FOREST & LAND FIRES IMPACT STUDY IN KATINGAN …

FOREST & LAND FIRES

IMPACT STUDY IN

KATINGAN-KAHAYAN

LANDSCAPE JANUARY 15, 2016

This publication was produced for review by the United States Agency for International Development. It was prepared

by Tetra Tech ARD.

This publication was prepared for review by the United States Agency for International

Development under Contract # AID-497-TO-15-00005. It was produced by Tetra Tech ARD.

The period of this contract is from July 2015 to July 2020.

Implemented by: Tetra Tech P.O. Box 1397 Burlington, VT 05402

USAID LESTARI Forest & Land Fires Impact Study in Katingan-Kahayan Landscape P a g e | 1

Forest & Land Fires Impact

Study in Katingan-Kahayan

Landscape

JANUARY 15, 2016

DISCLAIMER

This document is made possible by the support of the American People through the United

States Agency for International Development (USAID). The contents of this document are

the sole responsibility of Tetra Tech ARD and do not necessarily reflect the views of USAID

or the United States Government.


TABLE OF CONTENTS

LIST OF TABLES & FIGURES ............................................................................................. 3

ACRONYMS ......................................................................................................................... 4

EXECUTIVE SUMMARY ...................................................................................................... 5

1. Introduction ..................................................................................................................... 7

1.1 Project Background................................................................................................... 7

1.2. Forest & Land Fires in Katingan-Kahayan Landscape .......................................... 8

1.3. Purpose and Justification ........................................................................................ 9

2. Methodology .................................................................................................................. 11

3. Results ........................................................................................................................... 17

3.1 Economic Impact ..................................................................................................... 17

3.2 Health Impact ........................................................................................................... 23

3.3 Other Impact ............................................................................................................ 27

3.4 Fire Cause and Mitigation ....................................................................................... 28

4. Conclusion .................................................................................................................... 30


LIST OF TABLES & FIGURES TABLE 1: SAMPLE FRAME ................................................................................................ 13 TABLE 2: SUMMARY OF GROUP DISCUSSIONS ............................................................ 16 TABLE 3: TOTAL AREA BURNED IN PULANG PISAU DISTRICT ..................................... 18 TABLE 4: HOUSEHOLD WELLBEING IN STUDY AREA ................................................... 19 TABLE 5: DEPENDENCY RATIO FOR EACH CLUSTER .................................................. 20 TABLE 6: PERCENTAGE OF PUPILS VS WORKING POPULATION ............................... 20 TABLE 7: INCOME DECREASED VS POVERTY LINE ...................................................... 22 FIGURE 1: CLUSTERING BASED ON NUMBER OF HOTSPOT ....................................... 12 FIGURE 2: HOTSPOT DISTRIBUTION IN THE TARGET VILLAGES ................................ 14 FIGURE 3: NUMBER OF HOTSPOT IN 2012 - 2015 .......................................................... 17 FIGURE 4: TOTAL AREA BURNED IN 3 DISTRICTS ........................................................ 18 FIGURE 5: ESTIMATED LOSS FOR RUBBER IN EACH AREA ......................................... 21 FIGURE 6: PRODUCTION LOSS FOR NON-BURNED LAND ........................................... 21 FIGURE 7: PERCENTAGE OF HOUSEHOLDS REPORTED DECREASE IN INCOME ..... 22 FIGURE 8: INCREASE IN HEALTH EXPENDITURE .......................................................... 23 FIGURE 9: AIR POLLUTANT INDEX .................................................................................. 24 FIGURE 10: NUMBER OF CASES OF RESPIRATORY INFECTION ................................. 25 FIGURE 11: NUMBER OF CASES OF DIARRHEA ............................................................ 26 FIGURE 12: NUMBER OF TRAFFIC ACCIDENTS ............................................................. 26 FIGURE 13: STATUS OF FLIGHTS .................................................................................... 27 FIGURE 14: FIRE CAUSE .................................................................................................. 28 FIGURE 15: RESPONSIBLE PARTIES .............................................................................. 28 FIGURE 16: MITIGATION EFFORTS SUGGESTED BY COMMUNITY .............................. 29


ACRONYMS

BI Bank of Indonesia

BMKG Badan Meteorologi, Klimatologi dan Geofisika (Indonesian Agency for

Meteorology, Climatology and Geophysics)

BPBD Badan Penanggulangan Bencana Daerah (Provincial Disaster

Management Agency)

BPS Badan Pusat Statistik (Statistical Bureau)

CA Conservation Area

GHG Greenhouse Gas

GIS Geographical Information System

GoI Government of Indonesia

IFACS Indonesia Forest and Climate Support

IFM Intergrated Fire Management

IR Intermediate Result

KR Key Result

LBA Landscape Baseline Analysis

LEDS Low Emission Development Strategy

LPHD Lembaga Pengelola Hutan Desa (Management Authority of Forest

Village)

M&E Monitoring & Evaluation

ME&L Monitoring, Evaluation & Learning

PPP Public Private Partnership

RAN/D-GRK Rencana Aksi Nasional/Daerah-Gas Rumah Kaca (National/Local Action

Plan for Greenhouse Gas)


EXECUTIVE SUMMARY This Forest and Land Fires Impact Study was conducted to determine the magnitude of

impacts from the 2015 Indonesian fire and haze crisis on LESTARI’s Katingan-Kahayan

Landscape in Central Kalimantan – one of the worst affected areas in the country. According

to the World Bank, the fire and haze crisis cost the Indonesian economy approximately 16

billion USD (IDR 221 trillion), more than twice the amount spent on reconstruction efforts

following the 2004 tsunami.1 As much research had already addressed macro level impacts,

this study focused its scope on livelihoods at the household level.

A mixed methodology approach was utilized, consisting of two components: (1) Quantitative

Survey and 2) Qualitative Group Discussion. For the Quantitative Survey, 30 villages were

selected, distributed evenly across 3 districts/municipality: Pulang Pisau, Katingan, and

Palangka Raya. 13 households were selected from each village for a total of 390

respondents. The qualitative component employed a total of 6 group discussions in 6

villages across the landscape. Two villages per district/municipality were selected.

The research team determined the following key impacts:

A total land area of 304,113 ha burned in the Katingan-Kahayan Landscape

An economic loss of 60,243 USD (IDR 821.65 million) from burned rubber

plantations

40% production loss in non-burned plantation/agricultural land

75% of household incomes negatively affected

207% increase in health-related expenditures

Widespread primary and secondary school closure

Hence households in the landscape suffered from a range of negative impacts to their

economy, health, and education. This underscores the importance of LESTARI’s IFM

approach in engaging with communities to raise awareness and understanding of the

importance of managing and preventing fire. By supporting the development of informed

constituencies, it is expected that communities will be able to more effectively engage on the

fire issue through governance platforms such as the Multi-Stakeholder Forum. This will

foster a transparent dialogue across stakeholders to develop commitments and embrace a

“shared-burden” to fire management – a cornerstone to LESTARI’s IFM approach.

1 Indonesia Economic Quarterly – December 2015. The World Bank.


1. INTRODUCTION This study was undertaken to determine the magnitude of the 2015 forest and land fires’

impact in LESTARI’s Katingan-Kahayan Landscape, both at the landscape and

rural/household level. The study was performed by LESTARI‘s Monitoring & Evaluation

(M&E) Team from November – December 2015. This report summarizes the key findings

and is presented in four key sections: introduction, methodology, results and analysis, and

conclusion.

1.1 Project Background USAID’s LESTARI project supports the Government of Indonesia (GoI) to reduce

greenhouse gas (GHG) emissions and conserve biodiversity in carbon rich and biologically

significant forest and mangrove ecosystems. Built on the strong foundation of USAID’s

IFACS project, LESTARI applies a landscape approach to reduce GHG emissions,

integrating forest and peatland conservation with low emissions development (LEDS) on

other, already degraded land. This is achieved through improved land use governance,

enhanced protected areas management and protection of key species, sustainable private

sector and industry practices, and expanded constituencies for conservation among various

stakeholders. LESTARI is implemented under the leadership of Tetra Tech and a consortium

of partners including WWF-Indonesia, Winrock International, Wildlife Conservation Society

(WCS), Blue Forests, Yayasan Sahabat Cipta, PT Hydro South Pole Carbon, Sustainable

Travel International (STI), Michigan State University, and the FIELD Foundation. LESTARI

runs from August 2015 through July 2020.

LESTARI activities are targeted in six strategic landscapes on three of Indonesia’s largest

islands, where primary forest cover remains most intact and carbon stocks are greatest. In

northern Sumatra, the Leuser Landscape comprises significant portions of Aceh Selatan,

Gayo Lues, Aceh Tenggara, and Aceh Barat Daya districts, and includes the Aceh portion of

Leuser National Park and Singkil Wildlife Sanctuary. In Central Kalimantan, LESTARI works

in the Katingan-Kahayan Landscape, comprising Pulang Pisau, Katingan, and Gunung Mas

districts; Palangkaraya municipality; and Sebangau and Bukit Baka Bukit Raya National

Parks. LESTARI also works in four landscapes in Papua. Sarmi and Cyclops Landscapes

are located along the northern coast and comprise Sarmi district as well as Jayapura district

and municipality. The Lorentz Lowlands Landscape, comprising Mimika and Asmat districts

plus a large portion of Lorentz National Park, and the Mappi-Bouven Digoel Landscape are

located along Papua’s southern coast. LESTARI is managed from its headquarters in

Jakarta, with offices in each landscape as well as the provincial capitals of Aceh, Central

Kalimantan, and Papua

Overall Results of LESTARI are:

Key Result 1: At least 41% of total CO2-equivalent emissions reduced from land use,

land use change and deforestation averaged across all landscapes within the project

scope;

Key Result 2: At least 8.42 Million hectares of primary or secondary forest (and

peatland), including orangutan habitat, under improved management;


IR 1: Improved Forest Management:

Key Result 3: Management of at least six Conservation Areas (CAs) improved,

resulting in the conservation of valuable orangutan and other key species habitat,

and the reduction in poaching of threatened and endemic species;

Key Result 4: At least ten Public-Private Partnerships (PPPs) promoting low-

emissions conservation oriented development established;

Key Result 5: Funding leveraged from public and private sources, representing co-

investment in project outcomes;

IR 2: Improved Land Use Governance:

Key Result 6: Increased commitment of key private sector, government, and

community stakeholders regarding the positive benefits of conservation and

sustainable use of forests and the species they encompass;

Key Result 7: Policies, laws, regulations, and procedures in support of low emission

development and forest conservation and management increased, promulgated, and

enforced at all levels; and

Key Result 8: Model(s) for successful integration of district, provincial, and national

low emissions development and forest conservation strategies developed and shared

at all levels of government and with other key stakeholders.

1.2. Forest & Land Fires in Katingan-Kahayan Landscape The Katingan-Kahayan Landscape is located in Central Kalimantan, the third largest

province in Indonesia. The province is divided into three biophysical regions: coastal

mangroves and peat dominated swampland in the south; central plains and low hills formerly

covered by tropical rain forest but largely converted to agriculture; and higher hills and

mountainous areas that are generally still covered by forest and difficult to access. For the

purpose of the LESTARI project, the operational landscape is defined by Katingan, Pulang

Pisau, and Gunung Mas districts as well as Palangkaraya municipality.

31% of the landscape is covered in carbon-rich peatland. Even when there is no land cover

transition, emissions from peat using the RAN/D-GRK methodology account for 62% (24.5

Mio t.CO2-eq) of all land based emissions.2 The peatlands of Central Kalimantan have

undergone dramatic ecological and social change over the past few decades. Millions of

hectares have been drained and converted from forest to agricultural land and oil palm

plantations. These lands are at a much greater risk of uncontrolled fire, particularly when

rainfall is at below-normal levels.

In the Katingan-Kahayan Landscape and other parts of Indonesia, fire has long been an

integral part of agricultural practices and food production, providing fertility to soils while

helping to clear land for cultivation. Fire has also been used in land clearing for oil palm and

timber plantations. However, the uncontrolled spread of fire poses a serious risk to public

health, livelihoods, and conservation efforts in Indonesia. During the 1997-98 El Niño event,

2 LESTARI Landscape Baseline Analysis (LBA), September 2015.


major forest and peatland fires resulted in regional haze, thousands of hospitalizations, and

an estimated 5-10 billion USD in economic losses at the national level.3

From June to October 2015, also recorded as an El Niño year, the landscape again suffered

from forest and land fires that generated the smoke-haze problem. Tacconi 4 noted that in El

Niño years, degraded peatlands may be the most significant risk factor for the generation of

smoke-haze. This has resulted in devastating impacts to the health and wellbeing of

communities, crippled local economies, and destroyed significant areas of forest and the

biodiversity that they harbor, while significantly exacerbating climate change on a global

scale.

In October 2015, Bank of Indonesia (BI) in Central Kalimantan published its assessment

report5 on the economic impacts of the smoke and haze in Central Kalimantan. The study

assessed impacts related to economic growth and inflation, as well as other indicators

including health, education, and government reputation. Though the study used data and

information for September 2015 (the smoke-haze problem deteriorated in October 2015), the

impacts revealed at the provincial level were significant. These include:

From a total area burned of 10,015 ha, 3.21% or 321.55 ha were estimated as rubber

plantations and 2.23% or 223.52 ha were estimated as oil palm plantations.

Economic losses suffered by smallholders and companies amounted to 680,000

USD (IDR 9.3 billion).

Occupancy rates for hotels decreased up to 10-15%, causing income losses up to

152,000 USD (IDR 2.07 billion).

On September 2015, the number of flights departing from and arriving at Central

Kalimantan decreased up to 43.68% or 358 flights. Total income loss for this industry

reached 50%.

BI estimated that smoke-haze pollution during September 2015 caused a fall in

annual economic growth for Central Kalimantan up to 0.04-0.10%.

Other impacts included 21,905 people suffering from respiratory infection, 8,165

people having diarrhea, and the closing of schools for up to one and half months.

The recurring fires and smoke-haze problems in Central Kalimantan resulted in a

decrease in public trust towards the local government.

1.3. Purpose and Justification Despite several publications on the 2015 forest and land fires in Indonesia, including the

recent BI report for Central Kalimantan province, the LESTARI project considered it

important to undertake its own study for the following reasons:

The BI report on fire and smoke-haze impacts was limited to data and information

gathered during September 2015. In the meantime, fire and smoke-haze incidents

3 Early Warning and Response to Peatland Fires in Central Kalimantan, Erica Allis, International Research Institute for

Climate and Society, Columbia University, USA. 4 Fires in Indonesia: Causes, Costs and Policy Implications, Luca Tacconi, Occasional Paper No. 38, CIFOR, 2003. 5 Dampak Kabut Asap terhadap Perekonomian Provinsi Kalimantan Tengah, Ekspedisi Indonesia Biru, Bank Indonesia,

October 2015.


worsened during October 2015. The anecdotal information gathered prior to

undertaking field study indicated greater impacts than those reported.

While many research publications revealed impact on the macro level (national,

province), no research had been undertaken to understand negative impacts on the

micro level (rural, household).

The Landscape Baseline Analysis (LBA) found that projected emissions for the

Katingan-Kahayan Landscape constitute 58% of all baseline emissions over

LESTARI landscapes. This has significant consequence for the design of LESTARI in

the Katingan-Kahayan Landscape since maximum effort should be placed where

expected emissions are greatest. Therefore, peatland management is key and

should encompass all aspects of work within the peatland areas of the landscape.

Improving peatland management involves policy influence and advocacy work as a

means of realizing sustainable, transformative change. Hence gathering evidence of

forest and land fires impacts in this landscape is essential to enable the project to

communicate to policy makers in a convincing and constructive manner.

The primary objective of this study was to determine the magnitude of forest and land fires

impacts in the Katingan-Kahayan Landscape both at the landscape and rural/household

level. While it was understood that the forest and land fires resulted in a broad array of

impacts to GHG emissions, biodiversity, health, and the local economy, this study focused

its scope on livelihoods impacts from the household perspective. Nevertheless, this report

also presents data and information related to health and other impacts (e.g. education, traffic

accident, flight cancellation, etc.) gathered from primary and secondary data collection.


2. METHODOLOGY This chapter outlines the methodological approach used for the study. It starts with a

description of the research design, which includes the quantitative component of the study

with a detailed account of the sample design. The chapter then describes the qualitative

component and outlines how the qualitative dimension of the survey was designed and

conducted. Finally, constraints and limitations in executing the study are articulated.

The methodology employed for this study involved a mix of methods. Mixed methodology is

generally preferable to any single method as the phenomenon being investigated can benefit

from the strengths of both quantitative and qualitative research paradigms. The

methodology, therefore, involved: 1) Quantitative Survey and 2) Qualitative Group

Discussion. Each of these is described below.

Glover and Jessup6 classified forest and land fires impacts into two categories: 1) Fire-

related damages (i.e., timber, agriculture, firefighting costs, carbon emissions, biodiversity,

direct forest benefits, indirect forest benefits) and 2) Smoke-haze related damages (i.e.,

health, tourism, transport, industrial production losses, fishing decline). Considering some

constraints such as timing, resources, and expertise, this study limited its scope on

livelihoods impacts from the household perspective (micro level). The research team

developed the hypothesis that households suffered much worse from the forest and land

fires incident than the level portrayed in published information. This assumption was built

upon anecdotal information provided to LESTARI field staff in Central Kalimantan by rubber

smallholders in Buntoi Village (Pulang Pisau District) who reported that 90% of their rubber

plantations had burned during the recent fires.

Despite being focused on forest and land fires impacts at the household or rural level, this

study also collected secondary data and information from districts and provinces to get a

wider perspective of impacts. Various relevant institutions were visited. The data gathered

includes information on health, flight cancellations, total area burned, traffic accidents,

market prices, and rubber production, among others.

Quantitative (Household) Survey

The forest and land fires impact study was conducted in two districts and one municipality in

the Katingan-Kahayan Landscape, comprising Pulang Pisau, Katingan, and Palangka Raya.

It is worth noting that the unit of analysis was the project landscape. Thus interpretation of

impacts at the provincial level should be done with caution because the sample of districts

was not chosen to statistically represent the Province of Central Kalimantan.

A few steps were undertaken in order to acquire a sample of households for this study. First,

the sample size was determined using population data. According to the National Statistical

Bureau (Badan Pusat Statistik or BPS) data in 2013, total population for the targeted

districts/municipality was 522,900 people. An initial working sample size was then calculated

6 Indonesia’s Fires and Haze: The Cost of Catastrophe, D Glover and T Jessup, Institute of Southeast Asian Studies,

International Development Research Centre, Singapore.


using a 95% confidence level and 5% margin of error. A sample size of 390 respondents

was obtained to statistically represent data at the landscape level.

Village Selection: The second step was to select target villages. Considering the different levels of fire incidents within the three districts/municipality, the team decided to establish clusters based on a hotspot7 map provided by the LESTARI GIS unit. It was determined that there were 157 villages with hotspots across the three districts/municipality, or more than 50% of the 290 total villages.

FIGURE 1: CLUSTERING BASED ON NUMBER OF HOTSPOT

K-Means Cluster8 analysis was then used to divide all villages into three clusters: 1) Red –

villages with large numbers of hotspots; 2) Yellow – villages with medium numbers of

hotspots and 3) Green – area of villages where no hotspots were identified, but the area was

affected by forest and land fires. Figure 1 illustrates the clustering.

The next step was to determine the required sample of villages to visit. Effectiveness and

efficiency were the main considerations to establish this sample. It was decided that 30

villages would be targeted for surveying. This meant that 13 households should be selected

from each village for a total of 390 respondents. To be administratively efficient, 30 villages

were distributed evenly across target districts/municipality. In other words, 10 sample

villages were selected per district/municipality. Proportionate to size sampling method was

then used to divide the 10 villages into clusters (red, green, yellow). Finally, the target

villages to be surveyed in each cluster were determined using random sampling.

Household Selection: Household respondents within a village were selected using

systematic interval sampling while the starting points were determined by the field

supervisor. The length of the interval was two households. The short interval was utilized

due to the likelihood of finding villages with low population densities. However, when the

survey team found a densely populated area, the interval length could be extended to five

households. Table 1 presents the sample frame for this study, followed by an indicative map

of the study area in Figure 2.

7 Hotspots data obtained from MODIS and reflected number of hotspots until October 2015 8 Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a

cluster) are more similar (in some sense or another) to each other than those in other groups (clusters).

No hotspot identified in green area, but the area affected by forest and land fires

District/Municipality Area

Area with large numbers of

hotspot/center of fire

Area with medium numbers of hotspot


TABLE 1: SAMPLE FRAME

District/ Municipality

Cluster Target Village Number of Hotspots

Sample of household per

Village

Palangka Raya

Red

Kalampangan 7 13

Habaring Hurung 17 13

Tangkiling 19 13

Bukit Tunggal 68 13

Yellow

Bereng Bengkel 1 13

Petuk Katimpun 2 13

Pager 3 13

Green

Langkai 0 13

Tanjung Pinang 0 13

Banturung 0 13

Katingan

Red

Tewang Tampang 5 13

Kampung Melayu 8 13

Baon Bango 34 13

Yellow

Telok 1 13

Tewang Karangan 2 13

UPT Hiang Bana 3 13

Dahian Tunggal 1 13

Green

Kampung Baru 0 13

Tewang Kadamba 0 13

Petak Bahandang 0 13

Pulang Pisau

Red

Gohong 155 13

Buntoi 108 13

Jabiren 26 13

Kanamit 73 13

Paduran Sabangau

761 13

Yellow Anjir Pulangpisau 3 13

Purwodadi 1 13

Green

Talio Muara 0 13

Badirih 0 13

Pangkuh Sari 0 13

TOTAL 1,298 390


FIGURE 2: HOTSPOT DISTRIBUTION IN THE TARGET VILLAGES


Respondents Selection: A respondent was selected from the surveyed households in each

of the villages. The criteria used for this selection included: 1) persons are considered ‘adult’

by BPS and 2) the persons are decision makers in the household or have knowledge or

responsibility to manage household budget. Such knowledge was necessary when the

respondent had to answer questions regarding livelihood and income.

Questionnaire: The questionnaire was divided into 5 groups

covering general information about the respondent and his/her

household; economic condition of the household pre and post fire

and smoke-haze incident; impacts on agriculture; impacts on health

of household members; aid received by households during the

incident; and causes and fire mitigation.

Anonymity: Anonymity was ensured in all data analysis and reporting. Respondents were

assured that, to protect confidentiality, only aggregate, anonymous data would be released.

Interviewers clearly stated that participation in the survey was optional, and respondents

were asked if they were willing to participate. Any respondent not comfortable with the

confidentially of the activity, or unwilling to take part for any other reason, was not required to

participate in the survey. In such cases, the interviewer thanked the individual, terminated

the interview, and immediately moved on to the next household according to the household

selection guidelines.

Quality Control: For quality control purposes, a supervisor was assigned to each team of

interviewers. These individuals carried out a series of witnessing and data cleaning. Data

cleaning included checking for missing data, verifying that the skipped responses were

properly executed, and verifying that proper response coding was used. The final field check

was performed by the Landscape M&E Specialist in Central Kalimantan. The completed

questionnaires were subsequently sent to the Jakarta office and passed through another

review process by the Jakarta M&E Specialist and data entry staff.

Data Analysis: Data analysis was completed using SPSS by a statistician

under technical guidance from LESTARI Monitoring, Evaluation and

Learning (ME & L) Coordinator. Secondary data was used to enrich the

analysis of the household survey.

This survey was interviewer-administered. Survey supervisors and

fieldworkers were recruited locally, mostly from the Regional Statistical Bureau (BPS)

networks – known as Mitra BPS or BPS partners – who are experienced in conducting

household surveys and familiar with the local culture and language. A training session was

held in Palangka Raya on November 11, 2015. The survey ran for two weeks from

November 13 to 27, 2015. Data entry and analysis was performed in the Jakarta office. A

total of 21 people were part of the survey team under direct supervision of LESTARI ME & L

Coordinator.

On average, each interview required one hour and 13 minutes.

The survey team successfully interviewed 390 respondents – 45%

female and 55% male. For secondary data collection, the team

visited more than 15 institutions in targeted districts/municipality,


including government offices/dinas, hospitals/public health facilities, airport, markets, police

stations, and business associations.

Qualitative Group Discussions

Group discussions were conducted to

obtain more information about impacts,

causes, and fire mitigation at the

community level. The qualitative

component employed a total of six group

discussions in 6 villages across the

landscape. Two villages per

district/municipality were selected. One

represented the red cluster and the other

represented the green cluster. A total of

99 community members participated in

these sessions. Table 2 summarizes the

information of group discussions.

TABLE 2: SUMMARY OF GROUP DISCUSSIONS

District/ Municipality

Village Date Number of

participants

Palangka Raya Habaring Hurung November 14th, 2015 16 (9 female, 7 male)

Tanjung Pinang November 18th, 2015 15 (6 female, 9 male)

Katingan Kampung Melayu November 21st, 2015 17 (1 female, 16 male)

Petak Bahandang November 25th, 2015 17 (6 female, 11 male)

Pulang Pisau Talio Muara November 24th, 2015 15 (7 female, 8 male)

Gohong November 27th, 2015 19 (3 female, 16 male)

Group discussions were facilitated by field supervisors and attended by the Landscape M&E

Specialist. Follow-up questions and group sharing were used to glean insights from

participants. A guideline was provided to the facilitators.

Constraints and Limitations

Subtitutions were made to a few villages due to accessibility, but without ignoring

representation of clusters. Another limitation includes the limited scope of the study as

previously explained. Efforts were not made to assess fire-related damages such as impacts

on timber production, firefighting costs, carbon emissions, biodiversity, direct forest benefits,

and indirect forest benefits.


3. RESULTS This chapter presents the results of the quantitative survey and qualitative group

discussions. First, the findings regarding economic impacts are discussed. This is followed

by an analysis of impacts on health and other indicators. Lastly, a section is presented on

fire causes and mitigation efforts. This underscores the importance of LESTARI interventions

to facilitate mitigation efforts with key stakeholders through an Integrated Fire Management

(IFM) approach.

3.1 Economic Impact

TOTAL AREA BURNED

Local communities reported that the 2015

fire and smoke-haze incident was the most

severe compared to similar incidents in

previous years. This report was in

accordance with the results of an analysis

on hotspot data performed by the LESTARI

GIS unit. The findings demonstrate a

significant increase in numbers of hotspots

in 2015 compared to those identified in 2012

– 2014. Figure 3 illustrates this situation.

Though the fire incident was remarkable, it was not easy to obtain exact figures for the total area burned in the survey area. Different figures were provided by various government offices. For instance, the provincial government reported that the total rubber plantation area burned in Pulang Pisau district during the recent fire incident was 428.40 ha. However, the district agricultural office in Pulang Pisau reported that 4,364 ha of smallholders’ rubber plantations were burned in 2015.

Using data provided by the Provincial Disaster Management Agency (Badan Penanggulangan Bencana Daerah or BPBD), BI reported

FIGURE 3: NUMBER OF HOTSPOT IN 2012 - 2015

Source : MODIS Terra Aqua - FIRMS – NASA, data processed

that the total area burned in Central Kalimantan Province was 10,015 ha, of which 3.21%

was rubber plantation and 2.23% oil palm plantation. Nevertheless, information released by

the Government of Pulang Pisau indicates that 15,326 ha of land had burned in this district

(Table 3).

0

500

1000

1500

2000

2500

3000

3500

2012 2013 2014 2015

94 90

6141026

574124

585

3077

42 43 208 305

Number of hotspot distribution in Katingan, Pulang Pisau & Palangka Raya

during Jan-Oct 2012-2015

Katingan Pulang Pisau Palangkaraya


TABLE 3: TOTAL AREA BURNED IN PULANG PISAU DISTRICT

Sub-district

Total Area Burned (Ha)

Paddy Land Farm Land

Smallholders’ Plantation

Rubber Oil Palm Bush

Kahayan Kuala - - - - 50

Pandih Batu - 5 50 10 -

Maliku 6 - 501 700 1,787

Kahayan Hilir 240 100 325 40 1,800

Sebangau Kuala

- - 377 163 265

Jebiren Raya - 49 3,000 500 5,000

Kahayan Tengah

- 16 106 22 208

Banama Tingang

- 1 5 - -

TOTAL 246 171 4,364 1,435 9,110

Source: District Agricultural Office of Pulang Pisau, October 30, 2015

Hence this research study was not concerned with calculating an exact figure for total area burned in its target districts. Rather it was meant to demonstrate the severity of impact from the forest and land fires on livelihoods at the household level. Nevertheless, the lack of quality spatial data limits the effectiveness of policy interventions and intended outcomes. There is a clear need for better coordination between government agencies to ensure methods are standardized and high-quality, consistent data is utilized and disseminated. In addition to the information provided by local government offices, the research team tried to collect data from a village in Pulang Pisau for a case study. Data gathered from 126 villagers in Gohong Village demonstrates that 243 ha of smallholders’ rubber plantations were burned during the fire incident. Economic loss was estimated at 250,000 USD (IDR 3.4 billion). Management Authority of Forest Village in Gohong (Lembaga Pengelola Hutan Desa or LPHD)

FIGURE 4: TOTAL AREA BURNED IN 3 DISTRICTS

Source: GIS analysis using burn scar map, published by MoEF, 2015.

also reported that 30% of 3,155 ha of Hutan Desa in their village had burned.

Subsequently, an effort was made by the LESTARI GIS unit to run further analysis in order

to estimate the total area burned. Using burn scar data provided by the the Ministry of

Environment and Forestry, it was found that the total area burned in the Katingan-Kahayan

217.398

59.861

13.407Total Area Burned in 3 Districts in 2015 (ha)

Pulang Pisau

Katingan

Palangkaraya


Landscape was 304,113 ha – a figure much larger compared to most published information.

Of those numbers, 290,666 ha was divided into three districts. This is presented in Figure 4.

The total area burned in Blok C (Ex-Mega Rice Project) was found to be 157,311 ha.

During group discussions, communities in red villages also reported that 80 – 95% of their

lands were burned. Despite different estimations of total area burned, the data indicates that

forest and land fire impacts in the Katingan-Kahayan Landscape were indeed devastating.

How did this situation subsequently affect households in the study area? The next section

will discuss households’ situation pre and post fire and smoke-haze incident.

HOUSEHOLD SITUATION

The research team successfully interviewed 390 households

comprising 40% households in the red area, 30% households in

the yellow area, and 30% households in the green area. Prior to

presenting fire and smoke-haze impacts on the household, the

households’ wellbeing before the fire incident should be

discussed.

Household Wellbeing: The analysis of household wellbeing used the poverty line approach. This involved calculating average monthly expenditure per capita. The results were then compared with the official poverty line declared by BPS for Central

TABLE 4: HOUSEHOLD WELLBEING IN STUDY AREA

Cluster % Households below poverty

line

% Households above poverty

line

Red 21% 79%

Yellow 27% 73%

Green 16% 84%

Kalimantan. On September 2015, the poverty line for this province was determined to be

26.59 USD (IDR 362,729) per capita per month (http://kalteng.bps.go.id/Brs/view/id/529).

The study found that in a normal situation (no fire incident), people living in the green area

have better wellbeing than those living in red and yellow areas. This is presented in Table 4.

Dependency Ratio: The dependency ratio is an age-population ratio of those typically not in

the labor force (the dependent part) and those typically in the labor force (the productive

part). It is used to measure the pressure on the productive population. The analysis was

used to identify the area with a high dependency ratio and hence

more vulnerable to any disaster. In published international

statistics, the dependent part usually includes those under the

age of 15 and over the age of 64. The productive part makes up

the population in between ages 15 – 64. Table 5 presents the

dependency ratio in each cluster.

http://kalteng.bps.go.id/Brs/view/id/529


TABLE 5: DEPENDENCY RATIO FOR EACH CLUSTER

Cluster Number of

Dependents

Number of Productive

People

Dependency Ratio

Red 135 514 26.26%

Yellow 101 401 25.19%

Green 80 357 24.64%

Total 316 1,272 24.84%

On average, a household in the study area consists of four household members. As the

dependency ratio increases, there may be an increased burden on the productive part of the

population to maintain the upbringing of the economically dependent. The data

demonstrates that the red area had the highest dependency ratio. Further analysis showed

that compared to the other clusters, the red area exhibited the highest percentage of pupils

and the lowest percentage of working population (Table 6). Hence, the conclusion can be

made that people living in red area were more vulnerable than those living in other areas.

Vulnerability increased in parallel with severe forest and land fire impacts, as will be

discussed further.

TABLE 6: PERCENTAGE OF PUPILS VS WORKING POPULATION

Cluster Percentage of

Pupils

Percentage of Working

Population

Red 30.23% 36.95%

Yellow 24.60% 40.48%

Green 23.80% 39.59%

Total 26.69% 38.78%

LIVELIHOODS IMPACT

More than two-thirds of those interviewed

owned plantations or agriculture land. Land

ownerships varies, but the majority of

households in red and yellow areas owned

more than five hectares of plantations or

agriculture land. The main commodities

cultivated by these smallholders were rubber

(51%), paddy (29%), and palm oil (13%).

Rubber plantations were found to be

dominant in red and yellow areas. While

paddy was the main commodity for

households in green area, some of them also

cultivated rubber for their livelihoods.


FIGURE 5: ESTIMATED LOSS FOR RUBBER IN EACH AREA

From a total of 303 ha of rubber

plantations owned by sample households,

it was reported that 77% or 143 ha were

burned – 75 ha in red areas, 42 ha in

yellow areas, and 27 ha in green areas. All

burned areas were reported to have

productive rubber trees. Using data on

agricultural value, production cost, and net

income, the potential loss is estimated at

60,243 USD (IDR 821.65 million) or 220 to

550 USD (IDR 3 million to 7.5 million) per

ha. Figure 5 presents the estimated loss

for rubber in each area. Apart from

smallholders’ loss, the rubber business

association GAPKINDO (Gabungan

Perusahaan Karet Indonesia) reported a

decrease in productivity up to 30%.

During group discussions, communities in red areas areas in Katingan reported that 75% of

rattan gardens also burned during the fire. Other burned commodities include sengon

(Albazia falcataria), petai (Parkia speciosa), rambutan (Nephelium lappaceum), and palm oil.

FIGURE 6: PRODUCTION LOSS FOR NON-BURNED LAND

The study found that fire impacts were not

only suffered by those with burned rubber

plantations or agriculture land.

Smallholders whose land was saved from

fire also reported a significant decrease in

productivity. On average, production loss

in non-burned plantation/agricultural land

reached 40%. However, fire was not a

single cause for this situation. Long and

severe drought was perceived as the main

cause of low productivity. This was

compounded by a disrupted

photosynthesis process due to smoke-

haze and a significant decrease in working

hours due to low visibility. Figure 6

presents the percentage of production loss

in each area.

Likewise, group discussions revealed other impacts on livelihoods, such as fishing decline,

25% decrease in edible bird’s nest production, and a high mortality of poultry.


Income Decreased,

Expenditure

Increased: No area

free from impact,

whether due to direct

burning, smoke-haze

generation, or by fire

causing other related problems.

Though hotspots were identified in red and

yellow areas where plantation and

agriculture lands dominate, the impact of

fire and smoke-haze on household income

was distributed almost evenly across all

areas.

FIGURE 7: PERCENTAGE OF HOUSEHOLDS REPORTED DECREASE IN INCOME

For example, 73.5% households in green areas – where no hotspots were identified –

reported that their incomes decreased. On average, more than 75% of those interviewed

agreed that the fire and smoke-haze incident affected their household incomes. Figure 7

indicates that there were more households in yellow areas reporting a decline in income than

those living in other areas. This situation was compounded by the fact that 100% of those

living under poverty line in yellow areas suffered from a decline in income, as shown in Table

6.

TABLE 7: INCOME DECREASED VS POVERTY LINE

Cluster Income

Decreased?

Household Wellbeing

Below Poverty Line

Above Poverty Line

Red Yes 67% 76%

No 33% 24%

Yellow Yes 100% 79%

No 0% 21%

Green Yes 74% 75%

No 26% 25%

The initial finding does not indicate that households living

above the poverty line have a better situation. Further

analysis found that households with an average monthly

income from 73 to 147 USD (IDR 1 to 2 million), both in red

and yellow areas, suffered from a decrease in income by

more than 75%. In other words, these households potentially

fell below the poverty line. With a high dependency ratio in

both areas, this decline was devastating. Through group

discussion, the research team learned that people did

anything to survive, including selling their furniture.

HOUSEHOLDS WITH

AVERAGE MONTHLY

INCOME OF IDR 1-2

MILLION SUFFERED

FROM A > 75%

DECREASE IN

INCOME


Though the average decrease in income was less than 50% in all areas, this situation should

not be ignored because it may take months to years for households to return back to

stability. Moreover, this study found that a higher percentage of decline in income was

suffered by households working in the agriculture/plantation sector.

FIGURE 8: INCREASE IN HEALTH EXPENDITURE While incomes decreased,

households were burdened by

increases in expenditures. This

occurred not only because of

the increase in market prices

due to a disruption of goods and

services distribution, but also

because households had to

spend more on health-related

expenses.

According to survey data,

households spent more on

health, food, and water during

the fire and smoke-haze

incident. Health expenditures

increased an

average of 206.59% across all areas or three times higher than that spent in a normal

situation. The increase in health expenditures up to more than 300% was experienced by

households living in yellow areas, those who suffered most from income decline.

3.2 Health Impact The health impacts of air pollution from forest fires have been examined in a number of

studies across the globe, both immediately and with a time lag to assess the temporal

dimension. Fire haze is made up of highly visible particulate matter, both dense (PM10) and

fine particulate matter (PM2.5), the latter of which is easily absorbed by the human body,

reaching deep in the lungs and into the circulatory system. The major gases produced during

the biomass burning process include carbon dioxide (CO2), carbon monoxide (CO), methane

(CH4), nitric oxide (NO), nitrogen dioxide (NO2), and ammonia (NH3). The direct health

effects of these toxins is likely to be low as their concentration is dispersed in the open air.

However, the longer-term health effects from low-level exposure to carcinogens from

bushfire smoke may be a cause for concern. The WHO estimates that the 3.1 million outdoor

air pollution-related deaths globally each year are due to ischemic heart disease and strokes

(80%), chronic obstructive pulmonary disease and acute lower respiratory infections (14%),

and lung cancer (6%). Of those, 340,000 are due to landscape fire smoke (LFS).

Further, PM10 from wildfires appear to have different effects on health than urban PM10. An 8-

year study investigating air pollution levels, including those from bushfires, and hospital

0% 50% 100% 150% 200% 250% 300% 350%

Red

Yellow

Green

Increase in Health Expenditure


admissions showed that a 10 µg/m3 increase in bushfire (but not urban) PM10 was

associated with a significant increase in all respiratory admissions.9

The Indonesian Agency for Meteorology, Climatology and Geophysics (Badan Meteorologi,

Klimatologi dan Geofisika or BMKG) has declared values over 350 PM to be hazardous. On

October 16, 2015, a 1,759 µg/m3 PM10 was recorded in Palangka Raya. This level increased

significantly up to 3,700 µg/m3 by late October 2015. The haze was so thick that it turned the

air yellow, and pollution levels reached 10 times the minimum level considered ‘dangerous’.

FIGURE 9: AIR POLLUTANT INDEX

Official statistics show that from July to November 2015, there were 67,582 cases of acute

respiratory infection recorded in Central Kalimantan. Of those, 21,296 cases were recorded

for the Katingan-Kahayan Landscape (Katingan, Pulang Pisau and Palangka Raya). Figure

10 shows that the number of cases increased significantly in week 42 of October 2015,

especially in Palangka Raya. During group discussions, people reported that children and

the elderly were more vulnerable to smoke-haze exposure. A case of death due to

respiratory infection was also reported in one discussion. Most people stated that they did

not like to use masks because of feelings of discomfort or irritation. Further, the household

survey data shows that the highest number of cases of respiratory infection was found to be

in green areas, with individuals taking an average of 17 days of sick leave.

9 Compiled from many sources.


FIGURE 10: NUMBER OF CASES OF RESPIRATORY INFECTION

Source: Provincial Health Office, data processed

Other than respiratory infection, this study also found an increase in the number of cases of

diarrhea under the same period from July to November 2015. Official statistics show that

22,206 cases of diarrhea were recorded in Central Kalimantan province. Of those cases,

4,377 cases were recorded specifically in the Katingan-Kahayan Landscape, comprising

1,843 cases in Katingan, 1,287 cases in Pulang Pisau, and 1,247 cases in Palangka Raya.

It was assumed that the smoke-haze caused a decrease in water quality. As with respiratory

infection, the survey data also reveals that cases of diarrhea were found to be higher in

green areas. The average number of days of sick leave taken due to diarrhea was 6. Figure

11 illustrates the data on cases of diarrhea per target district/municipality.

206 197 189 160

53

200 215 193

288212

251326

238 257

354288

432380375

521584

363

559502

593556 578

687 682

947 957

759

962

825771

1226

882

407

37 46 55 64 62 87 75 95147

196 221258 234 251

126185

310

451

221

0

200

400

600

800

1000

1200

1400

Mg26

Mg27

Mg28

Mg29

Mg30

Mg31

Mg32

Mg33

Mg34

Mg35

Mg36

Mg37

Mg38

Mg39

Mg40

Mg41

Mg42

Mg43

Mg44

Juli 2015 Agust 2015 Sep-15 Okt 2015 Nov-15

Number of Respiratory Infection Cases in Katingan, Palangka Raya & Pulang Pisau

July - 7 November 2015

Katingan Palangka Raya Pulang Pisau


FIGURE 11: NUMBER OF CASES OF DIARRHEA

Source: Provincial Health Office, data processed

Notably, exposure to forest fires has more serious implications on infants and children’s

health because they are still developing physiologically, with potential consequences into

their adulthood.

Further, people also reported cases of eye, throat, and skin irritation. The survey data shows

that the highest number of cases for these health disturbances was found in the red area.

Increased traffic accidents due to low visibility were also recorded. Unfortunately, the

research team could only gather data from the police station in Palangka Raya. From August

to October 2015, traffic accidents had resulted in 59 victims and 8 deaths. The police station

in Palangka Raya estimated the potential loss at 7,504.20 USD (IDR 102.35 million).

FIGURE 12: NUMBER OF TRAFFIC ACCIDENTS

0

2

4

6

8

10

12

14

16

18

20

Agu-15 Sep-15 Okt-15

Number of Traffic Accidents in Palangka Raya

27 32 3650

28

60 6077

10495

109

155

111100

169

150141

167172

51 47

29

7892 95

74

42

6577

6780

8795

76

53 47 45 47

17 18

147

3138 39 44

6675

93 94109 110 112

6154

80

60

39

Mg26

Mg27

Mg28

Mg29

Mg30

Mg31

Mg32

Mg33

Mg34

Mg35

Mg36

Mg37

Mg38

Mg39

Mg40

Mg41

Mg42

Mg43

Mg44

Juli 2015 Agust 2015 Sep-15 Okt 2015 Nov-15

Number of Cases of Diarrhea in Katingan, Palangka Raya & Pulang PisauJuli - 7 November 2015

Katingan Palangka Raya Pulang Pisau


3.3 Other Impact

Schools Activities

Schools activities in all survey areas

were significantly affected by the

smoke-haze generated from forest and

land fires. Schools were closed for

almost two months. When schools were

operational, study hours were extended

to enable students to recoup the lost

time. This situation was burdensome for

children not only because of exposure

to severe pollution, but also due to

physical exhaustion from especially

long study hours.

Impacts on Airline Industry

The airline industry was widely known as being significantly affected by the low visibility

produced by the smoke-haze in Central Kalimantan. The research team gathered data from

the Tjilik Riwut Airport Authority office in Palangka Raya. The data shows that from August to

October 2015, only 279 flights out of 1,698 had the status of on-time. The remaining number

of flights were cancelled, delayed, or not operated. This situation resulted in a 42% loss of

income for the airport authority. Figure 13 presents the status of flights operated from Tjilik

Riwut Airport from August to October 2015.

FIGURE 13: STATUS OF FLIGHT

295

463

664

279

0

100

200

300

400

500

600

700

Delay Cancel No Operation On-time

Status of Flights


3.4 Fire Cause and Mitigation Understanding the community’s attitudes and perspectives to forest and land fires in their

landscape is crucial to designing and implementing an effective and sustainable fire

management strategy. Such an understanding is a prerequisite to building a targeted

awareness raising campaign that mobilizes communities and secures their buy-in.

Hence the research team included three key questions on fire causes and mitigation efforts

in designing the quantitative survey. Firstly, survey respondents were asked to select all of

the major contributing factors to the recent forest and land fire crisis. 70% of survey

respondents correctly identified drought conditions, as brought on by the El Niño weather

phenomenon. Notably, only 35% selected land clearing by companies as a major cause.

This is illustrated in Figure 14 below.

FIGURE 14: FIRE CAUSE

Secondly, survey respondents were asked to list all of the major responsible parties for the

forest and land fire crisis. The results are depicted in Figure 15. The majority of respondents

listed the community (88%) and local government (74%) as key culprits. Less than half of

those surveyed (48%) identified private companies as responsible parties.

FIGURE 15: RESPONSIBLE PARTIES

35%

59%

70%

5%

51%

0% 10% 20% 30% 40% 50% 60% 70% 80%

Land clearing by company

Land clearing by community

Drought

Land conflict

Cigarette

53%

74%

88%

48%

26%

National government Local government Community Company NGO


Finally, survey respondents were asked to suggest the most effective fire mitigation

technique. The most common answer was socialization activities aimed at improving

knowledge and awareness amongst all key stakeholders.

FIGURE 16: MITIGATION EFFORTS SUGGESTED BY COMMUNITY

These survey results hold important implications for LESTARI’s IFM approach in the

Katingan-Kahayan Landscape. Communities are mostly aware that drought conditions

exacerbated the severity of fires, and that government bodies have failed to develop and

enforce effective policies. However, communities must also recognize that private sector

firms have engaged in unsustainable land conversion practices that contributed significantly

to the fire and haze crisis. Hence LESTARI can help to facilitate communities’ understanding

of a “shared burden” approach to IFM, as each stakeholder (community, government, private

sector) has a role and responsibility in managing and mitigating fire. As surveyed

communities suggested socialization as the top mitigation effort, this reflects their openness

to dialogue and a key entry point for LESTARI’s IFM work. By empowering communities with

knowledge, LESTARI can help to build consensus and improve communities’ engagement

with other stakeholders to support effective fire management and prevention practices.

45%

5%

23%

11%14%

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

Socialization Provision of fireequipment

Monitoring & lawenforcement

Landmaintenance

Built drainage


4. CONCLUSION The results of this Forest and Land Fires Impact Study indicate that the impact of the 2015

Indonesian fire and haze crisis was devastating to the economic livelihood, health, wellbeing,

and education of households in LESTARI’s Katingan-Kahayan Landscape in Central

Kalimantan. Moreover, the results support the research team’s hypothesis that households

suffered much worse from the forest and land fires incident than the level portrayed in

published information.

The major underlying causes of these damaging fires are no secret. The unsustainable

clearing and burning of forests by both smallholders and large palm oil concessions, draining

of peatlands, and inadequate government capabilities regarding fire response and

prevention are all, to varying extents, responsible. This underscores the need for a broad-

scale response that convenes all stakeholders and recognizes the complexity and multi-

faceted nature of fire.

To meet such a challenge and mitigate future impacts to communities’ well being, an IFM

approach is crucial. LESTARI’s IFM consists of four pillars: Prevention, Preparedness,

Response, and Recovery. Prevention is the most important pillar, as it involves building a

broad basis of support amongst the community through awareness raising, education and

training, and stakeholder engagement. Survey respondents from this study most commonly

suggested socialization activities as a means for fire mitigation. This indicates a key entry

point for LESTARI to convene stakeholders, share evidence-based knowledge, and foster

cooperation in a manner that appreciates a “shared burden” approach to IFM. LESTARI’s

Multi-Stakeholder Forums (MSFs), at the provincial and district levels, present an ideal

platform for such transparent dialogue on the fire issue in order to gain stakeholders’

commitments towards sustainable land use.

Overall, this study will be utilized as an engagement tool to present evidence of forest and

land fire impacts in the Katingan-Kahayan Landscape and enable the LESTARI project to

communicate to key stakeholders in a convincing and constructive manner. It is expected to

contribute to LESTARI’s policy influence and advocacy work as a means of improving

community livelihoods and realizing sustainable, transformative change.

LESTARI

Wisma GKBI, 12th Floor, #1210

Jl. Jend. Sudirman No. 28, Jakarta 10210, Indonesia.

Phone: +62-21 574 0565 Fax: +62-21 574 0566

Email: [email protected]

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