTNKJ 2004). There are

five types of characteristic ecosystems in the island group, consisting of low-land tropical forest,

beach forest, mangrove forest, seagrass, and coral reef (BTNKJ 2004).

Figure 2.3. Map of islands and the coral reef areas within Karimunjawa National Park boundaries. (Figure modified from map courtesy of Karimunjawa National Park Agency, Wildlife Conservation Society).

The close proximity of the island group to Java Island, home to more than 60% of the

population of Indonesia (BPS 2005); pose a significant challenge for reef managers to address issues

of balancing demands for reef-generated resources with conservation efforts (Edinger, EN et al.

1998). Karimunjawa National Park (KNP) represents well the population-related reef management

issues that are common in developing countries (Bell et al. 2006), particularly in the Indo-Pacific

where efforts to mitigate local impacts that reduce reef resilience are currently scarce (Hughes et al.

2003). Interestingly, coral biodiversity in KNP still resembles that of other fringing reef regions in

eastern Indonesia (Edinger, EN et al. 1998). Despite historical unsustainable reef fishing practises

such as muro ami (Marnane, Ardiwijaya, Wibowo, et al. 2004), recent trends in the average of coral

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cover were moderate (around 40 – 60% of average for 3 and 10 meters depth, however

inconsistencies of sampling sites and size for each year between 2005-2008 (Ardiwijaya, Kartawijaya

& Herdiana 2007; Ardiwijaya, R. L. et al. 2008; Marnane et al. 2005)). Furthermore, time-series reef

ecological data resource for this region is lacking and recent relative to the establishment of marine

area for conservation with limited collaborative scientific support form NGOs (e.g. Wildlife

Conservation Society and Taka Foundation) (Ardiwijaya, R.L. et al. 2008; BTNKJ 2004).

There are more than 9000 registered residents living in KNP, of which approximately 40%

undertake fishing using a variety of artisanal fishing methods (BTNKJ 2008). Their selectivity in

fishing areas as well as fish targets also vary greatly mainly due to the bi-monsoonal season and local

knowledge to fish aggregation sites (Campbell & Pardede 2006; Yulianto & Herdiana 2006).

Migratory fishers have brought up different preferences in fishing behaviour that has likely resulted

from multi-ethnicity influences (Pet-Soede, L & Erdmann 1998) that originated both from the western

and eastern Indonesian archipelago (e.g. Jawa, Madura, Bugis and Buton tribes (BTNKJ 2004). Each

cultural group tends to have nucleated settlement pattern where those from Kalimanatan and Sulawesi

tend to aggregate in northern part of the region such as Kemujan, and Java in the southern part such as

Karimun island (BTNKJ 2004). Despite cultural heterogeneity, fish and reef resource are utilized as

‘all-access’ as shared as a ’common property’ with customary laws that exclude non-Karimunjawan

from fishing within the region (S. Haryanta, Pers. Comm., 2008).

Because of such social complexity (e.g. community heterogeneity and traditional resource

used with high dependency), further conflict due to reduced social adaptation to management

interventions can be avoided by proactively involving local community as actors that also perform

management task (Armitage, D. 2005). More, as an areas where high sense of resource ownership is

being displayed, current regulative framework of the working policy (2004 zoning) in KNP also needs

to be deliberately consistent with the potential collective decisions existed in the community that may

enhance acceptability of conservation initiatives (e.g. participatory management and customary

marine tenure) (Cinner, J 2005; Elliott et al. 2001; Pomeroy, RS 1995). However, in the recent

rezoning in 2004, extensive consultation with community was undertaken only in the beginning.

Moreover, several years after the zoning enacted low community compliance was observed in a report

by Wildlife Conservation Society (Yulianto & Herdiana 2006). The differing rules, procedures and

values in the community are suggested to have restrained efforts to achieve common consensus for

conservation and limit park manager to promulgate regulation (Rudd 2000; Rudd et al. 2001). On the

other hand, low institutional capacity (e.g. management resource and fund) had also limited practical

efforts to monitor and enforce zones in KNP, and even to communicate with the community (e.g.

warden and patrol boats) (S. Haryanta, Pers. Comm., 2008). Karimunjawa National Park might be just

one of the typical case in developing nations where conservation initiatives are not yet being able to

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reflect local social condition such as knowledge, experience, and their cooperative behaviour (Christie

2004; McClanahan, T et al. 2006). Long-term communication between regulators and the community

was not initially well formulated, thus, community perception and opinion has not yet fully taken

account of conservation interventions strategies. Correspondingly, community-based approaches to

fishery and reef management, such as adopting and cohesively attaching to local customary or

traditional norms in regulation (Satria, Arif, Matsuda & Sano 2006), are still lacking.

Historically, some of the extractive activities in Karimunjawa have been harmful to the reef

ecosystem (see section 2.2.2) and marine zonings areas, including no-take areas; have been regulated

to minimize the impact on reef habitat. However, area restriction established resulted in fishing

displacement such as to inshore subsistence fishers and yet effective livelihood support strategies to

reduce socioeconomic problems that drives unsustainable activities was absent. Correspondingly, how

people utilize resources relates to a multitude of social, cultural, and economic factors that shapes

social perception of resources (Fauzi & Buchary 2002; Marshall, N et al. 2007; Nazarea et al. 1998).

From this, Karimunjawan reef management needs to be able to acknowledge social perception of

resources, which means understanding both the varying ways of people utilizing the resource and the

relative values to them (Cinner, JE & Pollnac 2004). Evaluating social perception at early stages of

MPA planning and management may help identify areas of conflict and agreement, recognize shared

perceptions, and produce solutions (Cinner, JE & Pollnac 2004; Cocklin, Craw & McAuley ;

McClanahan, T, Castilla, et al. 2009). Specifically, social perception of risk relates to their adaptive

behaviour towards changes (e.g. resource depletion, transitional livelihood) (Adger, WN et al. 2005;

Cinner, J, Fuentes & Randriamahazo 2009; Grothmann & Patt 2005; McClanahan, T, Cinner, et al.

2009). Aside from maintaining the ecological functions of an MPA, therefore, it is critical for KNP

management to gain positive social perception of resource conservation and restrictions while

simultaneously prescribing livelihood-based policies that might be needed to improve local-level

social resilience (e.g. promoting economic growth).

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Coral reefs are in decline worldwide from disturbances that occur both at the global (Hoegh-

Guldberg et al. 2007) and local (Knowlton & Jackson 2008) scales (see also review by (Knowlton

2001; Wilkinson, C 2004). Local stressors that are influenced by a large and growing human

population in coastal areas (Curran et al. 2002) include overfishing (Hughes et al. 2003; Mumby, P.

2006b), physical disturbances (Nyström, Folke & Moberg 2000; Ostrander et al. 2000), and declining

water quality (McCook, LJ 1999). Fishing pressure can impact directly on trophic relations between

fish and benthos (Pinnegar, Polunin & Francour 2002; Steneck, R. S. 1998) and also indirectly on

benthic reef communities (Hughes 1994). In areas where predatory fish stocks are severely depleted

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and recovery potential is low, growing demands for fish food can prompt fishermen to target lower

trophic levels (e.g. herbivorous fishes) (Done 1992; Mcmanus, J. 2000). The loss of herbivorous

fishes reduces the grazing rate on the reef (Mumby, P. 2006b), thereby favouring an increase in algal

biomass which encroaches on corals via space competition, potentially shifting the reef community

towards macroalgal dominance (Hughes, Bellwood, et al. 2007). Increasing sediment and nutrient

loading are factors that can exacerbate such a shift by enhancing algal growth rate (Russ & McCook

1999). In this section, I analyse the role of these environmental stressors in determining reef

functioning, health and state in Karimunjawan reef (See Fig. 2.4).

Figure 2.4. Conceptual depiction of identified key reef stressors (red boxes) in Karimunjawa that are influencing reef ecosystem processes. The arrangement of human activities at local scale brings either desirable and undesirable (blue and red text, respectively) control mechanism to specific processes of the reef. Sustainable human activity can prompt negative controlling feedback both the ecosystem and the community (blue texts), whereas the opposite activity can potentially disrupt reef ecosystem process and risk in livelihood (red texts) (Impact 2). The interaction of coral and algae influence structural complexity that was affected by both physical impact of fishing and coastal pollution, which also determines the aesthetical value of the reef such as for tourism. Fishing can directly affect both habitat and fish species composition, which influences both the habitat condition and the amount of protein output form the reef.

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Being one of the important artisanal fishing areas in the Java Sea region, fishing at the

boundaries of KNP has been intense with clear effects on fish populations and reef habitats. Early

evidence of overfishing in Karimunjawa was observed by Edinger et al. (1998) at few reef sites

surrounding Karimunjawa main island (Kecil and Burung island, Cemara patch, Mrican lagoon).

Furthermore, constraints in departmental authorization (e.g. between National Park Agency and the

Ministry of Marine Affairs and Fisheries) appears to be restricting the regulation of fishing

intervention (e.g. regulation in gear and target fishes) limiting the protection to relatively small no-

take areas (BTNKJ 2004; Dirhamsyah 2006). The no-take zones aims to replenish fish stocks by

establishing enclosures around identified key fish spawning and aggregation sites. However, difficulty

in restricting resource access [much was still considered as part of ‘all-access rights’ (BTNKJ 2004)]

combined with low community support for MPA regulation meant that no take-areas were ineffective

in preventing the decline in fish populations (2008; Ardiwijaya, Kartawijaya & Herdiana 2007; 2008;

Rudd et al. 2001).

Although the intensity of past unsustainable fishing practises (e.g. cyanide fishing and muro-

ami (Marnane, Ardiwijaya, Wibowo, et al. 2004) had receded due to significant decrease in fish catch

felt in years following, small numbers of muro-ami fishermen were still operating. This situation was

likely to be triggered by economic pressure and slow fish-stock replenishment (pers. comm. Sutris

Haryanta, 2008). To date, fishing methods were characterised by effective yet non-selective methods

that operated seasonally (BTNKJ 2004). This means each type of fishing gear used (e.g. hook and

line, spear guns, hand spears, traps, small gillnets and tonda (traditional trolling) are specific only to

catch a certain range of fish families (Ardiwijaya, Kartawijaya & Herdiana 2007). Unfortunately,

currently dominating herbivorous fish families (e.g. Scarridae) were among targets of each of these

methods (Campbell & Pardede 2006); threatening species that control algal biomass and thereby help

provide space for corals to grow. Therefore, it is critical that reef manages in KNP are be able to

implement management remedies to avoid the loss of key functional species of the reef ecosystem.

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An increasing fishing pressure has significantly reduced the reef fish populations around

Karimunjawa Islands (Ardiwijaya, Kartawijaya & Herdiana 2007; Wibowo, Joni T 2006). The fishing

practices have modified the community structure of reef fish (Campbell & Pardede 2006), and have

caused direct physical damage to reef habitats and reef communities (Marnane, Ardiwijaya, Wibowo,

et al. 2004). The persistence of these impacts were also suggested from a recent baseline survey [see

also Maynard et al.(2008)], which indicated that several sites showed signs of macroalgal dominance

! $)

and had low abundance of herbivorous fish irrespective of marine park zoning (e.g. Tengah Kecil

(Tourism zone), Cemara Kecil (Buffer Zone). While past fishing impacts from practises such as

muro-ami are decreasing, recent observations of broken rock anchors on reef crests, fractured coral

colonies and interviews with boat operators suggest that rock anchors are still being used by local

fishermen. This is related to the fact that only a few mooring buoys have been installed within the

park boundaries near Karimunjawa and Kemujan islands. This number is inadequate to support the

large number of fishing boats that operate in these areas. As yet there are no specific regulations

concerning anchoring within KNP, another problem with installing mooring buoys has been the cost,

which together with the absence of standard procedures has prevented their widespread use within the

KNP.

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Tourism development can also contribute to reef health decline (Moberg & Folke 1999) where

increasing demand for reef service, such as sea food products, can lead to intensified fishing efforts

(Maypa et al. 2002). Since the Kartini catamaran was introduced in 2003 to help service the

Semarang-Karimunjawa crossing, there has been an increase in tourism influx to the islands.

Predatory fishes such as coral trout (genus Plectropomus) or emperors (family Lethrinidae) are more

sought after than herbivorous fishes (e.g. Scarridae and Siganidae) and as a consequence, adult

predatory reef fishes are nearly fished out on Karimunjawan reefs (Campbell & Pardede 2006). Some

fishermen target more remote fishing grounds to continue targeting sought-after species despite

greater travel and fuel costs, whereas other fishermen continue fishing on local grounds but with a

greater inclusion of herbivorous fishes. During two field trips to the Islands, I observed daily that

undersized and juvenile reef fish (including Scarrids and Siganids) are used to cater for tourists (see

Fig. 2.5). With the increase in tourist activity, coupled with local demands by a growing local

population, pressure on these particular fish species is likely to increase in the near future

(McClanahan, T et al. 2003; Wilkinson, CR 1999), potentially leading to an uncontrolled growth of

macroalgae within the reef system (Mantyka & Bellwood 2007; Mumby, P. 2006a).

! $*

Figure 2.5. Undersized reef fishes caught on Karimunjawan reefs. A: Small Parrotfishes (Scarridae) sold at the street market at Karimunjawa village, B: Young Groupers and Parrotfish caught in a protected zone and served as lunch to tourists, C: Young Rabbitfish (Siganidae) served as regular meals in a homestay (guesthouse) in Karimunjawa.

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The link between water-quality impacts such as sewage and pollutant outflows and sediment

run-off and coral reef degradation in Indonesia has been well documented (Edinger, EN et al. 1998;

2000; Holmes et al. 2000). Human development in the coastal perimeter is likely to contribute to the

nutrient enrichment of coastal marine areas (Szmant 2002), which can disturb reefs and slow down

recovery (e.g. inhibition of reef growth (Edinger, E et al. 2000; Kleypas 1996), and reduction of

competitive strength of corals against macroalgae (Loya 2004). In many parts of the Karimunjawa

district, domestic sewage is disposed of directly into the marine environment (Fig. 2.6), resulting in

distinct signs of eutrophication - e.g. colouration, odour (Gurel et al. 2005).

Figure 2.6. Direct disposal (A) and untreated (B) domestic waste polluting coastal waters in Karimunjawa.

A

B

C

A

B

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Karimunjawa is an example of managed reefs where the ecological studies begin in an

ecosystem that, at some extent, has already been degraded. Its historical ‘pristine’ reef state is fairly

unknown and first investigation of human influence on its reef by Edinger (1998) was not more than a

decade ago. Accordingly, recent ecological monitoring in Karimunjawa (2007; 2008; Marnane et al.

2005; Wibowo, Joni T 2006) has produced an evidence of a reef system where human influences have

shifted the baseline pristine to the partly regraded reef environment (Pauly, D 1995). The previous

sections have showed that localized major driving forces of coral decline are profound and may likely

lead to further degradations of reef state in the future (Edinger, E et al. 2000; Hutchings 1986).

Effective management of local scale impacts is therefore crucial, where to some extent the ecological

attributes of the reefs are still able to resist globally driven changes [coral bleaching, ocean

acidification (Hoegh-Guldberg et al. 2007; Knowlton 2001; Pandolfi, JM 2005)]. In this case, the

trophic structure, biodiversity, resistance and resilience are all important to consider in reef

conservation strategies (Bellwood, D et al. 2004).

In KNP, the working policy related to reef ecosystem management exclusively depends on a

centrally planned zoning scheme and has not yet fully considered the role of functional groups such as

herbivory as an important aspect of reef resilience. A relatively smaller portion of no-take areas than

to the park boundary was included with purpose displace fishing effort in suspected fish aggregation

sites; whereas larger buffer areas as restrictive measure to limits fishing only for subsistence purposes.

Yet, there was no regulation on timing or numbers of fishing on the larger part outside these protected

areas and countermeasures to manage local socioeconomic that drive compliance issues relevant to

the zoning regulation was beyond sufficient. In this case, inadequate ecological consideration as well

as inattention to socioeconomic factors associated to both the functioning of the working policy and

direct mitigation of the unsustainable activities suggest a call for an re-evaluation of local reef

management framework in KNP.

Relevant to the key local issues discussed in the previous section, there are several key

ecological aspects that area-based management (e.g. zoning) has not yet addressed. Some of the

reasons include, first, changes key reef species interactions that can produce large ecosystem response

(Knowlton 1992, 2004) such as the impact of herbivory removal from fishing. Secondly, the inherent

unpredictability of changes species abundance due to spatial and temporal variability in within reef

community members (Hughes et al. 2005; Jackson, JBC 1991) is not being anticipated by a relatively

static zoning approach. Thirdly, different trajectories of recovery and degradation of reef habitats and

features that can enhance ability to resist or recovery from synergies of local disturbances (Gardner et

al. 2005; Pandolfi, J 2003) was not included in the reef management precaution that still relying

! $,

solely on restrictive measures. On the social side, the 2004 zoning policy itself indirectly acted as a

‘social intervention’ rather than as a ‘conservation initiative’. For instance, the objective of

maintaining fish stocks (abundance and biomass) through fishing area restrictions is also an attempt to

control the social behaviour of people towards reef resources. However, compliance related to reserve

rules itself does not simply related on enforcement since local complexity of social dynamics also

involved (Christie et al. 2009; Cinner, Joshua E. et al. 2009; McClanahan, T et al. 2006). Therefore,

delivering socio-economic solutions to local reef resource users is another critical factor in producing

long-term future conservation policies for KNP.

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Managers and policy makers need better insight into the processes of socio-ecological

resilience to understand the complex but important socio-ecological problems in KNP. This means

better scientific knowledge that can avoid the ‘socio-ecological trap’- the situation when unresolved

an poverty trap develops a negative feedback of a socio-economic development that impedes the

reef’s capacity to recover, concurrently with stakeholder’s failure to improve or maintain habitat

complexity that interacts with socio-economic needs (Steneck, Robert S. 2009). Being complex

systems, coral reefs unavoidably will undergo changes either from natural or man-made disturbances.

Subsequently, the linked social system is also dynamic, and managing for social resilience is needed

to reduce vulnerability.

The aim of this thesis is to integrate the concepts of social and ecological resilience and

provide recommendations for marine protected area management in Karimunjawa islands. The first

chapter provides a broad overview of the literature on coral reef management in Indonesia. In chapter

2, I present the ecological and sociological problems, conceptual models for socio-ecological

resilience, and how they relate to marine protected area management in KNP. In Chapter 3, I present

the application of reef benthic community model projections as an analytical tool for managers to

assess resilience of reef habitats. In Chapter 4, I present the findings from the survey of community

perceptions and adaptations using local indicators of social resilience. In the final chapter I synthesise

the findings of Chapter 3 and 4 within the context of reef resource and livelihood management in

KNP. Management implications are discussed as recommendations for the working resource

regulation policies in KNP and wider implications for coral reef conservation in the Coral Triangle

region.

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The concept of resilience has been used in ecosystem studies since the early 1970s (Holling

1973) and has become a popular framework for describing links between socioeconomic and

ecological systems (Folke 2006). Along with its rapid theoretical development (Brand & Jax 2007),

resilience has been a fundamental point in understanding ecosystem behaviour, including coral reef

studies (Bellwood, D et al. 2004; Hughes et al. 2003; Hughes, Rodrigues, et al. 2007). However,

measuring ecosystem resilience is a complex task, particularly to reef managers in developing

regions. This is particularly due to the fact that less specific management guidelines having been

available as well as the need to address the complex processes involved [e.g. species interaction

between trophic structures and functional diversity (Bellwood, DR, Hoey & Choat 2003; Nyström,

Folke & Moberg 2000)]. In this chapter, Karimunjawa National Park (KNP) is used as a case study

area where reefs are dominantly protected by a restrictive policy based on conservation zones.

However, the designation of the latest 2004 marine zoning policy in KNP was a response limited to

the changes and alerts resulting from issues of local fish depletion and the related unsustainable

practices. Only a small protection zone has been designated relative to the total area (BTNKJ 2004).

Currently the KNP conservation framework has not yet included a deliberate ‘systems perspective’

approach or tools that can inform managers about the vulnerability of the reef system to future

environmental changes or hazards in order to find a specific management approach or intervention

that could promote ecological resilience to these disturbances.

This chapter examines the applicability of ecological resilience modelling in providing a

viable basis for evaluating the outcome of different management decisions in KNP, particularly how

local man-made disturbances are affecting the processes of the reef system. The model is built partly

based on the work by Mumby et al. (2007) and uses coral reef data obtained in KNP (Ardiwijaya,

Kartawijaya & Herdiana 2007; Ardiwijaya, R. L. et al. 2008; Marnane, Ardiwijaya, Pardede, et al.

2004; Marnane et al. 2005; Marnane, Ardiwijaya, Wibowo, et al. 2004; Wibowo, Joni T 2006) while

referring to data from relevant literature from other regions. The purpose of the model was to develop

a informative tool useful to managers to assess reef resilience (meeting minutes, KNP, Diponegoro

University and the University of Queensland, 23 September 2008), rather than a tool to accurately

simulate the complex behaviour of reef dynamics. The study was being developed to address several

key questions stemming from the meeting such as:

! %$

1. How can we aid local reef managers to explore possibilities of coral reef habitat response to

different levels of local disturbances given by limited ecological data?

2. How can we aid reef managers to better understand the impact of local disturbances to reef

processes and provide guidance to more resilient future coral reef habitats?

The study was an effort to provide a scientific and practical means of managing reef resilience

to support prioritization of management incentives in KNP. Its focus is on effects of fishing and

associated physical disturbances to the reef system processes, exploring different outcomes of reef

habitat conditions. It is designed to describe options for changes in fishing practices and management

interventions that can help avoid undesirable phase shifts and other semi-permanent ecological

change. The model can also be used as a learning aid where managers can ask questions relating to

the sensitivity of the systems to a range of environmental scenarios with the intent to work out how

management strategies can prevent or mitigate negative outcomes (e.g. herbivorous fish population

management, protection priority of vulnerable reef habitat).

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In August 2008, we (S. Afatta, K. Anthony, J. Maynard, L.F. Anggraini and D. Haryanti)

conducted a set of field surveys within the marine zonings at KNP. Its purpose was to get a

description of the recent condition of reef habitat within and outside the KNP zonings as well as

partial indications of reef resilience based on fish assemblage (e.g. certain fish trophic species

depletion due to exploitation (Dulvy, Freckleton & Polunin 2004)) and reef benthic structure (e.g.

presence of key functional reef fish associated with benthic algal cover (Bellwood, DR, Hughes &

Hoey 2006)). Surveys took place at 14 in-shore reef sites associated with Karimunjawa and Kemujan

main islands (Fig. 3.1). The reef sites selected were indiscriminate of park marine zonings. It include

both areas that are protected and unprotected from fishing activity within the National Park

boundaries. The sites were selected reef areas considered as favourable in-shore fishing grounds for

residents of the near dwellings in Karimunjawa and Kemujan main islands (pers. comm. Sutris

Haryanta, National Park Field Officer; Pak Darman, local resident and skipper, 2008). Another less-

populated region of Parang island district in the National Park boundaries was not surveyed due to

weather and logistical constraint at the time of survey. The surveys are (1) rapid visual census of the

abundance and distributions of reef fish; (2) fine-scale surveys of benthic groups and substrate

quality; (3) photographic surveys of visual signs of human impacts and resilience indicators.

! %%

The fish survey used three repetitions of timed-swims which each covered an approximately

50 x 5 meter belt transect in both the reef crest (3-5m depth) and reef slopes (7-9m depth), covering a

sample of approximately 750m2 per site (English, Wilkinson & Baker 1997). Reef fish were visually

identified and noted for their size-length in situ based on family groups of predators (e.g. Serranidaes

or ‘Groupers’, Lethrinidae or ‘Wrasses’, Lutjanidae or ‘Snappers’) and herbivores (e.g. Scarridae or

‘Parrotfishers’, Siganidae or ‘Rabbitfishes’) (Allen et al. 2003). Each group was divided into three

size-length visual estimation categories of 0 to 10, 10 to 20, and 20 to 30 centimetres. Fish abundance

for each size-length category per site was calculated from the mean total abundance of the three timed

swims (Fig. 3.2).

Figure 3.1. Fourteen reef sites surveyed in Karimunjawa and Kemujan island inshore reefs.

For the benthic substrate surveys in the reef crest habitat (depth of 3 – 5 m) of each site, we

took 3 sets of 10 digital photos of 1 x 1 m quadrate transects. The quadrate transects was placed

haphazardly with approximately 5 meters distance in-between. The sampling covers approximately 30

m2 of reef crest area per site. Coral environment within the fore reef habitat (depths of 5 – 15 m) was

not surveyed because SCUBA diving permission in the conservation zones was unable to be obtained

until the time of survey. The purpose was to obtain representative data of the benthic substrate

! %&

composition and condition of each site. For each quadrate transect photo, 36 random points of interest

(RPI) were digitally overlaid within quadrate frame (36 points/m2) using CPCe (Coral Point Count

with Excel Extension) software (Kohler & Gill 2006). The designated number of RPI sampled per

quadrate was for the purpose of data processing efficiency, yet, acquiring a reliable quantitative

description of each benthic category cover (1080 RPI within a ± 30 m2 belt transect per site) (Dumas

et al. 2009). The proportion of each benthic categories sampled within the total RPI sampled (36) was

treated as the relative percentage of cover for each quadrate. Microsoft Excel software was used to

calculate descriptive statistics and develop graphs. Major benthic categories visually observed were

Hard Corals; Non-Scleractinian Corals; Grazing Invertebrates; Other Invertebrates, Fleshy

Macroalgae; Other Macro/micro-algae; Settable Substrate; and Sand, Silt, and Sediments (For

descriptions see Table 3.1).

Table 3.1. Descriptions of benthic substrate categories visually sampled in each quadrant transect photo.

Benthic substrate Description Hard Coral

Scleractinian corals grouped by their growth forms such as Branching, Encrusting, Foliose, Massive, Mushroom, Sub-massive and Tabulate corals. (Veron, J 2000).

Other Corals Non-scleractinian corals such as Soft Corals (Xenia sp., Sarcophyton sp.), Fire Corals (Millepora sp.) (Veron, J 2000).

Grazing Invertebrates Sea urchins (Diadema sp.).

Non-grazing Invertebrates

Sponges (Encrusting, ‘Upright’ sponges growth forms) and Other Invertebrates (such as Sea Stars and Sea Cucumbers).

Fleshy Macroalgae Seaweeds or ‘Upright’ macroalgae >10mm height of local genera such as Caulerpa sp., Turbinaria sp., Sargassum sp., Padina sp. (BTNKJ 2008; Diaz-Pulido & McCook 2008).

Other Macro/micro-algae

Algaes that facilitate coral settlements and reef construction and cementation, which includes sub-categories of: Crustose Coralline Algaes and Calcareous Algaes (e.g. Halimeda sp.); visually distinct clumps of Filamentous Turf Algaes, including those overlaying other substrates on top of either living/dead corals or rubbles). (Diaz-Pulido & McCook 2008).

Settlement (‘space’) Providing Substrates

Recently dead corals (corals that have lost icoloration and have distinct early signs of algae overgrowth), Rocks (dead corals with deformed colony structure) and Rubbles.

Unsuitable substrate Trapped sediment, sand/silts including those overlaying other substrata.

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At the time of survey, fish survey showed a relatively low mean abundance of predatory reef

fishes (less than 10 counts) in all size-length categories considering the extent of the area surveyed.

Among the higher trophic group, Labridae (Wrasses) was the commonly found family with the

presence of economically desirable families such as Caesioneidae (Fusselliers) and Serranidae

(Groupers) being almost non-existent throughout the area surveyed. For herbivorous reef fish, such as

the Scarridae (Parrotfishes) and Siganidae (Rabbitfishes) families, the highest abundance (ranging

! %'

from ±35 – 40 fishes) was found in two buffer zone sites (Sintok East and Tanjung Gelam) and the

least incidence in other sites varied from 0 to 20 (Fig. 3.2). Additionally, a time-series survey from the

Wildlife Conservation Society (WCS) in Karimunjawa had described a trend in the decline of both

herbivorous abundance and biomass since the latest zoning regulations were enacted in 2004 to 2008

(Ardiwijaya, R.L. et al. 2008). Moreover, the majority of herbivorous reef fish, such as the Scaridae

family, were from 10 to 20 cm in size-length. This is relatively lower than the general adult size

lengths of Scarrids, such as the locally common Scarrus ghobban that normally ranges between 30-50

cm (Ardiwijaya, R. L. et al. 2008; BTNKJ 2008; FishBase 2010). From this, I suspected that past in-

shore reef fishing activity might have contributed to the decline of the higher reef fish trophic, such as

locally preferred predatory reef fishes. As they become rare, on the lower trophic, functional species

such as herbivorous reef fish that are important to maintain algal growth on the reef are becoming

more favourable to the fishers.

Results from the benthic survey showed that other than Tanjung Gelam, hard coral cover at all

sites varied from around 40% – 60% of cover (Fig. 3.3). Most of these sites were likely

counterbalanced with a proportion of suitable substrate for settlement such as dead corals and rubble

that were also varied in its cover proportion. Fleshy macroalgae were in low abundance across all

sites with the highest less than 10% of cover in Cemara Kecil. This included other coexisting

macro/micro-algae such as a substantial proportion of calcareous algae for instance Halimeda sp. and

distinct filamentous turf algae (e.g. Cemara Kecil, Tengah, Menjangan Kecil); sea urchin (Diadema

sp.) barrens (e.g. Legon Boyo, Legon Tole, Tanjung Gelam), and encrusting sponges (e.g. Tanjung

Gelam).

Due to the one-time nature of the survey, the past trajectory of the growth of the living

substrates (e.g. seasonality of algae) was not explained; therefore, inferences about resilience

indications based on community dynamics are strictly limited here. However, using live hard coral

cover as a proxy for habitat quality, variation occurred irrespective of any of the site protection levels

of zoning. This suggests that there are other ecological aspects that are involved in regulating

community structure and resilience such as herbivory, nutrient level, and site connectivity (McCook,

L et al. 2009; Smith, JE, Smith & Hunter 2001; Sotka & Hay 2009), which have not been fully

incorporated in past management approaches. At the time of survey, fleshy macroalgae cover was

relatively low compared to hard coral, which indicates there may be other herbivores that compensate

for the functions of the threatened herbivorous reef fishes (Aronson & Precht 2000) as well as effects

from the nutrient factor (McCook, LJ 1999). The presence of rocks and fragments of recently dead

corals (for description of terms refer to Table 3.1) also indicate intensive past disturbance to the

surveyed sites of either natural or human-influenced origin.

! %(

Figure 3.2. Mean fish abundance of herbivorous and predatory reef fish for each size-length categories in sampling sites during preliminary assessments in Karimunjawa, August 2008. Sites in each habitat (reef crest and slope) are clustered to their designated zonings (B=Buffer, C=Core/No-take, P=Protection, TU=Tourism Use, TF=Traditional Fishing). Mean abundance measures were calculated from three replicates of 50 x 5m belt transects. Colours represent three size length categories of <10, 10-20, and >20 cm in blue, red and green, respectively.

! %)

Figure 3.3. Mean percentage cover composition of each benthic category per site based on preliminary biophysical assessments in Karimunjawa, August 2008. Reef crest habitat of each sites are clustered into their designated zonings (B=Buffer, C=Core/No-take, P=Protection, TU=Tourism Use, TF=Traditional Fishing). Cover composition percentage and mean point count was measured from 3 sets of 10 quadrate transects, where 36 random points of interest were sampled for each transect (nRPI=360 x 3). Sintok East was excluded from the site comparison due to missing 4 quadrate transect photo samples.

From visual documentation during the survey, most herbivorous reef fish schoolings

encountered were relatively small in size-length (Fig. 3.4, B), while documenting larger fishes was

relatively uncommon (Fig. 3.4, A). Regarding pressures from human activity, grazing reef fishes,

such as parrotfish, were found to have local economical value as a fish catch, however, their role as a

local fishing commodity either for subsistence or trade was not explored further (Fig. 3.4, C).

Furthermore, building materials such as concrete leftovers were commonly used as anchors (Fig. 3.4,

D) in the subsistence fishing activity (e.g. handlines, traps) which could cause direct physical damage

to living coral (Fig. 3.4, E). Habitats suggested to be in a poor state of resilience were found in several

sites, though they were patchy, with features such as signs of macroalgae overgrowth (Fig. 3.4, F, e.g.

Legon Tole) and barren except for sea urchins (Fig. 3.4, G, e.g. Cemara Kecil).

! %*

Figure 3.4. Selection of photos documenting preliminary key findings taken during the baseline

survey in August 2008. Presence of large sized (above 30cm) Parrotfish was rare (A), where most of the schoolings were relatively small-sized (B). For specific reasons, herbivorous reef fish, such as the Scarridae family group are a local fish target (C). An example of a rock anchor used (D), and one that was left by fishermen, with demolished coral underneath (E). Sign of resilience loss in some sites where macroalgae (F) and sea urchin domination were apparent (G).

Supported by the above preliminary findings, though they did not provide substantial

interpretation of the past biophysical trend of the sites, it was apparent that there has been a series of

key local stressors that has not yet been given full attention in the local reef management process.

Issues include: (i) overfishing that is threatening the lower fish trophic level such as the herbivorous

reef fishes and (ii) direct anchoring on the reef bed such as the use of rock anchors as an additional

threat of physical damage to the living benthic substrate. These two issues were then further analysed

using mathematical modelling, paying attention to their impact on the reef benthic configuration and

relevant remedial action in management. As mentioned earlier in Chapter 2, from the field survey we

found visual signs of (iii) nutrient enrichment and sedimentation presumably due to coastal pollution

from village household waste and sewage (see section 2.2.2.4, Fig. 2.6). However this particular

threat to reef was not explicitly addresses in the modelling study, thereby it remains as limitation of

our modelling investigation (see Model Output Limitation, section 3.4). The reason was due to both

limitation in survey logistical constraints and secondary data to obtain recent information related to

the water quality of the study area (i.e. sediment rate, nutrient concentration). Yet, this does not

negate the fact that the control of threats related to domestic pollution from segregated dwellings

should also be the priority and a tractable issue relevant to the management focus of the park agency.

! %+

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Ecological modelling was considered as an appropriate tool to facilitate exploration into the

possible future conditions of the reef sites in KNP. Though it may not fully assess the health of a

complex reef system, as current local biological observational data is limited for specific meta-

analytical exploration, modelling can be an effective process to identify knowledge gaps and

prioritization in management options. In this study, ecological modelling was used to simulate the

benthic reef community response to different scenarios of grazing and rock anchoring intensity over a

10 to 30 year management timeframe. In this study, the model was based on the framework by

Mumby (2006b) and incorporates both the understanding of ecological processes (Done et al. 1996)

and disturbance sensitivity (Tanner, Hughes & Connell 1994) of the critical functional groups of

corals, macroalgae and reef fish (Bellwood, DR et al. 2004). Model simulations produce projections

of reef dynamics and alternative states under different disturbance scenarios. The model was

parameterized using conditional probabilities of disturbance responses such as loss of grazing, coral-

algae interaction and human-related physical damage (McManus, J. W., Reyes & Nanola 1997;

Mumby, P. 2006b; Mumby, P., Hastings & Edwards 2007; Saila, Kocic & McManus 1993) (Fig. 3.5).

Figure 3.5. Conceptual diagram depicting the layout of the benthic community dynamics model and key stressor functions influencing each community group. Two benthic groups of hard coral and fleshy macroalgae interact and compete for benthic space, which subsequently determines the main composition of the reef. Grazer loss due to overfishing leads to reduced mortality of macroalgae, thus growth and survivorship is enhanced whereas physical damage from rock anchoring causes the opposite effect.

The model incorporates a non-spatial projection of key benthic groups in response to a range

of environmental variables. The simulated coral-algae interaction assumes that space (turf)

availability of a reef quadrate is constant and equals 100% (Fig. 3.6). The quadrate space can be

occupied by several types of substratum in which its proportions are results of mathematical

! %,

calculation using differential equations. It quantifies the relative abundance of three major space

occupants of the reef benthic community: Hard Coral (C), Fleshy Macroalgae (M), and Turfs (T) in

differential equations (Eq. 1, 2, 3) using a modified mathematical approach suggested by Mumby

(2006). New colonization is due to growth or recruitment into free space (Eq. 3, Table 3.2).

!Figure 3.6. Conceptual diagram of benthic space occupation by living substrate groups assumed in

the model. Space is assumed to be a mix of settable substrate such a recently dead coral, rubble and rock for which turf algae provides foundation layers for the settling substratum. The model generalized three groups of substratum to be simulated, these are hard coral, fleshy macroalgae and other substrates.

The disturbance functions (e.g. grazing loss on macroalgae, hard coral mortality) were

expressed as non-dimensional functions as well as demographic responses for each community group

(e.g. the relative abundance of coral and macroalgae). The mathematical foundation is based on a

Lotka-Volterra model of inter-specific competition (Gotelli 2001). The dynamics of macroalgae is

determined by its capacity to overgrow coral in competition (!M-C MC) and the remaining proportion

after grazing (1 - dGM), assuming its natural establishment in any bare space/turf colonization (!M-

TMT). As for hard corals, new colonies may also establish themselves into free space (assuming

recruitment / survivorship) (!C-TCT) with hard coral loss from mortality: natural (grazer forage bite)

combined with damage from rock anchoring (dP+AC) and space for growth due to extirpation of

macroalgae (- !M-C MC). Consistent with Mumby (2007), the model can be expressed as:

(1)

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(2)

(3)

TNYN _,+"%(9.0.4")"0$P.)$,&(

The model was parameterized using conditional modifications of data from the literature in

other regions such as the Red Sea, the Caribbean, Jamaica, the Great Barrier Reef, and Curaçao

(Dutch Antilles) combined with disturbance scenario settings that approximate both the local

biological and social-economic environments of Karimunjawa. From the literature of different

regions, I set up probabilistic values for each variable by selection of the best-available species type

as the closest representation to each benthic substrata, which involved converting data values and

units to the spatial and temporal dimension of the model (for details for benthic components, model

conditional settings and cited literature refer to Tables 3.2 and 3.3).

Spatial and temporal dimension - Modifying the work by Mumby et al. (2006), the

simulation model represents a square space that approximates 0.25 m2 of the reef benthic area that can

be occupied by a mixture of substrata (see Table 3.3). For each time step of simulation, the interaction

of these benthic groups was iterated up to one thousand times so that consequent means and variance

can be calculated regarding benthic occupant proportions (relative abundance). The simulation

updated the composition of the cell in 6 month time steps because of the bi-seasonal variation of

Karimunjawan waters (western and eastern monsoons, (BTNKJ 2004)).

Space occupants – In the simulation, three benthic groups of hard coral, fleshy macroalgae,

and turf algae were determined as the major dynamic occupants in terms of their proportion of

occupied space within the cell. The relative abundance (proportion in space/cell) of the first two

groups would be used as a quantitative measure of a reef habitat condition or status. I set up five

putative habitat categories to help define starting conditions (input setting) and projected benthic

composition (simulated output), using the maximum and minimum value of benthic group percentage

cover proportions from the 2008 biophysical assessment data (Table 3.1). Benthic substrate categories

and their conceptual behaviours in the model were initially listed to determine which benthic

components were included or excluded in the simulation (Table 3.2). Afterward, a literature review

was conducted to define the parameter values of ecological and environmental variables (Table 3.3).

! &$

Table 3.2. Benthic state category settings used for simulation input and output based on a range of percentage of cover proportion data, part of the biophysical assessment in Karimunjawa in August 2008 (see Figure 3.3, Appendix 2).

Habitat State Proportion in space ( x 100% )

Hard Coral Fleshy Macroalgae

Poor 0 - 0.23 0.35 - 0.7

Moderate > 0.23 - 0.46 > 0.23 - 0.46

Good > 0.525 - 0.7 0 – 0.23

Table 3.3. Categories of substratum and the conceptual behaviour applied in the simulation.

Substratum Description Reef state determinants / Major reef occupiers

Scleractinian coral (hard corals) (e.g. ‘Tabulate’ growth forming coral such as Acropora spp. to represent spawning corals, and non-branching growth form coral such as Porites spp. for brooding corals)

Hard corals here include Scleractinian corals which are divided into two groups based on their growth forms to represent different reproduction strategies of the species, thus differing mortality, growth, and survivorship (see Table 3.3). Two groups of hard corals were initially defined only for referential purposes in literature exploration to place values on the range of growth and recruitment; however, hard coral would be treated as a single input in the simulation. Fleshy macroalgae refers to those of >10mm in height excluding calcareous articulated ones such as Halimeda sp.

Fleshy macroalgae (e.g. Caulerpa sp., Padina sp.)

Minor reef occupiers

The group includes non-scleractitian corals (e.g. soft corals, fire corals), calcareous macroalgae groups (e.g. Halimeda sp.). The group could randomly reduce the availability of settlement space proportion, however, this effect is indirectly included in parameters related to coral-macroalgae interaction.

Settlement / space providers

Cropped algae (‘Pro-resilience’ algae such as Filamentous Algae, Crustose Coralline Algae, Short Turfs)

These substrates provide settlement space for major reef benthic occupiers. The presence of bare space can initiate early settlement space for epilithic algae to lay the foundation for settlement. Initiated from cropped fleshy macroalgae if a grazing effect is present. Bare space (e.g. dead coral, rock, rubble)

Unsettleable and ungrazable substratum The group includes sand, sediment layers, and silt, which are ignored in the simulation.

Natural mortality – Fleshy macroalgae loss in each time step was assumed due to the

probability of seasonal die-off in each year. Data from the island of Seid Seikh, in the Red Sea

indicated that macroalgae cover decline could reach to 30% in 6 month period (Ateweberhan,

Bruggemann & Breeman 2006). Therefore, this was the maximum value set. This study was chosen

because there was the least differentiation in sea surface temperature variability compared with the

northern Java Sea waters (around 28 – 33 degrees Celsius) (Ateweberhan, Bruggemann & Breeman

2006; Putri 2005). For hard coral, the level of mortality occurring in addition to macroalgal

overgrowth could reach 2% of the colony per time interval (based on pubescent corals (three species)

in the Caribbean (60-250 cm2 in size) (Bythell, Gladfelter & Bythell 1993)).

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Disturbance mortality – Algal removal due to fish grazing was simulated based on a

predicted maximum value of 30% of the reefs being maintained in a cropped state per 6-month period

[modelled from Long Cay (LC), the Caribbean]. This value was selected seeing that there was a

relatively small difference in the recorded maximum parrotfish biomass from the Long Cay region

(1998 data, ~220 gr/25m2) compared to Karimunjawa (WCS 2007 data; ~231 gr/25m2, average from

43 reefs) (Ardiwijaya, R. L. et al. 2008; Mumby, P. 2006b). The worst case overfishing scenario

assumed that the herbivorous fish population has been reduced by 5% in a 6 month period (Mumby,

P. 2006a). However, this assumption excludes the possibility that the dominant grazing species in LC

such as Sparisoma viride (epilithic algae consumer (EC)) and Scarus vetula (coral excavator (CE))

could have a three to four-fold mean foraging capacity (bite size, bite rate) compared to species in

KNP such as Scarus rivulatus (EC/CE) and Scarus ghobban (EC) (Bellwood, D. & Choat 1990;

Bruggemann, Van Oppen & Breeman 1994).

Hard coral loss was simulated as the product of the probability of anchor hit and the

proportion of loss (extent of damage). The maximum value for risk of an anchor impact was a product

of probability based on two conditions. Firstly, the average of the maximum fishing days was 6 days a

week (~86% of each 6-month time step) and secondly, around 60% of fishermen conducted near-

shore artisanal fishing (e.g. using handline, reef net, muroami, spear, trap) (survey of 102 respondents

representing households (Wibowo, Joni T. 2006)). The relative percentage cover loss of hard coral

due to physical impact by anchors is based on a simulation experiment of a moderate-sized boat

anchor falling into a hard coral by Marshall (2000). Marshall (2000) mentioned “the relative

percentage of loss was measured as the absolute change of planar area of a coral colony divided by

the initial planar area before physical treatment”. The overall mean of planar damage was modified

as the probability of maximum hard coral loss (dANC) due to damage, whereas for massive corals it

was 5% (dANC=0.05) damage and 100% (dANC=1) for branching corals. Various intensity of

anchoring was applied for the simulation by adjusting the value of fishing trips and randomizing the

probability of hit and proportion of loss.

Space occupation (growth and recruitment) – The probability that fleshy macroalgae (M)

fill a space that is occupied by turf (T) is due to the product of growth rate of M and the competitive

strength of hard coral (C) over T. Cropped algae (recently grazed) have an up to 100% probability of

overgrowing space if there was zero grazing for the next one year and up to 70% with zero grazing for

the next 6 months [e.g. genus Lobophora sp. (De Ruyter van Steveninck, E & Breeman 1987)].

Another caged experiment from Orpheus Island, Great Barrier Reef, showed that for an

approximately six-month duration, the absence of grazing fish above ~15 cm size/length led to a ~

20% increase of algal cover. Macroalgae growth rate over cropped algae (space) was simulated

assuming macroalgae can overgrow living coral (Hughes, Rodrigues, et al. 2007). Macroalgae can

! &&

overgrow coral at the rate of 0.0004 m2 per 6 month, converted from an overall mean of 8 m2 per

annum (Mumby, P., Hastings & Edwards 2007; Nugues & Bak 2006).

The probability that C fills a space that is occupied by T is the product of the growth rate of C

and the competitive strength of C over T. The probabilistic value of coral occupying space in the

model was based on the adjusted recruit density per cell (n / space) in one six-month (t) cohort of

~0.1 individuals / 0.25 m2 for brooding corals (e.g. Porites sp.) and at least ~0.07 individuals / 0.25 m2

which was significantly lower for spawning corals (e.g. Agaricia sp.) (Mumby, P. 2006b). The

simulation allows hard coral to overgrow fleshy macroalgae (Jompa & McCook 2002). It is also

simulates hard coral growth using constant values for the lateral extension rate of brooding corals (4 x

10-5 m2/6-month) and a slightly faster rate for spawning corals (45 x 10-5 m2/6-month) based on

median rates calculated from 6 coral species (genus Poritidae and Agariciidae) from the Caribbean

region (Mumby, P., Hastings & Edwards 2007). These values were then treated as a range, which

would be randomly assigned during computation.

Macroalgae-Coral Interaction – For each time step, the model calculates the natural

probability of macroalgae interacting with corals which was calculated using an equation developed

by Mumby by best-fitting the data of Hughes in Jamaica (Hughes 1994; Mumby, P. 2006b). The

prevalence effect of coral was also applied when local hard coral cover is high (! 50%), thus the

coral-algal competition reduces the rate of macroalgal growth by up to 25% (De Ruyter van

Steveninck, ED, Van Mulekom & Breeman 1988; Jompa & McCook 2002; in Mumby, P. 2006b).

Hard coral recruit survivorship was reduced by 50% if macroalgae occupies more than 60% of the

proportionate space, based on studies of Lobophora sp. and Dyctiota sp. (Box & Mumby 2007)).

While there is no comparable data in KNP, this finding would appear relevant because of the

incidence of these benthic groups in KNP.

Table 3.4. Options of initial set of parameter values adjusted from the literature of other selected regions. Input values were set either as fixed, a range, or as an equation in which some would be set as benchmark values in the sensitivity analysis (See Table 3.4).

Symbol Model Component Input Value Options Reference

Macroalgae Mortality

Macroalgae mortality

Baseline natural macroalgae mortality

(Ateweberhan, Bruggemann & Breeman 2006)

Macroalgae mortality due to grazing

(Ardiwijaya, R.L. et al. 2008; Mumby, P. 2006a, 2006b)

Coral Mortality

Coral mortality

dGRmax = ~ 0.3dGRmin = ~ 0.05

dC

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Symbol Model Component Input Value Options Reference

Natural coral mortality

(Bythell, Gladfelter & Bythell 1993)

Probability of risk of anchor hit to coral

PANC(MAXIMUM) = 0.86 x 0.6 = 0.516 ! (~0.5) (Wibowo, Joni T 2006)

Proportion of coral loss due to anchoring (Marshall, PA 2000)

Colonization of macroalgae into space

Space occupation by macroalgae

(De Ruyter van Steveninck, E & Breeman 1987)

Macroalgae lateral growth

Proportional growth relative to individual cell size:

If the growth relativity to space size is ignored, then as a ratio:

(Mumby, P., Hastings & Edwards 2007; Nugues & Bak 2006)

Colonization of coral into space

Space occupation by coral (recruitment) (Mumby, P. 2006b)

Coral lateral growth (Mumby, P., Hastings & Edwards 2007)

Macroalgae – Coral Interaction

Effect of macroalgae on corals

(Hughes 1994; Mumby, P. 2006b)

Effect of corals on macroalgae

(De Ruyter van Steveninck, ED, Van Mulekom & Breeman 1988; Jompa & McCook 2002; in Mumby, P. 2006b)

Effect of macroalgae on corals (Box & Mumby 2007)

Model limitations, strengths and applications – The model presented in this chapter is not a

full representation of the complex process in the reef system, despite the fact that it was designed to

describe the health of a reef affected by local scale disturbance variables. For example, some

ecological aspects in the regulation of the benthic community were excluded, such as bottom up

forces of nutrient flux, that might simultaneously affect herbivory (Lapointe 1999; Littler, Littler &

Brooks 2009; McCook, LJ 1999), as well as external recruitment related to site connectivity.

Regarding the spatial magnitude and intensity of simulated disturbance, scenarios of coral mortality

!SP"M min = 0.2!SP"M max = 0.7

PANC

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due to anchoring, for example, may not represent the actual situation that is unknown. This was due to

insufficiency of socioeconomic datasets that could fine-calibrate input parameter values such as

fishing catch effort and selectivity to specific species group (Jennings & Polunin 1997; McClanahan,

T 1995) as well as the local boating profiles (McManus, John W., Rodolfo B. Reyes & Cleto L.

Nañola 1997; Saphier & Hoffmann 2005).

In this model, the presence of other benthic taxa such as sponges, soft corals, and benthic

invertebrates (including other forms of algae) that may render alternatives of benthic composition by

gaining space from coral or macroalgae loss (McManus, JW & Polsenberg 2004; Norström et al.

2009) was not involved in simulated benthic community interactions. Moreover, reef system changes

due to perturbations such as from disease, hurricane, mass bleaching and outbreaks have not yet been

considered in the disturbance variable. Thus, specifically, as benthic communities are dynamic, the

output of the model does not imply that the composition of the simulated major benthic group is the

predominant qualitative indicator of the possible reef condition in the future, nor that the presence of

macroalgae is the main descriptor of the extent of disruption of the reef (Bruno et al. 2009; Mumby,

PJ 2009). For these reasons, in general, the applicability of the model output may not be simply

transferrable to other regions or sites or time periods. Likewise, selected and defined parameters were

specific to reef management issues in KNP.

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A parameter sensitivity test was conducted to assess which parameters contribute most to

output variability. Regarding the primary use of the model as a predictor, this is important since

model validity is assessed by knowing which parameters in the model are more or less influential, as

well as which are redundant to the model outcome (Jørgensen & Bendoricchio 2001). This step was

done after the set of parameter value options was defined (see Table 3.3). To achieve this, a one-

factor-at-a-time (OAT) sensitivity analysis method was chosen, based on reasons of practicality for

both ease of calculation and graphical interpretation of results (Frey & Patil 2002; Hamby 1995). The

OAT test basically examines the relative change of model output by systematically perturbing

parameter values by a fraction of their base value (for the OAT summary see Table 3.4). For this

assessment, parameter input values were set either as a single value or range of maximum and

minimum values used as a benchmark for gradual adjustment. Each state variables were tested both

with a single base input value and the adjustment values set either as the standard deviation (+20%

and -20% SD) or one-third add of quartile division for range value (1st distance) (for full OAT results

see Appendix 3). The percentage difference of relative abundances in base output value relative to

from the adjusted values is defined as the ‘Sensitivity Index’ (Hamby 1995). In the study, all

mathematical calculations and graphical plotting were generated by executing programming script

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using MATLAB® R2008b software (The MathWorks™) (for M-File simulation scripts refer to

Appendix 4).

Table 3.5. Summary of parameter sensitivity assessment showing mean relative abundance output using base value and adjusted values. State variable sets using single base value were adjusted based on ±20% of SD. Those using range base values (maximum or minimum) were adjusted based on one-third adds. M and C is for Macroalgae and Coral output, respectively. In the computation, a randomizing effect was applied for certain state variable types. The computation was based on 100 iterations of a 6-month time step projection of 35% each of C and M as the starting condition. (See Appendix 3 for the complete assessment).

State variables Adjustments Parameter Input Value

Output Variables

Rel. abundance

Sensitivity Index (%)

Space Occupation by Macroalgae

Base (Min.)

0.2 M 0.155 C 0.310

1st distance 0.325 M (t+1) 0.155 0.003 C (t+1) 0.310 0.000

Space Occupation by Coral

Base (Min.)

0.07 M 0.176 C 0.307

1st distance 0.3025 M (t+1) 0.176 0.000 C (t+1) 0.307 0.001

Macroalgae Grazing

Base (Max.) 0.3 M 0.176 C 0.307

1e

0.2375 M (t+1) 0.197 12.459 C (t+1) 0.307 0.000

Baseline Macroalgae Mortality

Base

0.3 M 0.176 C 0.307

±20% SD

0.36 M (t+1) 0.155 11.960 C (t+1) 0.307 0.000

Macroalgae Lateral Growth

Base

0.0004 M 0.155 C 0.310

±20% SD

0.00048 M (t+1) 0.155 0.004 C (t+1) 0.310 0.000

Baseline Coral Mortality

Base

0.02 M 0.176 C 0.307

±20% SD

0.024 M (t+1) 0.176 0.000 C (t+1) 0.306 0.455

Coral Lateral Growth

Base (Min.)

0.00016 M 0.176 C 0.307

±20% SD

0.000165 M (t+1) 0.176 0.000 C (t+1) 0 0.000

Anchor Hit Probability

Base

0.5 M 0.155 C 0.254

±20% SD

0.6 M (t+1) 0.155 0.000 C (t+1) 0.254 0.183

Anchor Damage

Base (Min.)

0.05 M 0.155 C 0.308

1st distance 0.2875 M (t+1) 0.155 0.000 C (t+1) 0.299 0.121

PANC

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Calculations were made to assess the extent to which changes in the input parameters would

affect the relative abundances’ divergence from their baseline values. This was due to the focus of the

model in exploring the behaviour of the simulated system rather than estimating threshold values that

trigger output variation. Based on the sensitivity index, variables related to coral lateral growth were

considered non-sensitive to the output compared to other state variables (SI=0.000). This might also

be due to limitation in converting growth value data from selected literature, which has a different

measurement period to that of the modelled time-step, though unit conversion has been made to

match spatial and temporal scales. In this case, the two-dimensionality of the model requires data of

lateral metrics for growth in a 6-month time step. As the primary consideration was selecting taxa that

might closely represent the general local benthic group for Karimunjawa, coral and microalgae data

with similar specified measurements was not found. The model was more sensitive to changes in

input parameters to macroalgae (in terms of grazing) than for corals (in terms of anchoring

disturbances). Accordingly, this would be taken into consideration when setting values for

disturbance combination scenarios in the model’s implementation. In general, the nominal approach

of the test showed that the stressor function has a greater influence on the model output than the

space-coral-algae interaction function.

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In this analysis, graphical methods were used to visualize how disturbances of grazing loss due

to overfishing and coral damage due to anchoring are shifting the benthic community composition.

Two types of output data projections were used. The first was a projection of the benthic composition

change over time (P1) using the Monte Carlo (James 1980) approach (Figure 3.7, 3.8). The second

was a projection of the benthic composition frequency over time (P2) based on the Poisson

distribution (Consul & Jain 1973) approach (Figures 3.9, 3.10). For each projection, the first

disturbance setting applied was a scenario of the effect of three levels of grazing loss (P1-A, P2-A in

Figures 3.7, 3.9); the second looked at the effect of three levels of anchoring in a high grazing

situation (P1-B, P2-B, in Figures 3.8, 3.10), each setting was applied to three categories of reef

habitat. Habitat composition was projected on a decadal basis, which was relevant to the practicalities

of management in Karimunjawa (e.g. 15 and 30 year projections).

Reef categories were set at starting benthic compositions of ‘Good’ (10% M, 70% C),

‘Moderate’ (50% M, 30% C) and ‘Poor’ (70% M, 10% C). Grazing losses were set at three decreasing

levels of 20% (High), 10% (Moderate) and 5% (Low). Anchoring levels were set at 0.5 / 30% (Low),

0.4 / 37% (Moderate) and 0.5 / 58% (Low), for which the numerical values in each set refer to the

probability of hit and the proportion of damage, respectively. These were randomly generated as

pseudo-random (MATLAB® R2008b software (The MathWorks™))

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For a P1-A projection setting (Fig. 3.7), the gradual reduction of fleshy macroalgae grazing by

herbivorous reef fish affected the change of coral-algae composition over time. In the simulation, a

‘Good’ site that represents a coral-dominated reef habitat was found to be less impacted even by

grazing loss down to 5% (Fig. 3.7: Box A, B, C). The increase of grazing for a moderate habitat could

lead to an earlier sign of macroalgae control reduction (Fig. 3.7: Box D, E, F). As habitat quality was

further decreased from moderate to poor there is a much more drastic and earlier decline (Fig. 3.7:

Box G, H). Despite those transitions when macroalgae surpassing coral abundance in the shift was not

well visualized, in terms of the benthic community interaction, reduction in coral survivorship whilst

macroalgae is increasing was distinctly visualized. (Fig. 3.7: Box D, E, G). Among all site categories,

the recovering site (Poor) was found to be more sensitive, because of the ‘High’ grazing level that

was required to maintain coral survivorship (Fig. 3.7: Box G).

Figure 3.7. P1-A timeline projections of three starting point compositions of reef habitat: Good (10%

M, 70% C), Moderate (50% M, 30% C) and Poor (70% M, 10% C). Three scenarios of macroalgae grazing loss due to fishing in proportions of 20% (High), 10% (Moderate) and 5% (Low). Each time-step is the mean of outputs from 250 iterations of the 30-year projection (X-axis). The relative abundance (Y-axis) plot for coral and macroalgae is represented by red and green dots, respectively, with 95% confidence interval lines. The baseline mortality for both benthic groups is set as fixed using tested base values (Table 3.4). However, due to non-sensitivity, space occupation and growth parameter values were set as a random selection within the value range used in the OAT test.

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Figure 3.8. P1-B timeline projections of three starting point compositions of reef habitats: Good (10% M, 70% C), Moderate (50% M, 30% C) and Poor (70% M, 10% C). The grazing scenario was set as ‘best’ (20%). Anchoring levels were set at 0.5 / 30% (Low), 0.4 / 37% (Moderate) and 0.5 / 58% (Low), for which for which the numerical values in each set refer to the probability of hit and the proportion of damage, respectively. Each time-step is the mean of outputs from 250 iterations of a 15-year projection (X-axis). The relative abundance (Y-axis) plot for coral and macroalgae is represented by red and green dots, respectively, with 95% confidence interval lines. The baseline mortality for both benthic groups is set as fixed using tested base values (Table 3.4). However, due to non-sensitivity, space occupation and growth parameter values were set as a random selection within the value range used in the OAT test.

Using the P1-B projection setting, in general, Figure 3.8 depicts how short-term but frequent

physical disturbance by anchor use has affected coral survivorship at all site categories. In the best

grazing conditions and a shorter timeframe (fifteen years), the anchoring scenarios caused earlier

coral decline compared to the grazing effect in the P1-A setting (for comparison see Fig. 3.7, 3.8: Box

B) as well as the period required for macroalgae to start gaining over coral proportion (Fig. 3.7, 3.8:

Box E). In the P1-B projection, a high grazing level was shown to have a controlling effect to further

increase the level of macroalgae throughout the course of proportionate coral decline due to anchoring

impacts (Fig. 3.8: Box E, F, G, H). A similar projection setting was generated for ‘moderate’ and

‘low’ grazing scenario however, results were not presented considering the anchoring scenarios, on

! '-

the overall, generated similar yet, more deleterious effect to the trajectory to hard coral cover and the

opposite for macroalgae.

For the P2 setting, a colour contour plot (Anthony, 2008) was used to visually compare the

stochastic distribution of benthic composition between site categories. The first colour plot, using a

P2-A setting, generally showed that habitat composition tended to be distributed away from a coral

dominated state as grazing loss increased and habitat quality (coral-algae starting composition) was

lowered. In a shorter the ten-year simulation, for ‘Good’ reef, the increase of overfishing scenario did

not disrupt the trajectory towards a ‘healthy’ reef state as most of the occurrences of overfishing were

distributed in coral dominated reef areas (Fig. 3.9, Box A, D, G). However, a transitional trajectory

was observed when the reef site quality was lowered to ‘Moderate’, which is explained by the

distribution of benthic composition being altered partially towards ‘Moderate’ events as grazing loss

increases (Fig. 3.9, Box B, E, H). Moreover, for a ‘Poor’ site, the transitional trajectory was also

prompted to be at a high grazing level (Fig. 3.9, Box C), then the distribution of benthic composition

moved towards a coral-depauperate boundary as grazing decreased (Fig. 3.9, Box F, I).

Compared with the impact of grazing loss from P2-A, the P2-B projection result showed that

anchoring disturbance caused a more intense but dispersed perturbation of the distribution of benthic

composition at all site categories, even at a low level (Fig. 3.10, Box D, E, G, H). Similar to the result

from the P1-B projection, an increase of anchoring intensity affects coral replenishment by way of

reducing the likelihood of the reef to establish a higher hard coral cover state (for a ‘Moderate’ site,

Fig. 3.10, Box B, E, H). Among site categories, this situation occurs more prominently for a ‘Poor’

site as the distribution of low-coral cover was consistent as the anchoring level increased (Fig. 3.10,

Box C, F, I).

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Figure 3.9. P2-A colour plot projection of three reef habitats with starting point compositions of:

Good (10% M (X-axis), 70% C (Y-axis)), Moderate (50% M, 30% C) and Poor (60% M, 20% C), each marked with white crosshairs. Three scenarios of macroalgae grazing loss due to fishing were applied to the areas: 20% (High), 10% (Moderate) and 5% (Low). Each contour plot cell represents specific benthic relative abundance compositions relative to the axis. Each cell colour describes the frequency of occurrence of specific habitat compositions out of 250 simulated iterations, within a 10-year timeframe. The baseline mortality for both benthic groups is set as fixed using tested base values (Table 3.4). However, due to non-sensitivity, space occupation and growth parameter values were set as a random selection within the value range used in the OAT test.

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Figure 3.10. P2-B projection result of three reef habitats with starting point compositions of: Good

(10% M, 70% C), Moderate (50% M, 30% C) and Poor (60% M, 20% C), each marked with white crosshairs. The grazing scenario was set as High (20%). Three scenarios of coral mortality due to anchoring were applied with the probability of hits and the proportion of damage set at 5%~30% (Low), 40%~37% (Moderate) and 50%~58% (High).

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In general, habitat responses from the disturbance simulations exhibit particular reef system

processes that have been well documented in the literature. Habitat composition shifts observed in the

projections generally demonstrate that the combined effect of overfishing and direct damage of

artisanal fishing can alter reef habitats toward degraded assemblages (Knowlton & Jackson 2008;

Lokrantz et al. 2010; Mora 2008). In addition, the indirect effects of herbivorous reef fish removal can

increase algal cover with the consequent loss of corals (Bellwood, DR, Hughes & Hoey 2006; Hughes

1994; Mumby, PJ 2009; Sotka & Hay 2009). Thus, different points of return in coral recovery

simulate the reduction rate of herbivory, simulated as grazer fish loss, so that if a threshold was

exceeded, rebalancing attracting the system to coral-dominated can be difficult (Ledlie et al. 2007;

Mumby, PJ 2009; Mumby, P., Hastings & Edwards 2007). The preliminary attempt of this model in

assessing anchoring impact suggests that, even if grazing was optimum, direct and short-term

stochastic anchor damage (concentrated and patchy in the actual world) provides the potential to delay

or prevent coral from rebound (Rogers & Miller 2006).

In the short term, the subsequent predictions from this model could also be useful in

evaluating management (Costanza & Ruth 1998; Sutherland 2006), such as to review current

priorities for management investment in site protection. At the time of survey, most of the reef crest

area of the sampled sites was in 'good' category, except for Tanjung Gelam and Telaga North that in

'poor' and 'moderate' category, respectively. These categories were applied in consistent to the habitat

starting composition used in the simulation based on the hard coral and fleshy macroalgae

composition.

As an example of the model application for management, managers may infer that the

condition reef sites surrounding Karimunjawa and Kemujan Island were in the optimum condition in

terms of having low sensitivity to withstand possibilities of future loss of grazing and anchoring.

However, looking at biophysical factors, such as other substrate group composition, that may

augment or prevent the replenishment of living corals; most of the 'good' sites designated as

'traditional fishing zone' and 'tourism zone' have higher amount of 'unsettable substrate' relative to the

composition of substrates acting as space for coral growth. Therefore, despite their 'good' condition,

sites such as Legon Tole, Legon Boyo, Sintok Southwest and Ujung Lemu may have less potential of

recoverability given the residual benthic condition that might have been the result of past

disturbances. Thus, using the model as a proxy, managers can assume that current sites subject to

traditional fishing may likely to resist from the loss of grazing process associated to the overfishing of

herbivorous reef fish in the future. However, the designation of these sites as traditional fishing zone

! ''

may need to complement with management measures that can restrict or prohibit reef physical

damage caused by anchoring, since the devastating impact can be detrimental regardless to any site

category. Similar suggestion may be applied also to 'good' sites that were 'tourism use zone', however

with limited space for substrate growth, such as Indonoor and Tengah.

For example, existing reef sites with low coral cover such Tanjung Gelam might no longer

exhibit the buffer functions that were expected during the initiation of the 2004 zoning policy (i.e.

with previously high coral cover, operating as a reef fish spawning and aggregation site, with close

proximity to a main village (BTNKJ 2004)). Its close proximity to the main village suggests that the

area was prone to being fished in the past, as it was more easily accessible. Thus, also using the model

projections as a proxy, Tanjung Gelam, a 'poor' site is likely to be more sensitive to key local stressors

and may have higher potential of recoverably given with the composition of settlement providing

substrate at the time of survey. Adaptively, Tanjung Gelam could be temporarily set as a tourism

zone, replacing Legon Lele where coral cover was relatively high and low unsettable substrate (more

'space for growth') and was said to be less favorable for fishing (pers. comm. Sutris Haryanta, 2008).

The latter might have been a suitable candidate as a buffer zone reserve. The above example of

experimental management options demonstrates the usefulness of the simulation model as a tool

linking science and management.

The overall modelling study did not aim to deliver point-forecasts for the specific period of

when reef habitats transitions in Karimunjawa will occur, as well as the corresponding intensity of

disturbances that. Instead, the simulation predicted the pattern of changes to explore the causal

relationship between combination of types and intensities of disturbance, and the dynamics of reef

habitat modification. For the case of Karimunjawa, reducing fishing operation down to a critical

threshold is important to allow future recovery of coral reef habitats and replenishment of both reef

fish species. It is obvious that the extensive parameters applied to address complexity in representing

ecological processes are affecting its predictability through bias (Adkinson 2009; Walker, DM, Pérez-

Barbería & Marion 2006) and interpretation (Starfield 1997). However, a set literature gleaned data

has been used to set range and point values to parameterizing the underlying ecosystem response

functions, yet attempting to set this function was important in the context of limitation of empirical

data and understanding of the stochastic processes (McElhany et al. 2010). The consideration of

reducing the complexity of system represented in the model has taken place against the backdrop of

the robustness of management recommendations at local scale. Nevertheless, it emphasises the

importance of reducing future uncertainty, which serves as a critical outcome for communication to

local stakeholders and policy makers.

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In an attempt to make the abstract output data of the model understandable to people outside

the research community, the way in which the model results are visually represented in this study was

also considered. For example, in the P2 projections (Fig. 3.10, 3.11), by simply interpreting plot

colours using the colour bar legend and comparing plot distances to the white cross marks, the end-

user can approximate how likely a particular disturbance level is to cause a reef state ‘shift’ away

from its ‘current condition’. In the P1 projections, interpretation was more straightforward, as the

plotted line explains the likely abundance in the benthic compositions generated over time, benthic

composition ‘shift’ can be observed when coral (red line) or macroalgae (green line) surpass each

other. Thus, despite the interpretation being inherently subjective; the way results are being presented

communicates an understanding of reef systems to end-users such as the local managers.

Apart from the benefit of the modelling results of aiding reef managers to understand and to

estimate resilience of a coral reef ecosystem by predicting the increased likelihood of a system shift,

local management recommendations are therefore, also needed to reduce the local risks. Specifically,

based on causal link predicted from the model there are management opportunities particularly for

controlling preventable local disturbance mechanisms to the reef system. For the goal of maintaining

healthy coral reefs, fishing regulations and no-take area reserve that embrace the management of

grazing process in the coral reef may be required. Unfortunately, at the time of this manuscript is

being written, fisheries regulations that explicitly exist to manage ecosystem process is currently

inexistent in the Karimunjawa National park. Overfishing of herbivorous species and destructive

fishing practice are preventable disturbances that can be mitigated from local actions. For example, in

Karimunjawa, cemadar or parrotfishes are susceptible to trap capture, thus shifting fisherfolk away

from using fish traps could benefit the management of herbivorous reef fish (Hawkins 2004).

However, specific recommendation for gear and catch limitation for the herbivorous reef fish

including the surveillance of destructive fishing activities is unavailable in the region. Additionally,

will require the collaboration between park management and related stakeholders to tailor best local

strategies to address economic and cultural feasibility prior to establishing an outright ban or

limitation on fisherfolk’s harvest and fishing methods.

Minimizing impacts of the local reef stressors, including the mitigation of socioeconomic

drivers, may need to take place early to avoid future synergy with other disturbances that could occur

on a higher spatial scale and to a greater extent (Folke et al. 2004; Hoegh-Guldberg et al. 2007;

Nyström, Folke & Moberg 2000). This includes other human-related stochastic disturbances, such as

coral bleaching, eutrophication, coral disease, and storms (Hughes et al. 2003); all of which have not

yet been defined as environmental parameters for this model. Yet continuous monitoring projects in

the Karimunjawa would be important to better quantify variables, to better predict reef trajectories

and to explore local disturbance thresholds. However, the cost and benefits of such an ecological

! ')

investment also need to be balanced with socioeconomic priorities (e.g. livelihood based reef

management incentives (Cinner, J. E., Daw & McClanahan 2009), further discussed in Chapter 4).

Here I argue that it is likely that removing local stressors to individual reef communities via structural

change, to a desirable level, will be difficult. Thus, different ecological consequences will require

different management strategies (Petraitis & Dudgeon 2004).

This study demonstrated that the model has the potential to be used as an analytical tool in

assessing the resilience of reef sites in Karimunjawa National Park. Future projections of benthic

compositions provided insights into how different mechanisms of disturbances are affecting the coral-

algae interaction process. The model also allows some level of predictability regarding possible

disturbance responses of particular coral reef habitats based on the proportion of reef-building corals

and fleshy macroalgae. Although the model was numerically less accurate compared to the

computational design in other ecological modelling studies (e.g. Mumby, P. et al. 2006; Polovina

1984), it has advantages in scientific communication by means of providing a simpler generic reef

model that allows management with low scientific capabilities to foresee the future potential of sites

to resist stress and recover following disturbances. Thus, the model is of specific benefit for the local

management of Karimunjawa National Park where the local reef ecosystem data is limited and sparse,

and there are limited resources to conduct rigorous biophysical measurements.

In the practice, besides presenting the end-result of the modelling study, I argue that scientific

knowledge and information of coral reef ecology constituted in the modelling framework should also

need to be well communicated to managers. A suggested strategy is to also maintain communication

and collaboration with managers after the study and to support and participate during important stages

of management evaluation. This would provide better chance for effective delivery of the scientific

knowledge and information since direct, but gradual, engagement and consultation can bring both

better introduction and acceptance of information by the stakeholders. This can be performed such as

through involvement in internal dialogues, discussions, or workshops that may be part of a process of

evaluation and develop new management strategies. The achievement may also include the particular

scientific information or recommendation being adopted as reference materials cited in legal

documents and internal publications for the stakeholder’s needs. One-way presentation of results,

particularly using printed media (e.g. reports, publication), may not be fully comprehended by

stakeholders working for Karimunjawa, as they may not directly related to coral reef management and

less-scientific audiences. Another would be dissatisfaction or disapproval to the scientific finding by

particular stakeholder because the informed scientific analysis might inherently articulate the faults or

mistake of the particular institution. Working in region with multi-cultural background such as in

Indonesia, I argue that building sense of partnership, could result not only better institutional

acceptance to the application of new paradigm or practices, but also institutional edification.

! '*

In the long term, this study suggests that local management efforts to maintain key functional

reef fishes and minimize physical damage associated with fishing are vital to facilitate regeneration of

reef sites in Karimunjawa National Park. Achieving this would extend the park agency’s goal of local

reef fish management not only by maintaining a sustainable amount of fish extraction but also by

showing how the extraction is affecting the reef system processes. Accordingly, there is an added

challenge as developing fishery policies may be beyond the administrative authority of a marine

conservation management organization such as KNPA. Therefore, strengthening local scientific

capacity is important for KNPA prior to disseminating information about ecological issues and

promoting engagement with other stakeholders.

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Global climate change has caused severe problems for coral reef ecosystems; yet, human

impacts at local scales are still driving the decline of reef habitats around the world (Carpenter et al.

2008; Hoegh-Guldberg et al. 2007; Knowlton & Jackson 2008). The impact of overexploitation of

reef resources and unsustainable extractive activities have predominantly occurred in less-developed

coastal regions (Bell et al. 2006); such is the case in Karimunjawa National Park (KNP), Indonesia

(see Chapters Two and Three). Key functional reef species, such as herbivorous reef fish which are

locally declining, require better management (Mumby, PJ & Steneck 2008). In this case, achieving a

locally sustainable use of reef resources would also require the integration of both social and

ecological perspectives within the local reef management framework (Hughes et al. 2005; Walker, B

et al. 2002). Initially, this would require an understanding of local socioeconomic variables and at

least some understanding of the key drivers of fish decline, such as local livelihood dependencies on

key functional reef species, before socially adaptable remedies can be developed. Such remedies

would also benefit strongly from participation of the local people in marine reserve management.

(Christie 2004; Cinner, Joshua E. et al. 2009; Pollnac, R et al. 2010; Webb, Maliao & Siar 2004).

Fishermen have mentioned that economically profitable fish species have declined, including

those that are a rare commodity for both inshore reef commercial and subsistence fishers (Field Notes,

Biophysical Survey, August 2008). Biological data to support the allegation was minimal, although

some research has been undertaken (Ardiwijaya, R.L. et al. 2008; Campbell & Pardede 2006)

In the Karimunjawa islands, a National Park Agency (KNPA) has been appointed under the

decree of the Ministry of Forestry of Indonesia to administer a conservation area. This included

developing a multiple-use zoning policy that was established between 2004 and 2005. In the early

phase of the policy’s enactment, protection of areas of reef fish spawning and aggregation sites was

the ecological focus of the zonings and a social participation study was also undertaken (BTNKJ

2004).

However, within the management processes (planning, action, monitoring, and evaluation

(Schreiber et al. 2004)), limited resources meant that social research supporting biophysical data,

social research and monitoring have not yet been taken into account due to limitations in management

resources. This suggests that indicators of gradual social change and social transfiguration might have

! ',

been ignored and, therefore, are absent from the learning process of stakeholders (e.g. the local

community, reef managers, and state agencies).

In sum, key information regarding both local characteristics of resource users and resource

conditions has been missed, whereas in a data-poor situation such as Karimunjawa this is essential to

develop management precautions at the very least (Adger, WN et al. 2002; Johannes 1998). Thus,

there is a current paucity of information for stakeholders (the park agency, state agencies, NGOs) to

evaluate relative resilience of local resource users. This is true for evaluating the social consequences

of both future resource changes and different marine reserve policy options (Alcala & Russ 2006;

Bunce et al. 1999). From this basis, several key questions has set the point of departure of the

research. They were:

1. How does the local community perceive and adapt to past and future changes of reef resources

by referring to factors that could indicate social resilience?

2. What are the knowledge gaps in developing locally adaptable reef management measures for

the sustainability of both the livelihood of the local community and the reef ecosystem?

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Social resilience, as defined by Adger (2000), is “the ability of groups or communities to cope

with external stresses and disturbances as a result of social, political or environmental changes”. For

reef resource dependent communities such as in the Karimunjawa islands, social stability and the

communities’ response to resource changes predominantly influenced the local livelihoods (Pollnac,

RB & Pomeroy 2005; Pomeroy, RS, Katon & Harkes 2001; Pomeroy, RS et al. 2006). In traditional

coastal communities, perceptual learning processes, rather than scientific ones, predominate how the

social system responds to ecosystem signals; which then informs actions related to the process of

utilization of ecosystem goods and services (Berkes, F, Colding & Folke 2000; Kurien 1998).

Thus way communities collectively interact with their environment can influence their

decisions and activity, for example, whether to settle in a particular area, and for how long, or how to

gain their livelihoods (Adger, WN 1997; Adger, WN et al. 2002). These choices can have either

favourable or detrimental impacts on natural resources, such as coral reef systems.

Understanding the social aspect within marine resource management is essential since

reducing threats to the reef ecosystem means managing human behaviour (Hughes et al. 2005;

Nyström, Folke & Moberg 2000). Moreover, integrating the social perspective within resource

management can increase the efficacy of conservation policies that are often restrictive (e.g. area

closure) in the management of small scale fisheries in less developed regions in particular (e.g. in the

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Indo-Pacific (Aswani & Hamilton 2004; Lowry, White & Christie 2009; McClanahan, T et al. 2006),

and the Western Indian Ocean (Cinner, Joshua E. et al. 2009). Cinner et al. (2009) and Marshall &

Marshall (2007) assess four factors that describe social resilience at the local level: capacity to learn,

flexibility and adaptation, capacity to organize and the nature of assets of the community. Survey

results and discussions related to each of the factors are included in specific sections in this chapter.

Observing ecological and biological changes in reef ecosystems can take a long time and

confounding this are the interpretation gaps between scientist-managers and the local community,

which are often apparent (Kainer et al. 2009). One of the potential benefits of assessing capacity to

learn is that resource managers may identify an error of judgment by the community as they perceive

changes in the ecosystem, from which the specific scientific research study can then be developed to

retrieve specific information that both supports social expectations and local conservation objectives

(Kainer et al. 2009). As for the community flexibility and adaptation, stakeholders related to reef

resource management can identify critical gaps in securing and stabilizing local livelihoods, thus

providing momentum for the community to reconfigure whilst abating unsustainable socioeconomic

activities as well as adapting to resource regulations (Smit & Wandel 2006). For policy makers,

assessing organizational capacity will be a critical point of reference prior to improve community

trust, knowledge sharing and mobilizing the community toward proactive participation in resource

governance, rather than toward resistance (Lebel et al. 2006). Lastly observing assets could aid

stakeholders at the regional or national level to pinpoint and contribute to reinforcing assets that are

critical for the local community to cope with ‘surprises’ (market failure, reef resource loss, natural

disasters), thus, avoiding socioeconomic pauperization that forces unsustainable resource exploitation

(Adger, WN et al. 2005; 2002).

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The survey research was undertaken at Karimunjawa National Park from 14 - 21 April 2010

covering the three administrative villages of Karimunjawa, Kemujan and Parang (Fig. 4.1). Social

information was collected with the aid of a questionnaire form (Appendix 5) in sessions held with

individual community members. Respondents were selected either through snowball sampling (e.g.

respondent identification via personal reference of a previously identified respondent) or haphazardly

from sidewalk encounters, as housing areas were built in the proximity of the village main roads.

Each participant was required to answer a list of structured semi-close-ended questions, which allow

respondents to select between the pre-defined answers or give their personal answer (Rea, Parker &

Allen 2005). The design purpose was both for survey efficiency in terms of time, yet, minimizing

response bias as different comprehension of the question responses was highly likely for respondents

of different cultural and educational backgrounds, (Groves et al. 2009). Prior to the survey, local

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research assistants from the Taka Foundation in Semarang performed a pre-test on the questions in

terms of their wording, rephrasing, and sequence as well as holding an internal discussion for

agreement on transliteration for Javanese comprehension. Respondents were allowed to read

questions and write answers by themselves or questions were narrated and answers noted by the

interviewer. The latter was applied to situations when participants were limited in their Javanese

language, illiterate, unable to write or simultaneously conducting an activity.

Figure 4.1. Map of area surveyed in residential areas of Karimunjawa, Kemujan and Parang villages (in colours).

Each respondent was required to answer a similar set of questions related to the social

indicators assessed (Table 4.1, Appendix 5), which generally covered information related to

individual perception and knowledge about natural resources and their management, personal

opinions, past living experiences, demography, age, income, general knowledge and education.

Observational data such as the materials use in residents’ housing was obtained from reconnaissance

surveys, these included floors, roofing, walls and sanitation. Public facilities and infrastructure was

also recorded. The coding, response data entry, and statistical computation were conducted using

Microsoft" Excel" and IBM# PASW# software. Questionnaire response data was categorized as

nominal and ordinal data, which was treated as dichotomous and ranked variables, respectively (Rea,

Parker & Allen 2005) (Appendix 6). The distribution of each response category was determined as

relative frequencies (in percentages) proportional to the total value sampled from each question

(Agresti & Finlay 2009). Monotonic association between nominal variables was measured using Phi (

r! ) and Contingency coefficients. The former applies for two dichotomous variables and the latter

applies more than two (Healey 2008). A rank-biserial coefficient was used for nominal–ordinal

associations (Cureton 1956; Newson 2008) and Goodman and Kruskal’s Gamma ( r" ) for ordinal-

ordinal associations (Healey 2008). These coefficients take account of the distribution of the two

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categorical variables and values ranges from "1 to +1, where ±1 indicates perfect agreement or

disagreement, and 0 indicates no association. Statistical results will also be related with respondent

comments noted from discussions during questionnaire sessions (from here on referred to as ‘notes’,

for the summary see Appendix 7).

Table 4.1. Summary of types of information gathered through questions developed from social resilience indicators assessed in the survey research

Information Variables Socioeconomic variables related to asset

Age group Wealth based on income level Household appliances and materials for housing Level of education

Perception related to capacity in learning

Past to present fishery condition Future fishery condition Primary cause of change in fishery condition Past to present coral reef condition Future coral reef condition Primary cause of change in coral reef condition Knowledge of existing zoning regulation Types, functions and location of zoning acknowledged Knowledge of zones where fishing is restricted Knowledge of proposed key local reef issues Knowledge of 'climate change'

Perception related to livelihood flexibility and adaptation

Livelihood adaptation to hypothetical fishery decline Livelihood adaptation to hypothetical coral reef decline

Perception related to flexibility and adaptation to resource governance

Acceptance of zoning regulation Acceptance of no-take zone Preference of fishery regulation method

Preference in communication / learning efforts

Preferred communication media / method Preferred location for communication

Experience in migration and decision making

Migration based on origin Purpose of migration Period of live spent in Karimunjawa Planned period of time to live in Karimunjawa in the future Involvement in decision making, local organization

Involvement in decision making for natural resource regulation.

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The survey represented opinions of individuals aged 18 years and above, comprising of people

whose main occupation related to utilization of goods and services of marine resources (direct and

indirectly reef related, ±55%) and not reef related (±45%) (Fig. 4.2). A total of 209 respondents were

selected randomly from around 9000 residents from 2400 households registered in the Karimunjawa

district (BPS 2006; BTNKJ 2008). The response rate was 100% as all respondents have voluntarily

participated in a questionnaire interview session, which consisted of male respondents (68%) in a

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higher proportion than female respondents (32%). Age wise, the adult group (above 20 years old,

88%) was higher than the youth group (ranging from 18-20 years old, 12%).

Difficulties in obtaining a representative ratio of gender and age groups relative to the

available demographic data was due to interviews being ethically plausible only during the daytime.

This age/gender matrix was also influenced by the varying working schedule of individuals and

households. Opinions represented in the survey are, therefore, contingent on the size of population

sampled. Therefore, inter- and intra-community quantitative comparisons such as comparisons

between villages and comparisons between gender groups, respectively, were not explored in the

survey analysis.

Despite population representativeness and zero non-response of the survey response, response

bias was yet unavoidable. This might include factors such as underrepresentation and social

desirability that existed due to the difference in gender and age composition of the respondents

(Wright & Marsden 2010). Specific gender and age group have particular tendency of preference and

insincerity that may prompt answers or comments that were based on what respondent believe is

socially desirable (Wright & Marsden 2010). Thus, a dominant gender or age respondent group may

bring undesirable influence the overall survey result. In this survey, we presume that social

desirability can occur on areas of information that were likely sensitive such as personal income and

earnings, compliance with regulations, and knowledgeability of culturally regarded activities like

fishing. Response to this information could, therefore, be inflated or deflated on respondent's

interpretation, which implies that opinions gathered in the survey may not well-represent specific age

or gender group in Karimunjawa.

As an example, young adults with lesser attachment and experience with fishing might have

different expectation of future employment opportunities and alternatives than older adults. Moreover,

gender difference of adult household member, combined with cultural stereotyping, could have also

inflated or played down response related to sensitive information that might expose their household

social status or family condition (e.g. education, income, main occupation, household materials)

(Bernardi 2006). To minimise this particular response behaviour, a 'consent sheet' was being

introduced to respondent in each of the beginning of survey session (See Appendix 5). Moreover,

noted respondent comments were also used in the analysis, in combination with questionnaire data, to

improve the reliability of interpretation of opinions collected in the survey.

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Figure 4.2. Pie diagram showing distribution of respondents’ main occupation (n= 209) grouped by

relation to reef resources, both directly (A) and (B) and indirectly (C); as well as those not related to marine resource utilisation (D).

Around half of the Karimunjawa residents conduct fishing (BTNKJ 2008). At each of the

surveyed villages primary piers that also operate as primary fish landing sites were available. At the

time of survey, tourism development was most prolific at Karimunjawa village where accommodation

and tourism services were the highest registered (BTNKJ 2008). At the time of survey, seaweed

farming was a visually widespread practice, particularly in Kemujan area where some households

have relied on it for their main income. In contrast some residents of Parang had migrated from the

area: a large number of the youth and young adults were on a temporary leave to work collectively in

cities in Java (pers. comm., Head of Parang village and one of the Heads of Rukun Tetangga (smallest

neighbourhood system) of Kemujan village). These general observations in livelihood activities might

indicate some differentiation of coping strategies within the community as well as possibilities of

social instability together with a newer industry (seaweed production) that could improve stability

(Adger, WN 1999; 2002). Social resilience can be explained through a variety of indicators (Adger,

W. 2000). Therefore, analysis and discussion following this chapter focuses on the context of the

sustainability of local livelihoods and community dependency on reef resources in Karimunjawa.

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Flexibility and adaptation in livelihood was assessed by exploring individual responses to a

hypothetical decline in fish and coral reef conditions associated with decisions related to livelihood

mobility and diversity (Adger, W. 2000; Cinner, JE & Pollnac 2004) (Table 4.2). Information was

gained regarding the individuals’ adaptation to park regulations by questioning the respondents’ level

of knowledge and understanding of the marine zonings, approximately five years after it was enacted.

Additionally questions were asked to determine flexibility to resource regulations based on their

acceptance of zoning regulations and preferences about fishery regulations (Cumming et al. 2005)

(Table. 4.3). Interviewers agreed that the term ‘decreasing resources’ would mean a reduction to half

of what the respondent could obtain regularly, such as the weekly or biweekly fish catch, or a visual

indication of reef habitat, such as coral cover. To some respondents who were non-fisher s (crop

farmers, housewives, youths) and fishers, the coral reef was less tangible than fish. They included

individuals who have not experienced much direct visual observation of coral reef and their judgment

was derived from news or stories passed on from those who had more visual underwater experience.

Table 4.2. Responses to questions related to livelihood flexibility and adaptation to hypothetical decline in reef resource conditions. Responses in numbers 1 and 2 were based on one answer per respondent (n=209), number 3 was based on a maximum of three answers for any respondent who in number 2 chose not to stay in their current occupation (n=118).

No Information, Response Category Distribution

1 Effect of 50% decrease of fishery condition to main occupation

Stay with current occupation 46.38% Find alternative or transitional occupation 48.31% Emigrate 0.48% No answer 4.83%

2 Effect of 50% decrease of coral reef condition to main occupation

Stay with current occupation 48.33% Find alternative or transitional occupation 41.15% Become involved in conservation activity 3.35% Emigrate 0.48% No answer 6.70% 3 Preferred alternative / transitional occupation Aquaculture 37.60% Crop / land-based farming 24.00% Informal, small business 13.60% Salaried employment 13.60% Tourism 4.80% Fishing 2.40% No answer 2.40%

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In conditions of resource scarcity, the respondent would mostly decide to stay in a particular

occupation or find an additional occupation (No. 1,2, Table 4.2). Such a condition was typical of the

flexibility of most rural fishing communities in South-East Asia where despite strong occupational

attachment, occupational multiplicity may concurrently exist to cope with uncertainty, particularly of

the natural resources themselves (Allison & Ellis 2001; Bailey & Pomeroy 1996). Here, the term

occupation was defined as one particular activity that the respondent would rely on as source of

regular income. Extractive-based occupations predominate in Karimunjawa where the larger portion

of the community were registered as both fishers and farmers (BPS 2006) and yet occupational

heterogeneity was identified in the survey (Fig. 4.2). The survey was of insufficient duration to fully

understand how the community is managing the risk of resource uncertainty; however, these results

could be signs of risk spreading across livelihood activities (Adger, WN 1999). Moreover, the variety

of economic goals and orientations could also be associated with different strategies in livelihoods:

either diversifying or specializing in occupations (Smith, L, Khoa & Lorenzen 2005). For example,

we found that individuals with a strong attachment to a specific occupation, often the case of a full-

time and commercial enterprise such as fishing, could be in touch with another household member

who can obtain supplementary income from part-time (e.g. seasonal or migratory) jobs and

subsistence level occupations. For flexible individuals, on the other hand, the motive behind

occupational diversification might be strictly related to the diminishing condition of the natural

resources as assets, which could interfere with income security at either the individual or the

household level (McManus, J. W. 1997; Pomeroy, RS et al. 2006). This was illustrated by interview

comments stating the importance of having several occupations in the family during the particular

time when fish were considered scarce (No. 4, Table 4.5, r! = -0.084), particularly as the monsoonal

weather pattern was getting unpredictable and close-range fishing in inshore reef areas was yielding

less.

To benefit the rehabilitation process of the natural resources, the literature has suggested that

the arrangement of livelihood diversification has to develop to the extent where people’s dependence

to natural resources is reduced (Bailey & Pomeroy 1996; Cinner, JE & Bodin 2010; Cinner, J. E.,

Daw & McClanahan 2009; Pomeroy, RS et al. 2006). Based on the type of alternative occupation

preferred by respondents, at the time of survey, the community was likely to be reliant on both coastal

and terrestrial natural resources (No. 3, Table 4.2). Non-fishing household members such as the

women favoured terrestrial activities such as crop farming, either for subsistence or to meet small-

trade demands. In Parang village, for example, its typical red soil and flat ground allows planting in

almost all seasons, of crops such as corn and leguminous plants, and tropical fruit (A, B, C, Fig 4.3).

For this reason several Parang locals thought crop and fruit farming to be more promising than

seaweed farming which was more susceptible to the ais-ais disease, compared with inhabitants of

! (*

other village areas. At the two other villages we found seaweed drying was visually more common.

The Petinggi-s (head of village) commented that the practice had been growing for around five years

prior to the survey. To some families it has provided substitution of income loss for those who have

not survived much from commercial fishery (D, E, F, Fig 4.3).

Despite this apparent need to spread income sources through the substitution of occupations,

the livelihood mobility was relatively inward as the source of production was confined to local natural

resources (Gordon 1954). Overexploitation, (e.g. due to unsustainable fishing, forest clearing, and

coastal modification) or restrictions (e.g. area closure, species restrictions, and harvest regulations)

lead to a lack of assets that people could depend on for their livelihoods. Therefore, without

alternative assets expecting the community to suspend or exit from fishing would be unrealistic

(Cinner, J. E., Daw & McClanahan 2009; Smith, C & McKelvey 1986).

Figure 4.3. Photos showing semi-dry red soil ground characteristic in Parang island (A), allowing

much tropical fruit to grow like pomegranates, for example (B,C), whereas seaweed drying was visually more common in Kemujan and Karimunjawa area (D,E,F).

The overexploitation of resources itself could also promote conflict of both the use and

management of resources, particularly when there is a high competition for an ‘open-access’ marine

resources area such as in Karimunjawa (Berkes, F 1985; Pomeroy, R et al. 2007). Related to this, we

identified a number of elderly male respondents in Karimunjawa and Kemujan who have stopped

fishing, some of whom mentioned that the decision was due to a reduced tolerance to working

conditions that reduced fishing capability and being commercially outcompeted by other fishers. At

the time of survey, a large portion of this group have become involved in part-time carpentry, also

carrying out wood collecting and every so often employing members of their family (Fig.4.4).

However, most have experienced a new occupational risk of conflicts related to park regulations

rather than from the environment itself, since targeted resources such as trees were within the Forest

! (+

Protection Zone. Shortly before the survey, we noted that conflicts took place between wood

collectors and the park authority due to cases of violation of tree species and the forest-zoning

perimeter. As well there was a dispute about misplacement of the forest-zoning marker on private

ground that disregarded the owners’ rights. This case demonstrates that highly extractive livelihoods

if not counterbalanced with non-natural-based livelihood access may prompt successive exhaustion of

natural resources, such as the transition from coastal to island forest extraction. Furthermore, resource

managers overlooking the erosion of livelihood options concurrent with natural asset degradation

could further diminish user interest in participating in conservation since social conflicts could

strongly interfere.

Figure 4.4. Photos showing logging activities, some conducted by ex-fishing families (A,B), including

rock breaking to supply construction material (D). These supplementary income strategies could be found in combination for some households (C,E).

Regarding the need of current zoning regulations in KNP to secure resource tenure (e.g. fish

population management (see Chapter 3)) in addition to managing resource access (e.g. zoning policy

(BTNKJ 2004)), the adverse impact of shifting resource use patterns may need to be compensated by

non-natural-based capital asset use such as incentives of non-extractive but still reef-related

livelihoods (e.g. tourism) (Cruz-Trinidad, Geronimo & Aliño 2009; Fabinyi 2010). As an example, at

Karimunjawa kota area, where tourism services were nucleated (BTNKJ 2008), there were

households that already had a considerably high attachment to tourism as the main income

substituting fishing (pers. comm., Head of Village / Hamfah Homestay owner, 2010). However,

poorly developed local tourism could place more pressure on the reef system via increasing local

demand for reef fish (see Chapter 3).

This may indicate that an alternative livelihood portfolio may be necessary to allow a larger

segment of the community to cease or withdraw from fishing to provide the temporal or species

restrictions required for the replenishment of specific fish populations (see Chapter 3). However,

! (,

tourism itself can also bring adverse impact to reef sustainability if it is poorly managed since it could

indirectly increase local demand for fish (See Chapter 3). We also find that the proportion of the

community engaged in tourism is also less than those in extractive activities (Fig. 4.2). In this case,

the alternative occupations incorporated may not necessarily be attractive, not only in income

comparability, but also in their characteristics (e.g. risk, job satisfaction, culture) (Pollnac, RB &

Poggie 2008; Pollnac, RB, Pomeroy & Harkes 2001; Sievanen et al. 2005). In contrast aquaculture

such as seaweed farming was found to be more lucrative than tourism related activities such as

providing a boating service (No. 3, Table 4.2). However, resolving to remain dependent on an

extractive socioeconomic scheme also has a cost to the ecology. Despite the potential of seaweed

farming to reduce fishing efforts, there are economic uncertainties related to the risk of disease, loss

of demand and consequent price drops, as well as environmental issues that may stem from

unsustainable farming practices and disruptions of ecosystem functions (Bergman, Svensson &

Öhman 2001; Crawford, B 2002; Ólafsson, Johnstone & Ndaro 1995; Sievanen et al. 2005).

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Adaptation to marine resource regulations was assessed through questions related to the

knowledge of areas where fishing restrictions are applied in the Zona Inti (no-take zone) (No.1, Table

4.3), level of knowledge and understanding of marine zonings (No.2, 3, Table 4.3); acceptance of

zoning regulations (No. 4, 5, Table 4.3); as well as flexibility based on their preference of regulations

related to fishery (No. 6, Table 4.3).

Table 4.3. Response to questions related to perception and adaptation to zoning regulations in Karimunjawa National Park. Each information type has different sample sizes (as indicated) and respondents could only give one answer in 1 (n= 209), 2 (n = 173), and 3 to 6 (n=81). Numbers 2 to 6 were from structured questions where some responses were associated with one another (refer to table footnotes).

No Information, Response Category Distribution

1 Knowledge of any areas where fishing restrictions are applied (Zona Inti)

Yes, I know 38.94% No, I do not know 61.06% 2 Number of zoning types acknowledged * No-Take Zone / Zona Inti 31.03% Protection Zone/ Zona Perlindungan 30.34 Aquaculture-Use Zone/ Zona Pemanfaatan Budidaya 20.00 Tourism-Use Zone / Zona Pemanfaatan Pariwisata 17.93 Four types 20.83% Three types 12.50% Two types 19.44% One type 45.83% None 1.39% 3 Level of understanding of zoning ** Know both zoning function and location 16.75%

! )-

No Information, Response Category Distribution Know either only location or function 22.01% Know only zoning type 61.24% 4 Acceptance of current zoning regulations overall ** Agree 76.25% Do not agree 15% No answer 8.75% 5 Compliance to Core Zone (‘No take’) ** Agree 58.54% Do not agree 36.59% Not sure / Do not know 4.88% 6 Preferred alternative regulation in fishery *** Periodic / seasonal closure 22.58% Gear-related regulation 70.97% Regulation of non-Karimunjawan fishers 6.45% * = Participants that knew about zoning regulations

** = Relative to the type of zoning that the participant knew

*** = Participant does not agree to ‘no take’

Our findings suggest that individual awareness was persistently low (<50%) relative to the

results from a survey by the Wildlife Conservation Society in 2006 (with a lower number of

respondents, n=157, (Wibowo, Joni T 2006)). Furthermore, more than half of respondents did not

know about the presence of no-take areas (No.1, Table 4.3), yet the majority of respondents have

resided in the area before the 2005 park re-zoning (No.7, Table 4.9). Among the four types of zoning

questioned about, Zona Inti and Zona Perlindungan (Protection/Buffer Zone) were the types most

were familiar with, however, the majority did not know the zoning locations and functions (No.2, 3,

Table 4.3). Nevertheless, the majority (±76%) would agree to a zoning scheme (No. 4, Table 4.3),

suggesting that a lack of awareness of park regulations, rather than defiance, might have resulted in

low compliance.

Moreover, the lack of enforcement due to the low surveillance capacity of the park agency

might also contribute to the situation. This is particularly relevant as boats were seen fishing or taking

tourists to no-take areas whenever the patrolling rangers were out of sight (field obs., 2008, 2009,

2010). Studies in Indonesia and the Philippines by Crawford, et al. (2004) and Pomeroy (1995),

respectively, imply that surveillance is just one of the factors that influence community compliance

with natural resource management where inter-community institutions, external programs and

organizations, rights and ownership (e.g. resource tenure and customary management), and

demographic factors (e.g. poverty, population pressure and human capacity) could influence

compliance. Despite there having been a participative process during the 2004 re-zoning planning

process (BTNKJ 2004), since then communication and engagement between the park agency and the

! )$

community has not been particularly effective and previous community participation in the resource-

related decision making process was low (No.5, Table 4.9)).

In the case where management resources are limited, investing in communication might bring

more benefit than improving resources for surveillance as this could indirectly result in reducing costs

in enforcement by bridging collective action in resource management (Hanna, Folke & Maler 1996).

Yet, facilitating inter-community institutions would also depend on the cohesiveness of the

community, which will be discussed in section 4.3.5. Nevertheless, incorporating an effective

communication strategy between resource managers and users at stages of both the management

planning and the management process could increase community familiarity with the roles of

stakeholders. It could also encourage enhanced comprehension of the nature and purposes of the

regulations as well as building trust, as the concern and needs of the community are being taken into

consideration (Alder, Sloan & Uktolseya 1994; Lundquist & Granek 2005; Pomeroy, RS, Katon &

Harkes 2001).

Despite the lack of recognition of resource management institutions, indications of local

demands to regulate natural resources, particularly fishery, were apparent. From the semi-closed

ended questions, around half of the respondents (±58%) perceived no-take areas as the appropriate

way to manage fishing (No. 5, Table 4.3.). Yet, those of the opposite opinion chose other fishery

management options such as regulations associated with fishing gear (±70%), seasonal fishing area

closure, and several suggestions for policy and regulation of non-Karimunjawan fishers’ access (No.

6, Table 4.3).

This suggests management may need to provide options of measures that adapt to local

socioeconomic conditions, particularly when livelihood configuration is versatile (see section 4.3.2).

In this case, heuristic approaches and socially less detrimental alternatives (No. 6, Table 4.3) may

complement or replace the ongoing restrictive measures (e.g. area closure, zoning). In practice, a

sense of participation in conservation could also be embraced by the community as it involves the

accommodation of its opinions such as in deciding when to open or close specific areas, or which

specific artisanal method is to be controlled (Cinner, JE, Marnane & McClanahan 2005; McClanahan,

T. R. & Cinner 2008).

From the perspective of the resource user, the motivation to comply with the existing

regulations was likely to be conditional on how community members perceived the legitimacy of the

authorities charged with implementing the regulations. From noted comments, the individual motive

to either obey or violate park regulations, such as the choice between “being destructive” or “reef-

friendly”, was either based on the risk of infringement (e.g. legal penalty) and the practical fairness

and appropriateness of both the policy as well as the enforcing authority. For example, those who

! )%

have a commitment to conservation would appreciate park authority performance when enforcement

is exercised such as for fishing infringements related to the conduct of destructive methods (e.g.

‘arrest on cantrang’ (Suara Merdeka 2010). This also includes practical solutions that can be

beneficial to the community and environment, such as the previous installation of mooring buoys to

allow boats to park close to the reef area, which benefited by reducing anchoring and providing

shelter points during storms.

However, lack of consistency in enforcement has also created individual disappointment that

could reduce willingness to support resource management. For example, a few respondents have

commented that local enforcement was unfair as it was still insufficient to apprehend other residents

or external fishers who were discreetly conducting illegal fishing practices. For this reason, KNPA’s

enforcement support may need to involve collaboration with the community specifically when

operational resources such as on-site staffing were limited. As was demonstrated in other areas in

Indonesia, the process could involve an integration with a pre-existing local customary management

(e.g. appointing and delegating the local enforcer of sasi custom in Maluku (Novaczek, Sopacua &

Harkes 2001)) or establishing community-based surveillance (e.g. integrating village-level

community rules with formal enforcement authorities in Minahasa regency, North Sulawesi

(Crawford, BR et al. 2004).

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Several sets of questions were given to measure individual capacities in learning related with

perceptions about the changes in the conditions of both fishery and coral reefs (Adger, W. 2000)

(Table 4.5), perceptions of the dominant influence affecting change of resource conditions (Cinner, JE

& Pollnac 2004) (Table 4.6), knowledge of key local reef-related issues (Paton & Johnston 2001) and

experience in formal education (Table 4.8).

The majority of respondents perceive that both past fishery and coral reef condition were in a

declining trend (No. 1, 2, Table 4.5). The term past was agreed on by interviewers to mean occurring

within the period of five years prior to the survey. Some respondents reported about earlier situations

and this information was also included. Individual perceptions of the reef resources have likely been

influenced by livelihood experiences rather than any external source of information. For example,

some comments mentioned that the perception of fish condition was either based directly on taking

notice of the trends of the amount of fish their household could catch, or indirectly estimating the

changes of the number of fish available or sold locally (e.g. at landing ports or village markets) (1.A,

r! = 0.316, Table 4.3). These were among the indications of local ecological knowledge (LEK), which

might have been accrued via trial and error, during the survivorship process of the community

(Berkes, F, Colding & Folke 2000). Correspondingly, such information could also suggest that there

! )&

might be a latent demand in the community to conserve resources, as individuals have learned that the

resources they depend on are limited or depleting (Folke 2004; Johannes 2002a). Yet, in general, the

respondents comprehended both human and natural causal factors. Besides fishing activity, natural

event factors were also dominantly perceived to affect reef and fish failure (3.A, r! = -0.068, 3.B, r! =

0.222 Table 4.5; No. 1,2, Table 4.6). The bi-seasonality of the monsoon, in other words the change

between the unfavourable weather of baratan (the western monsoon) to the arrival of timuran (the

eastern monsoon) was thought to become more unpredictable. This was believed to cause fish loss (it

was suspected to disrupt fish behaviour, or, indirectly, restrict fishing operation) and coral damage

(due to the force of waves during storms). Similar rationales may have also been associated with the

dominant perception in responses about the decline in future resources (2.A, B r! = 0.122, -0.040,

Table 4.5; No. 3, 4, Table 4.6).

The coral reef appears to be physically less tangible than fish resources as the reef condition

was perceived indirectly, based on the extent of human activities that were considered detrimental to

coral, instead of direct observational experiences. This was illustrated by many respondents who

associated the status of the coral reef with the community tendency to undertake unsustainable fishing

practices such as muro ami fishing (trampling on the reef to guide fish into the net), cyanide fishing,

and anchor seine net fishing (1.B, r! = 0.086, Table 4.6). Moreover, both fishers and non-fishers have

admitted their visual experience of the coral reef was minimal or none. Most have relied on

information shared by diving tourists or members of the hookah group (divers using free-flow

compressed air via tubes from a boat for spear fishing or gleaning in deeper water). This, therefore,

might explain the exceptionally high no response category (18%, No.2, Table 4.5).

These findings imply that supply of external information such as the public dissemination of

scientific findings may need to be integrated with an LEK that is associated with specific ecological

issues (see Chapter 3). Thus, better adoption of science in the learning process towards developing a

‘native’ conservation attitude (Drew 2005; McClanahan, T et al. 2006) is recommended. Compared to

other communities in managed coastal areas in Eastern Indonesia where indigenous culture is existed,

the relatively heterogeneous (multi-tribal) and modernized (having interaction with the populous

urban culture of Java) community in Karimunjawa might have impede LEK from establishing

formalized customary resource management practices (BTNKJ 2004; Satria, Arif, Matsuda & Sano

2006; Thorburn, CC 2000). The versatility of the local economy in Karimunjawa is exemplified by

the variety of economic goals and orientations complementing livelihood mobility and resource use

change (see section 4.3.3). Because of this, the learning process of this heterogeneous community

might have been fragmented in terms of their ecological reinterpretation and knowledge transmission

(Reyes-García et al. 2007). This might have also eroded traditional values that were potentially

conservationist (i.e. traditional taboos (Cinner, J. E. & Aswani 2007). Moreover, the manifestation of

! )'

LEK itself may not necessarily have to be accurate since drastic changes were noticed after they

happened (Moller et al. 2004). Subtle changes, on the other hand, in the decreasing variety and

number of reef fish have been unnoticed.

Table 4.4. Test of associations between responses of perceived resource conditions (Table 4.3) and the related influential causal factors (Table 4.4.).

No. Associated Categories Coef. Value Approx. Sig. Level of Assoc.

1.A (1) Past fishery condition: declining (2) Dominant influence: fishing 0.316 0.000 Weak

(Value ! 0.3)

1.B (1) Past coral reef condition: declining (2) Dominant influence: fishing 0.086 0.213 Weak

(Value ! 0.3)

2.A (1) Past fishery condition: declining (2) Dominant influence: fishing 0.122 0.78 Weak

(Value ! 0.3)

2.B (1) Future coral reef condition: better (2) Dominant influence: fishing -0.040 0.563 Weak

(Value ! 0.3)

3.A (1) Past fishery condition (2) Dominant factors: natural events -0.068 0.332 Weak

(Value ! 0.3)

3.B (1) Past coral reef condition (2) Dominant factors: natural events 0.222 0.001 Weak

(Value ! 0.3)

4 (1) Occupational adaptation: need supplementary occupation (2) Past fishery condition: declining

r! -0.084 0.224 Weak (Value ! 0.3)

Table 4.5. Response to questions about past and future changes of fishery and coral reef conditions. All response categories were based on answers given limited to one (n=209).

No Information, Response Category Rel. Frequency 1 Past to current fishery condition Declining 49.52% Improving 22.60% Average 20.19% No response 7.21% Uncertain 0.48% 2 Past to current coral reef condition Worsening 49.52% Improving 18.27% Average 13.94% No answer 18.27% 3 Future fishery condition in 5 years Less fish 38.49% Depends on fishing activity 27.44% More fish 10.23% Same 8.84% Depends on park regulations 5.12% Depends on economic conditions 0.93% Depends on natural events 2.79% Depends on stakeholders 0.47% No answer 1.07%

! )(

No Information, Response Category Rel. Frequency 4 Future coral reef condition in 5 years Better 36.02% Depends on conservation 25.12% No answer 18.01% Worse 8.06% Depends on natural events 7.11% Average 4.74% Depends on stakeholders 0.95%

Table 4.6. Response to questions about the dominant activity that influence changes in fishery and coral reef conditions. All response categories were based on answers given more than one (Number 1, n=238; 2, n=219).

No Information, Response Category Rel. Frequency

1 Activity that has the most influence on the changes in fishery conditions

Fishing 46.21% Natural events 25.00% Park regulations 11.74% Legal issues 5.68% No answer 10.23% Land-based practices 0.76% Economic situation 0.38%

2 Activity that has the most influence on the changes in coral reef condition

Fishing* 54.59% Natural events 15.75% Boating (anchoring, grounding) 14.29% Water pollution (sewage and waste) 9.52% Park regulation 3.10% Other 1.47% No response 1.10% *) Including destructive fishing 16.49%

With regard to community adaptation to regulations, local acceptance and participation in

resource management were suggested to be at a higher level when local conservation strategies adopt

the integration of LEK with conventional science (Johannes 2002b; McClanahan, T et al. 2006;

Ruddle 1998). Theoretically, members of a culture would never understand that there are limits to the

resources they are relying on until they have experienced the effects of this and yet, the learning

process of the LEK often involves reinterpretation of many possible extremes of resource conditions

over a long period and in a small area (Aswani & Hamilton 2004; Drew 2005; Silvano & Valbo-

Jørgensen 2008). For this case, science could provide short-term, but more objective and spatially

wider, tests of the background mechanism of the ecosystem (i.e. ecological modelling (see Chapter

3)); which could therefore identify key changes, set thresholds, and encourage management

intervention to alter or avoid the extremes (Knowlton & Jackson 2008; Mumby, PJ & Steneck 2008).

! ))

This has been partially demonstrated in 2004 during a rezoning planning process in KNP when local

information of fish spawning and aggregation (SpAg) sites obtained from local fishermen have helped

determine priority sites (BTNKJ 2004). This also shows that the process of obtaining LEK itself is

participative, where policy makers and scientists are involved with the representatives of the local

community, thus, having the potential of building communication to grow local trust and support.

Despite the rationale of LEK’s contribution to local resource management, a recent review

(Cinner, J. E. & Aswani 2007) questions whether the LEK could intentionally develop an ethical

orientation towards local conservation. Even communities with strong local ecological knowledge

that perform customary management debated whether they were actually meant to conserve resources

(Cinner, Joshua et al. 2006; Cinner, J. E. & Aswani 2007). The survey identified signs of cognitive

learning of environmental impacts and environmental consequences of human behaviour within the

community, however, it was likely that the identified values and perceptions about key local reef

issues in Karimunjawa (see Chapter 3) had not yet developed an attitude promoting conservation.

This corresponds to several findings. Firstly, very few local respondents were well informed

about the four local reef issues asked about in the survey. Individually at each issue in the survey, the

highest response related to awareness of coastal pollution, yet this comprised less than half of the total

responses (39%) and most respondents (±60%) only knew about fewer than two issues (No. 1, Table

4.8).

Secondly, both internal and external socioeconomic factors have likely influenced community

initiatives in conservation. Internally, potentially conservationist local customs might have not yet

been translated into conservationist practices. For example, a number of respondents commented that

coastal littering was disrespectful to nature and also brought ‘bad luck’. However, this has resulted in

waste disposal in the terrestrial environment that was considered to be ‘less sacred’. Residents would

resort to conducting landfills and burning waste, as waste collecting activities or services were absent

in most of the village neighbourhoods. Correspondingly, this might explain the biased comments from

respondents in areas other than Karimunjawa Kota (the part of Karimunjawa village where most of

the administrative offices are located) who stated household waste in Karimunjawa did not contribute

much to coastal pollution. Externally, tourism growth was also associated with the increase of waste;

particularly inorganic waste (e.g. plastics, Styrofoam) such as was the case in Karimunjawa Kota. In

the area, despite presence of disposal bins and garbage collectors, and comments about past garbage

relocation to Java from Karimunjawa Kota, the team visually found scenes of garbage piled in the

proximity of village houses, partially converted mangroves and beach areas. Concurrently, we also

identified plastic bottle collecting, by only a few residents, for sale and reuse purposes. However,

whether this was motivated by conservation or merely commercial reasons was unknown. Here, we

! )*

suggest that external intervention may be essential to promote a community ethic of conservation,

particularly when the community is in transition due to development influences such as tourism.

Figure 4.5. Photos taken in the Karimunjawa Kota area showing a makeshift garbage dumping site

(A), unmanaged garbage (B, C), and collected plastic bottles (D).

Thirdly, we found LEK that represent a specific process of the reef ecosystem, however, how

disruptions to the process could lead an acute loss to the resources has likely been overlooked or

ignored by the community. For example, some fishermen interviewed commented that by intuition

most have realized the importance SpAg sites for future replenishment of fish population based on

their past experiences of knowing and fishing in those areas, rather than on information given by park

staff. However, SpAg sites are favourable fishing ground rather than a purposively sacred or

safeguarded area. Some who have the information would keep it undisclosed. Likewise, the grazing

behaviour of herbivorous reef fishes such as cemadar (parrotfishes) on bits of latoh (Caulerpa sp.,

including other fleshy seaweeds attached to coral), as well as bronang (rabbitfishes) on krangkam

(also seaweeds) was familiar to most seaweed farmers and subsistence small-scale fishers often

working in shallow reef-adjacent waters. However, most were not aware of the functional role of

these targeted species in the survivorship of coral by controlling macroalgae abundance (see Chapter

3). This corresponds to comments stating that the consequence of the exhaustion of the particular

species to the coral reef was not yet a concern for fishermen. This was supported by the belief that

water movement (e.g. wave force) would eventually remove fleshy seaweed from corals, which was

also considered a sign of an incoming baratan. Similarly, some admitted that anchoring directly on

the reef would damage living coral; however, most denied the potential for severe damage if the

! )+

conduct intensified. This was based on the knowledge that “anchor damage does not hit coral roots”,

and also “the living part of coral will replenish and coral will grow back again just like trees”.

From the above findings, I suggest that LEK in Karimunjawa has been able to identify some

patterns of the ecosystem, particularly extreme events (e.g. bad weathers, depleting fish). However,

this understanding, particularly of the reef, has likely been developing related to efforts in resource

extraction rather than for any deep understanding of the ecological process as such. Here, science can

give further understanding of the ecological process and causal links of human–resource interaction

which has likely been missed by LEK (Moller et al. 2004). Science also has a role in providing a

narrower biophysical perspective, by detecting relatively short-term signals or average patterns. This

provides information about the mechanism behind fluctuations of resources (e.g. ecological

modelling, see Chapter 3).

From the perspective of psychology, the local community may not have identified an acute or

chronic loss of reef resources. To overcome socioeconomic stress most would have likely adapted by

gaining from other resources pools rather than building a positive attitude towards resource

preservation (Hobfoll 2001). This may have placed the local community in a more vulnerable

situation as the resources are becoming depleted. Because of the attachment of the community to their

own land and because in KNP there is limited access to scientifically derived data regarding resource

depletion, it is highly worthwhile to incorporate the experience of the local resource users. Such an

approach is practical and can be cost-effective for awareness building as it could invite participation

and partnership between resource managers and the community (Johannes 1998). Thus, community

involvement in the management process and assessment of resources can build mutual learning where

transfer of knowledge can be broader and more autonomous compared to the existing formal

education.

The majority of respondents (±55%) only finished elementary school, followed by one third

who attended or finished high school, and a few finishing tertiary education (No. 2, Table 4.5). This

hierarchy was similar to the latest Karimunjawa District monographic data recorded in 2006, (BTNKJ

2008). As noted, the formal school curriculum related to environmental education and park awareness

has been applied in junior high school grades, thus, age groups involved are limited. The teaching,

performed by park staff, was fairly recent (around the past five years) and has not been intensive due

to limitations in staffing resources and the segregated locations of the schools. The children and

teenagers were in the age group who would have likely experienced this school curriculum related to

natural conservation and park awareness. These findings suggest that current involvement in formal

education might have a minimal influence on individual knowledge and awareness of local

environmental issues, presumably among adults in particular (r" = 0.360, Table 4.7).

! ),

Table 4.7. Degree of association between respondents’ level of formal education (No. 2, Table 4.6) and knowledge of key local reef issues (No. 1.b, Table 4.6) where both variables are treated as ordinals

No. Associated Categories Coefficient Value Approx. Sig. Assoc.

1 (1) Level of formal education (2) Level of knowledge of key issues

r" 0.360 0.000 Weak (Value ! 0.3)

Table 4.8. Response to questions related to three putative local scale reef related issues and level of education. Response no. 1 was based on answers given about up to four categories (n=249), Response no. 2 was limited to one (n=209)

No Information, Response Category Rel. Frequency

1.a Knowledge of human impact on reef ecosystem processes

Coastal pollution (sewage and waste) negatively influences coral reef condition (n=98). 39.36%

Targeting fish spawning and aggregation sites can threat fish stock recuperation (n=71). 28.51%

Physical damage from anchoring can potentially severely reduce live coral cover (n=54). 10.04%

Loss of herbivorous reef fish may trigger uncontrolled macroalgae growth, covering corals (n=26). 22.09%

1.b Know all four issues 0.49% Know three issues 10.24% Know two issues 26.34% Know one issue 30.24% Do not know any of the local issues 32.68% 2 Level of education Elementary School 55.29% Junior High 17.31% Senior High 18.75% Higher Degree Education 3.37% Did not attend school 5.29%

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The survey assessed organizational capacity based on responses regarding individual

participation in local community groups or organizational structures (No. 1,2, Table 4.9) as well as

knowledge sharing through the decision making process, particularly related to resource regulation

(No. 3,4, Table 4.9) (Armitage, D. 2005; Olsson, Folke & Berkes 2004). Living experience and

attachment to place was also individually measured through questions related to migration such as

origin, livelihood reason for migration, and living period in Karimunjawa (Adger, WN et al. 2002)

(No. 5,6,7,8, Table 4.9).

! *-

Table 4.9. Reponses to questions related to social capacity to organize including involvement in organization, participation in decision-making, and migration status and intention. Response to nos.1, 3, 4, 5, 7 & 8 were based on answers given limited to one (n=209). Samples were smaller for responses to nos. 2 (n=117) and 6 (n=66) as they were associated to responses in nos. 1 and 5, respectively (see table footnotes).

No Information, Response Category Distribution 1 Involvement in organization Involved 55.98% Not involved 44.02% 2 Number of organizations involved in * Less than 3 organizations 88.89% More than 3 organizations 11.11%

3 Involvement in decision-making process in the community

Yes 30.62% No 69.38%

4 Involvement in decision-making related to natural resource regulation

Yes 14.83% No 85.17% 5 Migratory status Born in Karimunjawa islands 68.42% Coming from outside of Karimunjawa islands 31.58% 6 Reason for migration** Fishing 26.87% Salaried employment 14.93% Crop / Land-based farming 13.43% Sea farming (aquaculture, gleaning) 11.94% Informal/Small-scale business 11.94% Family matters 7.58% Tourism 7.46% To sell marine products 4.48% 7 Length of time living in Karimunjawa Less than 5 years 7.21% 5 to 10 years 3.85% 10 to 15 years 12.02% More than 15 years 76.92% 8 Planned length of time to stay in Karimunjawa Less than 5 years 5.14% 5 to 10 years 6.07% More than 10 years 83.64% No answer 5.14%

* = Based on respondents who are involved in organizations

** = Based on respondents who are immigrants

The survey found that around half (55%) of the sampled respondents were participating in an

organizational activity at a local level (No. 1, Table 4.9). In general, the organizational experience

identified was not considerably associated to resource conservation. At the time of survey, many of

! *$

the respondents who considered themselves to be involved in organizations were associated with

government structures such as holding village administrative unit positions (e.g. Rukun Tetangga,

Rukun Warga) and religious activities (e.g. at mosques, mushalla-s). From comments made by

householders who are not the interviewees, the team identified activities associated with occupations

and conservation. This includes a fisherfolk association called Sinar Bahari based at Karimunjawa

Kota and Kelompok Pelestarian Penyu / KPP (sea turtle conservation group) based in Kemujan

village. Sinar Bahari’s group objective was to “unite local fishermen’s voices” (pers. comm.,

Founder of Sinar Bahari, 2010), which has likely been initiated as a advocacy platform particularly

for settling disputes with external fishers (Suara Merdeka 2002). As for KPP, a member of the

community spent part of his occupational time voluntarily nursing the initial turtle group and hatching

baby sea turtles collected and donated by other community members (pers. comm. KPP Initiator,

2010).

These findings indicate that there is variety of actors and interests within the community

which influences whether individuals or groups would potentially develop a collective decision such

as about resource conservation or other objectives (Agrawal & Gibson 1999). On the contrary, a

relatively heterogeneous Karimunjawan community (in terms of livelihood and cultural background)

might have found difficulty in making a collective decision about conserving resources (Nielsen &

Vedsmand 1999). Nevertheless, in the past, the role of external institutions was found to be effective

in mediating relationships and fostering communication. For example, between 2004 and 2005,

several community groups were initiated by a local NGO at each village as community resource

centres (Kelompok Swadaya Masyarakat / KSM-s). These have been able to gather community

opinion during the participative process for park rezoning during that period. (BTNKJ 2004; TAKA

2004).

Nevertheless, at the time of survey, the community might have considered the extent of

biological production (both marine and terrestrial resources) to be ‘sufficient’, including the

availability of alternative resources (Berkes, F & Jolly 2002). Presumably, this has brought less

resource-related adaptive pressure (e.g. subsistence security) that might have reduced the interest in

collective decision making, consequently resulting in less participation in conservation-related

interaction and practices by individuals or groups (Berkes, F & Jolly 2002; Laumann, Galaskiewicz &

Marsden 1978). We also suggest that there has been an extent of population movement related to

opportunities, reducing dependency on resources although there was also considerably strong

attachment to place. For example, seasonal emigration is more preferable to the youth and young

adults. Some commented that there has been increasing interest in cash income opportunities outside

Karimunjawa, such as labour hire jobs in Java, as well as temporary emigration for educational

reasons. The survey found that most respondents have settled for more than 15 years in Karimunjawa

! *%

(76%), 68% were Karimunjawan-born, while the rest were migrants who came to Karimunjawa for

various occupational reasons (Nos. 4, 5, 6 & 7 Table 4.9). A strong attachment to the particular area

was apparent as the majority (83%) decided to continue to reside there for the next decade or more

(No. 8, Table 4.9). However, some comments noted, particularly from middle to mature adults,

showed that most have past seasonal job experience in urbanized areas in Java. The reason to stay in

Karimunjawa was for security, in order to avoid to unpleasant urban issues (e.g. criminal or

residential problems). Less economic stress from a less demanding social lifestyle was also reported

as a reason to live in Karimunjawa.

For these reasons, facilitation by an external institution may be required to build platforms for

community interaction to develop adaptive capacity and promote knowledge sharing and decision-

making in response to resource change. Respondents who have experience in participating in the

decision-making process were fewer (31%) than those involved in organizations, and even less were

involved directly in resource management (Nos. 3 & 4, Table 4.9). Respondents who have been

involved in meetings and discussions related to park management went infrequently (once or twice)

and for short periods (less than a week’s participation). Some commented that only a minor

representation of the community was invited by the authority (mostly during the 2004-2005 rezoning

process). This comprised those who had a role in the village administrative unit and religious

activities; participation was less proactive and feedback to community members was very minimal.

Despite this situation, there was interest expressed about becoming involved in a communal

platform to share ideas and knowledge, as commented particularly by housewives and the youths.

Several women commented on their interest on participating in a community-based women’s program

such as the PKK (Pedoman Kesejahteraan Keluarga, a village-level women’s volunteer group) and

Kelompok UKM (Usaha Kecil Menengah / small to medium sized industry groups) which some

thought were only available on mainland Java. A youth group at the Nyamplungan sub-village in

Karimunjawa expressed interest in building a local youth group, “… here, young people are eager to

be trained… and the limitation of resources, from knowledge teaching (training) up to tools and

equipment, limits them (us) in realizing their (our) initiatives.... because the adults are less sensitive

than we are of the changes, not only the sea, but how the community is developing”.

This participation in group interaction may indicate that horizontal linkage (across space)

within the community may need to be reinforced prior to establishing vertical linkage across levels of

organizations (e.g. from local community, park managers, and NGOs to higher agencies and

authorities) (Berkes, F 2002). The process of mediation between social and ecological system

management may also be more productive when communities are focused as institutions on a set of

needs and interests and rules-in-use have been defined (Ostrom 1990). When there are no clearly

! *&

defined community objectives and environmental issues are attached to issues of value, equity and

social justice, the community will hold less interest even in mutual collaborative approaches with

external institutions to managing resources (Ludwig 2001).

As indigenous knowledge and institutions in Karimunjawa are weak (compared to indigenous

island communities in eastern Indonesia (Satria, Arif, Matsuda & Sano 2006; Thorburn, CC 2000),

building local community institutional capacity is essential to develop local consensus and

stewardship among community members in resource management. This is in addition to the need for

network building and facilitating the flow of information and knowledge (Crona & Bodin 2006; Hahn

et al. 2006; Scheffer, M et al. 2002). Correspondingly, this will likely challenge the local government

structure in providing the political space for community institutions to have a functional role in the

management and regulation of natural resources (Folke, Colding & Berkes 2003; Leach, Mearns &

Scoones 1999). This might include putting local to regional decentralization of decisions in resource

management, where the legal practice allows consideration of community aspirations and equity and

promotes local participation (Satria, A & Matsuda 2004).

Moreover, as issues of non-compliance were discernible in Karimunjawa (see section 4.3.3),

facilitation of the capacity of the resource manager unit to build trust with the community is essential

to ensure continuous participation in protecting the ecosystem. Thus, the process of bridging local

actors and external stakeholders itself is a nonmonetary investment of social incentive (e.g.

developing trust, identifying common interest, resolving conflict) (Hahn et al. 2006).

By developing local interaction platforms such as community organization, the community

can be better prepared in the event of a resource crisis as community members may well have already

assembled to learn, share knowledge, and develop coping strategies for the risk they will be exposed

to (Armitage, DR et al. 2008; Maarleveld & Dangbégnon 1999). Furthermore, such platforms could

also improve the relationship between resource users by acting as a hub in mediating user conflict and

building perceptions of local resources problem (Berkes, F 2009). Thus, collective action in solving

problems can also minimize overexploitation or degradation of openly accessible resources that could

result from dissimilarities in the thinking of individuals or groups in responding to uncertainty about

resources (Rammel, Stagl & Wilfing 2007).

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Asset-related information was collected both at the community level, through reconnaissance

and interviews with a key informant in each village, such as either the Petinggi (the Head of Village)

or other administrative authorities. This information was also gained through interviewing and noting

comments at the household and individual levels. Measured indicators include community

infrastructure and facilities, household appliances and housing materials, personal income and age

! *'

group (Table 4.10) (Cinner, J, Fuentes & Randriamahazo 2009; Cinner, JE & Pollnac 2004;

McClanahan, T.R. et al. 2008).

At the community level, physical assets such as facilities and infrastructure related to health,

education, and access were present, however, the number varied for each village district. A hospital

was not available, which makes locals rely mainly on the puskesmas (the community health centre) in

each village and the posyandu (the community-based clinic posts in sub-villages). The puskesmas was

only available in Karimunjawa village and the number and distribution of the posyandu were

consistent with the village population, the lowest number being in Parang, and the highest in

Karimunjawa (BPS 2006).

Schools were available starting from kindergarten up to junior high, which were either state

schools or Islamic schools at each village, with an exception of a fishery high school in Karimunjawa

village. In terms of access, asphalt layered roads were present, however, only for the main roads of

the villages, whereas at dukuh (sub-village) areas and Parang village the main roads were still only

partially paved or made of dirt (Fig. 4.6). We found main fish landing ports in each village, while the

ferry and catamaran services linking the region to Central Java Province were only at Karimunjawa

Harbor. Kemujan, and particularly Parang village (as separate islands), have the least access to the

external community as well as lower progress in development, because of their relative lack of mass

transport and even vehicles.

Figure 4.6. Photos showing the typical structure of village roads. Main roads constructed with

asphalt layering connect Karimunjawa and Kemujan villages (A), a brick pavement road in Parang village (B), whereas in the sub-village areas mostly soil roads still predominate.

At the household level, one specific concern was on productivity-related assets related to

electricity were limited in Karimunjawa. In each village, the main supply of electrical power relies on

a state-owned diesel-powered generator. However, the daily operating period was still limited in the

daytime, excluding Karimunjawa Kota area (yet, 20% of respondents did not have electricity at all

(No.1, Table 4.10)). Community members who can afford to obtain a gasoline-based portable

generator get electricity during the daytime (Fig. 4.7). Availability of energy also affects

! *(

infrastructure such as communications where, for example, the absence of constant electrical power

required for landline telephone service limits this service to Karimunjawa Kota alone. However, at the

time of survey, most people relied on a cellular phone service that covers all three villages, yet, there

were extra costs with purchasing the mobile phone unit and power supply.

The majority (>80%) owned essential household appliances that could support cooking,

transportation and entertainment (No.1, Table 4.10). Nevertheless, most have commented that the

limited electricity has hampered respondents from owning essential electrical appliances that might

enhance sanitation in terms of water supply (e.g. water pumps) and food storage (e.g. refrigerators),

including equipment that can support home industry activities (e.g. food processors).

Figure 4.7. Photo showing a gasoline-based generator used by a household to supply an additional

period of electricity, however, this was visually uncommon during the survey.

Financially, the majority (99%) of respondents has an average monthly household income of

up to A$600 (No.6, Table 4.10), which is below the 2009 national gross domestic product (A$2.224

(IMF; 2009)). Yet, with this extent of income, most houses sampled have been made of rigid

materials such as cement or wood based walls, cemented or tiled floors and a tiled roof (No.2, 3, 4,

Table 4.10; A, B, C, Fig. 4.7). However, some health and sanitation concerns were evident, as a few

houses had a dirt floor and asbestos walls. The toilet location, referred to as the area for bathing,

laundry and personal hygiene was mostly separated from the house rather than indoors (No.5, Table

4.10). This was likely because of how people obtain water, as most have to build wells to obtain

groundwater, or use piping to channel higher-ground aquifer water.

! *)

Table 4.10. Response distribution related to assets such as style of living based household appliances, housing materials, sanitation and individual assets such as approximate monthly income and age group. (Response No. 1 was based on answers given more than once (n=209); Response Nos. 2, 3, 4 & 5 were limited to one (n=209).

Type of information, Response category, Distribution (%) 1. Possession of household appliances Gas stove 87.56% Water tank 26.32% Electricity 80.38% Water pump 18.18% Television 77.03% Electric generator 14.83% Vehicle 70.33% Refrigerator 10.53% Audio player 44.50% Computer 9.09% Video player 36.84% Internet access 3.83% Electric fan 30.62% 2. Roof Material 3. Wall material Thatch 1.44% Cement/Brick 57.42% Metal 8.61% Wood/Plywood 28.71% Tile 89.95% Bamboo 1.44% Asbestos 3.35% 4. Floor Material 5. Sanitation Cement 39.71% Indoor toilet 31.58% Tile 44.50% Outdoor toilet 65.07% Soil 7.66% No toilet 3.35% Wood 8.13% 6. Average monthly income* 7. Age group (in years) < A$ 120 67.31% 18 - 20 11.54% A$ 120 - 600 32.21% 20 – 30 26.92% A$ 600 - 1200 0.00% 31 – 40 27.88% > A$ 1800 0.48% 41 – 50 20.19% > 50 13.46% * = Exchange rate of 1 Australian Dollar for approximately 8,000 Indonesian Rupiah

Despite being a low-income community, in general, the Karimunjawan households might have

already established a situation Reardon & Vosti (1995) described as ‘welfare poverty’ as basic

material needs such as housing, food, and entertainment have been fulfilled, although this may be at

minimal levels. However, ‘investment poverty’ (Reardon & Vosti 1995) may also be likely to occur

as there were limitations on human-made assets, although these assets were required to substitute or

complement current income generating activities that were highly dependent on natural assets.

The lack of physical assets for production, such as electricity, for example, might have

impeded or delayed the local community progressing towards alternative livelihoods. Consequently,

individuals or households would have avoided non-extractive investment because of their limited

ability to obtain a higher cost item such as a portable generator set for electricity during the daytime.

Despite this dynamic of livelihood activities being complex and although involvement in alternative

livelihoods may not necessarily be linked to relieving pressure on resources (Sievanen et al. 2005),

! **

both biophysical (Chapter 3) and social (Chapter 4), findings of this research imply that competition

for local natural resources, particularly reef-related, was already high.

The community requires prompt action to diversify assets that could generate less resource

dependant income (see section 4.3.2, (Ellis 2000; Pomeroy, RS et al. 2006)). Yet, the lack of

alternatives for subsistence living or income generation could result in more unsustainable use of

resources, as user competition is higher. In addition, the community is still strongly attached to

extractive occupations (see section 4.3.2, (Pretty 2003; Pretty & Ward 2001)). In this case, it is argued

that reducing the vulnerability of the community would likely depend on external intervention such as

from policymakers or donors. This may include in setting up poverty alleviation strategies, parallel

with the resource management framework, to improve productive asset holdings of the community.

These include fixed assets (e.g. tools and equipment for small-scale industry) in addition to human

assets (e.g. education) and social assets (e.g. establishment of community institutions, see section

4.3.5). Yet, as physical access to market is costly (due to the distance from mainland Java) and this

could cause failure (e.g. in the case of seaweed farming), these interventions will also need to include

market channels to avoid discouragement of non-extractive diversification.

Suitable development strategies include not only development of the physical assets

mentioned above, but also capacity building to promote innovation and adherence to market grades

and standards (e.g. via training workshops). Assistance and simplification of licensing and regulatory

requirements for small-rural-scale industries to join the regional market is also needed. Undertaking

investment in community assets is beyond the role and capability of the current resource management

institution (e.g. KNPA). Thus agencies and stakeholders will likely rise to the challenge of cross-

sectoral institutional coordination. Specifically this involves prescribing site-specific actions and

policies including improvement of local physical and social infrastructure for natural resource

management of Karimunjawa.

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In general, the purpose of this chapter was to produce evidence illustrating the association of

local livelihood dynamics with natural resources. The varying perceptions of individuals on both the

condition and behaviour of the natural resources have influenced the way livelihood-related risks are

being perceived. Accordingly, this also affects the local community’s socioeconomic decisions and

attitudes that could either contradict or support natural resource management and conservation

initiatives.

Livelihood-enhancing decisions in Karimunjawa have still been confined to a strong reliance

to natural resource exploitation. This suggests progressively weak social resilience, as there are

inadequate livelihood alternatives to reduce future vulnerability because of resource exhaustion.

! *+

Improving the local adaptive capacity of the Karimunjawan community demands, therefore,

sustainability of both the livelihoods and the natural resources.

Hence, this apparent need for the diversification of local livelihood arrangements to

compensate for the reduction of natural resource use means that this research has implications for the

evaluation of the resource management framework in KNP, which will be discussed at length in

Chapter 5.

*,

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In general, this thesis has achieve its aims by demonstrating the importance of identifying key

processes of both social and ecological system for improving or maintaining both socio-economic

needs of local community and the complexity of coral reef habitats.

In Chapter 3, the ecological modelling approach has facilitated the exploration of habitat

response to scenarios of local disturbance in Karimunjawan reef given the limitation of native

ecological data and resources to conduct rigorous biophysical measurements. The modelling output

also provided less-scientific stakeholders an informative approach to understand the complex

ecosystem processes related to the effect of local unsustainable in-shore fishing practices on coral-

algae interactions related to fish grazing in particular. In Chapter 4, social assessments of the local

community have provided an in-depth evaluation of the relative resilience of resource users,

particularly in terms of the capacity of the Karimunjawan people to adapt their livelihoods to changes

in reef-related resources they depend upon. The survey findings showed that an alternative livelihood

portfolio is an essential development aspect for the Karimunjawan community to allow suspension of

or withdrawal from extractive activities, and thus, the effectiveness of the regulatory interventions and

policy measures related to the activities.

The research initiative was building partly form inputs gathered from meetings and

discussions in the end of 2008, which involves park management staffs and academics relevant to the

conservation of Karimunjawa region. In the same period, a rapid ecological survey was conducted to

obtain recent information of biophysical condition and resilience indicator of the reef. Being in the

middle of the community, the surveys has also partly revealed recent key threats to the reef from the

local socioeconomic activities that were affecting health of local reef system. The ecological

modelling study was later carried out from early to mid 2009, generally, as an approach to analyse

and predict, but not estimate, future impact of these key threats to the reef. A social survey followed

later in early 2010 where a 6-month travel warning due to bombing in Jakarta took place in between.

The survey was generally meant to explore the likelihood of the community to mitigate and adapt to

future resource changes given to their recent perception and socioeconomic capacity. For each of the

ecological and social studies, the preliminary results has been communicated to the KNP and other

related governmental institutions through written reports and meetings. Disseminating scientific

results to general audience was also a notable experience. Less-scientific stakeholder seldom gave

unexpected response, such as dissatisfaction or disapproval by the member of the institution. This was

! +-

due to the informed scientific analysis might inherently articulate the faults or mistakes of the

particular institution.

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Some of the main findings extracted from the result of the ecological study include:

1. Regarding the primary use of the model as a predictor, the model design has been able

to integrate conditional modification of data from literature of other region and best

available local data and information to simulate the effect of various set of disturbance

scenario to reef benthic community interaction. The model was also considerably well

designed given by its simulated conceptual reef system behaviour and the sensitivity of

the input parameters derived from well-reviewed literatures to describe the health of a

reef affected by local scale disturbance, yet still approximate both the local biological

and socioeconomic environments of Karimunjawa.

2. The simulated projections of grazing loss to reef habitat composition generally

suggested that: (i) Reef sites in ‘good’ category would benefit from priority of

management investment in protection, given by their low sensitivity for any

possibilities of grazing reduction in the future. (ii) On the other hand, the recoverability

of reef sites in ‘moderate’ to ‘poor’ category reef, which was more sensitive to grazing

loss, can be maintained of improved if the exploitation and management herbivorous

reef species is not adequately addressed in the long-term.

3. The simulated projections of increasing anchor damage to reef habitat composition

generally suggested that: (i) Despite the relatively patchy and stochastic impact of

anchoring, it can potentially decelerate the recovery of reef site, regardless of any

categories, suggesting that immediate efforts is needed to stop or reduce local

anchoring methods that are damaging to coral reef. (ii) Reef management investment to

avoid reef perturbation from the intense but dispersed reef perturbation from anchoring

may be necessary in the short term. This may concurrently took place in the progress

of maintaining optimal grazing process of local reefs and mitigating other threats such

as coastal pollution, which may took longer period to be effectual.

4. The ecological modeling presented in this study can potentially being used as

analytical tool for local managers, with benefits mainly: (i) aiding reef managers to

understand and to estimate resilience of a coral reef ecosystem by predicting the

increased likelihood of a system shift, (ii) to foresee the future potential of sites to

resist stress and recover following disturbances, and (ii) to scientifically explore future

! +$

options of management actions while reducing the uncertainty of future threats to reef

ecosystem.

5. The model study suggested that local management efforts to maintain key functional

reef fishes and minimize physical damage associated with fishing are vital to facilitate

regeneration of reef sites in Karimunjawa National Park. Based on causal link

predicted from the model there are management opportunities particularly for

controlling preventable local disturbance mechanisms to the reef system. For the goal

of maintaining healthy coral reefs, fishing regulations and no-take area reserve that

embrace the management of grazing process in the coral reef should be required.

However, this will require the collaboration between park management and related

stakeholders to tailor best local strategies to address economic and cultural feasibility

prior to establishing an outright ban or limitation of fisherfolk’s harvest and fishing

methods.

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Some of the main findings extracted from the result of the social study include:

1. The social survey found that livelihood diversification strategy was a dominant choice

for individuals to adapt to both current and future depletion of marine resources, both

current and future. This situation will likely persist if non-natural-based livelihood

alternatives are limited in long-term, bringing an inherent threat of resource

exhaustion, both of marine and terrestrial. In regard to conservation goal of reducing

fishing effort in the region, livelihood diversification strategy may become possible a

solution, as individuals that has move themselves out from fishing were evident.

Despite that, local community may require more external support for diversification

specific to non-resource-extractive occupations since their current limited capacity can

only resolve them to remain dependent on an extractive socioeconomic scheme, such

as aquaculture, which would also bring another cost to the ecology.

2. Communication and engagement were a dominant factor that determines how local

community can be flexible, in this case – to accept, and adapt to park regulation. It was

found that low compliance of the community was more of result of lack of awareness

of park regulations, rather than collective defiance. In the case where management

resources are limited, investing in communication might bring more benefit than

improving resources for surveillance as this could indirectly result in reducing costs in

enforcement by bridging collective action in resource management.

! +%

3. The survey identifies internal motivation from respondent to regulate natural resources,

particularly fish resource that was apparent. Options of measures that are adaptive such

as gear regulation rather than restrictive may be more acceptable for the local

community with livelihood configuration that is versatile. In this case, heuristic

approaches and socially less detrimental alternatives may complement or replace the

ongoing restrictive measures (e.g. area closure, zoning). However, in terms of external

motivating factor, local compliance was also found to be conditional to the stewardship

and the fairness of the park field staff. The apparent chasm between local and non-

Karimunjawan fisherfolk on how regulation is being enforced, is an example of how

community members perceived the legitimacy of the authorities charged with

implementing the regulations.

4. Local Ecological Knowledge (LEK) gathered from past livelihood experience

dominantly influence community’s perception of the reef resource condition rather

than any external source of information. This suggested that there might be a latent

demand in the community to conserve resources, as individuals learned once the

resources they depend on are limited or depleting. However, integrating LEK with

conventional science is also critical due to several reasons, mainly: (i) local LEK might

have noticed the drastic ecological changes after they happened and science can inform

subtle changes, on the other hand, that might have been unnoticed. (ii) Despite that the

LEK has been able to interpret some patterns of the ecosystem, particularly extreme

events, and represent a specific process of the reef ecosystem, however, how

disruptions to the process could lead an acute loss to the resources has likely been

overlooked or ignored by the community. (iii) There were conservationist LEK

identified might have not yet been translated into conservationist practices.

5. The survey revealed that the majority of organizational experience identified was not

considerably associated to resource conservation. On the contrary, a relatively

heterogeneous Karimunjawan community (in terms of livelihood and cultural

background) might have found difficulty in making a collective decision about

conserving resources. For these reasons, facilitation by an external institution may be

required to build platforms for community interaction to develop adaptive capacity and

promote knowledge sharing and decision-making in response to resource change.

6. Results from the survey of asset suggested that Karimunjawa household might have

already established a ‘welfare poverty’ situation where in a low-income community

most households could fulfil basic material needs at minimal levels. However, both at

! +&

the community and household level, productivity-related asset was minimal, which

might resulted an ‘investment poverty’ situation. The particular attention was to the

physical assets related to electricity. Limited supply and availability of electricity in

the region was which has hampered households from owning essential electrical

appliances that can support non-extractive income generating activities. This suggests

that efforts to diversify physical assets that could generate less natural-resource-

dependent occupation are critical parallel with the resource management framework.

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The thesis has demonstrated a proactive approach for dealing with uncertainty of natural and

human systems by predicting and avoiding undesirable changes, rather than a reactive response such

as focusing in quantification of changes that have already occurred. Ultimately, this brings wider

implications to the Indo-Pacific bioregion where the larger part of the managed reefs are not in

pristine conditions because the proximity of a human dominated environment. In this case, providing

local management with an outline of the gaps of knowledge and novel areas of key research to gain an

understanding of the complex relationship between ecosystem change and social dynamics is

essential.

In broader context, the research has demonstrated that integrative science, such as between

ecological and social, is necessary for the management of natural resource in areas where efforts of

resource extraction and exploitation are also taking place at intense. The research framework

introduced in this study also has important implication for developing regions where high biodiversity

is centred, such as countries in the Coral Triangle region, given the uncertainty of environmental

changes of consequences that are expected in the coming decades derived from human population

growth and global climate change.

Moreover, the research exemplifies that in human-dominated natural systems the perspective

in conservation need to view human as affected agents acting within social–ecological systems rather

than external drivers of natural systems. Accordingly, resource managers need to include social

constructs to understand biophysical variations over the long term. On the other hand, when managing

resource utilization they may need to include biological constructs to explain social variations and

changes in response and adaptation.

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In general, outcomes of this thesis were successful in terms of providing information related to

key behavioural aspects of both the reef and humans that have been discernibly disregarded by the

local management unit (e.g. Karimunjawa National Park Agency). However, during the research

! +'

process there were still several conceptual and technical constraints that have affected the scope of

analysis and discussion and also the applicability of my research outcomes.

In Chapter 3, both the environmental and ecological model parameter setting was

predominantly based on the literature of other comparable areas. Consequently, the predictability of

the model may not be necessarily a representation of the true reef ecosystem features in Karimunjawa

and, yet, the interaction of benthic organisms other than coral and algae was not included. Therefore,

users assessing the risk of sites to local threats using the model output should necessarily complement

this by a broad range of activities to obtain deeper ecological knowledge, such as mapping of the

biophysical condition of reef habitats, and monitoring of both resource loss of key functional reef

species and the intensity of socioeconomic activities that are potentially unsustainable.

In Chapter 4, key social considerations from the survey of the Karimunjawan community were

primarily assumption-driven and this has not completely addressed both inter- and intra- community

characteristics such as comparisons between village developments or specific community groups or

social divisions. Accordingly, a deeper investigation of other socioeconomic factors that has not yet

included such local economic transactions, human capital and an analysis of the market may be

necessary to provide a better understanding for development-related-stakeholders prior to tailoring a

specific local livelihood framework for the community.

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To broaden our collective understanding related to the research topic and to include larger

issues such as climate change, there are several suggested multi-disciplinary directions of future

research in Karimunjawa or the broader region in Indonesia, which include:

1. Assessments of ecological exposure and sensitivity with the additional influence of climate

change - Objectives are to (i) explore future impact of the global climate to the regional / local-

scale oceanographic and atmospheric characteristics, and (ii) the associated interaction of both

future climatic variable and direct anthropogenic influences, with coastal and marine habitat.

Accordingly, several suggested studies include:

a. Assessments on the potential range of alternative states of other reef benthic primary

producers beyond the coral-macroalgae interaction. The purpose is to further obtain

ecological information of key reef processes linked to undesirable phase shift mitigation to

improve local strategies in reef habitat protection.

b. Developing temporal and spatial projection of both the state of in shore habitat, such as

coral reefs, and offshore habitat such as net primary production associated to future

climate variability. The aim is to identify regions or sites that may lose or gain potential

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species (i.e. fish and coral) given the changes of species productivity and distribution due

to environmental changes of their preferred habitat.

2. Assessments of socioeconomic response and adaptation - Objectives include (i) to estimate the

economic risks and consequences, and (ii) possible patterns of socioeconomic response and

adaptation of small-scale fishery affected by the alteration of habitat condition and the associated

species abundance. Given with the future variability of climate and resource exploitation of sites

or regions in Indonesia, several studies being suggested include:

a. Measuring the economic risks such of fishermen revenue, cost and occupational

opportunity to delineate sustainability thresholds of the economy of various small-scale

fishing key sectors impacted by the changes of habitat condition and species abundance.

b. Assessing plausible scenarios of socioeconomic impact associated to the food and

livelihood security such of changes in dietary protein supply, labour buffer and safety net.

Both of these studies can serve bioeconomic input for developing climate compatible

strategies of particular small-scale fishing regions or sites in Indonesia.

3. Assessments of climate mitigation and adaptation strategies - Objectives may include assisting

stakeholders to develop scenarios of (i) policy options and (ii) management strategies, given to the

above description and future prediction of the ecosystem status and socioeconomic condition of a

particular small-scale fishing system. The particular aim is to incorporate a research process to

have decision makers seek their own solutions instead of research outputs being delivered outside

the decision-making system after conducting research in isolation. Suggested analysis within the

participatory process include:

a. Analyse the socioeconomic trade-off between the consequences in economic viability and

resource sustainability as policy screening process to tailor optimum and effective

strategies for both coastal climate adaptation and poverty prevention strategies; and

b. Explore possibilities of behavioural response of resource user groups associated to their

perception and preferences to develop collective actions towards both resource

preservation and livelihood sustainability while satisfying constraints linked to non-

fisheries livelihood sectors

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Research included in my thesis is part of a capacity building project for managers in

Karimunjawa National Park Agency (KNPA) with funding support from the David and Lucille

Packard Foundation. Specifically, it provides management recommendations for the working policy

! +)

related to KNP, in particular to the 2004 KNP zoning policy that is effective at the time this

manuscript is being written, which includes:

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The sustainability of the reef resources of Karimunjawa greatly depends on the performance of

the local management framework in reducing the vulnerability of the reef habitat to local

disturbances. Accordingly, the working policy related to the zoning may need to undergo re-

evaluation and revision since there is aspects of the ecological process that have not yet been

addressed within the focus of the policy. Points of evaluation include:

1. The biological objectives of area restrictions, for example the Zona Inti only allows protection to

relatively limited reef sites to the park area size. This was expected to promote a spillover effect

for fish stock recuperation, however measurement of its success has not yet undertaken. More,

compounded by technical limitations to both surveillance and enforcement of resource user

activity, the uncontrolled extraction of mobile species beyond the closed or restricted area could

still proceed at an alarming rate.

2. Key resources indicators and ecological reference points to determine whether the use of reef

resources and the ecosystem is on a course of recuperation or degradation is spatio-temporally

beyond the function of the conservation zones.

3. Solely relying on zoning in managing the reef is unrealistic, as impacts to key local disturbances

associated with the socioeconomic activities are not directly mitigated.

4. The acceleration of reef resource extraction and use is beyond the KNPA’s capacity to monitor

and evaluate the ecosystem changes, as yet this is too difficult and expensive to conduct.

From the above reasons, several ecological directions related to the resilience management of

local reef habitat in KNP are suggested including the following:

1. The prevention of physical and biological conditions that can initiate the shift to a dominance by

macroalgae that are strong in the competition against corals, particularly those that in response to

grazing process, requires paying considerable attention to the perspective of local management

and their assessment strategies of the reef habitat in KNP.

2. Managing resilience and recoverability of the reef would necessarily require managing

competitive interactions that also determine reef health. Related to this, key local ecological

factors include: (1) the abundance of specific functional species that influence levels of herbivory

in particular, (2) the extent of activities that can potentially alter the reef structure such as

anchoring, and (3) the inhibitory factor of changes of nutrient levels on coral growth.

3. The development of a priority research agenda should include obtaining relevant information on

tipping points for both top-down herbivory and bottom-up nutrient controls. Suggested

! +*

assessment protocols to determine vulnerability and monitoring health status of reef habitats

include indicators of (1) herbivore population, (2) water column nutrient levels, (3) herbivory

assay and (4) the stocks of functional indicator reef species.

The management toolbox required for undertaking these measures needs to be realistic and

sensitive to the limitations of both the scientific observational data required and the investment

capability of local managers in terms of their scientific technical resources. Rigorous ecological

measurements may be expensive and resource intensive in labour, time and equipment. This suggests

that funding and effort may need to be directed towards ecological management and capacity building

rather than the measurement of ecological decline. For instance, ecological monitoring needs to rely

on a precautionary principle where predictive tools such as ecological modelling can be powerful in

providing the future estimated trajectory of reef ecosystem change.

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As a corollary, a community-based strategy is also necessary to complement the zoning policy,

particularly in relation to concerns about non-compliance. The compliance of local resource users

determines the effectiveness of the zoning regulations. Integrating socioeconomic considerations is

necessary throughout the management process, not just during the initial participative process of the

rezoning design. Alleviating problems of non-compliance in Karimunjawa cannot be achieved solely

by solving the technical limitations of the management unit surveillance and enforcement. This

argument is based on the following reasons:

1. There is a complex set of local socioeconomic factors driving the unsustainable human activities

that are detrimental to the protection of the reef ecosystem.

2. A multitude of socioeconomic motives prompt reef-related livelihood activities that could

potentially ignore the existing conservation regulations and reduce the social adaptability to the

local management efforts.

3. The local reef management process requires being more progressive in adjusting management to

local socioeconomic conditions, paying attention to cyclical planning and implementation, which

might have been considerably lacking in the past.

Therefore, it is critical that the local reef management unit proactively perform community

engagement. The evaluation of the working policy and regulations should constantly incorporate

community opinions, ideas, and participation in an iterative process. In practice, implicit

socioeconomic incentives as well as participative and co-management approaches may be necessary

to increase the adaptive capacity of the community to management and to improve local community

! ++

adherence to reef resource management and regulations. Several social directions stemming from this

thesis include:

1. Socioeconomic reliability is a critical aspect of marine protected area management success in

Karimunjawa where reducing local threats to reef resources inevitably requires managing local

livelihood activity particularly fisheries.

2. Specific to the goal of securing a sustainable future fish population and diversity, the protection

of fish reproductive sites such as the no-take zone needs to be critically coupled with a local

management scheme that can control fishing operations in the larger reef areas unrestricted to

fishing.

3. A community-based approach in regulating fishery may be necessarily to include

socioeconomically less repressive practices, through a flexible fisheries scheme such as

implementing a periodic closure to specific areas and seasonal fishing restrictions.

Correspondingly, building trust and a sense of ownership also needs to be greatly considered, by

engaging community members throughout the management process (e.g. planning, monitoring,

evaluation, communication). A regulatory approach may be inclusive. Such an approach allows

local people to decide and implement a locally reached consensus on fishing restrictions about

the kind of equipment used and the targeted fish species. The participation of reef users, such as

the fisherfolk, can also be beneficial in practical terms, to support limited ecological monitoring.

In this way both local knowledge and direct community participation are employed.

4. The KNPA’s role in community empowerment should focus on more than just promulgating

regulations and raising conservation awareness. It also needs to include institutional capacity

building such as organizational skills programs. When intra-community interests, knowledge

sharing and the decision making process converges in solid local platforms, such as the

community organizations, this would ease facilitation by other stakeholders delivering the

community the kind of support which is beyond the KNPA’s capacity, such as economic

incentives.

ZNYN[ ?)"7.0+$&3($&#)$)*)$,&.%(%$&:.3"(-,0($&)"30.)"+(0"#$%$"&'"(4.&.3"4"&)($&(5.0$4*&6.7.(

Reducing the impact of unsustainable livelihood activities in Karimunjawa is indirectly

associated with efforts in lowering the local economy’s high reliance on reef resources. Promoting a

transitional economy such as through alternative livelihood provision, ultimately, will require explicit

socioeconomic interventions. This would include, for example, building physical assets such as

community infrastructure and non-natural-based capital assets such as access to markets, aid and

economic programs. On the other hand, the administrative role of the KNPA limits its institutional

capacity exclusively to implicit social intervention such as community engagement for training and

! +,

capacity building. Anything apart from that is beyond the administrative function and responsibility

of the KNPA (The Ministry of Forestry Decree No. P.19/Menhut-II/2004, Forestry Law No. 41/1999

Article 56).

Therefore, the KNPA’s capacity to engage with stakeholders is also indirectly related to the

mitigation of livelihood-related threats to the reef. In this case, the institutional linkage is cross-scale,

with objectives not only of the establishment of support mechanisms to the park management process,

but also deliberately influencing local resilience agendas to conform with the governance functions in

regional or national institutions and other state agencies. In practice, other than the well-established

scientific collaboration with NGOs (e.g. Wildlife Conservation Society, Taka Foundation) and

academics (Diponegoro University, the University of Queensland), KNPA can take a leading role in

improving the coordination of state agencies responsible for the integrated development of

Karimunjawa Island. The expected outcome is to assimilate local ecosystem management priorities,

for example, with an island development program, governed by regional or national state agencies.

Moreover, local participation is also to support management process, which may include up to

enforcement and surveillance measures. Correspondingly, this will likely challenge the local

government structure in providing the political space for community institutions to have a functional

role in the management and regulation of natural resources. This might include putting local to

regional decentralization of decisions in resource management, where the legal practice allows

consideration of community aspirations and equity and promotes local participation. Nevertheless, the

process of bridging local actors and external stakeholders itself is a nonmonetary investment of social

incentive (e.g. developing trust, identifying common interest, resolving conflict).

,-

!2I2!28@2?(

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Mea

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Appendix 1. Visual census data of reef fish abundance

Ben

thic

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0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

S

oft C

oral

(CS

F)

5.00

0.

17

0.75

0.

14

0.00

2.

00

0.07

0.

37

0.07

0.

00

0.00

0.

00

0.00

0.

00

0.00

S

EA

UR

CH

IN

0.00

0.

00

0.00

0.

00

0.00

10

.00

0.33

0.

71

0.13

0.

10

22.0

0 0.

73

2.33

0.

43

0.10

S

ea U

rchi

n (O

IN)

0.00

6.

00

5.00

IN

VE

RTE

BR

ATE

S

0.00

0.

00

0.00

0.

00

0.00

2.

00

0.07

0.

25

0.05

0.

03

5.00

0.

17

0.53

0.

10

0.03

E

ncru

stin

g S

pong

es (O

SP

) 0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

Inve

rtebr

ates

(OIV

) 0.

00

0.00

0.

00

0.00

0.

00

4.00

0.

13

0.43

0.

08

0.05

0.

00

0.00

0.

00

0.00

0.

00

Not

Ava

ilabl

e (O

NA

) 0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

Upr

ight

Spo

nges

(OS

U)

89.0

0 2.

97

5.16

0.

94

0.35

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

FL

ES

HY

MA

CR

OA

LGA

E

260.

00

19.0

0

90

.00

PR

O-R

ES

ILIE

NC

E A

LGA

E

254.

00

8.47

6.

81

1.24

0.

22

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

Cal

care

ous

Mac

roal

gae

(MA

C)

0.00

0.

00

0.00

0.

00

0.00

2.

00

0.07

0.

25

0.05

0.

00

0.00

0.

00

0.00

0.

00

0.00

C

rust

ose

Cor

allin

e A

lgae

(CR

U)

6.00

0.

20

0.48

0.

09

0.00

17

.00

0.57

1.

19

0.22

0.

00

90.0

0 3.

00

6.33

1.

16

0.00

Fi

lam

ento

us T

urf A

lgae

(TU

R)

9.00

38

.00

496.

00

SE

TTLE

AB

LE S

UB

STR

ATE

9.

00

0.30

0.

60

0.11

0.

06

38.0

0 1.

27

2.50

0.

46

0.16

4.

00

0.13

0.

43

0.08

0.

08

Rec

ently

Dea

d C

oral

(CD

C)

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

D

efor

mat

ed d

ead

cora

l (O

RN

) 0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

49

2.00

16

.40

14.5

9 2.

66

0.30

Tu

rf co

vere

d ru

bble

(OR

U)

117.

00

3.90

3.

92

0.72

0.

00

368.

00

12.2

7 10

.09

1.84

0.

04

202.

00

6.73

10

.07

1.84

0.

35

Turf

cove

red

mal

form

ated

dea

d co

ral (

OR

C)

0.00

0.

00

83.0

0

U

NS

ETT

LEA

BLE

SU

BS

TRA

TE

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

83.0

0 2.

77

5.58

1.

02

0.23

S

and

(OS

D)

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

S

edim

en/S

ilt C

over

(OS

I) 60

9.00

20

.30

9.40

1.

72

0.84

67

7.00

22

.57

10.4

9 1.

91

1.42

18

6.00

6.

20

9.33

1.

70

1.28

TO

TAL

SU

BS

RTA

TE S

AM

PLE

D

972

750

882

Appendix 2. Quadrate transect data of benthic composition survey.

S

ite N

ame

B

enth

ic C

ateg

ory

In

dono

or

Mer

ican

Te

laga

- N

orth

S

UM

S

ME

AN

S

D

SE

IN

DE

X

SU

MS

M

EA

N

SD

S

E

IND

EX

S

UM

S

ME

AN

S

D

SE

IN

DE

X

HA

RD

CO

RA

L

355.

00

11.8

3 10

.10

1.84

1.

30

756.

00

25.2

0 8.

01

1.46

1.

30

292.

00

9.73

8.

45

1.54

1.

43

Bra

nchi

ng C

oral

(CB

) 94

.00

3.13

4.

70

0.86

0.

35

312.

00

10.4

0 11

.61

2.12

0.

37

122.

00

4.07

4.

85

0.89

0.

36

Enc

rust

ing

Cor

al (C

E)

13.0

0 0.

43

1.41

0.

26

0.12

22

.00

0.73

3.

83

0.70

0.

10

9.00

0.

30

0.70

0.

13

0.11

Fo

liose

Cor

al (C

F)

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

M

assi

ve C

oral

(CM

) 61

.00

2.03

3.

31

0.60

0.

30

96.0

0 3.

20

3.94

0.

72

0.26

72

.00

2.40

2.

99

0.55

0.

35

Mus

hroo

m C

oral

(CFU

) 0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

Sub

-mas

sive

Cor

al (C

S)

4.00

0.

13

0.43

0.

08

0.05

0.

00

0.00

0.

00

0.00

0.

00

4.00

0.

13

0.73

0.

13

0.06

Ta

bula

te C

oral

(CT)

17

1.00

5.

70

10.0

9 1.

84

0.35

26

5.00

8.

83

12.7

4 2.

33

0.37

66

.00

2.20

4.

97

0.91

0.

34

NO

N-H

AR

D C

OR

AL

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

Mill

epor

a (C

NS

) 0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

Sof

t Cor

al (C

SF)

1.

00

0.03

0.

18

0.03

0.

00

0.00

0.

00

0.00

0.

00

0.00

10

.00

0.33

0.

92

0.17

0.

00

SE

A U

RC

HIN

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

Sea

Urc

hin

(OIN

) 47

.00

33.0

0

15

9.00

IN

VE

RTE

BR

ATE

S

46.0

0 1.

53

3.75

0.

68

0.18

32

.00

1.07

1.

68

0.31

0.

24

158.

00

5.27

5.

74

1.05

0.

33

Enc

rust

ing

Spo

nges

(OS

P)

1.00

0.

03

0.18

0.

03

0.01

0.

00

0.00

0.

00

0.00

0.

00

1.00

0.

03

0.18

0.

03

0.01

In

verte

brat

es (O

IV)

0.00

0.

00

0.00

0.

00

0.00

1.

00

0.03

0.

18

0.03

0.

02

0.00

0.

00

0.00

0.

00

0.00

N

ot A

vaila

ble

(ON

A)

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

U

prig

ht S

pong

es (O

SU

) 1.

00

0.03

0.

18

0.03

0.

00

19.0

0 0.

63

1.79

0.

33

0.00

2.

00

0.07

0.

25

0.05

0.

00

FLE

SH

Y M

AC

RO

ALG

AE

17

.00

5.00

29

.00

PR

O-R

ES

ILIE

NC

E A

LGA

E

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

C

alca

reou

s M

acro

alga

e (M

AC

) 3.

00

0.10

0.

55

0.10

0.

00

0.00

0.

00

0.00

0.

00

0.00

25

.00

0.83

1.

82

0.33

0.

00

Cru

stos

e C

oral

line

Alg

ae (C

RU

) 14

.00

0.47

1.

61

0.29

0.

00

5.00

0.

17

0.53

0.

10

0.00

4.

00

0.13

0.

35

0.06

0.

00

Fila

men

tous

Tur

f Alg

ae (T

UR

) 61

.00

82.0

0

19

4.00

S

ETT

LEA

BLE

SU

BS

TRA

TE

11.0

0 0.

37

1.19

0.

22

0.11

61

.00

2.03

5.

30

0.97

0.

20

9.00

0.

30

0.70

0.

13

0.11

R

ecen

tly D

ead

Cor

al (C

DC

) 0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

Def

orm

ated

dea

d co

ral (

OR

N)

50.0

0 1.

67

2.41

0.

44

0.19

21

.00

0.70

1.

34

0.25

0.

19

185.

00

6.17

6.

20

1.13

0.

34

Turf

cove

red

rubb

le (O

RU

) 39

5.00

13

.17

7.86

1.

44

0.33

18

4.00

6.

13

6.19

1.

13

0.30

21

2.00

7.

07

5.89

1.

08

0.36

Tu

rf co

vere

d m

alfo

rmat

ed d

ead

cora

l (O

RC

) 21

5.00

62

.00

201.

00

UN

SE

TTLE

AB

LE S

UB

STR

ATE

19

4.00

6.

47

8.91

1.

63

0.35

6.

00

0.20

0.

61

0.11

0.

08

1.00

0.

03

0.18

0.

03

0.01

S

and

(OS

D)

21.0

0 0.

70

2.28

0.

42

0.10

56

.00

1.87

3.

88

0.71

0.

31

200.

00

6.67

8.

60

1.57

0.

35

Sed

imen

/Silt

Cov

er (O

SI)

355.

00

11.8

3 10

.10

1.84

1.

30

756.

00

25.2

0 8.

01

1.46

1.

30

292.

00

9.73

8.

45

1.54

1.

43

TOTA

L S

UB

SR

TATE

SA

MP

LED

69

6

95

7

87

7

S

ite N

ame

B

enth

ic C

ateg

ory

Te

ngah

Le

gon

Boy

o Le

gon

Tole

S

UM

S

ME

AN

S

D

SE

IN

DE

X

SU

MS

M

EA

N

SD

S

E

IND

EX

S

UM

S

ME

AN

S

D

SE

IN

DE

X

HA

RD

CO

RA

L

427.

00

14.2

3 9.

87

1.80

1.

44

591.

00

19.7

0 8.

21

1.50

1.

22

630.

00

21.0

0 9.

18

1.68

1.

32

Bra

nchi

ng C

oral

(CB

) 22

0.00

7.

33

6.04

1.

10

0.34

12

8.00

4.

27

5.63

1.

03

0.33

29

0.00

9.

67

8.17

1.

49

0.36

E

ncru

stin

g C

oral

(CE

) 39

.00

1.30

5.

31

0.97

0.

22

69.0

0 2.

30

2.93

0.

53

0.25

9.

00

0.30

0.

65

0.12

0.

06

Folio

se C

oral

(CF)

21

.00

0.70

1.

95

0.36

0.

15

7.00

0.

23

0.68

0.

12

0.05

34

.00

1.13

3.

88

0.71

0.

16

Mas

sive

Cor

al (C

M)

28.0

0 0.

93

2.18

0.

40

0.18

33

7.00

11

.23

8.28

1.

51

0.32

16

7.00

5.

57

6.03

1.

10

0.35

M

ushr

oom

Cor

al (C

FU)

0.00

0.

00

0.00

0.

00

0.00

1.

00

0.03

0.

18

0.03

0.

01

0.00

0.

00

0.00

0.

00

0.00

S

ub-m

assi

ve C

oral

(CS

) 14

.00

0.47

1.

85

0.34

0.

11

40.0

0 1.

33

4.47

0.

82

0.18

12

.00

0.40

0.

97

0.18

0.

08

Tabu

late

Cor

al (C

T)

92.0

0 3.

07

6.17

1.

13

0.33

8.

00

0.27

1.

05

0.19

0.

06

118.

00

3.93

8.

15

1.49

0.

31

NO

N-H

AR

D C

OR

AL

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

12

.00

0.40

2.

19

0.40

0.

00

Mill

epor

a (C

NS

) 0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

12

.00

0.40

2.

19

0.40

0.

00

Sof

t Cor

al (C

SF)

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

SE

A U

RC

HIN

0.

00

0.00

0.

00

0.00

0.

00

77.0

0 2.

57

3.60

0.

66

0.29

36

.00

1.20

2.

93

0.53

0.

21

Sea

Urc

hin

(OIN

) 3.

00

2.00

2.

00

INV

ER

TEB

RA

TES

3.

00

0.10

0.

31

0.06

0.

03

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

Enc

rust

ing

Spo

nges

(OS

P)

0.00

0.

00

0.00

0.

00

0.00

2.

00

0.07

0.

25

0.05

0.

02

1.00

0.

03

0.18

0.

03

0.01

In

verte

brat

es (O

IV)

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

N

ot A

vaila

ble

(ON

A)

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

1.00

0.

03

0.18

0.

03

0.01

U

prig

ht S

pong

es (O

SU

) 12

.00

0.40

1.

10

0.20

0.

18

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

FLE

SH

Y M

AC

RO

ALG

AE

20

7.00

0.

00

1.00

P

RO

-RE

SIL

IEN

CE

ALG

AE

17

4.00

5.

80

6.74

1.

23

0.06

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

C

alca

reou

s M

acro

alga

e (M

AC

) 20

.00

0.67

1.

60

0.29

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

0.00

0.

00

Cru

stos

e C

oral

line

Alg

ae (C

RU

) 13

.00

0.43

0.

97

0.18

0.

00

0.00

0.

00

0.00

0.

00

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Appendix 3. Model parameter sensitivity test results. Sensitivity index (SI) was measured as the proportion of the adjusted output value change relative to the ‘base’ output values. Values printed in bold indicates the SI of the affected benthic group output. Each parameter test was from 100 simulation and 1-year (t+1) runs. Parameter Name Adjustments Input

Value Output Rel.

abundance (t+1)

Sensitivity Index (%)

Min (Base) 0.2 M 0.155 C 0.310

Adjusted 1 0.325 M (t+1) 0.155 -0.003 C (t+1) 0.310 0.000

Adjusted 2 0.45 M (t+1) 0.155 -0.007 C (t+1) 0.310 0.000

Adjusted 3 0.575 M (t+1) 0.155 -0.010 C (t+1) 0.310 0.000

Max 0.7 M (t+1) 0.155 -0.014

Probability of Macroalgae Occupying Space

C (t+1) 0.310 0.000 -40% SD 0.00024 M (t+1) 0.155 -0.008

C (t+1) 0.310 0.000 -20% SD 0.00032 M (t+1) 0.155 -0.004

C (t+1) 0.310 0.000 Base 0.0004 M 0.155

C 0.310 +20% SD 0.00048 M (t+1) 0.155 0.004

C (t+1) 0.310 0.000 +40% SD 0.00056 M (t+1) 0.155 0.008

Baseline Macroalgae Lateral Growth

C (t+1) 0.310 0.000 Min (Base) 0.07 M 0.176

C 0.307 Adjusted 1 0.3025 M (t+1) 0.176 0.000

C (t+1) 0.307 0.001 Adjusted 2 0.535 M (t+1) 0.176 0.000

C (t+1) 0.307 0.001 Adjusted 3 0.7675 M (t+1) 0.176 0.000

C (t+1) 0.307 0.002 Max 1 M (t+1) 0.176 0.000

Probability of Coral Occupying Space

C (t+1) 0.307 0.003 Min (Base) 0.00016 M 0.176

C 0.307 Adjusted 1 0.000165 M (t+1) 0.176 0.000

C (t+1) 0.307 0.000 Adjusted 2 0.00017 M (t+1) 0.176 0.000

C (t+1) 0.307 0.000 Adjusted 3 0.000175 M (t+1) 0.176 0.000

C (t+1) 0.307 0.000 Max 0.00018 M (t+1) 0.176 0.000

Baseline Coral Lateral Growth

C (t+1) 0.307 0.000 Reduction Effect of Random 'Other 'Presence

100 Iteration Random

value from 0 - 1

No effect to C and M composition

Parameter Name Adjustments Input

Value Output Rel.

abundance (t+1)

Sensitivity Index (%)

-40% SD 0.18 M (t+1) 0.218 23.921 C (t+1) 0.307 0.000

-20% SD 0.24 M (t+1) 0.197 11.960 C (t+1) 0.307 0.000

Base 0.3 M 0.176 C 0.307

+20% SD 0.36 M (t+1) 0.155 -11.960 C (t+1) 0.307 0.000

+40% SD 0.42 M (t+1) 0.134 -23.921

Baseline Macroalgae Mortality

C (t+1) 0.307 0.000 Min 0.05 M (t+1) 0.263 -49.835

C (t+1) 0.307 0.000 Adjusted 1 0.1125 M (t+1) 0.241 -37.376

C (t+1) 0.307 0.000 Adjusted 2 0.175 M (t+1) 0.219 -24.917

C (t+1) 0.307 0.000 Adjusted 3 0.2375 M (t+1) 0.197 -12.459

C (t+1) 0.307 0.000 Max (Base) 0.3 M 0.176

Macroalgae Grazing Loss Scenario

C 0.307 -40% SD 0.012 M (t+1) 0.176 0.000

C (t+1) 0.310 0.911 -20% SD 0.016 M (t+1) 0.176 0.000

C (t+1) 0.309 0.455 Base 0.02 M 0.176

C 0.307 +20% SD 0.024 M (t+1) 0.176 0.000

C (t+1) 0.306 -0.455 +40% SD 0.028 M (t+1) 0.176 0.000

Baseline Coral Mortality C (t+1) 0.302 -1.822

-40% SD 0.3 M (t+1) 0.155 0.000 C (t+1) 0.284 11.877

-20% SD 0.4 M (t+1) 0.155 0.000 C (t+1) 0.277 8.890

Base 0.5 M 0.155 C 0.254

+20% SD 0.6 M (t+1) 0.155 0.000 C (t+1) 0.254 -0.183

+40% SD 0.7 M (t+1) 0.155 0.000

Anchor Hit Probability C (t+1) 0.253 -0.518

Min (Base) 0.05 M 0.155 C 0.308

Adjusted 1 0.2875 M (t+1) 0.155 0.000 C (t+1) 0.299 -3.121

Adjusted 2 0.64375 M (t+1) 0.155 0.000 C (t+1) 0.281 -8.960

Adjusted 3 0.9109375 M (t+1) 0.155 0.000 C (t+1) 0.269 -12.678

Max 1 M (t+1) 0.155 0.000

Anchor Damage

C (t+1) 0.266 -13.562

Appendix 4. Programming scripts in MatLab language used for benthic composition simulation and sensitivity assessment

Script for differential equation of coral-algae interaction using ‘equationmumby.m’ file (Courtesy of Mumby, P.J. 2006):

function Y = equationmumby (A,T,mort,MtoC,CtoT,MtoT) % Definition: Function called 'Mumby equation' accepts inputs of: % - A (Abundance), % - T (Available space), % - mort (Mortality), % - MtoC (Macroalgae and coral interaction), % - CtoT (Coral occupying space), % - MtoC (Macroalgae occupying space), %% Differential equation for Macroalgae (1) Y(1) = A(1)*( (MtoC*A(2)) + (1-mort(1)) + (MtoT*T) ); % Definition: % Macroalgae abundance at (t) = Addition due to competition + Reduction due to grazing + Addition due to space colonization % Y(1) = Macroalgae abundance at t. % A(1) = Macroalgae abundance at t-1. % A(2) = Coral abundance at t-1 %% Differential equation for COral (1) Y(2) = A(2)*(CtoT*T + (1-mort(2)) - MtoC*A(1)); % Definition: % Macroalgae abundance at (t) = Addition due to competition + Reduction due to disturbance + Addition due to space colonization % Y(2) = Coral abundance at t. % A(1) = Macroalgae abundance at t-1. % A(2) = Coral abundance at t-1

Script for Projection 1 using ‘plot2monte_iter’ file (Anthony, K.R.N.; Taruc, S.A.K.):

clf; clear all; %% SIMULATION RULES % Time interval = 6-monthly %% PARAMETER INPUT iteration = 200 ; scenario = 3; % Choose 1,4, or 9 only. year = 15; % Enter designated years. macroalgae_starting_composition = 0.6; %0.23 / 0.46 / 0.7 coral_starting_composition = 0.2; %0.23 / 0.46 / 0.7 mortality_macroalgae_baseline = 0.18; %~0.3 mortality_macroalgae_grazing = 0.2; %~0.3 / 0.05 mortality_coral_baseline = 0.02; %~0.02

% risk_anchor_hit = 0; % 0.5 % mortality_coral_anchor = 0; % 0.05 to 1 % macroalgae_coral_interaction = Please scroll and set in Set competition interaction parameter below %% Set starting composition Mzero = macroalgae_starting_composition; Czero = coral_starting_composition; A = [Mzero;Czero]; T = 1-sum(A); %% Set n of scenario for SC = 1:scenario %% Set n of year time = year * 2; for t= 1:time for I = 1:iteration % mortality_macroalgae_baseline = 0.18 + (rand*(0.3-0.18)); %~0.3 % mortality_coral_baseline = 0.012 + (rand * (0.028 - 0.012)); %~0.02 probability_macroalgae_occupying_space = 0.2 +(rand*(0.7-0.2)); %0.2 / 0.7 rate_macroalgae_occupying_space = 1; %0.0004; macroalgae_occupying_space = probability_macroalgae_occupying_space * rate_macroalgae_occupying_space; probability_coral_occupying_space = 0.07 + (rand*(1-0.07)); % 0.07 / 1 rate_coral_occupying_space = 1; %0.00018; coral_occupying_space = probability_coral_occupying_space * rate_coral_occupying_space; %% Set macroalgae baseline mortality mMb = mortality_macroalgae_baseline; %% Set macroalgae mortality due to grazing % if SC == 1 mMg = mortality_macroalgae_grazing; % elseif SC >=2 % mMg = mortality_macroalgae_grazing - (0.05 * SC); % end mMtot = mMb + mMg; %% Set coral basline mortality mCb = mortality_coral_baseline; %% Set coral mortality due to anchor damage %% For ONE anchor scenario

% risk_anchor_hit = 0; % ~0.5 % mortality_coral_anchor = 0; % 0.05 / 1 % pmCa = risk_anchor_hit * rand; % mCa = mortality_coral_anchor * rand; %% For 9 increasing anchor scenario % if SC == 1 % pmCa = 0.3; % elseif SC >= 2 % pmCa = 0.3 + ((0.6-0.3) * SC/scenario); % end % % if SC == 1 % mCa = 0.05; % elseif SC >=2 % mCa = 0.05 + ((1-0.05) * SC/scenario); % end %% For fix set of 1st 2nd and 3rd anchor scenario if SC == 1 pmCa = 0.3; elseif SC == 2 pmCa = 0.4; elseif SC == 3 pmCa = 0.5; end if SC == 1 mCa = 0.05; elseif SC == 2 mCa = 0.37; elseif SC == 3 mCa = 0.58; end mCtot = mCb + (pmCa * mCa); %% Set mortality vector mort = [mMtot; mCtot]; %% Set competition / interaction parameter % Macroalgae overgrowing coral MtoC = (0.83 * (exp(-0.0012* A(2,t))) * A(1,t)); % Macroalgae occupying free space MT = macroalgae_occupying_space; % Coral occupying free space CT = coral_occupying_space; % Competition effects: Coral to macroalgae if A(2,t) >= 0.5 MtoT = 0.75 * MT; else MtoT = MT; end % Competition effects: Macro algae to coral if A(1,t) < 0.6 CtoT = 0.5 * CT; else CtoT = CT;

end % Calculates Macroalgae / Coral Abundance at t+1, repeated it as much as iteration setting. A(:,t+1,I) = equationmumby(A(:,t),T(t),mort,MtoC,CtoT, MtoT); % Function - alculates the amount of turfs (T) based on the amount of corals and algae - total is M+C+T T(t+1) = 1-sum(A(:,t+1)); %% Summarize iteration data (MEAN AND STD) % Average meanA = mean(A,3); % Average each elements of A troughout iteration. % Standard Deviation stdevA = std(A,0,3); % Standard deviation each elements troughout iteration stdevMac = [ (meanA(1,:) + stdevA(1,:)) ; (meanA(1,:) - stdevA(1,:))]; stdevCor = [ (meanA(2,:) + stdevA(2,:)) ; (meanA(2,:) - stdevA(2,:))]; end % loop for iteration end % loop for time %% See multiple scenario values % Grazing Graz_Scen(SC)= [mMg]; % Anchoring Anc_Scen_Prob (SC) = [pmCa]; Anc_Scen_Mort (SC) = [mCa]; %% Set multi rows and colums if scenario == 1 rows = 1; columns = 1; elseif scenario == 3 rows = 3; columns = 3; elseif scenario >= 4 rows = sqrt(scenario); % So that rows and columns are relative to the scen. columns =sqrt(scenario); end %% Set subplot labelling subplot(rows,columns,SC); %% Generate Macroalgae and Coral plot plot(meanA(1,:),'og','MarkerEdgeColor',[0 0.4980 0], 'MarkerFaceColor',[0 0.4980 0], 'markersize', 5); hold on % to generate another plot on the same axes, without erasing the previous plot, until the hold off command is issued plot(meanA(2,:),'oy','MarkerEdgeColor',[0.6824 0.4667 0], 'MarkerFaceColor',[0.6824 0.4667 0], 'markersize', 5); % %% Smooth plot line (Linked to file: smoothLine.m) % For Macroalgae x = 1:time+1; ymac = meanA(1,:); [x,ymac] = smoothLine(x,ymac,10);

hold on; plot(x,ymac,'-g'); % For Coral x = 1:time+1; ycor = meanA(2,:); [x,ycor] = smoothLine(x,ycor,10); hold on; plot(x,ycor,'-m'); % Plot 95% confidence limits % For Macroalgae (STD+) x = 1:time+1; ysdM = stdevMac(1,:); [x,ysdM] = smoothLine(x,ysdM,10); hold on; plot(x,ysdM,'-b'); % For Macroalgae (STD-) x = 1:time+1; ysdM = stdevMac(2,:); [x,ysdM] = smoothLine(x,ysdM,10); hold on; plot(x,ysdM,'-b'); % For Coral (STD+) x = 1:time+1; ysdC = stdevCor(1,:); [x,ysdC] = smoothLine(x,ysdC,10); hold on; plot(x,ysdC,'-m'); % For Coral (STD-) x = 1:time+1; ysdC = stdevCor(2,:); [x,ysdC] = smoothLine(x,ysdC,10); hold on; plot(x,ysdC,'-m'); % %% Modify X and Y Axis xlabel ('TIME (YEARS)'); ylabel ('REL. ABUNDANCE (%)'); xlim ([2 time]); % Scale fit X axis label to designated range ylim ([0 1]); % Scale fit Y axis label to designated range set(gca,'XTick',(0 : 10 : time),... %Set label increments 'YTick', (0 : .1 : 1 ),... 'XTickLabel', {0: 5 : year},... %Set label scaling to manual by user 'YTickLabel', {0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100}); end % loop for scenario

Script for Projection 2 using ‘plot3contour’ file (Anthony, K.R.N.; Taruc, S.A.K.):

clf; clear all; %% SIMULATION RULES % Time interval = 6-monthly %% PARAMETER INPUT iteration = 2500 ;

scenario = 9; year =10; % Enter designated years. number_of_cell = 30; macroalgae_starting_composition = 0.3; %0.23 / 0.46 / 0.7 coral_starting_composition = 0.5; %0.23 / 0.46 / 0.7 mortality_macroalgae_baseline = 0.18; %~0.3 mortality_macroalgae_grazing = 0.2; %~0.3 / 0.05 mortality_coral_baseline = 0.02; %~0.02 % risk_anchor_hit = 0; % ~0.5 % mortality_coral_anchor = 0; % 0.05 / 1 % macroalgae_coral_interaction = Please scroll and set in Set competition interaction parameter below %% Set starting composition Mzero = macroalgae_starting_composition; Czero = coral_starting_composition; A = [Mzero;Czero]; T = 1-sum(A); %% Set initial matrix cell = number_of_cell; Z = zeros(cell, cell); Z(round(cell * Mzero),round(cell * Czero)) = 0.5; %% Set n of scenario for SC = 1:scenario %% Set n of year time = year * 2; for t= 1:time for I = 1:iteration %% Set macroalgae baseline mortality mMb = mortality_macroalgae_baseline; % mortality_macroalgae_baseline = 0.18 + (rand*(0.3-0.18)); %~0.3 % mortality_coral_baseline = 0.012 + (rand * (0.028 - 0.012)); %~0.02 probability_macroalgae_occupying_space = 0.2 +(rand*(0.7-0.2)); %0.2 / 0.7 rate_macroalgae_occupying_space = 1; %0.0004; macroalgae_occupying_space = probability_macroalgae_occupying_space * rate_macroalgae_occupying_space; probability_coral_occupying_space = 0.07 + (rand*(1-0.07)); % 0.07 / 1 rate_coral_occupying_space = 1; %0.00018; coral_occupying_space = probability_coral_occupying_space * rate_coral_occupying_space; %% Set coral basline mortality mCb = mortality_coral_baseline;

%% Set scenario of grazing without anchoring effect % if SC == 1 % mMg = mortality_macroalgae_grazing; % pmCa = 0; % mCa = 0; % elseif SC == 2 % mMg = mortality_macroalgae_grazing; % pmCa = 0; % mCa = 0; % elseif SC == 3 % mMg = mortality_macroalgae_grazing; % pmCa = 0; % mCa = 0; % elseif SC == 4 % mMg = mortality_macroalgae_grazing - (0.05 * 2); % pmCa = 0; % mCa = 0; % elseif SC == 5 % mMg = mortality_macroalgae_grazing - (0.05 * 2); % pmCa = 0; % mCa = 0; % elseif SC == 6 % mMg = mortality_macroalgae_grazing - (0.05 * 2); % pmCa = 0; % mCa = 0; % elseif SC == 7 % mMg = mortality_macroalgae_grazing - (0.05 * 3); % pmCa = 0; % mCa = 0; % elseif SC == 8 % mMg = mortality_macroalgae_grazing - (0.05 * 3); % pmCa = 0; % mCa = 0; % elseif SC == 9 % mMg = mortality_macroalgae_grazing - (0.05 * 3); % pmCa = 0; % mCa = 0; % end %% Grazing plus Anchoring if SC == 1 mMg = mortality_macroalgae_grazing; pmCa = 0.3; mCa = 0.05; elseif SC == 2 mMg = mortality_macroalgae_grazing; pmCa = 0.4; mCa = 0.37; elseif SC == 3 mMg = mortality_macroalgae_grazing; pmCa = 0.5; mCa = 0.58; elseif SC == 4 mMg = mortality_macroalgae_grazing - (0.05 * 2); pmCa = 0.3; mCa = 0.05; elseif SC == 5 mMg = mortality_macroalgae_grazing - (0.05 * 2); pmCa = 0.4; mCa = 0.37; elseif SC == 6 mMg = mortality_macroalgae_grazing - (0.05 * 2); pmCa = 0.5;

mCa = 0.58; elseif SC == 7 mMg = mortality_macroalgae_grazing - (0.05 * 3); pmCa = 0.3; mCa = 0.05; elseif SC == 8 mMg = mortality_macroalgae_grazing - (0.05 * 3); pmCa = 0.4; mCa = 0.37; elseif SC == 9 mMg = mortality_macroalgae_grazing - (0.05 * 3); pmCa = 0.5; mCa = 0.58; end mMtot = mMb + mMg; mCtot = mCb + (pmCa * mCa); %% Set mortality vector mort = [mMtot; mCtot]; %% Set competition / interaction parameter % Macroalgae overgrowing coral MtoC = (0.83 * (exp(-0.0012* A(2,t))) * A(1,t)); % Macroalgae occupying free space MT = macroalgae_occupying_space; % Coral occupying free space CT = coral_occupying_space; % Competition effects: Coral to macroalgae if A(2,t) >= 0.5 MtoT = 0.75 * MT; else MtoT = MT; end % Competition effects: Macro algae to coral if A(1,t) < 0.6 CtoT = 0.5 * CT; else CtoT = CT; end % Calculates Macroalgae / Coral Abundance at t+1, repeated it as much as iteration setting. A(:,t+1,I) = equationmumby(A(:,t),T(t),mort,MtoC,CtoT, MtoT); % Function - alculates the amount of turfs (T) based Zon the amount of corals and algae - total is M+C+T T(t+1,I) = 1-sum(A(:,t+1,I));

%% Prepare plot coordinate (KEN VERSION) if A(1,t+1,I) < 1/cell A(1,t+1,I) = 1/cell; end if A(1,t+1,I)> 1; A(1,t+1,I)= 1; end if A(2,t+1,I) < 1/cell A(2,t+1,I) = 1/cell; end if A(2,t+1,I)> 1; A(2,t+1,I)= 1; end M = round(A(1,t+1,I)*cell); C = round(A(2,t+1,I)*cell); Z(M,C) = Z(M,C)+1; end % loop for iteration end % loop for time %% COLOR CONTOUR PLOTTING %% Set multi rows and colums rows = sqrt(scenario); % So that rows and columns are relative to the scen. columns =sqrt(scenario); subplot(rows,columns,SC); pcolor(Z'); hold on x1 = [ 0.0, cell + cell/30, cell + cell/30 ]; y1 = [ cell + cell/30, 0.0, cell + cell/30 ]; fill ( x1, y1, 'w') hold on plot (x1,y1, 'w') %% Set subplot labelling xlabel ('FLESHY MACROALGAE (%)'); ylabel ('HARD CORAL (%)'); axis square set(gca,'XTick',(0 : cell/5 : cell),... %Set label increments 'YTick', (0 : cell/5 : cell),... 'XTickLabel', {0,20,40,60,80,100},... %Set label scaling to manual by user 'YTickLabel', {0,20,40,60,80,100}); %% See multiple scenario values % Grazing Scen_Graz(SC)= [mMg]; % Anchoring Scen_Anc_Prob(SC) = [pmCa]; Scen_Anc_Mort(SC) = [mCa]; end % loop for scenario

! Appendix 5. Survey questionnaire form in English and Bahasa !

THE UNIVERSITY OF QUEENSLAND Global Change Institute, Gehrmann Labs (Bld. 60) St. Lucia, Brisbane, QLD 4072, Australia Phone: +61 (21) 3365 9555, Fax: +61 (7) 3365 4755

TAKA FOUNDATION Jl. Gerung Indah, RT 04 RW III, Kelurahan Bulusan, Kecamatan tembalang, Semarang, Jawa Tengah, 50275 Indonesia Phone : +62 (24) 70741776 !"#$%&%'"($)*(+,#-"$%,()./00$)

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Appendix 6. Selected images of research activities and study area general condition.

Scenery of one of the settlement area in Karimunjawa village (February 2008).

Inshore reefs adjacent to the Karimunjawa main island seen from surface at Tengah

island (February 2008).

Team members conducting quadrate photo-transect for benthic reef and reef fish

timed-swim visual census (February 2008).

Selected photos of various reef benthic state documented during the biophysical

assessment in February 2008. Hard coral dominated (left), fleshy macroalgae dominated (middle) and urchin barren (right).

Screenshot of benthic category point count analysis from a quadrate transect photo

using CPCe program as an add-on in Excel (Microsoft®) program.

Screenshot of a benthic composition projection computation based on programming

script using MatLab® (MathWorks®) software.

Surveyors conducting questionnaire-based interviews with village members

(April 2010).

Village members filling out questionnaire form (April 2010).

Screenshot of questionnaire data coding and statistical analysis using IBM® PASW®

software.

R

elat

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Indi

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Info

rmat

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Key

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Inte

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es

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Dat

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ptat

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ulat

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en

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do

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g an

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d no

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shou

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ually

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tribu

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muc

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hel

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de

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in a

reas

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14

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Team

C

Appendix 7. Summary of respondent’s comments and interviewer’s notes from interview sessions.

Flex

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be re

spon

ded

in e

nthu

sias

m.”

Fish

erm

en

Kar

imun

jaw

a N

orth

re

side

nt

14-A

pr-1

0 Te

am A

Lear

ning

K

ey Is

sue

Anc

hor

“Anc

horin

g ca

nnot

giv

e de

vast

atin

g im

pact

on

cora

l sin

ce

cora

l are

like

tree

s, it

will

gro

w b

ack

agai

n.”

Fish

erm

en

Kar

imun

jaw

a N

orth

re

side

nt

14-A

pr-1

0 Te

am A

Lear

ning

K

ey Is

sue

Anc

hor

“To

park

(boa

t) an

d an

chor

on

cora

l ree

f are

as w

ill n

ot

dest

roy

cora

ls e

ntire

ly, s

ince

par

t of t

he c

oral

that

are

stil

l al

ive

will

gro

w a

nd re

cove

r. A

ncho

r doe

s no

t des

troy

up to

'c

oral

root

s'. I

t is

diffe

rent

with

pot

as, w

hich

cou

ld k

ill th

e w

hole

par

t of t

he c

oral

”

Fish

erm

en

Kar

imun

jaw

a K

ota

resi

dent

14-A

pr-1

0 Te

am B

Lear

ning

P

ast

Con

ditio

n C

oral

Ree

f “I

wou

ld b

e ha

ppy

to v

olun

taril

y jo

in a

mon

itorin

g of

the

cora

l ree

f. A

lthou

gh e

very

day

I go

out f

ishi

ng, I

sel

dom

di

ving

mys

elf,

othe

r (w

ho is

ofte

n) p

roba

bly

just

the

hook

ah d

iver

s, a

nd th

ose

acco

mpa

nyin

g to

uris

t (fo

r di

ving

).”

Fish

erm

en

Kar

imun

jaw

a N

orth

re

side

nt

17-A

pr-1

0 Te

am A

Lear

ning

P

ast

Con

ditio

n Fi

sh

“Fis

h ar

e ex

pect

ed to

incr

ease

as

mos

t of u

s no

w fo

cusi

ng

on s

eaw

eed

farm

ing.

It is

dec

reas

ing

rece

ntly

, how

ever

it

will

reco

ver,

fish

will

gai

n.”

Fish

erm

en

Kar

imun

jaw

a N

orth

re

side

nt

14-A

pr-1

0 Te

am A

Lear

ning

P

ast

Con

ditio

n Fi

sh

“Fis

h ar

e cu

rren

tly d

ecre

asin

g, h

owev

er, i

t see

ms

now

re

cove

ring,

sin

ce th

e us

e of

pot

as h

as b

een

redu

ced.

” Fi

sher

men

K

arim

unja

wa

Kot

a re

side

nt

14-A

pr-1

0 Te

am B

Lear

ning

K

ey Is

sue

Her

bivo

res

“The

dep

letio

n of

par

rotfi

shes

will

not

affe

ct c

oral

s, s

ince

fis

h w

ill c

ome

back

aga

in…

Jus

t mak

e su

re th

at c

yani

de

fishi

ng is

not

con

duct

ed, o

ther

wis

e it

will

kill

cor

als

for

sure

.”

Fish

erm

en

Kar

imun

jaw

a K

ota

resi

dent

14-A

pr-1

0 Te

am B

Lear

ning

K

ey Is

sue

Rub

bish

“W

aste

from

our

hou

ses

does

not

influ

ence

the

cora

l and

th

e w

ater

con

ditio

n, s

ince

our

com

mun

ity d

id n

ot u

sed

to

dum

p di

rect

ly in

the

coas

tal o

r sea

…. a

nd w

e us

ually

bur

y it

in th

e gr

ound

or b

urni

ng it

dow

n.”

Fish

erm

en

Kar

imun

jaw

a N

orth

re

side

nt

14-A

pr-1

0 Te

am A

Lear

ning

K

ey Is

sue

Rub

bish

In

Kar

imun

jaw

a ko

ta, g

arba

ge c

olle

ctin

g is

pre

sent

, but

not

in

oth

er v

illag

es. H

owev

er, i

n K

arim

un k

ota,

sm

all f

lood

ing

is a

lread

y ha

ppen

ing

alth

ough

som

etim

es, d

ue to

clo

gged

co

ndui

t.

Teac

her

Kar

imun

jaw

a N

orth

re

side

nt

15-A

pr-1

0 Te

am A

Lear

ning

K

ey Is

sue

SP

AG

S

Trad

ition

al

Kno

wle

dge

“I un

ders

tand

that

taki

ng fi

shes

out

of t

heir

spaw

ning

and

ag

greg

atio

n si

te w

ould

affe

ct th

e nu

mbe

r of f

ishe

s in

fu

ture

, how

ever

, me

and

othe

r fis

herm

en k

now

this

from

ou

r fee

ling

(intu

ition

) and

exp

erie

nce,

rath

er th

an p

ark

staf

f in

form

ing

us.”

Fish

erm

en

Kem

ujan

re

side

nt

16-A

pr-1

0 Te

am C

Not

e A

ppro

ach

Com

mun

icat

ion

The

com

mun

ity n

eed

a pl

ace

whe

re th

ey c

ould

sha

re

idea

s, d

evel

op o

rgan

izat

iona

l ski

ll an

d co

mm

unity

gro

ups.

Fi

sher

men

K

arim

unja

wa

Nor

th

resi

dent

14-A

pr-1

0 Te

am A

Not

e A

ppro

ach

Com

mun

icat

ion

“Dis

tribu

ting

broc

hure

s to

pub

liciz

e cu

rren

t reg

ulat

ion

wou

ld b

e ef

fect

ive

for P

aran

g co

mm

unity

.” H

ead

of

Par

ang

Vill

age

Par

ang

resi

dent

15

-Apr

-10

Team

B

Not

e A

ppro

ach

Live

lihoo

d “…

Mos

t of u

s w

ould

def

inite

ly a

gree

for a

con

serv

atio

n so

lutio

n th

at c

ould

als

o st

reng

then

loca

l eco

nom

y”

Fish

erm

en

Kar

imun

jaw

a N

orth

re

side

nt

14-A

pr-1

0 Te

am A

Not

e S

ituat

ion

Fish

Th

e nu

mbe

r of r

abbi

tfish

es is

sus

pect

ed to

incr

ease

due

to

aggr

egat

ion

in s

eaw

eed

culti

vatio

n ar

ea. F

or m

ost

seaw

eed

farm

er, t

hese

fish

es a

re d

istu

rbin

g si

nce

they

al

so s

uspe

ct s

eaw

eed

graz

ing

by th

ese

fishe

s.

Fish

erm

en

Kar

imun

jaw

a K

ota

resi

dent

15-A

pr-1

0 Te

am B

Not

e S

ituat

ion

Fish

ing

Red

uctio

n in

cya

nide

/ po

tas

feed

ing

was

rela

ted

to th

e in

crea

se in

sea

wee

d fa

rmin

g. S

eaw

eed

farm

ers

now

kee

p an

eye

on

thos

e co

nduc

ting

cyan

ide

fishi

ng, t

o pr

otec

t th

eir c

ultiv

atio

n. T

he s

witc

h to

sea

wee

d fa

rmin

g its

elf

mig

ht h

ave

redu

ced

the

use

of p

otas

sium

cya

nide

for

fishi

ng.

Teac

her

Kar

imun

jaw

a N

orth

re

side

nt

15-A

pr-1

0 Te

am A

Not

e S

ituat

ion

Fish

ing

Fish

erm

en d

escr

ibe

indi

catio

n of

inco

min

g w

este

rn

mon

soon

(bad

sea

son)

by

obse

rvin

g kr

angk

am (f

lesh

y se

awee

ds) b

eing

det

ache

d fro

m th

e co

rals

.

Teac

her

Kar

imun

jaw

a N

orth

re

side

nt

15-A

pr-1

0 Te

am A

Not

e S

ituat

ion

Fish

ing

Ther

e is

con

flict

of i

nter

est b

etw

een

thos

e w

ho c

ondu

ct

sust

aina

ble

fishi

ng (n

on-tr

awl a

nd n

on-lo

nglin

e) a

nd th

ose

who

stil

l con

duct

ing

who

m a

re m

ostly

ext

erna

l fis

herm

en.

Cro

p Fa

rmer

P

aran

g re

side

nt

15-A

pr-1

0 Te

am B

Not

e S

ituat

ion

Fish

ing

Mos

t fis

h-ag

greg

atin

g de

vice

has

sw

itche

d fro

m m

angr

ove

to te

rres

trial

sta

ndin

gs.

Fish

erm

en

Par

ang

resi

dent

15

-Apr

-10

Team

B

Not

e S

ituat

ion

Par

k “..

. Cur

rent

ly, i

s no

sur

veill

ance

rega

rdin

g th

is (c

yani

de

fishi

ng) a

ctiv

ity, s

ince

mos

t are

con

duct

ed in

dis

cree

t.”

Fish

erm

en

Kar

imun

jaw

a K

ota

resi

dent

14-A

pr-1

0 Te

am B

Not

e S

ituat

ion

Par

k Zo

na In

ti zo

ning

regu

latio

n is

stil

l unc

lear

for f

ishe

rmen

, of

ten

brin

gs c

onfu

sion

in e

mer

genc

y si

tuat

ion

such

as

whe

ther

to p

ark

boat

at t

hose

are

as d

urin

g st

orm

s.

Fish

erm

en

Kar

imun

jaw

a K

ota

resi

dent

14-A

pr-1

0 Te

am B

Not

e S

ituat

ion

Par

k “It

is ju

st n

ow th

at I

am b

eing

info

rmed

that

my

fam

ily a

nd I

resi

de w

ithin

a N

atio

nal P

ark”

Fi

sher

men

K

emuj

an

resi

dent

16

-Apr

-10

Team

C

Not

e S

ituat

ion

Sup

port

Sm

all l

oans

for g

ear p

rocu

rem

ent h

as b

een

avai

labl

e,

how

ever

, it d

id n

ot a

im th

e rig

ht c

omm

unity

mem

ber a

nd

tend

to b

e se

lect

ive

to th

ose

in c

lose

rela

tion

with

the

gove

rnm

ent a

utho

rity.

Fish

erm

en

Kar

imun

jaw

a K

ota

resi

dent

14-A

pr-1

0 Te

am B

Not

e S

ituat

ion

P

ark

Mos

t fis

herm

en d

o no

t kno

w w

here

all

of th

e zo

na in

ti is

lo

cate

d. M

ost k

new

onl

y M

enya

wak

an is

land

, whe

re th

e fo

reig

n re

sort

settl

ed.

Fish

erm

en

Kar

imun

jaw

a K

ota

resi

dent

14-A

pr-1

0 Te

am B

Not

e S

ituat

ion

S

uppo

rt “O

nce

the

gove

rnm

ent h

elpe

d us

by

dist

ribut

ing

free

teak

w

ood

seed

s to

thos

e th

at o

wns

min

imum

land

are

a of

1

hect

are.

Eve

ntua

lly, t

his

only

hel

ps th

ose

in m

oder

ate-

inco

me

leve

l.”

RT

lead

er

Kem

ujan

re

side

nt

14-A

pr-1

0 Te

am C

Inte

rvie

wer

s and

not

e ta

kers

:

Te

am A

: Adh

itya

K. W

arda

na (T

aka

) and

Sih

am A

fatta

K. T

aruc

(GC

I-U

Q)

Team

B: F

ebria

n A

hmad

i (Ta

ka )

and

Lely

Fik

a A

nggr

aini

(UN

DIP

) Te

am C

: Ahm

ad M

usto

fa (T

aka

) and

Dw

i Har

yant

i (U

ND

IP)

Not

e

Situ

atio

n P

ark

The

zona

inti

surv

eilla

nce

som

ehow

is s

till l

imite

d. T

he

mur

o am

i can

stil

l ope

ratin

g, c

ausi

ng d

isco

mfo

rt to

thos

e ag

ains

t it.

Fish

erm

en

Kar

imun

jaw

a K

ota

resi

dent

14-A

pr-1

0 Te

am B

Not

e

Situ

atio

n P

ark

Dis

agre

emen

t to

regu

latio

n w

as m

ore

rela

ted

to th

e im

plem

enta

tion,

rath

er th

an th

e pu

rpos

e. F

or e

xam

ple,

te

rres

trial

zon

ing

perim

eter

s of

ten

inac

cura

te, a

nd

mar

kers

was

pla

ced

with

out c

onsu

ltatio

n or

con

sent

from

th

e ow

ner o

f the

adj

acen

t lan

d, w

hich

then

cau

sing

a

conf

lict.

Teac

her

Kar

imun

jaw

a N

orth

re

side

nt

15-A

pr-1

0 Te

am A

Not

e

Situ

atio

n P

ark

Som

e pa

rts o

f the

com

mun

ity a

re w

orry

on

the

pres

ence

of

traw

l and

cya

nide

fish

er, a

nd fe

lt un

fair

on h

ow p

ark

enfo

rcem

ent e

xclu

des

exte

rnal

fish

er.

Fish

erm

en

Kar

imun

jaw

a K

ota

resi

dent

15-A

pr-1

0 Te

am B

Not

e

Situ

atio

n

Sup

port

In g

ener

al, K

arim

unja

wa

peop

le a

re o

pen

to e

duca

tion

and

train

ing

rela

ted

to e

nviro

nmen

tal a

war

enes

s an

d al

tern

ativ

e liv

elih

ood.

The

re h

as b

een

few

in th

e pa

st,

how

ever

, mos

t did

not

hav

e th

e ch

ance

, as

mos

t who

has

be

en in

vite

d ar

e ke

y pe

rson

or p

etin

ggi o

nly.

Hou

sew

ife

Kar

imun

jaw

a K

ota

resi

dent

15-A

pr-1

0 Te

am B

Org

aniz

ati

on

Invo

lvem

ent

Loca

l In

Kar

imun

jaw

a ko

ta, s

ettle

s a

fishe

rmen

ass

ocia

tion

calle

d S

inar

Bah

ari

Fish

erm

en

Kar

imun

jaw

a K

ota

resi

dent

14-A

pr-1

0 Te

am B

Org

aniz

ati

on

Situ

atio

n Y

outh

“T

he y

outh

s ar

e th

e on

es w

ho h

ave

the

mos

t sen

sitiv

ity to

w

hat i

s go

ing

on a

nd w

ill h

appe

n in

Kar

imun

jaw

a. W

e ha

ve s

ever

al y

oung

peo

ple

who

are

eag

er to

be

train

ed,

parti

cula

rly b

uild

ing

orga

niza

tiona

l cap

acity

. We

need

re

sour

ces,

and

lim

itatio

n of

reso

urce

, fro

m k

now

ledg

e up

to

tool

s an

d eq

uipm

ents

, lim

its th

em in

real

izin

g th

eir

idea

s. M

ost o

f the

you

th h

ave

high

inte

rest

in to

uris

m…

.”

Teac

her

Kar

imun

jaw

a N

orth

re

side

nt

15-A

pr-1

0 Te

am A

Org

aniz

ati

on

Dec

isio

n M

akin

g Fi

sher

men

“M

eetin

gs B

TNK

J he

ld re

late

d to

mar

ine

reso

urce

re

gula

tion

and

man

agem

ent w

ere

seld

om in

vitin

g us

(Leg

o vi

llage

fish

erm

en).”

Fish

erm

en

Kar

imun

jaw

a K

ota

resi

dent

19-A

pr-1

0 Te

am B