An assessment of the socio-economic and ecological impacts ...
ASSESSMENT OF SOCIO-ECOLOGICAL IMPACTS OF CLIMATE …
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ASSESSMENT OF SOCIO-ECOLOGICAL IMPACTS OF CLIMATE CHANGE AND NATURAL DISASTERS ON THE LIVELIHOOD OF BALAKOT MOUNTAINOUS COMMUNITY A THESIS SUBMITTED TO LAHORE COLLEGE FOR WOMEN UNIVERSITY IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY IN ENVIRONMENTAL SCIENCE BY LAILA SHAHZAD DEPARTMENT OF ENVIRONMENTAL SCIENCE LAHORE COLLEGE FOR WOMEN UNIVERSITY, LAHORE 2018
Transcript of ASSESSMENT OF SOCIO-ECOLOGICAL IMPACTS OF CLIMATE …
ASSESSMENT OF SOCIO-ECOLOGICAL IMPACTS OF
CLIMATE CHANGE AND NATURAL DISASTERS ON
THE LIVELIHOOD OF BALAKOT MOUNTAINOUS
COMMUNITY
A THESIS SUBMITTED TO LAHORE COLLEGE FOR WOMEN
UNIVERSITY IN PARTIAL FULFILLMENT OF THE REQUIREMENTS
FOR THE DEGREE OF DOCTOR OF PHILOSOPHY IN ENVIRONMENTAL
SCIENCE
BY
LAILA SHAHZAD
DEPARTMENT OF ENVIRONMENTAL SCIENCE
LAHORE COLLEGE FOR WOMEN UNIVERSITY, LAHORE
2018
CERTIFICATE
This is to certify that the research work described in this thesis submitted by
Ms. Laila Shahzad to Department of Environmental Science, Lahore College for
Women University has been carried out under my direct supervision. I have
personally gone through the raw data and certify the correctness and authenticity of
all results reported herein. I further certify that thesis data have not been used in part
or full, in a manuscript already submitted or in the process of submission in partial
fulfillment of the award of any other degree from any other institution or home or
abroad. I also certify that the enclosed manuscript has been prepared under my
supervision and I endorse its evaluation for the award of BS/MS/PhD degree through
the official procedure of University.
________________
Prof. Dr. Arifa Tahir
Supervisor
Lahore College for Women University,
Lahore
Date:
_________________
Dr. Faiza Sharif
Co-Supervisor
Government College University, Lahore
Date:
Verified By
________________
Prof. Dr. Tahira Mughal
Chairperson
Department of Environmental Science
Stamp
_________________
Controller of Examination
Stamp
Date: ___________
AUTHOR’S DECLARATION
I Laila Shahzad hereby state that My PhD Thesis titled
Assessment of socio-ecological impacts of climate change and natural disasters
on the livelihood of Balakot mountainous community
is my own work and has not been submitted previously by me for taking any degree
from Lahore College for Women University, Lahore
or anywhere else in the country world.
At any time if my statement is found to be incorrect even after my Graduate the
university has the right to withdraw my PhD degree.
Laila Shahzad
October 1, 2018
PLAGIARISM UNDERTAKING
I solemnly declare that research work presented in the thesis titled
“Assessment of socio-ecological impacts of climate change and natural disasters
on the livelihood of Balakot mountainous community”
is solely my research work with no significant contribution from any other person.
Small contribution/help wherever taken has been duly acknowledged and that
complete thesis has been written by me.
I understand the zero tolerance policy of the HEC and Lahore College for Women
University, Lahore towards plagiarism. Therefore, I as an Author of the above titles
thesis declare that no portion of my thesis has been plagiarized and any material used
as references is properly referred/cited.
I undertake that if I am found guilty of any formal plagiarism in the above titled thesis
even after award of PhD Degree, the University reserves the rights to
withdraw/revoke my PhD degree and that HEC and the university has the right to
publish my name on the HEC/University website on which names of students are
placed who submitted plagiarized thesis.
Laila Shahzad
October 1, 2018
DEDICATION
My work is dedicated to my darling Mother Mrs. Shams Shahzad
and to my Beloved Husband, Mr. Hammad Ahmed Malik;
Without their love, support and prayers
I couldn’t be able to reach here.
Acknowledgments
All praises be to Allah almighty, the Most Gracious and the Most Merciful, for all the
blessings that He has given me, especially in guiding me to knowledge and wisdom.
And all respects are for His Last Prophet Hazrat Mohammad (Peace Be Upon Him),
Who is the utmost educator for the mankind.
I deem it great privilege in offering my thanks to Vice Chancellor, Lahore College for
Women University, Lahore for providing me all financial support to carry out this
study. I offer my profound thanks to Chairperson, Department of Environmental
Science Prof. Dr. Tahira Mughal for facilitating my work.
It is honor for me to write few words of heartfelt thanks to my respected Supervisor,
Prof. Dr. Arifa Tahir, Professor at Lahore College for Women University, Lahore for
her support and guidance at each step throughout the course of time. I am also
thankful to my Co-supervisor; Dr. Faiza Sharif, Associate Professor at Sustainable
Development Study Center, GC University, Lahore for her help in designing the
ecosystem based assessment of my study.
With words of appreciations, I am indebted to Prof. Dr. Hamid Mukhtar Director IIB,
GC University, Lahore for his never-ending support at every stage of completion of
this work. My thanks is also due to Mr. Murtaza Ali Shah, Senior Engineer NESPAK
Pakistan and Syed Salaar Dogar, NARC, Islamabad for helping me in getting
meteorological and land use data. I am thankful to Ms. Asma Mansoor for her help in
finalizing my draft. I am also thankful to all my colleagues at SDSC for their moral
support specially Mr. Muhammad Umar Hayyat and Dr. Waqas Ud Din.
I am also grateful to the People from Tehsil Balakot (community and officials from
government departments) who participated in this study and responded to my endless
questions.
I owe my deepest gratitude to my parents Mr. Ilyas Ahmed Malik, Mr. Shahzad Gull,
Mrs. Shams Shahzad for their prayers and absolute support throughout this tough
time. My Thanks is due to Mrs. Anam Fouad for always taking care of my children in
my absence. This journey can never end, without thanking my Late Mother in law
who encouraged me to start it. I love you (Naveeda Aunti) for supporting me even
from far throughout this time.
Last but Least, my life support system, My Husband, Mr. Hammad Ahmed Malik for
his unconditional love, support and prayers to go through all thick and thin during
this long journey and supporting my field studies & tiring excel work also. “I hope
you know; this accomplishment was never possible without YOU by my side”. I thank
my sons for bearing my always short time for family.
LAILA SHAHZAD
CONTENTS
Title
Page No.
List of Table i
List of Figures iii
List of Abbreviations v
Abstract viii
Chapter 1 : Introduction 1
1.1 Background 1
1.2 Overview of vulnerability due to changing climate and the
livelihood 4
1.3 Pakistan‟s vulnerability to climate change and natural disasters 6
1.4 Context of climate based vulnerability and livelihood of Balakot
Mountainous Community 8
1.5 Rational 13
1.6 Research questions 13
1.7 Objectives of the Study 14
Chapter 2: Review of Literature 15
2.1 A connection of Socio-ecological system 15
2.2 Mountainous community and Livelihood in face of climatic
changes 20
2.3 Vulnerability to Climate change and Natural disasters 23
2.4 Measure of Vulnerability and Adaptive Capacity
2.4.1 Component of vulnerability
2.4.2 Dimensions of vulnerability
26
2.5 Assessment of Vulnerability 30
2.5.1 Vulnerability capacity assessment
2.5.2 Livelihood vulnerability assessment
2.6. Adaptation 33
2.7 Climate change mapping and assessment 40
2.8 Estimation and Mapping of Forest Ecosystem Services 44
2.9 Research gaps identified from the survey of literature 55
Chapter 3: Materials and Methods 57
3.1 Community ranking based on wellbeing status 62
3.2 Vulnerability Capacity Assessment of Indigenous Community 64
3.3 Livelihood vulnerability quantification
3.3.1. LVI Approach I
3.3.2 LVI Approach II
67
3.4 Climate Data and it analysis for change detection 73
3.5 Ecosystem services assessment in context of climate based
vulnerability
3.5.1 Climate regulation by carbon sequestration
3.5.2 Vulnerability assessment of forest to the climate change
74
3.6 Land use mapping 79
3.7 Data Analysis 80
Chapter 4: Results 81
4.1. Livelihood trend and wellbeing status of the study population 82
4.2. Changing climate and Livelihood impacts
4.2.1. Livelihood mapping
4.2.2 Livelihood resources and Major hazards
4.2.3. Institutions
4.2.4. Coping strategies in mitigating climate change
4.2.5.Perceptions of the local community on climate change
86
4.3. Livelihood vulnerability analysis
4.3.1. Computing Livelihood Vulnerability Index (LVI)
4.3.2 Calculating LVI-IPCC
99
4.4. Balakot‟s trend of temperature and precipitation 110
4.5. Forest service‟s assessment and vulnerability analysis
4.5.1 Community‟s perception on Balakot forest services
4.5.2 Change in Delivery of Forest Services to local Community
114
4.6. Land use and climate change mapping and livelihood impacts 126
Chapter 5: Discussion 133
References 145
Annexures x
Plagiarism Report xxxi
Publication list xxxii
i
List of Tables
Table No. Title Page No.
1 Study Framework and methods used 58
2 Sampling Design for Study Population 60
3 Criteria indicator for well-being characterization of
community
63
4 Major Components and Sub-Components of LVI 68
5 Ecosystem Services Measured and Valued in Study
Area
75
6 Land Use Classification in Tehsil Balakot 80
7 Wellbeing characteristics of study population
indicating different social groups
84
8 Seasonal and Livelihood Monitoring Calendar of
Local Community
88
9 Coping strategies of locals in changing climate and
their vulnerability status according to their well-being
94
10 Observations of locals on climate change in the
region
97
11 Summary of LVI scores for UC Kawai and UC
Balakot
101
12 Results of LVI-IPCC for UC Balakot and UC Kawai 107
13 LVI and LVI-IPCC based on contributing factors and
vulnerability scores for Tehsil Balakot
108
14 Rainfall Pattern in winter and summer periods over
30 years‟ time span (millimeter)
113
15 List of goods and services of the surrounding forest
identified by community
116
ii
16 Tree density and status of degradation at five
different sites in Tehsil Balakot
121
17 Average biomass and Soil Carbon at five
different sites in Tehsil Balakot
122
18 Species-Wise Carbon Stock Assessment (t/ha)
in Balakot tehsil
124
19 Percent response and change in stated time period in
land use data
128
iii
List of Figures
Figure No. Title Page No.
1 Climate based vulnerability of forest ecosystems in a
socio-ecological system.
3
2 Map of Study Area 12
3 Millennium Ecosystem Assessment and its linkages
with human well-being
18
4 Triad of Vulnerability Analysis 29
5 Execution of research methodology 61
6 Map of study area Tehsil Balakot indicating two
Union Councils for LVI analysis
67
7 LVI-IPCC framework based on the definition of
vulnerability
73
8 Mapping of hazard severity ranking of Balakot &
Venn diagram of institutions
92
9 Spider diagram indicating major component scores of
Livelihood Vulnerabity Index (LVI)
105
10 Vulnerability triangle showing levels of exposure,
sensitivity and adaptive capacity (LVI-IPCC)
109
11 Graphical representation of Mean Annual Minimum
Temperature for a period of 30 years
111
12 Graphical representation of Mean Annual Maximum
Temperature for a period of 30
111
13 Graphical representation of Mean Annual Rainfall for
a period of 30 years in Tehsil Balakot
113
14 Representing Average Month-wise Precipitation in
Tehsil Balakot
114
iv
15 Provisionary forest services to Balakot community 117
16 Regulatory forest services valued by locals 117
17 Identified Cultural forest services to local people 117
18 People‟s perception of change in surrounding
forest services
119
19 Land use changes reported in Tehsil Balakot
for the year 1990
129
20 Land use changes in Tehsil Balakot for the
year 1995
130
21 Land use changes in Tehsil Balakot for the
year 2010
131
22 Land use changes in Tehsil Balakot for the
year 2015
132
23 Theoretical Framework of Tehsil Balakot
indicating nexus of ecosystem services,
climate change impacts and livelihood
140
v
List of Abbreviations
Abbreviations Explanation
AC Adaptive Capacity
AGB Aboveground Biomass
AGTB Aboveground Total Biomass
ARIES Artificial Intelligence For Ecosystem Services
ASL Above Sea Level
BBF Balakot-Bagh Fault
BGB Below Ground Biomass
BTTP Billion Tree Tsunami Project
CFUGs Community Forest Users Groups
CEDRA Climate Change and Environmental Degradation Risk and
Adaptation Assessment
CCVCA Community-Based Climate Vulnerability And Capacity
Assessment
CRA Community Risk Assessment
CVCA Climate Vulnerability Capacity Assessment
DFID Department For International Development
ETM Enhanced Thematic Mapper
FAO Food and Agriculture Organization
FGDs Focus Group Discussions
GCMS Global Circulation Models
GDP Gross Domestic Product
HKH Hindu Kush Himalayan
IAMS Integrated Assessment Models
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ICIMOD International Centre For Integrated Mountain Development
IFRC International Federation of Red Cross and Red Crescent
InVEST Integrated Valuation of Environmental Services and
Tradeoffs
IPCC Intergovernmental Panel on Climate Change
KPK Khyber Pukhtoonkhawa
LVI Livelihood Vulnerability Index
MEA Millennium Ecosystem Assessment
NDVI Normalized Difference Vegetation Index
NGO Non-Governmental Organizations
NTFP Non Timber Forest Products
PPPA Pakistan Participatory Poverty Assessment
PRA Participatory Rapid Appraisal
PCA Principal Component Analysis
SES Socio-Ecological Systems
SLA Sustainable Livelihoods Approach
SOC Soil Organic Carbon
SolVES Social Values For Ecosystem Services
SOVI Social Vulnerability Index
SPSS Statistical Package For The Social Sciences
TAR Third Assessment Report
TESSA Toolkit For Ecosystem Services Site-Based Assessment
TEV Total Economic Valuation
TM Thematic Mapper
UC Union Council
UNDP United Nations Development Program
vii
UNEP United Nations Environmental Programme
UNFCCC United Nations Framework Convention On Climate Change
UNISDR United Nations International Strategy For Disaster
Reduction
USGS United State Geological Survey
VCA Vulnerability Capacity Assessment
VRF Vulnerability To Resilience Framework
WRI World Resource Institute
WWF World Wide Fund For Nature
viii
Abstract
Climate change poses profound risks to the livelihoods of vulnerable rural
mountainous communities due to their higher dependence on natural resources which
causing higher degradation. The current study had assessed the vulnerability due to
climate change and livelihood practices of the Tehsil Balakot of Khyber Phuktoon
Khawa (KPK), Pakistan and how these practices help to elate their adaptive capacity.
Moreover, vulnerability of mountain forest in provision of forest services and land use
changes were also determined. Based on mixed method approach including ten focus
group discussions, survey of two hundred households and in-depth interviews with the
locals; different hazards and their associated livelihood effects were explored.
Wellbeing status of the community and resulting adaptation strategies were also
analyzed. Temperature and rainfall data of last 30 years (1988 to 2017) was collected
from the Pakistan Meteorological Department to validate people‟s perception of
climate. Later the mapping of three integral ecosystem services as provisionary,
regulatory, and cultural (recreation) through the local community‟s perception had
been done. Carbon stock assessment as a climate regulatory service of the forest was
carried out from the trees and the soil of Tehsil Balakot whereas livelihood
vulnerability was evaluated through a composite indicator as Livelihood Vulnerability
Index (LVI) and Livelihood Vulnerability Index of Intergovernmental Panel on
Climate Change. Lastly land use change was analyzed using geographical information
system (GIS). It was clearly depicted that the changing climate has significantly
influenced the livelihoods of the local community through resource degradation,
insufficient basic services, low agricultural productivity and social inequity. The poor
people were facing additional burden due to their low adaptive capacity towards
climate change. Furthermore, the analysis has shown that these forests provide myriad
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of services to their surrounding communities in form of the timber, fuelwood, climate
regulation and recreation. The total carbon stock assessment for the Tehsil Balakot
was determined as 243.79 t/ha. The average tree biomass as 207.41 t/ha and soil
carbon was found as 36.38 t/ha. In the climatic trends, there was an overall decrease
in mean minimum annual temperature by a factor of 0.0024 for each year whereas
there had been an overall increase in mean maximum annual temperature by a factor
of 0.0412 for each year. The mean annual rainfall of thirty years was 1471.27 mm.
The comparative analysis within Tehsil Balakot showed that Union Council Balakot
was more vulnerable with a LVI score of 0.41 than Kawai with an aggregate score of
0.35. The results of in-depth analysis of differential vulnerability showed that
households in Balakot had the low adaptive capacity and higher exposure to natural
disasters. The study has concluded that these forests are playing a vital role for the
livelihood of the surrounding community as well contributes in climate change
impacts mitigation. After working with communities, it is suggested that government
policy should focus on those emergent issues which were identified relevant by
communities and are most critical for their livelihoods. Developmental and
community planners should also use such studies to assess the root causes of
vulnerability to specify indigenous needs in policy making.
1
INTRODUCTION
1.1 Background
From the last two decades, the risk of natural disasters has increased with their higher
frequency and magnitude. In less developed countries; this risk is more even where
the human population is higher in number with more dependence on their ecological
resources. The changing environment has further worsened the situation (Malik et al.,
2012; Huong et al., 2018). Human society is facing increased vulnerability related to
demographic, environmental degradation, poor socio-economic conditions,
development in high-risk zones and higher competition for scarce resources
(UNISDR, 2005; Aryal et al., 2017). Ecological and social vulnerability of humans to
such disturbances and disasters are influenced by poor resilience. This condition
points to the situation where disasters could increasingly threaten the population,
economy and sustainable development in developing countries (IPCC, 2014).
The world is facing greater threats from the increased frequency and intensity of
natural disasters, food insecurity, biodiversity‟s loss, water scarcity and
desertification, degradation of ecosystems, and growth of populations and cities
(FAO, 2011). Many of these pressures on natural resources are due to the changing
climate and global warming. These multitude challenges force the study of complex
ecosystem processes that lead to improvements in or deterioration of its natural
resources (Liu et al., 2016). For this purpose, it is necessary to set the common
framework for better understanding of complex socio-ecological systems (SESs). The
concept of socio-ecological system is widely used as we are living in an era where
humans have a determining role in global change. Humans and their societies are
central part of ecological systems and ecosystems which many want to protect are
entrenched in various social levels (Gardner and Dekens, 2007; Ferrara et al., 2016).
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A socio-ecological system is set of components which are interconnected and worked
when linked. All ecological systems are characterized by space and time; at same
instant the social system is also defined by time and space. With these two
components, there is a third component in social systems which is known as structure
of significance, the ability of human to produce a view of right or wrong about
something (Pereira et al., 2005; Flint and Luloff, 2005). The products of these
interactions within an ecosystem are called as ecosystem services, which are benefits
to local and global communities in form of provisioning services (fiber, water, food);
regulating services (carbon sequestration; flood, erosion and disease control); cultural
services (sense of peace, tourism and recreational benefits); and supporting services
(soil fertility, nutrient cycling) to sustain life on Earth (MEA, 2005). Effective and
standardized evaluation of social-ecological systems is crucial for reinforcing
increased resilience of human communities and for developing adaptation policies
(Altaweel et al., 2015). An assessment of large, regional and global expanded
ecosystems, the provision of their services, and relation to human well-being needs an
integrated approach (Jellinek et al., 2014).
Therefore, studying human-environment interaction considering their socio-ecological
systems become so important research theme in changing climate conditions. It needs
to investigate how humans are living and adapting to the environmental change, how
their social needs are affecting their ecological systems upon which they are
dependent for their livelihoods. What are the vulnerabilities of local communities and
to what are they resilient. It is vital to measure their adaptation capacities and
strategies in response to climate change (Fisher, 2010).
A framework developed for the study is shown as Figure-1.
3
Figure-1 Climate based vulnerability of forest ecosystems in a socio-ecological system
4
1.2 Overview of vulnerability due to changing climate and the livelihood
Intergovernmental panel on climate change (IPCC) in its fifth assessment report
mentioned that the changing climate is one of the biggest challenges of the 21st
century that will bring about unexpected extreme events to the whole world. In
particular, South Asia is the home of one fifth of the world‟s population and is
considered as the most disaster prone region of the world. With ever increasing
population coupled with poverty, natural resource dependence and degradation; this
region is highly vulnerable to climate change and resulting natural disasters (IPCC,
2014). Pakistan faces a natural disaster almost every year is now well-thought-out as
one of the most vulnerable and highly effected country by changing climate in South
Asia (Rahman and Khan, 2013; Sarwar et al., 2016). Climate change is defined as the
weather pattern which departs from a decadal time span (IPCC, 2007) and it is even
more evident in mountainous regions due to their marginalization, higher dependence
on natural resources and extreme poverty (Macchi, 2011). People of mountains are
highly vulnerable because of higher exposure to the climatic variability and extreme
events (Gentle and Maraseni, 2012). Whereas, the local people of mountains are
“vulnerable” and they need to adapt to climatic changes for their survival and better
livelihood opportunities (UNDP, 2011). Vulnerability to the changing climate is the
amount at which a system faces adverse effects of climate and its related phenomenon
and becomes unable to cope with it (IPCC, 2007). Vulnerability of a system is the
function of exposed people, places or assets, which are sensitive to the variability and
unable to cope with it (Smit and Wandel, 2006).
The use of term “vulnerability” is from many different disciplines in many different
ways ranging from public health, food security, climate change, natural hazards,
livelihood safety and disaster risk management (Soares et al., 2012). IPCC in its
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literature mostly cited vulnerability as a term which corresponds more to exposure
and sensitivity of a system (IPCC, 2001a, b; 2007a, b). Assessing vulnerability to
climate change at community level involves a participatory rural appraisal tool which
enables local people to share, to plan and to assess their daily life knowledge and
conditions (Mascarenhas, 1992). However, the concept of livelihood is developed by
Chambers (1994a) according to which “livelihood can be described as the means of
gaining a living, and encompassed livelihood capabilities, and tangible and intangible
assets”. To achieve livelihood goals, people make different activities which are called
livelihood strategies (He et al., 2013). Adaptive capacity (AC) is known by both
policy and academia, important for the livelihood of the vulnerable societies to
prepare themselves for the adverse impacts of anthropogenic climate change
(Williams et al., 2015). IPCC has defined AC as an „„adjustment in natural or human
systems in response to actual or expected climatic stimuli or their effects” (IPCC,
2007). The adaptations can contribute to curtail transitions in human beings and their
systems to somehow more warmer or cold conditions (Nykvist, 2014).
The idea of adaptation firstly devised in the field of ecology and evolutionary biology
(Winterhalder, 1980). The term “adaptation” is acknowledged after evolvement of
global climate change and natural disasters. It is highlighted in many studies that it is
necessary to adjusting the dynamic environment to progress the adaptive capacity of
individuals and systems (Smit et al., 2014). Adaptation comprises two main concepts:
vulnerability and resilience (McManus et al., 2012) which are particularly prevalent
in mountain settings (Yuen et al., 2013). Exposure and sensitivity is inversely
proportional to adaptive capacity (Yohe and Tol, 2002). An AC of individuals,
organizations, and communities is integral part of the resilience of human systems
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which is the ability of people and institutional systems to cope with upcoming and
rapidly changing environment (Smit and Wandel, 2006).
1.3 Pakistan’s vulnerability to climate change and natural disasters
Hazards do exist naturally in an area but exposure of ill prepared and vulnerable
communities‟ results in the form of massive lose from natural disasters like floods,
earthquake, droughts, etc. Pakistan is one of the most disaster-prone countries in the
world which faces multi-hazards (Shah et al., 2018). It has a history of the worst
natural disaster and their impacts on the economy (Shafique and Khan, 2015).
According to the risk management index calculated on the global level, Pakistan ranks
in the category 4 (2.0-2.4) which indicates poor disaster risk management and poor
adaptive capacity with a high likelihood of having current and future disasters (Kreft
et al., 2017). There are a number of factors behind the vulnerabilities of Pakistan‟s
community to natural disasters. These include the fragile natural environment, lack of
awareness and education, poverty, poor construction practices and agricultural
management and weak early warning systems. Poor communication infrastructure and
lack of critical facilities aggravate vulnerabilities of communities (Sarwar et al., 2016;
Shah et al., 2017). In the coming decades; frequency, severity and impact of certain
hazards may increase which might lead to greater social, economic and environmental
losses (Shepherd et al., 2013). It is supported by most of the literature that the risk of
natural disasters and climatic change are closely associated; more extreme weather
events in the future are probable to increase the frequency and scale of disasters in
fragile ecosystems (IPCC, 2014).
Asia occupies 14% of the World‟s forest with 432 million ha of natural forest and 116
million hectare of planted forest (MacDicken et al., 2015). Pakistan is having only
3.1% of total forest land. Pakistan‟ forest area comprises of 40% of conifers on
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mountains in the northern part of the country with scrub forest on the hills and in
temperate zones. Conifer forests are placed in Khyber Pakhtun Khawa (KPK), Azad
Jammu and Kashmir (AJK), Balochistan and northern Punjab region (Acharya et al.,
2011). Khyber Pakhtunkhwa is covered with 70% of forest, a majority found in the
Malakand and Hazara divisions (Khan and Khan, 2009). The forest covers 1.3 million
hectares consist of Pinus gerardiana (chilghoza), Abies spp. (Fir), Cedrus deodara
(Deodar), Pinus roxburghii (Chir Pine) and other trees are present on the highest,
medium heights, and the lower areas (Shaheen et al., 2016). These species play a
vital role in maintaining soil on mountain slopes, provision of fuel wood and non-
wood products, medicinal plants, livestock and as well as other forest services,
including wildlife habitat is well recognized (Shaheen et al., 2017). The Himalayan
forest landscapes extend from tropical dry deciduous forests species; Oak (Quercus
leucotrichophora) and pine (Pinus roxburghii) in the foothills to timberline
(Steinbauer and Zeidler, 2008).
A fast decline is reported in the overall forest land of Pakistan from 3.3% in 1990 to
1.9% in 2015 (FAO, 2016). The second highest source of GHGs emission globally is
because of deforestation which released almost 2 gigatons of carbon yearly
(Kindermann et al., 2006; Eggleston et al., 2006). Mountain forest like other biomes
play a significant role in absorbing atmospheric carbon dioxide into trees and soils
which is carbon sequestration (UNFCCC, 2013). Therefore this is by far the most
accepted, cost effective and long term course of reducing global warming and climatic
changes (Ciurean et al., 2013). The world‟s forest occupy almost 3869 million hectare
of land which have almost 421 x 106
tons of total aboveground biomass (Rametsteiner
and Whiteman, 2014; Bain et al., 2015). This indicates that the pool of carbon tends
to accumulate till the equilibrium state of forest growth. In converse deforestation will
8
result in losing carbon sinks (Whiteman, 2013). It is said that in 21st century, climate
driven change will be dominant in terrestrial ecosystems affecting specially forest
biodiversity, and altering species structure and function (FAO, 2016; Thorne et al.,
2017). Himalayan forests are facing rapid degradation due to economic development
as well as higher population pressure (Upadhyay et al., 2005; Lindner et al., 2014).
These local forests are contributing in global climate change mitigation and if the
pace of degradation and deforestation will continue; this will be a greater loss for
local communities‟ as well national calamity. These provides livelihood to local
people with no other life opportunity (Shedayi et al., 2016). It is reported that sub-
tropical Himalayas of Kashmir accounts for 186.24 t/ha of total carbon (Shaheen et
al., 2016); similarly in another local study of District Neelum Azad Jammo Kashmir-
Pak, it is reported that 57% of the local community was using herbal medicines for
their ailments (Shaheen et al., 2017). This shows higher dependence of local people
on natural resources of their areas, which makes them more vulnerable to the
changing climatic conditions. The mountain forest and their associated communities
are more vulnerable to climatic changes as having higher exposure and sensitivity to
the perturbations and stressors (Chaudhary and Bawa 2011; Gobiet et al., 2014). The
social elements coupled with ecosystem functions need to maintain or adapt to change
for subsistence livelihood (IPCC, 2014).
1.4 Context of climate based vulnerability and the livelihood of the Balakot
Mountainous Community
The current study was conducted in Balakot (34° 32' 22.7940'' N and 73° 21' 0.8460''
E.), the biggest Tehsil of District Mansehra, Khyber Pakhtonkhwa (KPK) Province of
Pakistan. The area is surrounded by Balakot sub-forest division which is connectivity
of the Main Kaghan Forest Division, KPK Pakistan and has an estimated area of
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20,879 acres (8.449.1 hectares). The main land use types identified are the forested
area, cultivated land, settlements, water bodies and a part is the barren land (UNDP,
2007). The area is highly disaster prone as it lies in the most active seismic zone of
Pakistan which extends stepwise from Balakot-Bagh Fault (BBF) in the Himalayan
(Pathier et al., 2006; Baig, 2006; Mona, 2014). The worst affected earthquake of
Pakistan in 2005 occurred in Balakot due to this fault line and resulted in loss of
almost 80% of the houses. (Munir and Mirza, 2007; Sarwar et al., 2016). Balakot is
known for its real multi-hazard scenario of floods, earthquake and landslides; many
studies have shown higher susceptibility to earthquakes and landslides with steep
topography resulting in also the flood hazard (Halvorson and Hamilton 2007;
Basharat et al., 2016). Balakot lies in the Lower Himalayan with an elevation of about
500-5000 above sea level (asl) and river kunhar flowing through the whole town with
an intensity of 75 m3/s. The average precipitation remains between 1300 to 1600 mm
per year with a minimum of -3 0C temperature recorded in winter and highest of 41
0C
in summer. The summer and winter temperatures of last 40 years have shown great
variations (Soomro et al., 2012).
Pakistan‟s part of Himalayan is facing an increase in summer and winter‟s
temperature which has affected the water volumes as well crop production at local
level (IPCC 2007). The change in the rate of precipitation has severely affected the
livelihood of locals who depend mostly on natural resources for their livelihood.
Climate change has emerged as a challenge and threat to carry on traditional practices
of daily life. Himalayan livelihood is marginalized and vulnerable to the changing
climatic conditions (Macchi, 2011; Aryal et al., 2014a).
The current study is unique in its nature, observing socio-ecological system of the
forest dependent community in a highly disaster prone area and linking it with climate
10
variability. The local community is mostly rural and has low education level. The
livelihood activities of people varied due to ecological factors; close proximity to
mountain forest and topography. The major occupation of the residents is wage labor
followed by agriculture and seasonal migration to main District Mansehra and Naran
Valley (UNDP, 2007). Tourism is another preferred occupation but limited to summer
season. Majority of rural women are involved in livestock rearing and crop
production. This area has two cropping seasons, Kharif (dominating rice, maize and
other seasonal vegetables); other is Rabi (wheat production mainly with seasonal
vegetables). Very few households are producing yield which can be sold in the market
where rest of the mountainous community members have a small area of enough
production to meet their own demands only. After agriculture, local forest has
become a major source of income in supporting livelihoods (Soomro et al., 2010).
The vegetation of the dry sub-tropical Himalayan forest is dominated by Pinus
roxburgii sarg. (Named after William Roxhburgii) commonly called “chir pine”. The
tree is popular among the local community for its fuelwood value, medicinal as well
timber value (Ullah et al., 2017). However, the forest cover has changed over time
due to use of fuelwood, the region is of extremely cold winter nights and have no fuel
available other than forest woods. In the region, soil infertility, wind erosion and no
irrigation infrastructure are the few known reasons for the decrease in production of
crops (Qasim et al., 2010; Soomro et al., 2012). The mountain forest is therefore
providing many valuable services to the local community in the form of water, fuel
wood, timber, and medicinal plants. In addition to this, these forests are indirectly
acting as barriers to natural hazards, controlling soil erosion, helping in carbon storing
and soil nutrient formation. Many of the locals are involved in nature based tourism
which is also a significant service provided by the mountainous forest (Soomro et al.,
11
2010; Basharat et al. 2016). In the view of climate change, these ecosystem services
are exposed and expected to diminish. As a result, local people are highly vulnerable
due to their marginalized and natural resource-dependent livelihood. The map of
study area is shown in Figure-2.
12
Figure-2 Map of study area showing a) Pakistan b) KPK Province c) Tehsil Balakot d) Settlements in Tehsil Balakot are represented as
dots while union councils are mentioned in Blocks (yellow)
13
1.5 Rational
There are very few studies conducted in Pakistan which underpin the connections of
society and ecosystems in marginalized mountainous regions. These remote mountains
are covered with forest which is providing livelihood to the local community. Many
households are involved in agriculture on these slopes; which further increased their
vulnerability to climate change and natural disasters. The conceptual note underpins the
study is very interdisciplinary dealing with people their livelihood, ecosystems and
climate change. The current study has explained the links of an ecological system to a
social system. It assessed how the socio-economic and environmental changes affect the
livelihood, vulnerability and adaptive capacity of various social groups. There is not a
single study conducted in Himalayas of Pakistan analyzing a vulnerable and affected
people to highlight climate change and its effects on livelihood. This condition has
provided my study a rationale to know how the livelihoods of the poor vulnerable people
of Balakot are influenced by changing climate and what the coping strategies are and how
they visualize their future as communities depend upon ecological resources for their
livelihood.
1.6 Research questions
There were many questions associated to livelihood, forest ecosystem services, climate
and land-use change in a socio-ecological system of Tehsil Balakot; summing up these as
follows:
What are the spatial dynamics of ecological resources in the socio-ecological system
of Balakot?
14
What are the impacts of climate change on rural mountainous communities?
What are the differential vulnerabilities and adaptation practices of local community
in changing climate?
What are the ecosystem services provided by the mountain forest and its extent of
contribution to the livelihoods of local community?
What is the current land use pattern and change in land use over a period of time and
how this is affecting the livelihood in changing climate?
1.7 Objectives of the Study
To answer the above stated questions following objectives were designed:
Study the nexus of socio-ecological systems to understand how community‟s
livelihood depends upon ecological resources of the area.
Assessment of indigenous community-based climate vulnerability and adaptive
capacity from changing climate and natural disasters
Identifying the ecosystem services provided by mountain forests and measuring the
impacts of climate change and natural disasters on identified services.
Assessing the land use pattern in the study area and measuring the possible impact of
changing climate and land use on the livelihood of locals
15
Review of Literature
2.1 A connection of Socio-ecological system
Socio-ecological system is intricate relation of biodiversity community, physical
environment and social institutions, act as a functional unit (Wamsler et al., 2016). As
SESs contain many subsystems such as a resource system, resource units, users and
governance systems are relatively distinguishable but intermingle to yield different
outcomes which affect these subsystems and their components either larger or smaller
SESs (Ostrom, 2009). People and nature has co-evolved in the history which has led
towards development and refinement in the management of ecosystems (Burgi et al.,
2015). Socio-ecological systems (SES) are important because people look at their future
by learning from their past and therefore their current natural systems are shaped by their
past management practices. Globally millions of people depend upon natural
environment for their livelihoods (Fabinyi et al., 2014). These Human-environment
systems provide essential services to society such as food, fiber, fodder, energy, drinking
water etc (Camp, 2017). Some government policies escalate the resource destruction; on
the other side some resource users have invested their time and energy to achieve
sustainability. A good representation of system reflects the uniform and stable interaction
among its components (Makkonen et al., 2015). It can be measured on the basis of its
common or overlapped structural units such as biodiversity is the source of many
ecosystem goods, such as food and genetic resources, and changes in biodiversity can
influence the supply of ecosystem services (Farley and Voinov, 2016; Fuhrer et al.,
2014). Explicitly biodiversity loss will deteriorate the ecosystem functions by changing
the natural composition and distribution of species (Bloger, 2001; Giller and O'Donovan,
16
2002) ultimately this will cause far-reaching socioeconomic consequences in the future,
through the provision of unsatisfactory ecosystem services to human society (Martens et
al., 2003). Most important step for identifying and assessing factors is classification of
social-ecological systems according to their topographies that influence resilience and
vulnerability of communities and their resources (Alessa et al., 2009; Ostrom and Cox,
2010; Blair et al., 2014).
Ecosystem services are normally the benefits society takes from the natural systems for
their livelihood and wellbeing. On the other hand processes and functions of ecosystems
are natural but are part of socio-ecological systems where human interference in the
environment shapes ecosystems and culture (De Groot et al., 2002). Socio-ecological
systems are complex systems of how people take benefits by interacting in processes and
functions of different ecosystem at various scales (Deressa et al., 2009). Forests provide
human economy as well as well-being with a wide range of ecosystem services like
timber, non-wood products, watershed protection, and recreation also provide tourism,
hunting activities and mushroom picking. Potential impacts of natural disasters and
climate change is often expressed in literature as degrading human through disturbing
their ecosystems (IPCC, 2001a; Adger et al., 2003; Smit and Wandel, 2006; Adger, 2006;
Agrawal and Perrin, 2008). For example, the Millennium Ecosystem Assessment (MEA,
2005) considers climate change as one of the underlying factor for the degradation of
ecological services in the most poor and vulnerable regions of the world. It further
reported that poor people in developing countries often have more dependence on natural
resources for their existence and survival (UNEP, 2009; IPCC, 2007; WRI, 2007).
Livelihood of local communities in mountain areas mostly depends upon the goods and
17
services provided by natural ecosystems (Birch et al., 2014). The challenges provided by
climate change in form of threats to livelihood and ecosystem services are well known
now in 21st century. Several studies over the world are going on to assess value of
ecosystem services in time of changing climate and affecting communities‟ livelihood
(Clemens et al., 2017). Ecosystem services are increasingly considered for research and
decision making for sustainable development that which areas should be maintained on
basis of their higher ES supply (Bagstad et al., 2013; Birch et al., 2014). These
indispensable benefits can be summarized into four major categories (Figure-3, MEA
2005).
I. Supporting services are the services of ecosystem which are needed for the
production of other ecosystem services such as primary and secondary production,
formation of soil, nutrient cycling etc.
II. Provisioning services are the products of ecosystem i.e., fuel, fiber in form of wood
and textiles, food in form of seeds, fruits, nuts, roots, spices, fodder, and other
cosmetic & medicinal products.
III. Regulating services are most important for the human society as they are obtained
by regulating ecosystem processes such as climate and water regulation, carbon
sequestration, water and air purification and protection from natural hazards.
IV. Cultural services are the intangible non-material benefits which society take from
the ecosystems such as aesthetic value of ecosystem & its products, spiritual values,
sense of satisfaction with nature, recreation etc.
18
Figure-3 Millennium Ecosystem Assessment and its linkages with human well-being
[Source MEA, 2005]
In a socio-ecological system, livelihood vulnerability of people due to environmental
change was observed in Nepal (Kok et al., 2016). The study involved proposing a method
consisting of both quantitative and qualitative analysis like spatial distribution patterns,
main indicators of vulnerability etc. and was also demonstrated by applying it to find out
vulnerability patterns in terms of farmers of drylands. The study concluded that the
19
present method can play a significant role in strategic thinking to reduce vulnerability
thereby helping the concerned decision-makers to take necessary steps in this regard.
Due to climatic fragile social-ecological system of Nepali Himalaya is being rapidly
exposed to the effects of brisk climatic change. Due to which the changing climate is
adversely affecting the livelihood of the area. Effectual alteration responses can lessen
the negative effects of the change and evaluations of vulnerability of the local social-
ecological ecosystems are starting the process, however, inadequate study has evaluated
the climate change incited vulnerability of Nepali Himalayan social-ecosystems at
various scales (Fisher et al., 2010). A research work estimated the vulnerability of social-
ecosystems at the household level and inside three rural community clusters of the
Kaligandaki Basin in the Central Himalaya, Nepal. Information was gathered through
face to face interviews with 360 households on exposure, sensitivity and adaptive ability
of the social-ecosystem as vulnerability is determined through a complex system. This
information was incorporated to develop the vulnerability indices. The social- ecosystem
discloses momentous levels of exposure to the change in climate and shows a receptive to
change and in intense weather events although the limited ability to acclimatize across all
spatial scales result in increased ecological vulnerability. This study showed that due to
the limited adaptive ability in the Nepali household the country needs and adaptation
policy to concentrate on the requirements of the majority household through the needy
approach (Aryal, 2014). Scientific evidence can be coincided with the perception of local
people. Local knowledge has been used an effective source of information and can be
efficiently assembled by adopting systematic tools which will test explicit propositions.
The indigenous knowledge can help policy makers to plan mitigation measures and
20
adaptation strategies for climate change in areas where locals are experiencing vast
changes in their day to day life (Mercer et al., 2007).
2.2 Mountainous community and Livelihood in face of climatic changes
By definition, mountain landscapes are precincts of extremely sensitive biophysical and
ecological characteristics such as ecotones- the transitional zones, physical gradients as
temperature, elevation and precipitation (Gardner and Dekens, 2007). Descriptively,
mountain regions substitutes about 24% of the world‟s land surface (UNEP, 2002) and it
maintain 12% of the universal human population (FAO, 2011). Mountainous
communities retain the world‟s poorest people those are tool to sustaining mountain
ecosystems and play a vital role in delivering environmental services to downstream
areas (Gret-Regamey et al., 2012). It is said that because of the higher vulnerability to
climate change and facing marginalized conditions, mountain communities will have
poor livelihood. Past continuous environmental, economic and social developments have
altered many mountain regions increasingly into disaster-prone (Hein et al., 2016).
Mountain regions and their occupants are disproportionally affected due to the
apocalypse events because an ecosystem having mountainous area is more vulnerable and
sensitive than it has plain area (Liu et al., 2016). Climate change is one of the most
important global challenges affecting mountain ecosystems (Briner et al., 2012).
Disasters hit mountainous communities and cause indirect great impacts downstream,
affecting millions of people. Mountain climates vary noticeably with different exposures
and provide limited resources. Inhabitants of these regions use their indigenous
knowledge and developed refined practices for forestry, farming, water use and livestock
rearing and breeding on the steep slopes and in extreme erratic settings. Mountain can be
21
perceived as an asset to adapt to climate change (Wang et al., 2013; Shen et al., 2013).
However, mountain ecosystems are highly vulnerable to climate and land-use changes,
both of which affect livelihood of locals.
Mountain areas are good repositories of biological and cultural range and offer vital
amenities with a tangible economic value (Carpenter et al., 2006; Fisher et al., 2009). By
facilitating key environmental services those are protection against gravitational hazards,
timber production, recreation, biodiversity conservation and carbon storage, freshwater,
and hydropower to more than half of humanity, mountain ecosystems play an essential
role and demand of current era (Gao et al., 2016). Moreover, these act as building blocks
to promote the sustainable global development, poverty reduction and the transition to a
green economy. The elevated regions are considered as water towers to at least half of the
world‟s people for their subsistence livelihood (Elkin et al., 2013). Mountains are the
sensitive indicators and acts as early alarming system for climate change such as glacier
melting or glacier lake outburst floods. Many scientists opine that the fluctuations
occurring in mountain ecosystems may give an early sight of future calamities in lowland
environments (Zoderer et al., 2016). High mountain regions influence the global and
regional climates and weather conditions by interrupting circulation of air. Alternatively,
they cause effect on wind, precipitation and temperature patterns (Singh et al., 2010). It
is predicted that greenhouse gas emissions due to human activity will affect the global
temperatures between 1.1 and 6.4 ˚C (IPCC, 2007). This will have cascading effects on
global water cycle which in turn affects precipitation and runoff patterns. This will
further negatively influence in areas where hydrological system is due to snowmelt.
22
Approximately more than 1 billion people in the world rely on water runoff for their
livelihood that will face water scarcity (Yimit et al., 2011).
The Himalayan region provides a variety of ecosystem services; timber, fuel wood, food,
medicinal resources, regulation of hydrological cycles, climate regulation, protection of
natural and cultural heritage, recreation and tourism opportunities and generation and
preservation of habitats, preservation of soil fertility, cycling and movement of nutrients
(Price and Egan, 2014; Schirpke et al., 2016). To some extent, diversity of these services
is the result of geographic complexity which has influence over the weather patterns in
the region. This establishes microclimatic conditions that form the unique range of
ecosystems. This phenomenon is explained by the Himalayan ranges; north side of it acts
as a barrier and hindrance to the southwest monsoon from the Bay of Bengal. This will
result less moisture towards the western side and comparatively more precipitation on the
eastern side. This precipitate recharges four major rivers (Brahmaputra, Ganges,
Irrawaddy, and Salween) of the Hindu Kush-Himalayas with a substantial volume of
water (Xu et al., 2007).
Mountains environment are also at high-risk of avalanches, landslides, volcanic
eruptions, earthquakes and glacial lake outburst floods which threaten life. These can
wipe out major livelihood resources such as standing crops, stored food, seeds, and fertile
land (Veith and Shaw, 2011); while fragile soils and vegetation cover make these areas
more vulnerable to environmental degradation (Peterson and Halofsky, 2017). Forest
ecosystems is being altered and destroyed by climate change induced diseases (Joshi and
Negi, 2011). Mountain ecosystems and people are become the target of global trend as
increasing pressure on land and mountain resources due to economic demand and
23
changes in population growth and lifestyle. It is clear that the biophysical instability of
mountain ecosystems has direct sordid consequences for the socioeconomic vulnerability
of mountain people (Kok et al., 2016). These amplify natural disasters and disturb
people‟s lives in mountainous regions worldwide. These people retain traditional
ecological knowledge on how to manage the land in a challenging mountain
environment. Their traditional land management practices (e.g., trenching, terracing, and
irrigation systems are still helpful today for low- production at high altitudes (UNEP,
2002; Rahut and Ali, 2017). Sustainable mountain development is a global concern and
priority for addressing the current challenges (Gobiet et al., 2014). Increasing elevation
and declining moisture in eastern Himalayas create various vegetation types such as
tropical seasonal rainforests, tropical montane rainforests, evergreen broadleaf forests,
and also the distinctive monsoon forests over limestone, where water is rapidly lost, and
the monsoon forests on riverbanks with water availability over the year (Chaudhary and
Bawa, 2011).
2.3 Vulnerability to Climate change and Natural disasters
Worldwide ongoing three highly significant issues of vulnerability consideration are
environment, development, and sustainability (Adger 2006; Abson et al., 2012).
Vulnerability to climate change has begun when globally averaged accumulative
temperature of ocean and land surface shows warming of 0.85 (0.65 – 1.06) °C over the
years from 1880 to 2012. Ultimately, the cover of snow and ice has contracted, and sea
water level has increased. Human given stimulation on the climate system is unequivocal,
and latest observed anthropogenic emissions of greenhouse gases are the highest in past
(Xu et al., 2007). Since the pre-industrial time, economic and population growth are
24
become the reasons for these emissions. Different concentrations of atmospheric gases
like carbon dioxide, methane and nitrous oxide are increased exceptionally in last
centuries (Macchi, 2010). Current climate changes have widespread influences on living
being and natural ecosystems. Warming of the climate system is unambiguous and
explicit in present scenario. Since the 1950s, many of the recorded fluctuations are
unparalleled over decades to millennia in continuous manner (UNFCCC, 2013; Angell
and Stokke, 2014). But some of the biggest effects of climate warming are being detected
at high altitude and latitude. Extent of exposure within communities is varied for whole
population and individual household (Phuong et al., 2017). Disasters have increased the
economic loss and make a society highly vulnerable (Kellens et al., 2013).
IPCC (2014) in its latest fifth assessment report identify that human beings are interfering
in the natural systems producing distinct changes in climate. The major determinants of
climate change impacts are from higher exposure and vulnerability to climate related
hazards. Socio-ecological systems recognize societies and their ecosystem as
interconnected in their functions. People do not live in isolation; they have their
dependence on the system they live in. In 21st century, vulnerability of different
ecosystems is exacerbated due to climatic changes and low adaptive capacities of people
(MEA, 2005). Although it is not certain how climate will affect different systems, but
few known facts are proving that it is the single most aspect to influence life and
livelihood in so many ways (IPCC, 2007). Most importantly climate is affecting
additionally to the most vulnerable. Scientist has accepted that climate is influencing life
on planet earth by changing rainfall pattern, weather shift, shifts in harvesting of crops,
rising sea level, receding glaciers etc. (Richards et al., 2003; de Sherbinin et al., 2008).
25
The global climate risk index for year 2016 has ranked Pakistan on eighth number,
stating high climate risk area due to prevailing risk factors and poor adaptation (Kreft et
al., 2015). Different ecosystem and their associated communities will have to adapt and
response to changing climate and life. Climate vulnerability to the forest communities is a
question of their survival because it will affect forest productivity, effecting livestock,
availability of certain medicines and local market as well. Similar is case with
agriculture, most rural local people are involved in agriculture and it is by far biggest and
single source of income to them (Agrawal and Perrin, 2008). Climate variability can
influence negatively significant to the agricultural productivity hence threating their
livelihood. Climate is infecting coastal communities as well; several studies have
reported a downward shift due to rise in sea level and unpredicted changes (Bergstrom et
al., 2011).
IPCC has explained climate change as a constant risk to human beings and their
livelihood (2001, 2007). Whereas UNFCCC consider climate change attributed to human
activities which alter atmospheric composition. AR5 (fifth assessment report) clearly said
that there is high confidence in having higher vulnerability of human livelihood due to
climate changes (IPCC, 2014). Environmental vulnerability is related to the risk of
damage to the natural environment. Assets at risk include ecosystem, population, and the
physical and biological systems and these are degraded by anthropogenic activities (Kaly
et al., 2002; Bergstrom et al., 2011). The environmental vulnerability assessment is a
tool used for evaluation of the resource system affected by natural environments and
interfered by human activities (Fan et al., 2009). It is evident that mountain communities
are more vulnerable than others due to the inequalities exist between nations and societies
26
within a country (Schild, 2016). These are particularly vulnerable regarding their high
relief, steep slopes, shallow soils, facing climatic conditions, vertical processes and
geological unevenness (Liu et al., 2016).
Asia is known as the super market of disasters because of high frequency of disastrous
floods faced by China, India, Bangladesh and Pakistan during the past two decades (Abid
et al., 2016). Statistics showed in 2010, floods damaged the population and their houses
more severely than the disasters of 2005 earthquake in Kashmir, Haiti earthquake, the
Nargis and Katrina cyclones and the Indian Tsunami (Ainuddin et al., 2013). Floods are
considered as most destructive disaster due to their spatial extent and potential to cause
economic loss (Qasim et al., 2016). Extents of exposure within communities are varied
for whole population and individual household. It is proved from climate change science
and practices of countries that adaptation actions aligned with mitigation reactions are
mandatory in order to introduce the wide-ranging impacts of projected climate change
(Fussel, 2007).
2.4 Measure of Vulnerability and Adaptive Capacity
Vulnerability is defined as a state of susceptibility to harm from exposure to stresses
associated with environmental and social change and from the absence of capacity to
adapt (Adger, 2006). There are basically two types of determinants of vulnerability:
generic and specific (Adger et al., 2003). Specific determinants of vulnerability depend
on the type of hazard and the specific context in where it is being used. For instance the
causes of vulnerability to drought of a rural community present in semi-arid Africa will
be different from the factors that make Norway, a rich industrialized nation, vulnerable to
disastrous weather events such as floods and storms. Similarly their vulnerability will be
27
evaluated using different factors as in this case for assessing the vulnerability of African
rural community to drought, income data and isolation will be considered whereas for
Norway factors like the efficient allocation of land resources and physical infrastructure
shall be taken into account. On the other hand there are certain factors known as the
generic determinants of vulnerability like poverty, health conditions, governance and
economic differences which are useful in the sense that they help to assess the
vulnerability at a national level and thus give a better idea about the vulnerability of a
country and its adaptation measures in relation to climate hazards (Brooks et al., 2005;
Fussel, 2007). By definition, “vulnerability is a set of conditions determined by physical,
social, economic and environmental factors or processes, which increase the
susceptibility of a community to the impact of hazards.‟‟ The physical factors are
represented by factors such as: population density, distance to/from a settlement, quality
of construction materials and of the techniques used to build the infrastructure (Ainuddin
et al., 2013). Vulnerability has been studied in wide range of disciplines, but initially it
was studied in geography with relation to natural hazards and poverty, whereas in recent
time it is studied in connection to climate change and adaptation (Schoon, 2005; Fenton
et al., 2007).
The concepts of vulnerability, adaptive capacity, adaptation strategies are mostly
interrelated and have wide applications in global change science (Smit and Wandel,
2006). In relation to climate change the definition of vulnerability falls into two major
categories of literature; First view vulnerability as possible damage to a person or a
system by a climatic hazard or an event (Adger, 2006) and secondly as a system that have
it in its state before an event happens (Cutter et al., 2003; Hinkel, 2011). Vulnerability of
28
the local community can be measured through VCA which is very useful tool in
developing baseline information on community vulnerability to hazards and capacities
existing locally to reduce potential risk of disasters (IFRC, 2006a; b; c; d). It is a
participatory tool to develop a framework which will include transect walk of the study
area to understand livelihood of community, risk mapping, climate based data of
temperature and rainfall, seasonal and livelihood calendars (Macchi, 2011; Gentle and
Maraseni, 2012). The vulnerability includes disproportionate poverty rates, high
prevalence of food insecurity, and poor health, high demand of natural resources,
marginalization, and low livelihood diversity. These features are the driving forces of
mountain resident‟s vulnerability, and are anticipated to be further provoked by climate
change (Wei et al., 2013). Mountain‟ indigenous people and their livelihoods are
particularly in frontline of adaptation to other extreme climate scenario (UNEP, 2002).
This stresses the adaptive capacities of both mountain inhabitants and lowland
communities (Prasad, 2010).
2.4.1 Component of vulnerability
Studies have supported three components of vulnerability that frame real connotation of
the term (Figure-4). Exposure is an extent when a subject or a system is in contact to the
perturbation whereas Sensitivity is degree or extent of disturbance in a system or to a
subject due to certain exposure. Adaptive capacity is the ability of a system to adapt of
adjusts to a definite disturbance and copes with transformations (IPCC, 2001b; Cutter et
al., 2003). In addition to these three key elements, a comparative analysis of different
approaches for explaining vulnerability of a particular area suggests a number of other
factors namely temporal variability, various contexts, scale-interdependency along with
29
different scales and dimensions. In the conceptual framework of vulnerability, adaptation
and adaptive capacity both play an instrumental role along with resilience (IPCC, 2007b).
Changes in environment and sustainability science emphasize the need to understand the
different changes taking place in the general functionality and composition of the
biosphere and therefore it is important to identify the extent of vulnerability of areas
undergoing such changes (Posey, 2009). Studies have shown that vulnerability is solely
not related to exposure to hazards but also depends largely on the sensitivity and
resilience of the system exposed to such stresses (Hatt, 2013). For the proper
identification and quantification of the extent of vulnerability of a system, using a large
number of approaches is necessary in order to explain a variety of interactions involved
in determining the vulnerability of a system (Arias et al., 2016). A holistic and
harmonized approach towards vulnerability determination will be of great significance in
reducing the vulnerability of a particular system and will also in turn help the decision
makers in taking effective measures in the future (Adger, 2006; Fussel, 2007; Hinkel,
2011).
Figure-4 Triad of Vulnerability Analysis
30
2.4.2 Dimensions of vulnerability
Literature appraisal has helped in mentioning that for all vulnerability studies, dimensions
should be known. It has supported three important dimensions to be considered in
vulnerability analysis and these are scale, dynamics and diversity (IPCC, 2007b). For
example, mostly studies which are based on vulnerability assessment are either location
wise i.e. a community level or region based i.e. Asia, Central America etc. scalar studies
work on a specific area. In this case, some static variables calculated at global level may
be ignored at dynamically coping capacities of a local level e.g. GDP of a country can be
used to assess vulnerability at community level (Perez-Agundez et al., 2014). Third
dimension is diversity which indicates that measuring community level vulnerability can
highlight diversity and heterogeneity of locals and their diverse environment (Fabinyi et
al., 2014). All these dimensions of vulnerability influence nature and societies living
together.
2.5 Assessment of Vulnerability
Vulnerability assessments can be conducted according to a range of approaches from
descriptive to quantitative (Choe et al., 2017). Vulnerability assessment is a study of
conditions and process resulting from physical, social, economic and environmental
factors that increase the susceptibility of a community to the impacts of hazards (Gerlitz
et al., 2016). Diverse set of methods and indices have been explained thoroughly to
integrate and examine interactions between social and ecological systems, non-linear
feedbacks, spatial and temporal variation, human and their physical, social surroundings
with the help of vulnerability assessment. Their application includes the measurement of
trends in poverty, human development, food security, vulnerability and bio-diversity
31
(Kotzee, 2016). Chambers (1994b) described that Participatory rural appraisal (PRA)
tools are a family of methods and approaches use to gather data of risk profiling in a
community; i.e., focus group discussion, seasonal and livelihood calendars, transect walk,
household surveys, venn diagrams etc. These tools are based on principle of knowledge
sharing from locals to researchers for developing understanding of different phenomenon
(Fussel, 2007). The techniques of participatory rural appraisal are used in almost all parts
of world in assessing livelihoods, vulnerabilities and risks associated with climate change
and natural disasters (Conway, 1985; Chambers, 1994a; Chiwaka and Yates, 2005;
Macchi, 2011; Daze et al., 2009). Some of the very popular tools and techniques which
are used in climate based vulnerability and adaptive capacity assessment are as follow:
CARE international has developed “climate vulnerability and capacity analysis (CVCA)”
(Daze et al., 2009); IUCN has established “frameworks for assessing vulnerability to
climate change” Marshall et al., 2009); a Toolkit developed by Tearfund named as
“climate change and environmental degradation risk and adaptation assessment
(CEDRA)” (Wiggins, 2009); “Vulnerability to Resilience Framework (VRF)” produced
by Practical Action (Pasteur, 2010); International Federation of Red Cross and Red
Crescent Societies (IFRC) provided and used “VCA Toolbox” 2006a, b, c, d) in their
member states; and ICIMOD Nepal has provided “Framework for Community-Based
Climate Vulnerability and Capacity Assessment in Mountain Areas (CCVCA)” (Macchi,
2011). Such participatory techniques gathered data of indigenous people regarding their
climate based vulnerability and adaptive capacity.
2.5.1 Vulnerability capacity assessment Vulnerability capacity assessment (VCA) in a
broader context is aggregation of Vulnerability assessment approach (VA) and
32
sustainable livelihoods approach (SLA) which specially considers gender issue and social
groups of marginalized population as well as their inherent livelihood assets and coping
capacities (Chambers and Conway, 1991; DFID, 1999; Adger, 1999;). It is an
investigative tool designed to collect data of local communities from the risk in their
vicinity and their coping practices. VCA requires participation of both interviewee and
interviewer. It is a participatory rural approach which includes transect walk of the study
area to understand livelihood of community. After data gathering, focus group
discussions can be conducted with community representatives, like school teachers,
NGOs, elders in community to assess climate based data. Seasonal, climate-based
calendars and risk mapping of whole area are included. This VCA has main objective to
gain understanding of how local people are living in marginalized environment,
influenced by climatic variability and what are their coping mechanisms
2.5.2 Livelihood vulnerability assessment
Livelihood vulnerability highlights vulnerability to someone‟s source of living. There are
several methods to assess vulnerability of people‟s livelihood. First study to use
livelihood vulnerability index (LVI) was in Mozambique to analyze the vulnerability of
farming households to climate change and variability (Hahn et al., 2009). The LVI
includes seven major components as socio-demographic profile, health, food, and natural
disasters, livelihood strategies, social networks, climate variability and water. Each
contained several sub-components. Multiple indicators have been used by LVI to assess
exposure to natural disasters and climate variability, social and economic characteristics
of households that affect their adaptive capacity, and current health, food, and water
resource characteristics that determine their sensitivity to climate change impacts. It is
33
widely used in different parts of the world by climate scientists to understand the specific
vulnerability related to water, food, health and others sectors (Osbahr et al., 2008; 2010).
Hahn et al., 2009 firstly applied LVI in Mabote and Moma Districts of Mozambique,
Africa to assess climate change vulnerability in coastal and inland communities. Later in
Trinidad and Tobago islands, Shah et al., 2013 applied LVI to understand climate based
vulnerability of wetland-dependent communities by adding few more components.
Madhuri et al., 2014 used LVI in Bhagalpur Bihar, India to indicate vulnerability in flood
affected households. Gentle et al., 2014 assessed differential impacts of climate change
based on distinct well beings of the communities in the Lamjung district of Nepal. The
study coupled LVI with participatory well-beings ranking. Panthi et al., 2015 calculated
livelihood vulnerability to climate change through LVI on agro-livestock smallholders in
the Gandaki River Basin of Nepal. Gerlitz et al., 2016 used the multidimensional
livelihood vulnerability index in the Hindu Kush Himalayan (HKH) region to examine
livelihood vulnerability due to socio-economic and climatic changes. Alam et al., 2017
identified livelihood cycle and vulnerability in the rural riverine households of
Bangladesh using LVI. Houng et al., 2018 measured household livelihood vulnerability
of agriculture communes in Northwest Vietnam. However, most recently Zhang et al.,
2018 examined the vulnerability of communities to climatic changes using LVI in the
Gannan Plateau, which is one of most environmentally sensitive region of China.
2.6. Adaptation
Adaptation is a very important factor that will play a crucial role in the climate change
impacts regarding sustainable management of life and livelihood resources. Adaptation to
the current climate change impacts requires not only minor changes like change in
34
planting dates and crop varieties but rather some huge costly investments like
highlighting climate risk prone areas and prioritizing them in order to successfully cope
with the changing scenario. This demands cooperation and support from governmental
organizations, researchers and farmers but unfortunately this issue has been not given due
attention. Results from a study have shown that Southern Africa and South Asia
including Pakistan, in absence of adaptation strategies, will have to suffer from severe
impacts of climate change in terms of food insecurity (Michelle et al., 2012). Better
adaptation directly strengthens the resilience, which reveals the ability of systems to
return to a former condition after facing stresses (Engle, 2011; Wilder et al., 2010).
Currently, investigating the adaptability of rural communities to natural disasters is one
of the major challenges for rural regions of the world (Woods, 2012; Urgenson et al.,
2010; Su et al., 2012). Most of the studies focused more on the vulnerability and
resilience of small mountainous rural communities, climate change, resources and
production. Unfortunately, evaluation of adaptive capacity of these regions is limited due
to lack of understanding approach how adaptation occurs (Berrang-Ford et al., 2011;
Swanston and Janowiak, 2012).
Adaptive capacity assessment is primarily based on socioeconomic elements of studied
areas (Brooks et al., 2005; Vincent, 2007; Posey, 2009). Many studies have investigated
that both socio-economic background and natural disaster conditions should be
considered when evaluating the adaptive capacity (Jiang et al., 2016). These communities
require equal attention for its preservation and empowerments while currently are being
neglected. Aryal (2014) explored disaster vulnerability in Nepal from a local perspective.
The study gathered thirty-nine case studies based on disaster histories in Mountains,
35
Hills, and Terai regions of Nepal. The case studies helped in investigating the perception,
process, risk and exposure to vulnerability within the communities. Similarly Adger
(2006) reviewed vulnerability in socio-ecological systems and its different analytical
approaches in context of environmental change. He furthered considered the concept of
vulnerability as a powerful analytical tool to describe exposure and marginality of social
and physical system.
Adaptive capacity in terms of natural hazards has been defined broadly in literature, (e.g.
Adger et al., 2003; MEA, 2005) described it as the ability or capacity of a person or a
system to change its behavior to cope up with anticipated stresses. Smit and Wandel
(2006) reviewed the concepts of vulnerability and adaptive capacity of human
communities in face of global changes like climate change. They proposed that
adaptation can be considered as a response which is associated with human vulnerability
to environmental hazards. The analysis of vulnerability and adaptive capacity is based on
scales which vary from an individual, household, community, to type of hazards like
drought, floods and others (IPCC, 2007b). Adaptations are important from the
perspective of climate change because of local communities need to mitigate negative
effects to avoid unseen danger (Bandyopadhyay et al., 2011).
Vulnerability is commonly used to explain the potential threat to rural areas faced by
climate inconsistency and alteration. Analytical measures of vulnerability are still being
evolved and demand for selection criteria of prioritizing adaptation responses is also
increased rapidly with awareness of climate change and its potential effects on rural
communities (Schoon, 2005). The consequences for policy advice of imperfectly
examining vulnerability through the lens of an impact/hazard modeling approach to risk
36
management. It showed how hazard/impact modeling can be complemented with more
holistic measures of adaptive capacity to provide quantitative insights into the
vulnerability of Australian rural communities to climate variability and change (Nelson,
2010).
Malakar and Bhandari (2012) conducted study of the relative importance of
socioeconomic factors associated with differential community vulnerability to floods and
landslides were carried out in Nepal. Three disaster impact variables; deaths, family
affected, and loss of animals were considered in this analysis. The regression analysis
was used to assess how the community‟s vulnerability to floods and landslides was
associated with socioeconomic factors. The study concluded that the effects of education
on reducing disaster vulnerability tended to be more pervasive than those of
income/wealth in the case of floods and landslides in Nepal.
In Cameroon, the mostly rural households and a large numbers of urban households rely
on different products of plant and animal for their nutritional, energy, cultural and
medicinal needs. This study highlighted the possible impacts of climate-induced
variations on forest ecosystem goods and services and its outcome on the economic and
society that include both national economy and forest-dependent people. The analysis
used four identified vulnerable sectors, food, energy, health and water through a dialogue
of multi-stakeholders. The analysis gave the possible implications of the vulnerability of
these sectors for planning local and national adaptation strategies that includes: reducing
poverty, enhancing food security, water availability, combating land degradation and
reducing loss of biological diversity (Sonwa et al., 2012).
37
Angell and Stokke (2014) observed climate based vulnerability and adaptive capacity in
Hammerfest city of Northern Norway. Data was gathered from different sources using
semi-structured interviews. Institutional, socio-economic and natural vulnerabilities were
observed in current and future expected scenarios of climate. The main purpose of the
study was to develop models for local climate vulnerability and to test them in the
municipalities for assessment of their adaptive capacity. It was observed that local
government of Hammerfest was much interested in improving state condition as many
adaptation practices were already in place only collaboration in different department is
needed. KC et al. (2015) quantified vulnerability to climate change in Georgia through a
holistic approach by integrating biophysical and social vulnerability with geographic
vulnerability. Data was taken from the state on the basis of IPCC vulnerability equation
coupled with framework. In addition climatic data of temperature and precipitation was
taken for the period of 1971 to 2012 from 77 stations. It was shown that extreme hydro-
climate events like floods and droughts had increased in frequency and magnitude as
there were more anomalies seen in drying and warming in the region. The study was
good attempt to explore vulnerability of human environment system. Quantifying current
social vulnerability helped in predicting how climate change may affect society in future.
Bhatta (2015) considered the mountain ecosystems as beneficial for the livelihood of a
community in many various ways and are being affected by global environmental
changes rapidly. The study showed the regional effects of climate change in ecosystem
services, the livelihood and present adaptation approaches of local individuals in the
mountain of central Nepal. The most important observed affects were precipitation,
irregular rain falls, crop production, and paddy cultivation. This study also shows that the
38
local people showed substantial efforts in forest conservation and management and
gradually increased the forest cover. In spite of high potential for the forest ecosystem
services, the availability of forest gods have decreased due to the strict regulation on
forest taking out. The density in the tree canopy was changing due the restricted use of
forest goods. Numerous local adaptation strategies, such as changing both agricultural
practices and water harvesting and management, are increasing efficiency in resource
use. To increase the adaptive capacity of poor households, it is essential to incorporate
climate change adaptations within the local planning process.
Gentle and Maraseni (2012) discussed that the rural mountainous communities mainly
depend on natural resources of ecosystem for their livelihoods and existence. For the
purpose, Jumla District of mid-western Nepal was chosen which is an underdeveloped
and a remote mountainous area. The participatory rural appraisal was used to gather data
form the local community. The methodology was derived from the climate vulnerability
capacity assessment (CVCA) to assess the vulnerability of mountainous people from
climate change and their adaptation practices. It was shown that food shortages, unequal
resource allocation, resource depletion were the problems of the region. Agriculture was
adversely affecting the poor due to climatic variability. Adaptation practices were
improved in Well-off people whereas poor were unable to cope the current conditions.
Local ecosystem was badly depleted. It was concluded that the local governments,
involvement of stakeholders is needed to have a sustainable livelihood and development
in the area. Pavoola (2004) had evaluated livelihood practices of farmers in face of
vulnerability and adaptation to climate change in Morogoro, Tanzania. It is the largest
town of Tanzania which will see higher impacts of climatic changes by 2100 as predicted
39
to warm 2-4 degree C. mean monthly and annual rainfall was studied from the period of
1922–1988 to assess the climatic variability in region. It was identified that different
livelihood approaches were adopted by the agriculture households to adapt to climatic
variability like agriculture intensification, livelihood diversification, and migration. These
approaches had severe environmental impacts such as changes in pattern of water flows,
soil erosion, deforestation etc. due to finding solutions for better livelihood; local people
had depleted more natural resources. There was a need to adopt technical solutions by
government including proper management of natural resources and elevation of enhanced
market participation to reduce vulnerability to changing climate of locals.
Bagstad et al. (2015) conducted a study based in Pike–San Isabel National Forest,
Colorado. The study methodology involved using tools like Social Values for Ecosystem
Services for the statistical modeling of twelve types of value surfaces and Artificial
Intelligence for Ecosystem Services for biophysical modeling of important factors like
regulation of sediments, yields of water beautiful view sheds and most importantly,
carbon sequestration and storage along with hotspot and regression analysis. Results of
the study showed poor relationships between both perceived services and biophysically
modeled ones thus implying that the perception of the public regarding provision of
ecosystem services is quite limited. The study concluded that such approaches can help in
managing ecosystem service based resources thus proving to be beneficial for the
resource managers in the long run.
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2.7 Climate change mapping and assessment
Climate has always threatened life of mountain people, due to extreme weather
conditions. Nelson et al. (2013) conducted a study in United States in order to evaluate
the effects of climate change on the ecosystem services and the well-being of humans
depending on these services. It was suggested that climate change will change the
patterns of crop and seafood production in the US. Moreover, rise in sea levels and
increase in the incidence of stormy weather events thus increasing the value of
undeveloped coastal habitats as protectors of populations and property. In addition to this,
extreme events like droughts and variable hydrological cycles will modify and threaten
availability of water throughout US. The study recommended the use of cost-effective
adaptive strategies to maintain productivity, use of reservoirs and water markets in order
to store and use water effectively in addition to keeping records of natural assets
associated with ecosystem services so that adequate adaptation strategies can be
prioritized and adopted accordingly. A large scale study has been carried out to assess the
impacts of climate change on forest sector of United States under National Assessment
study (Alig et al., 2004). It was suggested that in view of the climate change and
ecological scenarios, less cropland shall be converted into forests compared to the
baseline environments. Secondly, bio-geographical models showed that a change will be
seen in the overall composition of forests whereas economic models also demonstrated
that the forest area in the US is expected to expand less in view of the climate change
scenarios. Moreover, climate scenarios showed an approximately 10 percent increase in
the severity of fire hazards throughout US. It was also observed that the income of the
producers dependent of forests was most likely to be affected by climate change.
41
Jorgenson et al. (2015) analyzed future changes in northwest Alaska based on time and
temperature scenarios. A total of 23 biophysical drivers were studied in sixty ecotype
regions to explain ecosystem changes. The study used two hundreds and forty-three
potential transitions for all ecotypes for a period of 30 years as 2040, 2070 and 2100
ending respectively. It was found that mean annual air temperatures was +0.97 °C per 30
years during the ~1949-2010 period. The modeling proved an overall 13% change in
ecosystems, with 23 ecotypes losing their areas and 33 Trends of climatic change were
determined with cold and warm phases in historical data. The feedbacks and responses
were poor because increase or decrease in each driver may result in variation in predicted
climate changes. Ecosystems showed constant change at widely varying rates of each
driver. The study showed that change in climate pattern will remain steady in the century,
although climate warming will be nine-folds higher than current rate.
Goetz et al. (2013) conducted a study in order to find out the fluctuations that are
witnessed in the mitigation costs during the management of an optimal forest in view of
climate change and considers a substitution process between carbon sequestration and
timber production at the stand level. The results of the study showed that there was an
increase in carbon sequestration costs in presence of climate change once carbon
sequestered per hectare surpasses a certain threshold. The study concluded that carbon
sequestration by the forests can be used as a mitigation measure both in the short-term
and medium-term. Bele et al. (2015) conducted a study based in Congo Basin forests in
order to highlight the threats to the forest, the need for taking requisite measures to adapt
this forest to the changes in climate and an assessment of possible adaptive measures that
can be taken. The results of the study showed that a sustainable approach for the
42
management of these forests should be used such that it conserves the region‟s natural
biodiversity without having any deleterious effects on the forest resources. Moreover,
such an approach also holds importance in the sense that it will develop the rural areas in
a very sustainable manner on one hand while eradicating poverty through employment
opportunities on the other hand.
Rawlani and Sovacool (2011) considered the role of local community against climatic
changes in Bangladesh. The study was to build community responsiveness by conducting
interviews for the impacts from climate change. In Bangladesh it was predicted by IPCC
that there will be increase in temperature by 1–3°Celsius by 2050 which will raise see sea
level, more of waterlogging, erosion, flooding in monsoon etc. the study supported that
climate change will adversely affect the six major sectors including water resources and
coastal zones, agriculture and food security, infrastructure and human settlements,
forestry and biodiversity, human health and fisheries. The study concluded to adapt to
national policy of climate change adaptation in sectors of comprehensive disaster
management, mitigation and low carbon development, social protection and health,
infrastructure, research and knowledge management, and capacity building and
institutional strengthening. Chaudhary and Bawa (2011) studied that Himalayas are
facing climatic variability which will threaten socially, economically and
environmentally almost two billion people living in its purlieu. Data was gathered using
household‟s survey and focus group discussion (FGD) in total of 28 villages of Himalaya
across Nepal and India. The regions were divided into two groups, low altitude and high
altitude. Questionnaire was about the 18 indicators of climate change impacts like
biodiversity changing, distributional range shifting, advanced summer onset, warmer
43
weather, decreased mountain snow, less winter severity, low frost, unpredictable rainfall,
early budburst and flowering, water resource drying, notification of mosquitoes etc.
People of Himalayas are more sensitive and have widespread knowledge on effects of
climatic events on biodiversity; seasonal changes in budburst and flowering, new
agricultural pests and weeds and appearance of mosquitoes. Positive and negative effects
in all these parameters had shown climatic shifts. These factors were important
parameters to answer climatic effects in this global concern region. Schickhoff et al.
(2015) conducted a study on Himalayan treelines in order to gather knowledge about the
level of different responses the study site can generate in addition to its sensitivity to
climate change. The study methodology involved a number of field surveys, results from
already published literature and utilization of data obtained by the authors during the
course of their research. The results of the study showed that the treelines of Himalaya
are quite varied and diverse therefore generalizations about their response to climate
change and sensitivity towards it would be inappropriate. Moreover, a considerable shift
in treeline vegetation has been observed particularly due to decline in land use and not as
a result of climate change. Also tree growth-climate relationships and their growth
patterns have reported a high level of sensitivity of the mature treelines to the changes in
temperatures and humidity thus implying that a change in climate can act as a driver of
various structural, physiological and rather complex responses.
Shrestha et al. 2013 analyzed the effects of temperature and rainfall on the phenology of
vegetation in the great Himalaya which is the region of great biodiversity, sacred
landscape and a major source of Asia‟s rivers possibly influences the 20% of world‟s
humanity. Despite of it global concern, this region is less observed for the sake of
44
changings in climatic conditions. NDVI (Normalized Difference Vegetation Index) was
measured for the data of period 1982 to 2006. It was examined that temperature or
precipitation changes through localized areas reveal vulnerability of Himalayas as three
times than the global average. Phonological changes were observed in all major
ecoregions by the changings in phenology of local ecosystems. Differences were
observed for the average start of growing season as well length of growing season. NDVI
(Normalized Difference Vegetation Index) values from remotely sensed imagery marked
it as the most vulnerable region to climate change. Riva et al. (2013) studied impacts of
climate change on the socio-economic and environmental condition of Charazani Valley,
Andes- Bolivia. Qualitative analysis was used based on community and household
interviews gathering social and environmental indicators. The rural livelihood was
threatened due to changing pattern of rainfall and temperature in the region, which was
shown by the climatic data like flooding, rainfall, frost, droughts etc. These intense
weather patterns had affected agriculture, socio-economic conditions and livelihoods of
Bolivian people. It was concluded that lack of adaptive strategies are due to limited
economic resources. Farmer families were most vulnerable to climatic changes as well as
household which totally depend upon forest-based earnings. However, there will be need
to enhance the adaptive capacity and to lessen the Vulnerability of climate change in
Adean region.
2.8 Estimation and Mapping of Forest Ecosystem Services
Tropical Rainforest are well known for the provision of their ecosystem services and their
incessant supply depends upon the effectual management adjacent to deforestation and
forest degradation. Indigenous communities are highly depended on rain forest and its
45
ecosystem services and their demands are unknown due to lack of knowledge (Grainger
and Lindquist, 2015). Delgado-Aguilar et al. (2017) conducted a study to show the
importance of knowledge regarding to ecosystem services that the local individuals are
taking from Ecuador tropical rainforest. A spatial explicit assessment of ecosystem
services using participatory mapping in the Sumaco Biosphere Reserve was conducted to
understand and gather information of local people forest use and its management as it is a
protected area with increase population and pressure. At first semi-structured interviews
were conducted then people were asked to point out on 3-D maps where they utilize
ecosystem services. Then the highlighted areas were digitalized and analyzed with
statistical and GIS techniques. As a result, the areas highlighted were not randomly
chosen but were most abundant from four kilometers or less than roads and people used
forest ecosystem services more because the markets were at distance. This study shows
that with help of GIS-based and spatial mapping forest ecosystem services can be
identified and highlighted so it can be provide with protection and guidance for the
management.
Boon and Ahenkan (2011) assessed the link of climate change, ecosystem services and
livelihood. Worldwide the escalating impacts of climate change become visible on
ecological systems especially livelihood of forest dependent communities become
vulnerable due to these ecosystem changes. They used Human-Ecological approach to
examine the impacts of climate change on ecosystem services and their livelihood in
western Ghana. Primary and secondary data was collected from the communities
regarding the services of the ecosystem.
46
Birch et al. (2014) studied benefits of community forest in Kathmandu Valley of Nepal
using Toolkit for Ecosystem Services Site-based Assessment (TESSA). It helped in
mapping current ecosystem services value and alternative state provided by the site.
Methods for assessing these services were available in TESSA and were modifiable to
rapid assessment and measurement. Kuenzer and Tuan (2013) measured the ecosystem
service value of a Mangrove Biosphere reserves in Vietnam by combining earth based
observations with a detailed socio-economic household survey. It was done to assess
depth of the direct and indirect values communities are extracting from the reserve.
Economic valuation method was adapted to value or measure the value of services taken
by locals. Briner et al., (2013) used an integrated economic-ecological modeling
framework to assess climatic and economic effects on forest and agriculture services in
mountainous region of southern Switzerland. In a mountainous region, provision of
ecosystem services depends upon biophysical impact of climate change, socio-economic
changes and climate-led changes in land use.
Schetke et al. (2018) studied the need of climate protection in Germany with
implementation of ecosystem services concept in planning and management. This study
shows urban planning and climate protection strategies and use of renewable energies.
This study analyses the laws and regulations of federal state level in Germany to provide
a better understanding of application of Ecosystem services concept in the organizational
level for climate protection. At federal state level the climate laws of federal state were
also analyzed to provide understanding framework at local level. Climate protection
amendment of German federal building code was considered with urban planning. This
resulted to show that biotic and abiotic factors of ecosystem services play a important
47
role in other planning domains besides landscape planning. This study brings climate
protection with renewable energy policies and ecosystem services concept. Scholars till
date has shown negative effects of renewable energy on ecosystem services provision and
this study shows the legal documents analyzed highlight the part of abiotic ecosystem
services providing renewable energies in mitigating climate change.
Makkonen et al. (2015) conducted a study to analyze Finland‟s forest policies and
coherence between different types of policy outputs which affect forest ecosystem
services most importantly carbon sequestration and forest bioenergy both of which are of
prime importance in dealing with the present climate change. The results of the study
showed that numerous policy instruments specifically allowed the promotion of
bioenergy as compared to carbon sequestration. Moreover, the study concluded that an
ecosystem service whose market already exists operates much rigorously as compared to
the one which is currently in its stages of development and thus remains highly
unpredictable.
Hayha et al. (2015) carried out study at Fiemme and Fassa Valleys of North Italy,
renowned for their high quality timber production. Ecosystem services of mountain forest
were mapped and measured from the monetary benefits and biophysical driver on annual
basis. Total economic valuation (TEV) technique along with GIS mapping was done for
the surrounded forest and forest products. It was revealed that that TEV was 820 €/ha/yr.
The cost of provisioning services was 40% of the TEV while the regulating and cultural
services were accountable as 49% and 11% respectively. The hydrological protection
service was characterized as majorly important in areas of landslides and avalanches.
This information enabled to identify priority areas and possible trade-offs and synergies
48
among different services. Such studies are important for the decision makers to know
economic importance of forest services while making forest policies.
Muhamad et al. (2014) conducted a study based in West Java, Indonesia in order to
evaluate rural people‟s perceptions regarding ecosystem services provided by a forest via
different landscapes. The study methodology involved conducting direct interviews with
the respondents selected on the basis of simple random sampling. The results of the study
showed that rural people were well aware of the ecosystem services. Moreover important
socio-economic factors like number of livestock, agro-forest and agricultural land area,
location of the residence and place of origin all influenced an individual‟s perceptions
regarding ecosystem services. Also people who were living near a remnant forest felt
they had greater access to ecosystem services.
Kuenzer and Tuan (2013) conducted a study to assess the ecosystem services value of
Can Gio Mangrove Biosphere Reserve in Vietnam. Earth-observation based mapping was
coupled with the socio-economic household survey to evaluate the importance of
ecosystem services provided by mangrove forest. Remote sensed and radar data from
2011 were utilized to develop the specific extent of mangrove covered area. The results
of household survey showed comprehensive understanding of all value existed in
mangroves by different occupational groups, namely, forest managers, fisherman, shrimp
farmers, and other farmers. Native people had no understanding of common value of a
natural resource if no direct source of income is generated. Along this, depending on
occupation, people have better understanding the importance of mangroves as highest
value was shown by local and migratory fisherman, followed by forest managers, while
49
shrimp farmers have the least knowledge about mangrove benefits, and also showed the
least willingness to further protect them.
Mandoza et al. (2014) studied the ecosystem services and their connection with
livelihoods and patterns of poverty in seven different villages of Cambodia. Data was
collected using a mixed methodology of focus group discussions and household surveys.
Main livelihood activities provided by the ecosystems were forestry, coastal fishing low-
lying agriculture and self-farming etc. It generated primary income to 85-90% of
households. Forest played an important role their livelihood. For forests, fisheries and
wild food collection, there were issues about a general decline in the resource as well as
about access rights to the resources left. It was suggested that ecosystems are degraded
because of primary source of livelihood in rural Cambodia, and appropriate ecosystem
management should be cater to have sustainable living including protection of resources,
excess of resources to poor, extended agriculture for the poverty eradication,
discouragement of illegal fishing and forest clearing.
Lindner et al. (2010) summarized the impacts of climatic changes and vulnerability in the
European forest ecosystems. It was done using direct and indirect assessment of forest to
produce social, economic and ecological services in face of exposure, sensitivity and
potential impacts in different bioclimatic regimes. Boreal and temperate regions of
European forests were under serious threat of climate change. Excess amount of carbon
dioxide and high temperatures were impacting Northern and Western Europe in positive
way in short run. Whereas, adverse impacts like famines, floods, risks were affecting
more in Southern and Eastern Europe. Inherent adaptive capacity of forest is diverse but
slow so there is need to enhance adaptive capacity against the variable extreme
50
environmental conditions. Temporary measures can increase adaptive capacity like tree
growth improvement, northward specie expansion etc. The study has concluded that
climatic variability was effecting the production of forest goods and its services will be
reduced in almost all bioclimatic zones of Europe because of higher susceptibility.
Sonwa et al. (2012) assessed the vulnerability of forest ecosystem to climate change in
Cameroon of Congo Basin by taking data of climatic impacts on the ecosystem goods and
services provision. Most of the rural community depended on the forest ecosystems for
their economic and social well-being. The Congo Basin forest was fulfilling major needs
of food, fuelwood, water and medicine. The study gathered information about rainfall and
temperature patterns which has been of major shifts. As a result the identified forest‟s
goods and services are becoming more vulnerable to climate change as well as
anthropogenic activities. This will be challenging for the locals to adapt and for the
national economy as well. It was concluded that Poverty reduction will be an indirect
strategy designed at political level by enhancing adaptation. Furthermore adaptation
capacities of rural local people should be built to fight against climate change.
Willemen et al. 2013 considered the role of ecosystems in supporting livelihood and
subsistence of local people in Congo which is known for having highest biodiversity in
Africa. Out of total, 67% of its land is covered with forest. Five important ecosystem
services were mapped including food production, carbon stock, timber production, fuel
wood and tourism. These ecosystem services were quantified to see the direct and
indirect beneficiary group. The study had highlighted importance of each ecosystem
services and its spatial scale e.g. few services were more beneficiary for local population
than global population like fuel wood over carbon stock. It was established that
51
conservation strategies must be adapted to preserves ecosystems because of their
dynamic input into human made systems. There will be need of integration of trans-
disciplinary research, assessment, monitoring and sound policy development on different
spatial levels socio-ecological system.
Oort et al. 2015 described that ecosystem provides goods and services on many segments
according to their income and basic needs. For this, CFUGs (Community Forest Users
Groups) adopt distinct methods to know the customers as well as consumers demands in
the turbulent environment of local and national market. After getting information,
CFUGs found that farmland is under great pressure of increasing cropping intensity,
increased water used for irrigation, increased use of pesticides and fertilizers also
decreased water quality. They also found that water availability affects agricultural
production and forest and soil affect water quality. Due to increase demands of water
which is used in land crops, Irrigation and forest goods, they forecast that this challenge
may also increase in monsoon (intense rain) and decrease during off monsoon. For this
they decide that sustained management can control unsustainable water what are
necessary for the local and national level people to raise their earnings and also helpful
when shortage of water affect their productions.
Lal (2009) conducted a study in order to elucidate the potential role of carbon sequestered
by the soils worldwide for dealing with the global climate change and its positive
implications on food security through an improved soil quality. Results showed the
carbon sequestration potential of peat soils to be approximately three petagram at 1
mg/ha/yr soil carbon pool rate by the end of twenty-first century. This could in turn help
to tackle the problem of food insecurity as this will increase cereal and food legume
52
production especially in the developing nations while playing a vital role in carbon
sequestration. Gorte (2009) conducted a study to analyze and evaluate different questions
regarding carbon sequestration in forests as part of report by United States Congress. The
report mainly focuses congressional interest in the carbon sequestration by the forests, a
review of how carbon is basically impounded by a variety of forests, role of forest carbon
in global climate change, accounting of carbon, effects of types of land use and
consequent leakage. The report concluded by focusing on programs currently operating at
the federal level and their role in forest carbon sequestration.
Balthazar et al. (2015) studied that land cover changes effects the provision of goods and
services of eco-systems. The study was conducted in Western Andean Range which has
higher population density with agriculture as a single source of income. Different
methods were used to show the similarities between the Photograph and satellite image.
For this first method was aerial photographer for which land cover data from 1942 to
2014 was taken and these images compare with spatial cover of landscape maps to check
its generalizability. Finally, Multi-homogeneous method was used which reduces
imprecision and dissimilarities between the images of photograph and satellite. Rapid
deforestation of native forests and increased agriculture resulted.
Rural people have higher reliant on their neighboring landscapes. Studies revealed that
rural people in West Java, Indonesia utilized many ecosystem services including
provisioning, variable, social, and supportive services. People‟s perception regarding
their use of ecosystem services was assessed. Extractive doings that encounters with
forest safeguarding, such as capturing birds to sell, quiet happens. It was not because
defendants did not observe the significance of biodiversity preservation, but because it
53
was providing them with direct financial support. They reportedly appreciated their
neighboring forest in providing multiple services. Future conservation strategies should
include means of earning income for the rural people by development of agro forests as
barriers around forests and economic use of the trees and shrubs. (Muhamad et al., 2014).
Silva et al. (2014) showed the economic benefits from a variety of ecosystem services
provided by sea side wetland territories in Steart Peninsula Somerset, UK. Ecosystems
containing both biodiversity and abiotic elements deliver a varied variety of amenities
supporting human comfort. A valuation was carried out to assess marginal changes in the
ecosystem services using coastal management project. This required utilizing seawater in
flooded areas to defending farmland. Several research gaps were identified for valuing
ecosystem services.
Mountain ecosystems deliver a range ES for instance the provisioning wood and food,
natural danger defense, habitation variety and social services. It was predicted that
changing climate in these marginalized region will have three kinds of impacts including
direct biophysical impacts, land use impacts and socio-economic impacts. The study was
carried out in southern Switzerland using an integrated ecological and economic
modeling. Results indicated that there will be higher impact of climate change on
provision of ecosystem services than land use change. Land use change will have its
impacts on higher elevations. Simulation study suggested a policy consideration for
economic condition in mountain regions (Briner et al. 2013).
Forsius et al. (2013) synthesized results from a big Finland project conducted by Long
term ecological research network. Integrated methods were used including remote
sensing, impact scenarios analysis, laboratory experiments and dynamic modeling. These
54
models would estimate ecosystem services at scales linking to social, economic and
political schemes. Climate change was projected to have positive and negative effects on
ecosystem services, the rotation period exploiting yield in forestry was expected to
decline, and opportunities may introduce crops new to the area or increase farming of
currently minor crops. Climate change was predicted to pose a key warning to numerous
threatened and valuable species, water and air quality, and sight-seeing services reliant on
current climate conditions. As a result, adaptation policies were scheduled nationwide,
although most of the definite adaptation processes are directed at the local scale by
specific farmers, private initiatives and societies.
Shaheen et al. (2017) conducted the study in Neelum Valley, Pakistan in order to
evaluation the ecosystem services and overall vegetation structure of the present study
site. The study methodology involved a questionnaire based survey regarding the
assessment of ecosystem services provided by the forest choosing five different sites. The
questionnaire was based on important factors like size of the families, threats to the forest
services and concerned conservation practices, amount of fuel wood used, medicinal and
edible species offered by the forests etc. A weight survey method was also used in order
to measure the consumption of fuel wood. Results of the study suggested that the forests
were very beneficial for the local communities in terms of provision of mushrooms for
sale and as source of food, fodder for animals, medicinal plants for treating and curing
diseases and fresh vegetables for consumption. The study concludes that due to excessive
utilization of forest resources, the local forest has been found to be degrading. The study
calls for effective conservation strategies and sustainable use of forest services in order to
protect this precious natural reserve.
55
2.9 Research gaps identified from the survey of literature
There is now a global acceptance that the changing climate is evident and unavoidable
(Stern, 2007; IPCC 2007). The fifth assessment report of Intergovernmental panel on
climate change (IPCC) states that the climate change is one of the biggest challenges of
the 21st century that will bring about unexpected extreme events throughout the world
ranging from polar regions to the tropics, islands, rich as well poor countries (IPCC,
2014). Impacts of climate change and variability are increasing over the past years. A
number of events are happening simultaneously, including an increase in average
temperature and erratic pattern of precipitation; increase in both frequency and intensity
of extreme weather events; melting of glaciers and snow; and sea level rise (Sam et al.,
2017; Zhang et al., 2018).
In particular, South Asia is the home of one fourth of the world‟s population and the
Hindu Kush Himalayas (HKH) is the most critical region where melting of the glaciers
will extremely influence water supplies and the livelihood change in few next decades
(Shrestha et al., 2015; Gerlitz et al., 2016). With ever increasing population coupled with
poverty, natural resource dependence and degradation; this region is highly vulnerable to
climate change and resulting natural disasters (Tewari, 2010; Ullah et al., 2017). The
region has already experienced warming above than global averages, which is responsible
for cascading environmental impacts (Elalem et al., 2015). Mountains are the hotspots of
climate and land use change (Sharma et al., 2013). Land use changes are intricate which
arises due to modifications of land conversation process (Lambin, and Geist, 2001).
These changes have potential impacts on biophysical, social and human dimensions in
any area (Veldkamp and Verburg, 2004). There is still inadequate research in Pakistan on
56
how the changing climate will affect the livelihood of people who mostly depend on one
or more ecological units those are forest ecosystem, agricultural ecosystem etc. in
addition vulnerability analysis of these communities is another weaker side of the country
where each community has adapted different adaptive safeties to cope with changing
environment.
Climate change vulnerability analysis for forest ecosystem was done to increase the
scientific understanding of how climate affects life of people who rely on this valuable
resource (forest) and how communities adapt and mitigate to changing climate and
manage their livelihood. Pakistan is a hazard prone country and hard hit by different
disasters. There are key gaps in country‟s preparedness plans and adaptation strategies.
There should be education and awareness among vulnerable communities of Pakistan to
reduce and mitigate negative impacts of disasters and enhancing their resilience.
Therefore it was identified that such studies are need of time and can be fundamental to
manage and adapt the future change.
57
Material and Methods
The climate change vulnerability analysis in the livelihood of locals and ecosystem based
assessment were studied using mixed methods approach. The mixed method approach
combines quantitative and qualitative data to develop description and subjective
measures. The study has used interpretive paradigm as an important tool of studying
social part of study (anthropology) (Gentle et al., 2014). The pragmatist approach has
used tools and frameworks to assess the nexus of socio-ecological system. Details of
approach used are shown in the Table-1.
Study area
Khyber PukhtunKhawa (KPK) is one the important province of Pakistan having seven
major divisions with 25 Districts. District Mansehra comes under Hazara Division with
five tehsils. Tehsil Balakot is biggest among others and is a mountainous area with an
average elevation of 900 m. The multi-hazard scenario of the region makes it a
significant area of disaster risk research and climate vulnerability analysis (Baig, 2006).
Balakot Tehsil of District Mansehra has fifteen (15) UCs and total population of 273,089
distributed in 45,659 households which is characterized as totally rural (Pakistan Bureau
of Statistics, Population Census 2017). It spreads over an area of 800 square kilometer.
58
Table- 1 Study Framework and methods used
Study
System
Research
paradigm
Framework Used
in study
Tools used Level of data
collection
Data
analysis
Society
(Local
People)
Mixed
methods
approach
based on
quantitative
and
qualitative
data
Wellbeing
ranking
Participatory
rural
appraisal:
Vulnerability
Capacity
Assessment
Livelihood
Vulnerability
Index
Household
surveys
Participants
observation
Focus group
discussions
In-depth
interviews
Households
/Community
Govt. official
/Representatives
from forest and
agriculture dept.
SPSS
NVIVO
Ecosystem
associated
Biophysical
parameters
Forest
service‟s
assessment
based on
climate
change
vulnerability
land use
mapping
Climatic data
Field surveys
of Balakot
forest
Focus group
discussions and
interviews
GIS and RS
for Land use
analysis
Pakistan
Meteorological
Department
Households
/Community
Forest GPS
points along
with trees and
soil data
SPSS
ARCGIS
59
Study population and sample size
At 95% confidence level and ± 10 intervals, a minimum sample size of 96 households
was needed. A total of 200 households from four villages were surveyed using a
systematic sampling technique in areas having more settlements and population density
(Table-2). Under each union council, there was a patwar circle and many villages. Urdu
was used as the language of interview during the survey which had been broadly spoken
in the local community. The selection of the villages was done on the basis of presence of
appropriate settlements and their close proximity to the forested land and water bodies.
Participatory and qualitative research methods such as focus group discussions (n=10),
interviews of households (n=200) and other representatives (n=23) were done to gather
data across the study area. To conduct VCA, open -ended questionnaires were designed
which has sections as basic information of respondents/household, resource profiling,
livelihood and seasonal mapping, institutional information and coping strategies. VCA
helped in assessing the vulnerability status of community.
Details of research methodology followed are shown in Figure-5.
60
Table 2 Sampling Design for Study Population
Province
KPK Division
District
Mansehra
Tehsil
Balakot
Union
Councils Villages Households
7
Divisions
25
Districts
71 Tehsils
Hazara
5 Tehsils
Balakot
Baffa Pakhal
Darband
Mansehra
Oghi
15
4
Kawai
Paras
Balakot
Tarrana
200
Source: Pakistan Bureau of Statistics, Population Census 2017
61
Figure-5 Main steps followed for execution of research work
62
3.1 Community ranking based on wellbeing status: A participatory approach of
community livelihood based on their wellbeing status was used developed by Pakistan
Participatory Poverty Assessment to assess the level of relative wealth and poverty
among the locals (PPPA, 2003). It was carried out to rank the community on set criteria
of wealth and poverty. These basic of population characteristics were inquired to
categorize the sampled population into a wellbeing group. Respondents were asked about
their landownership, as owing a land in this area was considered symbol of richness and
stability. Further they were asked about the status of school attending children. Food
access and its availability in their household were also inquired. Local people were asked
about their health status in terms of chronic (more than 3 months) and acute illness (a
week or more); further migration pattern was also inquired.
From the data obtained, local people were categorized in four wellbeing groups, namely
well-off, better off, poor and very poor population. Scholars mostly used well-being
categorization based on socio-economic status for empirical validity (Richards et al.,
2003; Sharma 2010; Gentle and Maraseni 2012; Gentle et al., 2014). Major indicators
have been identified to develop community strata as shown in Table-3.
63
Table- 3 Criteria indicator for well-being characterization of community
Major Criteria
Indicators
Wellbeing status of local community
Well-off Better-off Poor Very poor
Education Children are attending
private schools
Children are attending
public/private schools
Children are attending
public schools only
Children are involved in
labour
Land ownership Owners of large fertile
lands
Owners of small land No irrigated land/
working as wage labour
No irrigated land/
working as wage labour
Food production
and sufficiency
Sufficient food through
out the year/ storage for
six months
Food available and storage
for three months
Have to buy food from
markets/ no storage of
grains
Have to buy food from
markets/ no storage of
grains
Money landing
and loaning
Money lenders in
community
Money lenders in few
cases
Loan takers Heavy loans taken
64
3.2 Vulnerability capacity assessment of indigenous community
The study included combination of different participatory and qualitative techniques to
gather data from stakeholders; local people as community representatives, people of
NGOs, and government organizations. Informant‟s observations were recorded using
technique of participatory rural appraisal (PRA) (Joshi et al., 2017). Vulnerability
Capacity Assessments (VCA) is a PRA technique used in current study which involved
community risk profiling through transect walks, focus group discussions (community
ranking of hazard severity, seasonal calendar, livelihood seasonal monitoring calendar,
venn diagram), and individual semi-structured interviews to assess multiple stressors of
local people (Aalst et al., 2008; Macchi 2011). Tool used to conduct VCA in Tehsil
Balakot is attached in Annexure- 3 and Short description of each of this method is given
in Annexure-4.
A transect walk was conducted in the Balakot mountainous community to assess the
distribution and location of resources and the landscape. It provided the clear picture of
the main land use type, vegetation, soil type, daily water source, sanitation system,
housing condition, etc. It was carried out by dividing the total area in small segments
across river Kunhar and on slopes of the mountains. The information gathered during the
walk was noted on the paper sheets and photography was done to keep a record. Focus
group discussions (FGDs) were done with people of Tehsil Balakot considering different
age groups and gender. Semi-structured questionnaire and interviews were carried out to
conduct each discussion comprising of twelve people. Small sample size is preferable in
conducting good FGDs (Babbie 2009). It was tried to include different people in the
context of their age, gender, religion, ethnicity and caste (USAID 2010). Most of the
65
FDGs were organized in houses of laborer councilors while few were in nearby small rest
houses; community representatives were asked to bring their neighbors and others for a
group session. Total ten FDGs were conducted comprising 118 people, 65 females and 53
were males. Two people couldn‟t participate in one FDG due to some illness. It was
asked from the respondents to identify the major seasonal events in a year which had
significant influence on their livelihood. Local people then marked the period of a year
(months) which have disturbed their lives in last 10/20 years. They were inquired about
the rainy season and the dry season like: Is it prolonged, shorter or any change observed?
Similarly, questions about water quantity and quality were asked. The local men and
women were asked about the natural resources of the area upon which their daily life
activities depend on. The status of resource availability and seasonal changes were asked
to assess the resources present in the past but no longer existed anymore. New resources
were inquired which they have adopted to combat seasonal changes in the area.
Community mobility was inquired on the basis of their movement from Balakot Tehsil to
main District Mansehra/ Abbotabad City or international migration for better livelihood.
In another activity, community people were asked to rank hazard severity which has
impacted their livelihood over time, ranking varies from 0 to 5 i-e 5 indicating highest
hazard. Role of local institutions was also inquired. People were asked about
organizations and stakeholders working to support their day-to-day life issues. Men and
women were asked separately about the group or people who support and guided them in
the decisions about their livelihood activities, like agriculture, forestry, animal husbandry,
landslides, unpredictable rainfall. Based on identified changes, each of the household
representatives was asked about coping strategies to these changes in their region. On the
66
basis of hazards faced by the community, people described the ways of coping with stress
of limited food and water. The last step was to define “vulnerability status of social
groups” on the basis of livelihood options available in the area. During the FGDs,
community people were able to plot a seasonal calendar, a livelihood monitoring
calendar, hazard severity mapping as well a venn diagram of the effective organizations
working in tehsil.
3.3 Livelihood vulnerability quantification: For further quantification of livelihood
vulnerability from climatic and other hazards in the study area, an index (Livelihood
Vulnerability Index) was used. This concept of vulnerability assessment using an index
was taken from the basic definition of vulnerability given by IPCC. Two approaches
were used; LVI and LVI-IPCC. The Livelihood Vulnerability Index was established on
the descriptive information generated by the field survey which was based on 37
subcomponents. These sub components were coupled into eight major components and
three factors of vulnerability in both UCs (Table-4).
67
Figure-6 Map of study area Tehsil Balakot indicating two Union Councils for LVI
analysis
68
Table-4 Major Components and Sub-Components of LVI
Vulnerability
factors
Major Component/ Sub Components
Units Explanation and the
surveyed questions
Adaptive capacity 1. Socio-Demographic Profile
Dependency ratio per house
Households with a head who is female
Households having access to radio, telephone or television
Head of household never joined any school/college etc.
Ratio
Average
Percentage
Percentage
This section consists of four
questions inquiring
households‟ characteristics.
2. Livelihood Strategies
Any member of household working outside the Tehsil for
spontaneous work
Any family member involved in local tourism for their
livelihood
Household depend upon fishing and hunting for their daily
life
Crop cultivation as a main source of income
Agricultural livelihood diversification in a household
Household having livelihood without any contribution of
crops cultivation
Household having no direct water supple facilities to
produce crops
Percentage
Percentage
Percentage
Percentage
1/no. of
livelihood
opportunities
Percentage
Percentage
This section consisted of 7
questions which deals with
the pattern of livelihood each
family adopt; respondents
were asked about their
dependence on the natural
resources of their area; forest
agriculture fisheries etc.
3. Social Networks
Household having social support in terms of getting and
providing help
Family members in household can borrow money from a
Ratio
Ratio
This section consists of 4
questions which helped in
assessing data of their social
69
certain social group
Is there any private money lender in your community to
borrow money from?
Have you or any family member in household has ever
seek help from any government office (last 12 months)?
Percentage
Percentage
networking where they look
for help in their daily chores
from family friends and their
Union Council
Representative.
Sensitivity 4. Health Status of Individuals in HH
Average time to reach basic health facility near home
Affordability of basic health services
Household with members having chronic illness
Individuals in a HH missed the school/job due to sickness
Households having toilet in use
HH having wood to cook and other purposes
Min
Percentage
Percentage
Percentage
Percentage
Percentage
This section consists of 6
questions which intended to
assess the availability of
health facility near their
place of residence;
occurrence of illnesses and
absentee from work or
school due to illness.
5. Food related Issues
Food sufficiency (household has food storage for six
months)
Average crop diversity
Household dependency on fishing/hunting for food
Household saving seeds for future
Percentage
1/no. of crops
Percentage
Percentage
This section consists of 4
questions which inquired
about the availability of
sufficient food, types of
crops they grow, saving of
crops and seeds for next
growing season etc.
6. Water Related Issues
70
Dependency of household on natural water sources
Average days without water supply per month in a
household
Household without a water piped water
Consistency of drinking water supply
Percentage
No. of days
Percentage
Percentage
This section consists of 5
questions which helped to
evaluate the availability of
water, its source and mode
of storage.
Exposure 7. Natural Disasters
Number of hazards/natural disasters faced in the last 5
years
Family members didn‟t get any warning of natural
disasters
Death/Injury in your household due to natural disaster
Damage to physical properties and loss of agriculture land
as a consequence of natural disasters
Range/count
(0-5)
Percentage
Percentage
Percentage
This section consists of 4
questions which dealt with
gathering information
regarding the incidence of
different disasters and
associated loses
8. Climatic Variability
Mean standard deviation of monthly average of average
maximum daily temperature
Mean standard deviation of monthly average of average
minimum daily temperature
Mean standard deviation of monthly average precipitation
Celsius
Celsius
Millimeters
This section consists of three
questions which were taken
from Pakistan
Meteorological Dept. This
data is based on 30 years
analysis ranging from 1988
to 2017.
71
3.3.1 Approach I: LVI
The eight components were inquired based on field survey questions as described in
Table-3.4. The eight components calculated at household level were socio-
demographic profile (SDP), livelihood strategies (LS), social network (SN), health
(H), food (F), water (W), natural disaster (ND) and climatic variability (CV). These
components were inquired using 37 sub-components.
Each major component of LVI was measured through four steps;
1. Compute the questionnaire data of sub-component and transform into percentage,
ratio and index.
2. Unit standardization of all transformed data of each sub-component was done. This
was carried out for balancing the weights based on Sullivan et al., 2002.
3. Calculate the average of each standardized score to get the final value for each
main component.
4. Last step involves the weighted averages of all major components to obtain the LVI
value.
This procedure confirms the equal contribution of main components to generate the
overall LVI. The scale of LVI calculated from this approach ranges from 0
(minimum) to 0.5 (maximum) as described by Hahn et al., 2009.
The formula followed is as:
– Equation (1)
Where, sS= original sub-component for each of the site,
smin= minimum value for each sub-component
smax = maximum value for each sub-component.
72
After obtaining values of sub-components, average of each sub-component was
calculated using the following formula:
∑ index
ni 1
Equation (2)
Where, MS = one of the eight major components for study site
index = subcomponent, n = number of subcomponents in each major component.
The above values were calculated for each of the eight components and LVI was
calculated using the formula mentioned below:
∑
∑
⁄ Equation (3)
This can also be written as:
Equation (4)
Whereas SDP represent socio-demographic profile for each UC, LS is livelihood
strategies, SN is social networking, H is for health, W for water, CV is climatic
variability and ND is natural disasters.
3.3.2 Approach (II): LVI-IPCC
An alternative method of livelihood vulnerability based on IPCC definition was also
used. It is organization of livelihood components calculated in first approach into the
LVI-IPCC framework. According to the framework, exposure represented by “e” is
ranking of exposure to any natural hazards/disaster which local community has faced
in last 5 years. Whereas “s” is for sensitivity and “a” is for adaptive capacity
measured for household. For the calculation of LVI based on IPCC framework, same
73
data is used but entails grouping the eight main components into adaptive capacity,
exposure and sensitivity as described in Figure-7. The LVI-IPCC scale ranges from -1
(minimum) to +1 (maximum).
( ) Equation (5)
Figure-7 LVI-IPCC framework based on the definition of vulnerability
3.4 Climate Data and it analysis for change detection:
In addition to the field surveys, last 30 years meteorological data of temperature and
precipitation (1988-2017) was taken from the Balakot station of the Pakistan
Meteorological Department, Govt. of Pakistan. The Balakot station (34o 23‟ N;
73o 21‟ E) is 995.40 m high and established in 1957. This station represents climatic
data of Tehsil Balakot (Pakistan Meteorological Department, 2017). It was used to
relate the field observations with temporal and spatial variations in temperature and
rainfall pattern, which validate the study data (Gentle and Maraseni 2012; Boissiere et
al., 2013). The climate data was used to get a picture of mean annual temperature and
LVI-IPCC
Climate Vulnerability
EXPOSURE
Natural Disasters
Climatic Variability
SENSITIVITY
Health
Food
Water
ADAPTIVE CAPACITY
Socio-demographic
Livilihood Startegies
Social Networks
74
precipitation differences of last 30 years. Regression trend analysis was carried out on
the data of mean minimum and mean maximum temperatures and precipitation data to
develop a straightforward view of change in a numeral figure. In addition
precipitation data was divided into mean winter and mean summer periods, further
mean summer period was taken as pre-monsoon, post-monsoon and mid-monsoon
periods. The decadal analysis was done to know the change in rainfall pattern.
3.5 Ecosystem services assessment in context of climate based vulnerability:
The ecosystem services mapped in the study area were categorized according to the
Millennium Ecosystem Services (MEA, 2005). To gather data on provisionary,
regulatory and cultural services of forest to local community, a questionnaire was
used in face to face interview as well as focus group discussions were conducted
while to estimate carbon stock of the forest, field surveys were carried out into the
forested area (Martinez-Harms and Balvanera, 2012.). Five sites were randomly
chosen from the Tehsil depending upon the observation of forest degradation by the
local community. Methods of Forest service‟s assessment are given in Table-5.
75
Table 5 Ecosystem services measured and valued in study area
Ecosystem services mapped Data input method Change in provision of
services
Provisionary
Fuel wood
Fiber/food
Fodder to livestock
Fresh water
Focus group
discussion\
Questionnaire
Interviews with Key
informants
Focus group discussion
Household survey
Regulatory
Climate regulation (Carbon
sequestration)
Water Purification
Protection from natural
hazards
Aboveground/
Belowground
biomass
Questionnaire based
survey
Cultural
Educational value
Sense of peace
Recreational/ecotourism
Spiritual and religious value
Focus group
discussion\
Questionnaire based
survey
76
Provisionary services: Using focus group discussion and interviews through the
questionnaire, local people were asked to value their forest services as high, medium
and low. They were further inquired about of fuel wood consumption, and collection
pattern, fiber/food, fodder to livestock and fresh water availability. They were asked
about their family size and size of their grazing herds (Butt, 2006; Raymond et al.,
2009; Acharya et al., 2011).
Regulatory services: Local people were inquired about the roles of forest for
protecting the community and their assets from natural hazards, and in purifying
water for use. They were asked about the role of trees in cooling their surroundings.
Cultural services: The role of local forest in providing peace, harmony, and
education was asked. It was also inquired to assess the value of tourism associated
with nature. Cultural benefits are mostly intangible which make them difficult to
valuate.
Change in delivery of services: In the survey, considering the on-going process of
forest degradation, locals were asked about change in delivery of forest goods and
services from last 10-20 years. It was made sure that respondents for this part of study
must be living in the area from last 20 years (Shedayi et al., 2016). The change in
delivery was measured as “positive” which indicate the goods and service has
increased, “negative” means it is decreased and “none” refers to no effect in the stated
period of time.
3.5.1 Climate regulation by carbon sequestration: To estimate the carbon stock, a
non-destructive method was used in which height and diameter at the breast height of
an individual tree was measured in field. The selection of five forest sites was made
77
on the basis of community utilization and access of local people to the mountain
forest. From each site, 10 quadrates of 25m*25m were taken, making a total area of
625 m2. The quadrats were selected randomly throughout the study area to have
representative forest and species mass. Similarly, from each site soil samples were
taken from two depths: surface at 0 cm and sub-surface about 20cm deep. It was done
as most of sites were rocky conditions below 20 cm. The height and diameter at breast
height (DBH, 1.37 m from ground) of all the trees were measured in sampling
quadrats following standard techniques (Ahmed and Shaukat, 2012). For each site;
latitude, longitude and altitude were noted using GPS (Garmin, Rino-130),
Anthropogenic burden on forest was observed through grazing, deforestation and
distance from their settlements.
To estimate Aboveground biomass (AGB) of an individual tree following the
allometric equation was used: AGB (kg) = tree volume (m3) * wood density (kg/m3)
Whereas Tree volume was calculated as follow: V= π r2H; π = 3.14; radius was taken
from diameter of tree; and wood density of species was taken from the world
agroforestry database (Cheng 1992.)
For pinus specie (Shaheen et al., 2016), aboveground total biomass was calculated as:
AGTB 0.0509 × ρD²H wh\ere, AGTB is in kg; wood specific gravity (ρ) in g cm³;
tree diameter at breast height (D) in cm; and tree height (H) in m.
For estimation of below ground biomass (BGB), aboveground biomass was multiplied
by factor of 0.26 as the root to shoot ratio: BGB (kg/tree) = AGB (kg/tree or ton/tree)
* 0.26
Total Tree biomass was calculated using following relation:
TB = Aboveground tree biomass + Belowground tree biomass,
78
Whereas it is provided that total carbon is half of the total biomass in a tree (IPCC,
2007), therefore carbon stock calculated from Biomass is equal to the Total
Biomass/2 or Total Biomass*0.5
Soil Carbon: Soil samples were tested for their carbon content by Walkley Black wet
oxidation Method. Soil organic matter was calculated by using soil bulk density,
organic carbon and depth of collected soil. Soil bulk density was measured by oven
dried weight of soil divided by the volume of cylinder (Nizami et al., 2009). The
measured amount of carbon was transformed into soil organic carbon by using
following relation: SOC (t/ha) = OC (Mg/Kg) * Bulk Density (g/cm3) *soil depth
(cm).
3.5.2 Vulnerability assessment of Forest to the climate change: Vulnerability
assessment of the forest was carried out on the basis of people‟s perception of
exposure and sensitivity to climate and other socio-economic changes (Boon and
Ahenkan, 2011; Bhatta et al., 2015). Local forest of Tehsil Balakot was exposed to
climatic changes and as a result the delivery of forest goods and services to local
people was changed in comparison of last 20 years. Keeping this view-point, people‟s
perception was inquired for the change in delivery of any forest service which will be
forest susceptibility for future provision of services. A theoretical framework of study
was developed to indicate vulnerability of local forest due to climate change by
posing potential change in the livelihood and well-being of the community.
79
3.6 Land use mapping through GIS and remote sensing
Land use maps were generated for the Tehsil to plot the change over a span of years.
Remote sensed data of Landsat 5 and Landsat 7 were taken with path 150 and row 36.
Images of 1990, 1995, 2000, 2005, 2010 and 2015 were taken for determining the
variability. Landsat 7 Enhanced thematic Mapper Plus (ETM+) and Landsat 5
Thematic Mapper (TM) were used from United State Geological Survey (USGS). The
interpretation was done using Erdas imagine software through supervised maximum
likelihood classification, also used Google Earth Engine and ArcGIS for further
processing on classified raster. Final output maps were designed and developed using
ArcGIS 10.5. Six major classes of land use were described and shown in Table-6. .
Changes in time periods were calculated for each land use class between a final year
V2 and an initial year, V1.
( | ) Equation (6)
80
Table-6 Land Use Classification in Tehsil Balakot
Land use Classes Description in study area
Forest All type of forests where trees growing in patches and
canopies
Settlement Continuous and discontinuous impervious layers and
aggregated buildings of all kinds where people living
Vegetation
(Agriculture)
Regularly ploughed land for irrigated crops or growing rain-
fed crops
Barren Land Land with eroded soil and top surface soil with no vegetation
and no settlements
Ice & Snow Area covered with ice and snow continuously or for a part of
time in a year
Water Bodies Water courses like rivers and streams, lakes and ponds
3.7 Data Analysis
All the data assembled was processed using SPSS version 21, frequencies, percentage
responses and descriptive maps were generated. The respective formula sheets were
prepared for applying all methods using MS Excel where needed. Maps of study area
and land use were furnished using ArcGIS.
81
4-RESULTS
Topographically Balakot is a highly vulnerable region as was badly destroyed in the
earthquake of 2005 (UNDP 2007). The community was living on the mountain slopes
along the River Kunhar where top of the mountains were covered with pine trees and
the slopes were mostly bare having unstable housing structures. It was observed in the
community living close to forested mountains and river kunhar that overall they were
facing negative effects on the resources, their availability, quality and quantity. Major
contribution to change was because of climatic and non-climatic matters. Social and
economic stresses in people were increased after the deadly earthquake of 2005 which
has devastated their agriculture land, forest area, livestock, etc. The technique of
participatory rural appraisal in form of vulnerability capacity assessment helped in
analyzing the situation of the local mountainous community. All focus group
discussions highlighted that the local people were living in a marginalized area with
dependence on fishing, forest and agriculture resources for their livelihood. Statistical
analyses representing the percentage and frequency response of VCA are shown in
Annexure-5 while glimpses of field survey during data collection are shown in
Annexure-6.
82
4.1. Livelihood trend and wellbeing status of the study population
The survey of the Balakot area resulted in categorizing the community according to
their wellbeing status using a semi-structured questionnaire (Table-7). The data of the
well-being was compiled to assess overall differential vulnerabilities and adaptation
practices based on livelihood in the study area. Out of the total household surveyed,
9% (n=18) were categorized as well off, 27% (n=54) were better off, 30% (n=60)
were poor while 34% (n=68) were very poor population. It was witnessed that
“ownership of land” was a main criterion of wealth in the community. Mostly poor
households had limited irrigated lands and less food production. In most cases, no or
less food production was a duple burden of buying food from local markets. The
vulnerability due to the climatic changes was observed as threating their agriculture
and resulting in producing more natural disasters. According to local people‟s
perspective; changing climate is threating their land which is their main asset. The
climate threat was common among all wealth groups. In terms of education, the
household with better education had better options of income diversification. In most
well-off population, their girls were studying in universities in main towns. On the
contrary, children were taken as helping hands in income generation in the poor
families. The mountain forest is a source of livelihood in many ways as reported by
the community; livestock grazing on the slopes and collection and selling of fuel
wood and non-timber forest products. In terms of migration pattern, well off families
had someone working abroad or in urban areas of Abbotabad KPK, while better off
households had seasonal migration to main District Mansehra. Most of poor families
reported seasonal migration for wage labor in mid summers due to higher tourism in
this region. However, health conditions were reportedly poor among the impoverished
83
community; poor households had one or two persons having chronic illness (more
than three months) at home along with impure water available.
84
Table-7 Wellbeing characteristics of study population indicating different social groups
Indicators of
wellbeing
Well-Being Category
Well off Population Better off Population Poor Population Very Poor Population
Education
Children were studying in
private schools and colleges/
Girls are studying in Hazara
University
Children were in private and
public schools Only in public schools
Children were involved in
labor with elders
Employment
(Income source)
More than one person in home
had jobs or doing business/
Lending money to others as
loan
Doing adhoc jobs in Mansehra
Districts/ working in guest
houses for more than two years
Labor on daily wages Unemployed/ Involved in
labor in some cases
Land
(residential/comm
ercial)
Own land of houses/ large
irrigated land available /
owners of the guest houses
Own house and small irrigated
available in few cases/ kitchen
gardening is very common
Rented houses/huts mostly
/a small part of land
No land for house/ Living
in temporary huts
85
Indicators of
wellbeing
Well-Being Category
Well off Population Better off Population Poor Population Very Poor Population
Health status
Healthy individuals mostly/
have a filtered drinking water
source in house
Better individuals with some
acute illnesses / drinking source
in house available
Collect water from an
away source/ One family
member at least diseased
Collect water from a
faraway source/ Chronic
illness- more than two
individuals diseased
Migration pattern
One or more individual is
working in abroad (outside
Pakistan)
Domestic migration mostly for
a week or less (jobs in
Mansehra District)
Domestic migration for
wage labor N/A
Dependence on
natural
resources
No collection of firewood
usually have gas cylinders/
big size herds grazed by wage
laborer
Collection of firewood on
weekly basis/ a medium sized
herd
Collection and selling of
firewood and grazing of
small herd
Collection and selling of
firewood and grazing of
rented livestock on daily
basis
86
4.2. Changing climate and Livelihood impacts
4.2.1. Livelihood mapping: There was significant interest by the local people in
mapping their seasonal and livelihood calendar. Water shortage was reported as a
main factor affecting agricultural production by 90% of the respondents. During
FGD‟s, people reported food shortages during months of heavy rain. Maximum
livestock and crop diseases were reported in the months of July and August. July was
considered as the most vulnerable month to the agricultural productivity and
availability of forest products due to heavy rains and floods sometimes. This fact was
validated by meteorological data for the month of July which showed an average of
320 mm rainfall during 30 years period (Figure-13). There were four main livelihood
prospects recognized in the area: forest, agriculture production, fishing and nature
based tourism (Table-7). The data showed that only 5.5% households had their own
business, 11% were doing jobs in the main district; 19.5% respondents were involved
in tourism based work, and 44% households had one or two individuals involved in
agriculture. Most of the farmer‟s families reported maximum agriculture loss in year
2010 due to intense rainfall resulting in floods and landslides. The reported impacts
were also linked with decreasing drinking water in the wells and loss of irrigation
water (Arias et al., 2016). Similarly, loss in the forest cover, the reduced availability
of Non Timber Forest Products, and less grazing land was also reported by the locals
due to rapid deforestation and increase in human habitation (Table-8). Few
households had big herds of livestock; the rest had small numbers which used to graze
in forested land. Trees of Pinus roxburghii were famous for fuel wood collection and
a reduced number of the common chir pine was also reported during interviews with
locals. Mostly, women and young girls along with their mothers (77% households)
used to collect the wood from the forest on the daily basis or weekly basis. This
87
collection got increase in winter season because of the lower temperature and need of
fire in houses to warm the surrounding. Agricultural activities were the main source of
income which provides life support to the rural community; overall 20% of
households were owners of agricultural land, 31% had rented land for cultivation and
72% were worked as laborer (Table-8). Approximately in all households, sowing and
harvesting of seasonal vegetables were done by females. Only houses which had more
production than their own needs were selling their products in the local market; only
11% of households had food storage for the period of six months. Storage of food for
six months was identified as a coping practice to avoid natural hazards and food
shortages. As reported by the locals, landslides were common after heavy rainfall in
the region which further aggravated the situation. Wage labor was a common practice
in poor families; mostly men (72%) were involved in farm activities; seasonal labor
was offered to work on riverside huts constructed for tourists.
88
Table-8 Seasonal and Livelihood Monitoring Calendar of Local Community
Activity Jan Feb Mar Apr May June July Aug Sep Oct Nov Dec
Seasonal hazards identified (The number of * shows intensity of an event)
Rainfall/ Hailstorm * * * ** *** *** * **
Dry period * * *
Flood ** *
Landslides * * ** * * *
Human disease * ** ** *
Food shortage/ quality effected * * *
Water shortage/ quality effected * * * *
Livestock pest/disease * **
Crop pest/ disease * * ** *
Livelihood opportunities mapped on the annual basis
Wheat W w h/s* h/s* p w w
Rice p p w w h/s*
Maize p p w w h/s*
Tomato/potato etc.
89
Walnuts s s c s s
Peach / pear/
plum/ Apples/ etc.
Fodder c c c c c c c c c c c c
Firewood c c c c c c c c c c c c
Livestock grazing
Non-timber Forest Products
(NTFP)
c/s c/s c/s c/s c/s c/s c/s c/s c/s c/s c/s c/s
Fishing c/s c/s c/s c/s c/s c/s c/s c/s c/s c/s c/s c/s
Meat/Butter/ Wool
Milk
Tourism
Running cottages/ lodges
Tourist guiding,
pottering/drivers etc.
Migration
International
National/Domestic/Local
Key to Table: c - collecting; h - harvesting; p - planting; w – weeding, s – selling; s* – selling in case only if
production is more than their own need.
90
4.2.2 Livelihood resources and Major hazards: It was witnessed from focus groups
discussions and questionnaires, that 88% of locals were relying on the natural
resources of their area for a livelihood. Almost 92.5% of households were getting fuel
wood from the surrounding forest to cook the food and heating homes. In addition to
this, collection and selling of NTFPs and the forest floor was used for rearing the
animals. It was reported that 93.5% of locals used medicinal plants for the treatment
of basic ailments; only 6.5% were depending on English medicines available in local
markets. During FGD, people were asked to map the hazards in their area (Figure-14).
Ranking of hazard severity was from 0 to 5, 0 for least and 5 for the highest severity.
Landslides and erratic rainfall ranked as a severe hazard measured by the community
(Figure-8a). Floods and wheat cultivation affected by unpredicted rainfall (ranked 4)
according to the local community.
4.2.3. Institutions: Institutional analysis of the Balakot community was done to
identify resource users, organizations and the stakeholders. A venn diagram was
prepared (Figure-8b) to identify different institutions of the Balakot Tehsil which
support and influence the decision making of local people. The role of each
stakeholder was identified by the community to be influential in making decisions for
their betterment. The people who lived inside the premises of Tehsil Balakot were
closely associated with community affairs, whereas others like armed forces and
representatives from the Non-governmental organization appeared to help locals at the
time of any crises or disasters. Most of the poor who participated in FGD had taken
loans to buy materials, education of children, food shortages, to cover illnesses and to
migrate to main cities and districts. Interfering spheres of different stakeholders
showed the common approach towards managing the lives of locals and providing
solutions to their problems (Hatt 2013). Community identified their representatives of
91
the union council as important decision makers whenever they needed. Balakot
Tableghi markaz was a group of senior local preachers who used to gather on a daily
basis to listen to the issues of their community. Money lenders were few (12%)
known rich families who have provided money as loan in the community. The tool
has provided a clear understanding of the organizational role which has helped people
in spending and managing their life.
92
Figure-8 Results of FGD shows (a) Mapping of hazard severity ranking of Balakot (b) Venn diagram of institution / stakeholders
marked influential by the community
93
4.2.4. Coping strategies in mitigating climate change: The FGD‟s identified the
coping mechanism of local community to mitigate the changing climate and better
livelihood options (Table-9). The poor respondents told that they were forced to
involve their children in wage labor than schooling due to low income; 46.5% of
children have never visited the school or either left in early childhood. Children
(14.5%) of well-off families were getting education in private schools. It was
observed that well-off groups were people who had many alternatives available than
poor or very poor people. A lot of land has been converted into cultivated field area
near houses particularly, 88% respondents said that cropping pattern and techniques
have changed over time due to change in temperature and rainfall pattern. However,
75% respondents claimed that forest cover and availability of NTFPs has also
reduced. A clear decline in forest area was due to increase in agricultural activities
which demand higher removal of trees. Food storage was a coping practice during
winter times; only 5.5% households were now able to store food for six months. The
assessed impacts in most households were decreased production of seasonal and
annual crops, reduced firewood, non-availability of NTFPs and change in rainfall
pattern. The poor households had difficulties with their day-to-day livelihood
activities whereas well-off and better off families had plans for a longer time period.
94
Table -9 Coping strategies of locals in changing climate and their vulnerability status according to their well-being
Observed Changes Wellbeing
Groups Livelihood Effects Coping Mechanisms
Vulnerability status
based on livelihood
strategies
Erratic rainfall
Variation in
temperature
Change in forest cover
and reduction in NTFP
collection and selling
Reduction in the water
quantity and water
sources
Drying of grazing land
and reduced herds
More landslides and
floods
Well-off
Decreased production of wheat,
rice and maize (selling capacity
was influenced); Decreased
number of livestock (goats,
sheep, etc.)
Cropping pattern has changed; learning new
agriculture techniques to increase productivity;
new cropping varieties, storage of food items,
i.e. rice, grains, etc. buying and selling land,
money lenders of community, livelihood
diversified.
Least Vulnerable in
Changing Climate
Better-off
Decreased production of wheat
and maize crops; seasonal
vegetables had lesser production
too; Decreased number of
livestock (goats, sheep etc.)
Storage of few food items, changing cropping
patterns, introducing other crop varieties, part of
social groups, especially from forest dept. and
tableghi markaz. Community has started small
scale agriculture outside their homes. Learning
the better options of livelihood diversification
Less Vulnerable to
Climate Change
95
Observed Changes Wellbeing
Groups Livelihood Effects Coping Mechanisms
Vulnerability status
based on livelihood
strategies
Erratic rainfall
Variation in
temperature
Change in forest cover
and reduction in NTFP
collection and selling
Reduction in the water
quantity and water
sources
Drying of grazing land
and reduced herds
More landslides and
floods
Poor
Limited production seasonal
crops; Limited livestock to graze
on payment, scarcity of
resources i.e. fuel wood, NTFP,
water quantity and quality etc.
No storage of food items, cropping pattern is
changing if land available, selling labor in
Mansehra, selling their livestock and land,
children involved in labor, reduced tourism in
the area resulting in less labor; poor access to
community groups and unable to influence
decision making.
More Vulnerable to
Climate Change
Very poor
Wage labor and sources of water
were reduced, less fuel wood
was available than previous
years; under debts
Most Vulnerable to
Climate Change
96
4.2.5. Perceptions of the local community on climate change in the region
A detailed analysis was done to assess the observations of community for climate change
and its adaptation. Percentage and frequency of questions inquired is presented in Table-
10. Respondents were asked about their views about climate change and most of the
respondents were familiar to term climate change whereas only 3.5% of the respondents
were not familiar to term climate change. Reasons of climate change were also
determined and 60.5% of the respondents indicated deforestation as a major reason of
changing climatic conditions, whereas 6.5% of the respondents indicated pollution and
energy exhaust, industrialization and global warming as reasons of climate change.
Observation on the land use planning was resulted as 64.5% of the respondents said that
there was no proper land use planning. In case of increase in disasters frequency and
intensity, 59.5% of the respondents agreed a multitude. The change in temperature was
also assessed. 83.5% of the respondents observed a change in temperature where 59.5%
of the respondents said it has no effect on income. Respondents were asked about the
change in irrigation system and 34% of the respondents agreed of alteration. In terms of
loss in biodiversity, 62.0% of the respondents related it with climate change. Change in
flowering and fruiting pattern of crops was observed by 52% respondents, 41.5%
observed less food diversity and 40% observed change in harvesting season of crops.
Change in annual rainfall was felt by 40% of the respondents whereas 43% also observed
increase in glacier melting. Change in snow pattern of the area was also observed by
57.5% of the respondents however 71% of the respondents described loss in natural
resources of their region after the earthquake of 2005 and floods of 2010 and 2013.
97
Table-10 Observations of locals on climate change in the region
Variable Description N (%) Variable Description N (%)
Are you familiar
with the term
climate change?
Yes 193 (95.5) Have you
observed any
change in
temperature?
Yes 167 (83.5)
No 7 (3.5) No 14 (7)
No idea 0 No idea 19 (9.5)
What do you think
are the reasons of
climate change?
Deforestatio
n
121 (60.5) If yes, what is
that change?
Increase in
temp.
129 (64.5)
Land use
change
66 (33) Decrease in
temp.
27 (13.5)
Any other 13 (6.5) Both 13 (6.5)
Do you think there
is proper land use
planning in your
region?
Yes 37 (18.5) How these
changes in
temperature
affect your
income?
Increase in
income
17 (8.5)
No 129 (64.5) Decrease in
income
64 (32)
No idea 34 (17) No effect 119 (59.5)
Do you agree that
earthquakes are
regular feature of
your area?
Yes 118 (59) Is this change in
climatic
conditions
affecting your
health?
Yes 143 (71.5)
No 82 (41) No 46 (23)
Does the disaster
increased here?
Yes 119 (59.5) No idea 11 (5.5)
No 81 (40.5) Have you
observed any
change in
flowering and
fruiting pattern
of crops?
Yes 104 (52)
Have you felt any
change in snow
pattern?
Yes 115 (57.5) No 53 (26.5)
No 56
(28)
No idea 43 (21.5)
No idea 29 (14.5) Is there any
change in food
diversity over
past ten years?
Less
diversity
83 (41.5)
Do you understand
term resistance to
Yes 39 (19.5) More 52 (26)
98
be applied in your
cropping system?
diversity
No 97 (48.5) No change 22 (11)
No idea 64 (32) no idea 43 (21.5)
Which crop is
abundant here?
Maize 34 (17) Do you observed
any change in
harvesting
season of crops?
Yes 80 (40)
Wheat 65 (32.5) No 58 (29)
Rice 20 (10) No idea 62 (31)
Corn 21 (10.5)
Are the natural
resources depleted
after the disaster?
Yes 142 (71) Have you
observed any
change in annual
rainfall?
Less 74 (37)
No 31 (15.5) More 81 (40.5)
No idea 27 (13.5) No change 26 (13)
Do the people
living here are
suffering from
more health
problems?
Yes 166 (83) No idea 19 (9.5)
No 28 (14) Have you felt
any change in
glacier melting?
Yes 86 (43)
No idea 6 (3) No 62 (31)
Is the climate
change leading to
biodiversity loss?
Yes 102 (51) No idea 52 (26)
No 84 (42) If yes, did it
result in
formation of
artificial lake?
Yes 48 9 (24)
No idea 14 (7) No 67 (33.5)
Do you think the
organizations are
considering
climate change an
issue?
Yes 124 (62) No idea 85 (42.5)
No 25 (12.5) Is there any
reservoir to store
flood water?
Yes 32 (16)
No idea 51 (25.5) No 124 (62)
99
Is the Government
working on
making people
resilient to
changing climatic
conditions?
Yes 73 (36.5) No idea 44 (22)
No 79 (39.5) Have you
observed any
change in
irrigation
system?
Yes 68 (34)
No idea 48 (24) No 67 (33.5)
No idea 65 (32.5)
4.3. Livelihood vulnerability analysis
This section describes the results of livelihood vulnerability analysis which was carried
out at household level to quantify the root causes of vulnerability in rural communities of
Tehsil Balakot. Firstly, results of LVI in Tehsil Balakot are presented along with
describing sub components and major components and secondly LVI-IPCC is explained
with its contributing factors.
4.3.1 Computing Livelihood Vulnerability Index (LVI)
Household level of vulnerability was calculated at both study sites; results are shown in
Table-11 and Figure-9. It was found that both areas were vulnerable to the changing
climate, however overall LVI values were little higher for UC Balakot (0.43) than UC
Kawai (0.33). This indicates that riverbank communities were more vulnerable than
people living on slopes. The major differences in the sub-component scores were of
natural disasters accounting 0.52 for Kawai and 0.78 for Balakot. Balakot community
was exposed to more hazards due to floods and landslides. More destruction in terms of
loss of land and damage to properties was measured in Balakot than Kawai. Climatic
variability was similar in both study areas due to having similar meteorological data of
100
Tehsil. On the other hand, health accountability of the household was not much different
having a major component score of 0.45 (Balakot) and 0.46 (Kawai). Both areas had no
household gas supply for cooking, therefore using woods, leaf litter and other biomass
fuels to cook and heat homes in the cold night. There was one community hospital which
was far from Kawai and close to Balakot. However, it was found that many households
had poor health conditions due to having more habitants and small houses. In terms of
food availability, households had less storage of seed of seeds in Balakot (0.07). Most
households had no crop diversity; they were seeding same crops over time which
indicates fewer adaptations in changing time. The major component score of food was
0.34 for Kawai which is more than Balakot (0.24) indicating higher vulnerability. Most of
the households had more dependency on natural water sources in Kawai (0.66) than
Balakot (0.42). For water variability in households, Balakot had higher index value (0.49)
than Kawai (0.45). Socio-demographically Balakot had shown poor statistics with an
index value of 0.4 as compared to Kawai (0.28). On the whole in UC Balakot, villages
are highly vulnerable, having an aggregate score of LVI 0.41 where the maximum score
is 0.5. In case of UC Kawai, households were highly vulnerable too but less than Balakot
as having 0.35 LVI score.
101
Vulnerability
parameters
Variables Questions inquired Units BALAKOT KAWAI Max.
Value
Min.
Value Actual
Value
Standardized
Value
Actual
Value
Standardized
Value
EXPOSURE Natural
disasters
Number of hazards/natural
disasters faced in the last 5
years
range/count
(0-5)
4.4 0.8 2.8 0.27 5 2
Family members didn‟t get
any warning of natural
disasters
percentage 100 1 100 1.00 100 0
Death/Injury in your
household due to natural
disaster
Percentage 52.5 0.525 24.5 0.25 100 0
Damage to physical
properties and loss of
agriculture land as a
consequence of natural
disasters
percentage 77.5 0.775 56.7 0.57 100 0
0.78 0.52
Climate
Variability
Mean standard deviation of
monthly average of average
maximum daily temperature
Celsius 12.8 0.052 12.8 0.052 34.7 11.6
Mean standard deviation of
monthly average of average
minimum daily temperature
Celsius 6.9 0.197 6.9 0.197 20.8 3.5
Mean standard deviation of
monthly average
precipitation
mm 116 0.266 116 0.266 324.4 40.3
0.172 0.172
Table -11 Summary of LVI scores for UC Kawai and UC Balakot
102
SENSITIVITY Health Average time to reach basic
health facility
Min 20.5 0.24 33.6 0.44 70 5
Affordability of basic health
services
percentage 32 0.32 29.5 0.30 100 0
Household with chronic ill
members
percentage 22 0.22 18 0.18 100 0
Household members
missing school or work due
to illness (in last 2 weeks)
percentage 11 0.11 9 0.09 100 0
Household having toilet in
use
percentage 83.5 0.84 77.8 0.78 100 0
Household using wood percentage 98.6 0.99 95.4 0.95 100 0
0.45 0.46
Food Food sufficiency
(household has food storage
for six month)
percentage 24.4 0.24 39.2 0.39 100 0
Average crop diversity 1/no.of
crops
0.18 0.29 0.21 0.36 0.5 0.05
housing dependency on
fishing/hunting for food
percentage 39.5 0.40 35.6 0.36 100 0
household primarily
dependent on self-farmed
food
percentage 22.5 0.23 34.4 0.34 100 0
household saving seeds percentage 6.8 0.07 23.5 0.24 100 0
0.24 0.34
Water Dependency of household
on natural water sources
percentage 42 0.42 66 0.66 100 0
103
Average days without a
water supply per month
days 8.55 0.71 6.71 0.34 10 5
household without pipe
borne water
percentage 49 0.49 55 0.55 100 0
Consistency of drinking
water supply
percentage 32 0.32 25 0.25 100 0
0.49 0.45
ADAPTIVE
CAPACITY
Socio-Demo
Dependency ratio per
household
Ratio 2.44 0.44 1.56 0.25 5 0.4
Households with a head
who is a female
percentage 26 0.26 18 0.18 100 0
Households having access
to radio, telephone or
television
percentage 66 0.66 48 0.48 100 0
Head of household never
joined any school/college
etc.
percentage 23 0.23 19 0.19 100 0
0.40 0.28
Livelihood
Strategies
Any member of household
working outside the Tehsil
for spontaneous work
percentage 54 0.54 41 0.41 100 0
Any family member
involved in local tourism
for their livelihood
percentage 22 0.22 4 0.04 100 0
Household‟s dependence
upon fishing and hunting
for their day to day life
percentage 21 0.21 16 0.16 100 0
104
Crop cultivation as a main
source of income
percentage 48 0.48 54 0.54 100 0
Agricultural livelihood
diversification in a
household
1/no.of
livelihoods
0.24 0.00 0.22 0.00 100 0
Household having
livelihood without any
contribution of crops
cultivation
percentage 42 0.42 34 0.34 100 0
Household having no direct
water supple facilities to
produce crops
percentage 36 0.36 21 0.21 100 0
0.32 0.24
Social
Networks
Household having social
support in terms of getting
and providing help
Ratio 1.51 0.36 1.22 0.29 4 0.1
Family members in
household can borrow
money from a certain social
group
Ratio 1.01 0.34 0.89 0.26 2 0.5
Is there any private money
lender in your community
to borrow money from?
percentage 20 0.20 12 0.12 100 0
Have you or any family
member in household has
ever seek help from any
government office (last 12
months)?
percentage 82 0.82 65 0.65 100 0
0.43 0.33
105
After calculating and summarizing LVI for both union councils, a spider diagram
(Figure-9) was developed to indicate value of major components and resulting
vulnerabilities. In both study areas, exposure to natural disasters had comparatively
higher score than other components.
Figure-9 Spider diagram of Tehsil Balakot indicating major component scores of
Livelihood Vulnerability Index (LVI)
0.00
0.20
0.40
0.60
0.80Natural Disaster
Climatic
Variability
Health
Food
Water
Sociodemographic
profile
Livelihood
strategies
Social Networking
Balakot
Kawai
106
4.3.2 Calculating LVI-IPCC
The three major components of vulnerability were calculated from eight major
components. Adaptive capacity index consist of socio demographic profile, livelihood
strategies and social networks in a community. Sensitivity index is composed of
health, food and water related issues. In exposure index only natural disasters and
climate variability is considered. Overall both communities had shown very low
adaptive capacity, therefore highly vulnerable to environmental and social changes in
the study area. There are three categories to recognize the vulnerability status as
described by IPCC, 2007 as shown in Table-12. For LVI- IPCC approach +1 indicates
most vulnerable and -1 is for least vulnerable. The contributing factor value for IPCC-
LVI approach is 0 for low contributing factor value and 0.6 for high contributing
factor value. Results of LVI-IPCC have suggested that the community of Tehsil
Balakot has higher exposure level. UC Kawai has comparatively low exposure to
natural hazards and climatic variability than UC Balakot.
107
Table -12 Calculation of LVI-IPCC for UC Balakot and UC Kawai
Categories for LVI- IPCC status
of vulnerability
UC Balakot UC Kawai
Adaptive Capacity > (Exposure +
Sensitivity) = Less Vulnerable
a < (e + s)
0.077 < (0.091 + 0.136)
0.077 < 0.227
a < (e + s)
0.057 < (0.096 + 0.099)
0.057 < 0.195
Adaptive Capacity = (Exposure +
Sensitivity) = Moderately
Vulnerable
Adaptive Capacity < (Exposure
+Sensitivity) = Highly Vulnerable
An overall impact analysis showed in Table-13 indicated that low adaptive capacity
was due to poor social status coupled with low social support. Sensitivity was
influenced by the primary factors of water and health related issues whereas exposure
was significantly due to presence of nature hazards already established in study area.
On the whole, LVI and LVI-IPCC for Balakot scored 0.41 and 0.0054 and for Kawai
0.35 and 0.0040 respectively.
108
Table-13 LVI and LVI-IPCC based on contributing factors and vulnerability scores for Tehsil Balakot
Contributing
factors Major components
No. of sub
components
Balakot Kawai
Major
components
values
Contributing
factor values
Major
components
values
Contributing
factor values
Adaptive capacity
Social demographic 4 0.40
0.077
0.28
0.057
Livelihood strategies 7 0.32 0.24
Social networks 4 0.43 0.33
Sensitivity
Health issues 6 0.45
0.091
0.46
0.096
Food related 5 0.24 0.34
Water issues 4 0.49 0.45
Exposure
Natural disasters 4 0.78 0.136
0.52 0.099
Climatic variability 3 0.172 0.172
LVI (0 minimum to 0.5 maximum)
LVI- IPCC (-1 minimum to +1 maximum)
0.41
0.0054
0.35
0.0040
109
Vulnerability triangular diagram was developed from the scores of LVI-IPCC
(Figure-10). It ranges from 0 to 0.14 which showed that UC Kawai was more
sensitive to climatic and livelihood changes with less adaptive capacities however UC
Balakot has higher level of exposure. An in-depth analysis showed Balakot has
geographically more prone to natural disasters and as a result community has learnt
some adaptations due to facing loses.
Figure-10 Vulnerability triangle showing levels of exposure, sensitivity and
adaptive capacity (LVI-IPCC) in Tehsil Balakot
0.000
0.020
0.040
0.060
0.080
0.100
0.120
0.140EXPOSURE
SENSITIVITYADAPTIVE
CAPACITY
BALAKOT
KAWAI
110
4.4. Balakot’s trend of temperature and precipitation
Results of temperature and precipitation data were mapped using linear regression
analysis; Climatic trends are frequently analyzed in their linear component and
variables to quantify change in historical timeline of 20 or 30 years (Hartmann et al.,
2013; Thompson et al., 2015). Intergovernmental Panel on Climate Change (IPCC) in
its Fifth Assessment Report (AR5) used linear regression to quantify the change in
global surface temperature over the historical record (IPCC, 2013)
In current study, average analysis of temperature (1988-2017) showed an erratic trend
of increasing and decreasing temperature throughout thirty years (Figure 11 and 12).
There was an overall decrease in mean minimum annual temperature by a factor of
0.0158 for each year whereas increase in mean maximum annual temperature was
recorded by a factor of 0.0253 for each year. Mean Minimum temperature of 11.2 °C
was observed in year 2005, while mean maximum temperature was 26.6 °C recorded
in year 2010. This statistical trend of temperature was then compared with perceptions
of local community people in the focus group discussions.
111
Figure-11 Graphical representation of Mean Annual Minimum Temperature for
a period of 30 years in Tehsil Balakot
Figure-12 Graphical representation of Mean Annual Maximum Temperature for
a period of 30 years in Tehsil Balakot
y = -0.0158x + 12.486 R² = 0.0543
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per
atu
re (
C°)
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mean minimum temperature
y = 0.0253x + 24.585 R² = 0.0372
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112
Like temperature, there was also an unpredictable rainfall pattern. Overall, the mean
annual rainfall of thirty years (1988 to 2017) was 1457 mm. Unpredicted rainfall was
one of the identified hazards which has impacted community livelihood and ranked
higher in hazard ranking. A drift in rainfall was calculated for a decade period i.e.
1988-1997, 1998-2007 and 2008-2017 to observe changes in pre-post and mean
monsoon periods (Table-14). A decreasing trend of mean winter rainfall was observed
during 1998 to 2007; which was much less than 1988-1997 and 2008-2017. This
higher pattern of winter rainfall has negatively influenced wheat productivity as
described by women during FGDs. A decreasing trend of pre-monsoon rainfall was
observed in months of March to May during 1998-2007 and 2008- 2017. This was the
time when usually in the past there was plenty of rainfall. It was also reported by the
community and validated by the statistical data. The mean monsoon period was
remained same in the data analysis of three decades. Similar results of winter
temperature and rainfall were informed by the work of Shah et al., 2010. The data
has indicated that there has been a general decreasing trend in the average amount of
annual rainfall by a factor of 14.35 mm (Figure-13). In thirty years period, highest
rainfall was in the month of July; which was also considered a vulnerable month to
livelihood activities by the community during FGDs (Figure-14). In whole, it was
observed in analysis of climate data and reported by the community people that
temperature shifts has provided with longer dryer periods than past with unpredicted
rainfall in the region.
113
Table-14 Rainfall Pattern in winter and summer periods over 30 years’ time
span (millimeter)
Year Average
Annual
rainfall
(Jan-Dec)
Mean
Winter
(Dec-Feb)
Mean Summer
Pre-Monsoon
(March-
May)
Mean-
Monsoon
(June-Sept)
Post-
Monsoon
(Oct- Nov)
1988-1997 1656.65 108.17 144.32 205.52 84.22
1998-2007 1370.37 88.32 83.15 195.27 80.29
2008-2017 1342.90 101.47 92.61 183.87 79.60
Source: Pakistan Meteorological Dept. Govt. of Pakistan (2017)
Figure-13 Graphical representation of Mean Annual Rainfall for a period of 30
years in Tehsil Balakot
y = -14.357x + 1680.5 R² = 0.113
0
500
1000
1500
2000
2500
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Rainfall
114
Figure-14 Average Month-wise Precipitation in Tehsil Balakot
4.5. Forest service’s assessment and vulnerability analysis
4.5.1 Community‟s perception on Balakot forest services: These forests were valued
by the local people for their subsistence livelihood due to provision of goods and
services. A list was prepared with the community in which they highlighted goods and
services they are taking from the local neighboring forest (Table-15). Mostly, people
were rural and influenced by climate based vulnerability. Water was identified as an
important service of ecosystem which is essential for agriculture, forestry and
livestock rearing. According to survey response (Figure-15), 67% households gave
high value to forest fuel wood, 46% identified higher forest role in providing fresh
water, 60% gave higher weightage to fodder to livestock, and 44% gave high value to
NTFPS. In terms of regulatory services (Figure-16), 73% of households agreed that
trees have a higher role in regulation of climate, with 62% identified the role of forest
0
50
100
150
200
250
300
350
400
Jan Feb March April May June July Aug Sept Oct Nov Dec
Pre
cip
ita
tio
n (
mm
)
Monthwise distribution (1988-2017)
115
in purifying their water. Balakot is highly vulnerable to natural disasters, 64% of
respondents‟ recognized the greater role of forest in protecting from natural hazards.
Cultural services provided by the local forests (Figure-17) were mostly ignored which
indicate their intangible nature (Schirpke et al., 2016); local people were agreed that
their surrounding forest is important for their livelihood and peace; 81% gave it
higher value, 58% considered it important for recreation and tourism, 53% gave it low
value in terms of spiritual and religious attachment. Locally valued services were
mostly those which sustain human wellbeing (Clemens et al., 2017), studies on
mapping ecosystem services have reported similar findings where local people‟s
perception develop a sense for the decision making and to sustainably manage the
local resources (Burkhard et al., 2012; Oort et al., 2015)
116
Table-15 List of goods and services of the surrounding forest identified by
the community
Ecosystem
services *
Goods and Services Identified
Components of Human
well-being and livelihood
Provisionary goods Fresh water
Fuel-wood
Fodder to animals
Medicinal value (barks; leaves;
stems; seeds; roots)
Food value (honey, fruits and
vegetables, fish, nuts, mushrooms)
Timber production
NTFPs (Resins etc)
Basic life necessity
Shelter
Food
Adequate livelihood
Health of individuals
Acesss to clean air water
and food
Feeling well about own
place
Longevity due to peaceful
living
Access to goods
Life security
Social interaction and
cohesion
Livelihood provision
Regulatory services Local climate regulation (carbon
sequestration)
Flora and fauna diversity
Air quality regulation
Water purification
Pest control
Natural hazard protection
Cultural
attachments
Recreation and tourism
Spiritual values
Sense of place
Aesthetic value
* Categorization of the forest services were followed as given by Millennium
ecosystem Assessment (MEA, 2005)
117
0%
10%
20%
30%
40%
50%
60%
70%
80%
do you think forest
has a role in
providing fuel wood?
do you think forest
has a role in
providing fresh
water?
do you think forest
has a role in
providing fodder to
livestock?
do you think forest
has a role in
providing fiber/food
products?
per
cen
tag
e re
po
nse
%
high
medium
low
Figure-15 Provisionary forest services to Balakot community
Figure-16 Regulatory forest services valued by locals
Figure-17 Identified Cultural forest services to local people
0%
10%
20%
30%
40%
50%
60%
70%
80%
trees are helping in
regulation of climate
forest has a role in
purifying water?
these forest are
protecting you from
natural calamities?
per
cen
tag
e re
spo
nse
%
high
medium
low
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
nature provide
sense of peace
forest are
impotant for
recreation
forest as
spirtual and
religious value
forest has
educational
value
forest are
important for
your
livelihood
per
cen
tag
e re
spo
nse
%
high
medium
low
118
4.5.2 Change in Delivery of Forest Services to local Community: Local people‟s
perception for the change in services was mapped and results are shown in Figure-18.
In the absence of any alternative source of energy, local people were cutting more
trees for fuel wood which increased in the winter season due to very low temperature.
In addition to this, many families have their livestock grazing in the forest which is an
additional benefit to them. In the survey, considering this on-going process of forest
degradation, locals were asked about change in delivery of forest goods and services
from last 10-20 years. It was made sure that respondents for this part of study must be
living in the area from last 20 years (Shedayi et al., 2016). The change in delivery
was measured as “positive” which indicate the goods and service has increased,
“negative” means it is decreased and “none” refers to no effect in the stated period of
time. In terms of provisionary services, 66% of respondents said that fuel wood has
reduced, 49% reflected that there is no effect in water quality and quantity. This
perception of local people was because of greater availability of spring water in the
region. The respondents (56%) shared that the availability of fodder to the livestock
has decreased due to change in forest structure and composition whereas 39% said
that there is no effect noted in availability of non-timber forest products (NTFPs). For
the regulatory services of the forest, 82% of respondents said that the forest cover has
declined. The reduced forest cover has increased the community‟s vulnerability to
climate change and natural disasters. In terms of cultural services, 83% responded
said that role of forest in creating a sense of peace has decreased which is due to
increased tourism in the area. The recreational value associated with the local forest
has increased which was shown by 54% positive responses.
119
Figure-18 People’s perception of change in surrounding forest services
0% 20% 40% 60% 80% 100% 120%
positive
negative
none
chan
ge
in s
erv
ices
percentage response %
Educational
Spiritual/religious
Recreation
/tourism
Sense of peace
Protection from
natural hazards
Water purification
Climate regulation
Fiber and food
products
Fodder to livestock
Freshwater
Fuelwood
120
Role of forest in Carbon sequestration: Carbon stock assessment was done to assess
the important regulatory service of forest in combating climate change. Results are
shown in Table-16. Out of five selected sites for carbon stock assessment, two (Site 1
and 4) were purely stands of Pinus roxburgii, which were moderately degraded as
observed from stumps present. Site 2 and 3 showed the higher number of Pinus
roxburhii as compare to Cedrus deodara and Quercus leucotricophora both sides
showed higher degradation which was due to reason that human settlements was
greater and closer to the forested sites. Site 5 had pinus stands and quercus in good
health, the site was far from the human tenancy. This pattern has indicated that the
forest degradation was greater where people had better access considering their
vicinity and slope of the mountain. Near the mountain tops, better forest growth was
observed with less floor grazing (Jina et al., 2009; Joshi et al., 2013).
121
Table-16 Tree density and status of degradation at five different sites in Tehsil
Balakot
Tree species Common
name Site-1 Site-2 Site-3 Site-4 Site-5
Pinus roxburgii Chir Pine 95 57 77 116 95
Cedrus deodara Deodar - 10 4 - -
Quercus
leucotricophora Banj Oak - 13 12 - 30
Aggregate 95 80 93 116 125
Status of degradation Moderately
degraded
Highly
degraded
Highly
degraded
Moderately
degraded
Non
degraded
Fuel wood consumption
kg/day/capita 2.40 3.84 4.62 1.38 1.01
Herd size (average in
household) 4.41 2.23 6.13 2.45 3.24
The study revealed that the average carbon stock value at Tehsil Balakot was 243. 79
t/ha (Table -17) which is also comparable to the value of carbon stock reported by
Houghton and Hackler, 1999 as 250 t/ha in Southeast Asian Forests. Few similar
studies reported more carbon stock as the Central Himalayan with the value of 262.6
t/ha (Jina et al., 2009); Garhwal Himalayan with the maximum of 490.33 t/ha (Joshi
et al., 2013) but our results showed a higher value of carbon stock than a related study
conducted in Muzaffarabad Region, AJK Pakistan showing an average value of
186.29 t/ha (Shaheen et al., 2016). The fluctuation in carbon stock values may be
attributed to the type of vegetation and method of allometric measurement used
(Segura and Kanninen, 2005; Zhang et al., 2012; Rosenfield and souza, 2013). The
122
current study has reported an average biomass calculated from the aboveground and
the belowground biomass as 414.82 t/ha; carbon biomass of 207.41 t/ha with soil
carbon matter as 36.38 t/ha. This value is much lower for the Himalayan region as a
study reported 1157-827 t/ha (Sharma et al., 2014). It is said that the forest biomass is
mostly effected by the type of anthropogenic activity involved on land, therefore
higher grazing and the human habitation pressure will lead to lower forest
productivity (Bhadwal and Singh, 2002; Czegledi and Radacsi, 2005).
Table-17 Average biomass and Soil Carbon at five different sites
Site No Tree
Density/ha
Total
Biomass
(t/ha)
Biomass
Carbon
(t/ha)
Soil Organic
Carbon
(t/ha)
Total
Carbon
(t/ha)
1 95 316.43 158.22 31.25 189.47
2 80 280.18 140.09 27.92 168.01
3 93 298.01 149.01 38.55 187.56
4 116 516.01 258.01 43.41 301.42
5 125 663.5 331.75 40.77 372.52
Average 101 414.82 207.41 36.38 243.79
123
The results of species-wise carbon stock assessment (Table-18) has indicated that
Pinus roxburgii was more significant specie having the highest biomass value of
average 194.66 t/ha whereas Cedrus deodara had 1.7 t/ha and Quercus
leucotricophora had 47.5 t/ha. The average DBH value recorded for cedrus spp was
122 cm which was highest at site-2 with a minimum value of 25 cm for quercus. The
tree features like the height and DBH effects the ability of tree in biomass production;
our study has reported lower values in terms of tree height as compare to other studies
in Himalayan (Shrestha et al., 2013; Nautiyal and Singh, 2013; Baral et al., , 2009).
The average tree DBH in the current study was also lower than the studies in the
Nepal forest and the sub-tropical Indian forest (Mishra et al., 2009; Shrestha et al.,
2013). Average tree height for the forest stand was 14.2 m with a maximum value
for Pinus roxburgii. The carbon stock assessment was highest for Pinus roxburghii
showing 97.33 t/ha and least for Cedrus deodara as 0.85 t/ha which indicated that
Pinus roxburgii has the highest contribution in carbon stock of Tehsil Balakot.
124
Table-18 Species-Wise Carbon Stock Assessment (t/ha) in Balakot tehsil
No. Species Site-1 Site-2 Site -3 Site-4 Site-5 Biomass
t/ha
Carbon
stock t/ha
% Contribution in
Total Carbon
Stock
1 Pinus roxburgii 210.5 95.2 121.5 255.5 290.6 194.66 97.33 79.8
2 Cedrus deodara - 6.3 2.2 - - 1.7 0.85 0.69
3 Quercus leucotricophora - 64.2 66.8 - 106.5 47.5 23.75 19.47
125
There is considerable research in the world on goods and services of different
ecosystems to human beings and their accountability. The degradation in quantity and
quality of the environment will reduce or decline the services of these natural
ecosystems (Shaheen et al., 2017). It was observed that the site-2 and site-3 were
having a higher rate of forest degradation which is apparent from the lower value of
soil organic carbon (Wani et al., 2010). As the both sites had greater grazing pressure,
fuel-wood collection and close to human settlement; earlier studies have shown
similar results where degraded pine forest had low productivity and poor soil
condition (Jina et al., 2009, Soto-pinto et al., 2010; Rawat, 1988).
126
4.6. Land-use and climate change mapping and livelihood impacts
Tehsil Balakot has been affected by changing in its land use scenarios which was
shared by most of the households during in-depth interview. Many were of view that
availability of fresh and clean water has reduced along with reduced forest cover.
Results revealed in Table-19 and represented in Figure-19-22 indicated that there
were significantly increase in the settlements in year 2015 than 1990. A drop in
population from 1995 to 2010 was due to a higher death toll in earthquake of 2005. It
was documented that 90% households suffered two or more than two deaths in this
disaster (Qasim et al., 2010). Forest cover was significantly reduced from 1990s to
1995 and 2010. An increase in forest cover in 2015 was due to a provincial program
namely Billion Tree Tsunami Project (BTTP) which was an afforestation effort in line
with international Bonn Challenge (WWF, 2017.). Pakistan promised to restore six
million hectares of degraded forest land by year 2020 according to this commitment.
Another greater change reported by locals in their FGD was conversion of forest land
into cultivation. Vegetation in the map and tabular data represents all type of
cultivation carried out in the study area. Tehsil Balakot has higher production of
maize and wheat, rice production comes in third place with many seasonal vegetables.
Agriculture has been a substantial livelihood strategy in this region. It can be seen
from the land use mapping that agriculture has got momentous increase which will
affect climate and livelihood in positive and negative too. Barren land is the region
has increased also which was majorly due to drying of river body. On the hand, ice
and snow has reduced too which was supported by aged people during FGD that
glacier‟ melting is amplified in the region coupled with flooding and resulting
landslides. Water bodies including rivers, springs and lakes have significantly
127
reduced in its volume affecting agriculture, fishing, livestock rearing and related
livelihood activities.
128
Table-19 Percent response and change in stated time period in land use data
Land use
Classes
Description in the study area Land use (% response) Percentage change
1990 1995 2010 2015 1990-1995 1995-2010 2010-2015 Overall
1990-2015
Forest All type of forests where trees
growing in patches and canopies
30.05 12.56 19.24 24.67 -58.81
+53.34 +28.08 -17.90
Settlement Continuous and discontinuous
buildings where people living
1.64 10.45 5.67 18.26 +537.19 - 45.74 + 222.04 +1013.41
Vegetation
(Agriculture)
Regularly ploughed land for
irrigated crops or growing rain-
fed crops
4.54 5.75 6.08 18.26 +26.65 +5.73 +200.32 +302.20
Barren Land Land with eroded soil and top
surface soil with no vegetation
and no settlements
14.98 5.71 16.3 21.07 - 61.88 +185.46 +29.26 +40.65
Ice & Snow Area covered with ice and snow
continuously or for a part of
time in a year
31.82 46.55 32.54 16.91 +46.29 - 30.09 - 48.03 - 46.85
Water Bodies Water courses like rivers and
streams, lakes and ponds
16.97 19.15 20.19 5.09 +12.84 +5.43 -74.78 -70.05
+ indicates increase in certain activity whereas a minus (-) indicates decrease.
129
Figure-19 Land use analysis in Tehsil Balakot for the year 1990
130
Figure-20 Land use analysis for the year 1995
131
Figure-21 Land use analysis for the year 2010
132
Figure-22 Land use analysis for the year 2015
133
Discussion
The study showed how human has their central role in managing, degrading or
restoring the ecological units. Balakot mountainous community and their livelihood
under changing climate was a typical example of socio-ecological system; where
locals were putting additional burden on natural systems and resources like forests,
agriculture, fishing and many more. On the other hand, natural systems were showing
transitions due to higher human pressures.
Climatic trends and perceptions: Local people perceptions about climatic changes in
their region confirm the findings of scientific facts such as temperature and
precipitation records of past years (Aryal et al., 2014). Local people (natural resource
dependent communities) use their close interaction with nature to predict climatic
changes such as the start of seasonal rains, melting of snow, first snowfall to compare
the trend (Martello 2008). Local people have more holistic approach in knowing their
environment and developing a perception of change (Aryal et al., 2016). Local
people‟s perception was recognized as an important indicator of community
livelihood and knowledge of extreme events in Tehsil Balakot (Figure 4a).
Agriculture was a subsistence livelihood practice; had become very risky due to
higher dependence upon precipitation and temperature. The local community had
shared their experiences and highlighted the change in snowfall pattern affect the
harvesting of their crops especially Maize and Wheat. It was reported in similar
studies that cropping patterns of different seasonal crops has been changed in the
mountainous regions (Macchi, 2011; Gentle et al., 2014; Chaudhury et al., 2016). Old
age people mentioned during a FGD that their seasons have changed altogether, as in
past snowfall was a common feature in Tehsil Balakot but now it is limited in higher
altitudes. The daily life of locals was altered because of change in rainfall and
134
temperature which further affected their agricultural productivity. Climatic data has
validated this shift of rainfall from pre-monsoon to mid-monsoon period. It is reported
in a study that changes in summer and winter temperature coupled with unpredicted,
low rainfall has affected the crops growth cycle (Arias et al., 2016). The minimum
temperature showed a further decreasing trend in winter season while increase in the
maximum temperature was shown in the summer season; hence contributed to the
extreme weather conditions in the study area. These results are similar to previous
studies conducted in the Himalayan region (Chaudhary and Bawa, 2011; Shrestha and
Aryal, 2011; Aryal et al., 2016). An erratic trend in rainfall was also found in the
study area and noted by local people with an overall lower frequency. Such results are
in line with the studies carried out in Himalayas by different scientists (Xu et al.,
2007; Aryal et al., 2014).
Differential impacts on livelihood: As Rainfall pattern has shown a decreasing trend
for the last 30 years which was informed by the local community in their FGDs; it
might be the main reason which affect their overall agricultural shifts and productivity
(Gould et al., 2015). The cropping activity was totally dependent upon rainfall in this
region. It was observed by the community that rainfall has become unpredictable
which affected their crop productivity through change in sowing and harvesting time;
hence made the local life difficult to survive (Boissiere et al., 2013; Williamson et al.,
2015; Arias et al., 2016). Cultivation of land was an adaptation as well resilient
activity. Well-off households had large land to cultivate however poor families were
working on these farm lands. Females in the area had a prime role in cultivation of
crops and collection of firewood. Livestock rearing was also done by women and
young girls in many of the households. It is also reported that women worked in the
agricultural fields and livestock grazing in most of the developing countries (Acosta-
135
Michlik and Espalon, 2008; Olivier and Heinecken, 2017). Seasonal variations
showed significant influence on their livelihood strategies, especially those were
related to the mountain forest and agriculture. Most of the farming families reported
low agricultural productivity after the worst floods in the year 2010 which destroyed
their lands and damaged their crops (Regmi, 2007; Ullah et al., 2015). The livestock
rearing, collection and selling of NTFP were also threatened by changing climatic
patterns. As IPCC has reported that agriculture is most significantly affected sector
from climatic changes and in agriculture, livestock production is most susceptible
economic area (IPCC, 2007; Panthi et al., 2015). Livestock production and rearing
was identified as another climate dependent livelihood activity by the locals. Most of
the poor families were involved in grazing big herds of land-masters on daily wages.
Similar findings were reported in Jumla District of Nepal (a mountainous region)
where management practices of crop growth were common in front and back of
homes (Gentle and Maraseni 2012). It was noted that people had poor adaptation
practices due to limited knowledge and the prevailing poverty; as the coping strategies
of the community were the mix of adaptation actions in changing climate (Herman-
Mercer et al., 2016; Maitib et al., 2017).
Community was convinced that the forest cover of the mountains had declined
resulted in more landslides incidents. As a result of reduced tree cover, availability of
Non-Timber Forest Products (NTFPs) had also reduced which was reported by people
in a FGD. Many men and women were involved in the collection and selling of
medicinal herbs from the forest; the number of which had also reduced due to natural
disasters. Similar pattern in Nepal was observed when community members were
taking fuel wood from the nearby forest resulted in reduced forest size (Macchi,
2011). It was observed during the transect walk in the community living close to
136
forest mountains and river Kunhar that overall community people were facing
negative effects on the resources, their availability, quality and quantity (Ullah et al.,
2015). Local people had reported more landslides in their area due to the construction
of more houses every year on uneven slopes which have further deteriorated grazing
grounds. The well off families had big herd sizes which were their prime asset after
landownership. Almost every family had farm animals ranging from few sheep to
cattles and grazing in the forest lands was carried out by poor men on daily wages in
case of big herds. Similar findings were reported by a study conducted in the Rasuwa
District of Nepal where livestock was single livelihood source for poor families (Joshi
et al., 2017). Another study in Himalayan has described livelihood patterns of
Nepalese herders and how their perceptions help them to understand in climatic
adaptations (Aryal et al., 2018).
Major contribution to change in livelihood patterns was because of climatic and non-
climatic factors as described by locals in their FGD‟s Social and economic stresses in
people were increased after the deadly earthquake of year 2005 which has devastated
their agriculture land, forested area, livestock etc. A preliminary study has shown the
downfall (56%) of forest area just after the earthquake (year 2005) in Balakot (Qasim
et al., 2010). Almost 75% of respondents still lived in the temporary shelters
provided by the Government at the time of earthquake. After 13 years of disaster, only
well-off population could rebuild their homes while rest of community is striving in
same condition with lost assets (Basharat et al., 2016). In such marginalized area,
ecological resources were degraded due to population pressure and change in
livelihood pattern. Therefore, climate can be seen as an instrumental factor in
determining livelihood for the poor rural communities (Boissiere et al., 2013; Fabinyi
et al., 2014). A study conducted by Malakar and Bhandari (2012) reported similar
137
findings in Nepal rural mountainous communities those were highly vulnerable due to
declining natural resources.
Himalayan region has an old custom of in and out migration of locals to explore new
avenues majorly because of extreme weather pattern and socioeconomic instability
(Maharjan et al., 2012; Aryal et al., 2017). Differential impact on livelihood was also
due to migration pattern in the Pakistan‟s part of Himalayan; local people reported
that they have to move to main District Mansehra and to urban areas of Abbotabad for
finding new income opportunities from the end of October to mid-March. The reason
for this type of migration was severe winter season in the region; so life activities had
been almost restricted. On the other hand, well-off families had reported that their
household members were working in the gulf countries; which in line with a report‟s
findings where unskilled people used to work in booming construction industry of
gulf (MoLE, 2014).
The overall analysis carried out using indices has shown that UC Balakot higher
dependence ratio per household with more female headed households than UC Kawai
which make their low socio-demographic profile. In addition to this, UC Balakot has
low education and less income in most of the households. Most households had
shown less livelihood diversification that showed their dependence on one source of
income which was on-farm activities in most villages. Poverty and vulnerability are
thoroughly linked; poor households are characterized as more vulnerable (Rahut and
Akhtar, 2017). Many studies have reported similar findings (Adu et al., 2018; Sujakhu
et al., 2018; Huong et al., 2018) where poverty is leading to vulnerability in most
parts of the world. In addition, literature has strongly supported the idea of livelihood
diversification leads to community resilience (Cannon and Muller, 2010; Wilder et
al., 2010; Shah et al., 2018). UC Balakot had many households involved in nature-
138
based tourism; ranging from running huts for tourists to selling day to day items. This
area is a popular tourist destination which has resulted in unstable construction of
motels and huts on the riverbank as well as hill slopes. Social networking is taken as
an adaptation strategy in rural livelihood (Sujakhu et al., 2018) as it enhanced
community linkages and a support system. The livelihood was under stress due to low
adaptive capacity which has indicated the people had low socio-demographic profiles
with poor social networking. In addition to this, people had less livelihood adaptations
in both areas. Similar finding were reported by an earlier study done by Gerlitz et al.,
2016 in Hindu Kush Himalayan (HKH) where the community was identified more
vulnerable due to low adaptive capacity and higher exposure to climatic and socio-
economic factors. Surveys in this mountainous region has shown that the majority of
households observed changes in their environment, precipitation and monthly
temperatures; further it was reported that these changes will be adverse in next few
years (Colom and Pradhan, 2013; Zaheer and Colom, 2013; Gambhir and Kumar,
2013; Tse-ring et al., 2010). In a similar study conducted by Wang et al., 2016 uneven
seasonal precipitation distribution was also reported in this region will undesirably
effects agriculture and livestock production. Literature reported less rainfall and
extreme weather array in this region of Hindu Kush Himalayan which has provided
environmental and socio-economic shocks to the livelihood of marginalized
communities (Akhtar et al., 2008; Gerlitz et al., 2016, Alam, 2017).
Forest ecosystem assessment and vulnerability of mountain forest: The Balakot
mountainous forest (Moist and dry temperate of Himalayan) were more vulnerable to
the adversative effects of changing climate due to not only climatic factors but also
other socio-economic stressors (Chaturvedi et al., 2011). This part of Himalayan
forest is reportedly having higher degradation pressure due to higher population
139
pressure (Shaheen et al., 2011). It was projected by IPCC (2014) that climate change
will be more visible at higher elevations and in marginalized communities. Forest
dependent communities identified change in forest cover and decline in provision of
ecosystem goods and services. It is said that in 21st century, climate driven change
will be dominant in terrestrial ecosystems affecting specially forest biodiversity, and
altering species structure and function (Villa et al., 2011; Wilson et al., 2012; Thorne
et al., 2017). Pinus roxburghii has become dominant in absence of Quercus
leucotricophora as it was popular for fuel-wood in past and over cutting has resulted
in decline of specie (Soomro et al., 2012). The study has attempted to develop the
nexus between human wellbeing, due to livelihood opportunities from forest
ecosystem in face of climate based vulnerability; the framework has shown the
Balakot community will be vulnerable if locals have low adaptations to change,
however a resilient community will show better adaptations for their survival (Figure-
23).
140
Figure-23Theoretical Framework of Tehsil Balakot indicating nexus of ecosystem services, climate change impacts and livelihood
141
Land use changes and livelihood analysis: In HKH region the environmental changes were
reported earlier in 1970s; which included higher deforestation, burgeoning population
growth, glacier melting, soil erosion and low lying flooding (Sterling, 1976; World Bank,
1979; Karan and Iijima, 1985; Schickhoff, 1995). Hence with poor evidences and empirical
studies an in-depth livelihood analysis was not possible. In the current study, the land use
change data has long-established fact that agriculture and water bodies were significantly
reduced whereas settlements due to growing population had amplified which was also
documented by Padilla et al. (2010) and Khurshid et al. (2016). Higher population will
subsequently put higher pressure on natural resources which in turn elevates poverty. This
vicious cycle was reported already in Bangladesh, India, Nepal and other neighboring
countries (Gentle et al., 2014; Aryal et al., 2016). Water resources of HKH are critical for
Pakistan as an agricultural economy, the increase in global warming and climate change will
likely effect the hydrological cycle. This will have cascading impacts on agriculture
productivity and livelihood (Khattak et al., 2011; Kamwi et al., 2015; Yang et al., 2014;
Aryal et al., 2018). Further melting of glaciers in higher Himalayan is reportedly producing
damaging impact in form of floods to communities living downstream (Xu et al., 2007).
However, in the study area the drying water bodies were extending barren lands in the region
(Mahmood et al., 2016). Reduction in forest size and cover was already described for higher
need of fuel wood in HKH (Khan, 1970; Gentle and Maraseni, 2012; Aryal et al., 2017;
Yohannes et al., 2018). These land use changes in the HKH region will have long term
effects on the livelihood of rural people.
Policy implications: Pakistan has recently approved and implemented the Pakistan Climate
Change Act (2016) which indicated that deforestation and climate change are linked with
each other; if climate change has to combat, forest policy needed to be changed. In northern
areas of Pakistan, fast declining of tree cover has resulted in producing more and more
142
disasters. The absence of strict policy implementation has led to degradation of natural
resources in the area. On the other hand, provincial government has started a programme
under Bonn Challenge to restore the forest cover (BTTP, 2016). This initiative would help to
reinstate the barren peaks of Pakistan‟s part of Himalayan. It was observed that local
community depending upon their well-being status were coping to changing climate; e.g.
most people has started cultivation of wheat and maize crops in their home land while living
on the mountains. Local government has facilitated by starting a project Billion trees tsunami
project; under which females are getting trained on nurseries establishment on their roof-tops.
Pakistan‟s vulnerability to extreme events is increasing with every passing year as Pakistan
was on 12th
position in 2012, 8th
position in 2015 and it ranked 7th among the world‟s top
exposed countries in 2016 to climatic variability and global warming (Kreft et al. 2015,
2016). Keeping this scenario in consideration, the government should develop policy
initiatives to mitigate impact of climate change. After gathering all the information, it was
understood and convenient to rank the social groups of Tehsil Balakot who are vulnerable to
the climatic and others changes; the well-off population was least vulnerable as they have
opportunities to diversify the livelihood; whereas the poor and very poor population were
most vulnerable to adapt any change or variability in the environment. Gentle et al. (2014)
provided parallel findings where mountainous communities of Nepal were highly vulnerable
to climate change. Abid et al. (2016) has reported higher vulnerability to climate change in
farmer‟s families due to their dependence on climatic factors to earn livelihood. The study
also revealed increasing population pressure on water resources in the region; local people
had described about the decline in quantity and quality of the water. As a measure to it,
community people had stopped themselves to dump their waste materials in the river body; so
the preservation of important natural resources could be achieved through minimizing
negative anthropogenic activities.
143
Conclusion
People in Tehsil Balakot were vulnerable due to their poor social and environmental
conditions. The current study highlighted vulnerability at a household level using
acknowledged methods. Surveys in this region showed that the majority of households had
already observed the change in environment and climate as well. Poverty was a contributory
factor to higher vulnerability and climate change. Well-off and better off people were
considered as more resilient in their daily life where as poor and very poor group had to face
difficulties from social and environmental changes. All FGD‟s highlighted that the local
people were living in a marginalized area having dependence on forest and agriculture
resources for their livelihood. Stability was considered a coping aspect in changing
environment. The lives of villagers were also affected by economic, political and
demographic pressures. However, income and livelihood diversification were recognized as
important adaptation strategies.
Himalayan forests are facing degradation due to prevailing poverty and higher natural
resource dependence. This region has become more vulnerable in changing climate and
environmental gradients. The mountain forests are combating the global warming by storing
excess carbondiooxide and reduce forest cover will enhance community vulnerability.
Overall local community identifies the role of local forest in providing beneficial services to
sustain their life and to provide livelihood. Land use analysis also indicated change which
will positively and negatively affects the rural livelihood. Such studies are important for
policy makers to conserve the resources which are under higher anthropogenic pressure. It is
therefore concluded that the vulnerable communities will become progressively more
vulnerable if the local government will not encourage people to enhance their coping
mechanism by initiating rural development programs. Because without financial and political
144
support to start adaptation plans; the potential of poor people to do it on their own is
ineffective and very limited.
Sustainable forest management is needed in highly vulnerable and marginalized regions to
support communities and natural resources at the same time. More studies are needed to
understand the effects of global climate change on local areas which are obviously not clear
and reported in large scale global studies. Local perceptions can aid in developing national or
local adaptation plans to mitigate the effects of changing climate. There are few empirical
studies using indices to identify root causes of vulnerability across many sectors in Pakistan.
It is recommended to study in-depth issues for poverty alleviation and combating climate
change. The study offers an assessment approach which can be replicated for regional and
national level to know the causes of vulnerability. Realistic studies are needed to highlight
exposure, sensitive and adaptive capacity of rural people to enhance their resilience and
adaptations to change. This can help decision makers and planners to address the challenge
which is biggest in 21st century. This study implies that disaster prone areas like Tehsil
Balakot needs special attention from the policy makers to help the local people mitigate from
natural hazards and climate change.
145
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Annexure-1 Map of Study Area for forest ecosystem services assessment
xii
Annexure-2 Aerial view of Balakot and River Kunhar
(Source: Quickbird Image)
xiii
Annexure-3 Study Tool: Vulnerability Capacity Assessment
Vulnerability Capacity Assessment and livelihood of Balakot Mountainous
Community in face of changing Climate
General information about village and respondent(s)
Basic information of respondents/ household:
Name of respondent: ___________________________ Age of respondent: ________
Gender: male female
Education: no formal education primary secondary
higher
Head of household is: male female
Types of households: very poor poor better-off well-off
Do you own land of your household: yes no
Access to electricity (govt. supply): yes no
Access to sui gas (govt. supply): yes no
Access of drinking water: yes no
Distance to cemented road: ___________________________ minutes walking time
Migration pattern: abroad working in main Districts working in same
Tehsil N/A
To Be Filled By Interviewer
Date of interview: ___________________
Name of Tehsil___________________________ Union
Council______________________
Name of village: ___________________________
Elevation/ Altitude: ________ m above sea level (recorded by GPS)
Coordinates: ________________________________________(recorded by GPS)
No. of household (for personal record): ________
xiv
What are your main sources of income? (More than one response possible)
agriculture forestry based
remittances livestock based fishing based
jobs/ services combination of different sources
Is your income sufficient to cover and support your basic needs of life (food,
healthcare, clothing, and schooling)?
Income is more than sufficient less than sufficient
sufficient
Is there any income source or an opportunity you no longer find?
Over the period of last 10/20 years, is there any new opportunity or source of income
have arisen in this area?
What are the important socioeconomic and climatic changes noted in the region?
What do you think these changes have affected your livelihood?
xv
Resource profiling through Transect Walk
(Normally done in a segment along with local people)
What are the natural resources available your daily activities?
What are the resources men usually use?
What is purpose of use?
What are the resources women usually use?
What is purpose of use?
What are the resources that you used to use but no longer can access them? Name
them (e.g. fresh water, fuelwood, some plants as medicine etc)
What is the change in abundance and seasonal availability of any resource?
How this change has effected your live?
Any new resource available now which was not available in past? (e.g. plants,
materials for energy production
xvi
Interview guidelines for focus group discussions (FGD)
Livelihood and Seasonal mapping
(While getting perception of changes, it is good not to mention the idea of „climate
change‟ as this might create bias answers).
Have you ever feel or witness any change in weather pattern of your area?
How will you describe the change?
Do the changes you have mentioned impact on the food availability of your
household? on the
no change less food more food uncertain
In a year, how many months do you and your family has food storage (enough food)?
0-3 months 3-6 months 6-9 months 9-12
months
Has this change prevailed over last 10/20 Years?
If yes, describe how and why?
Do you have diversity of Food in your area?
grains available (rice, bread, cereals etc.) sufficient vegetables
sufficient dairy/meat or fish sufficient fruits
xvii
Have you ever felt any change in food diversity?
less more no change uncertain
What are the main activities women/men are carrying out on this land?
Who decides what to grow on land?
How takes care of livestock in the house?
What are the migration patterns you do in pursuing your life activities (daily,
seasonal, or yearly)?
Any change in migration?
Any experience of a hazard or a disaster over period of last 10/20 years?
If yes; what type of?
When did it happen?
xviii
Have it effected your _________?
family land livestock any other
Do you think these disasters/hazards have become more frequent from the past?
Have you ever felt any change in rainfall pattern of your area for period of 10/20
years?
If yes, how you will describe in change in temperature?
What is reason of this change according to you?
Do you think these changes have effected your life activities?
Have you ever felt any change in temperature of your area for period of 10/20 years?
If yes, how you will describe in change in temperature?
What is reason of this change according to you?
xix
Do you think these changes somehow have effected your life activities?
Do you think changes in temperature or rainfall has effected your crops?
In what way you will describe the change on crops productivity?
Which plant is most common fuel of the region?
Have you ever felt any change in number (less abundant, more abundant or
disappeared) of plant specie?
Any alternative fuel?
According to you, fish productivity has been affected by any reason?
yes no
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Institutions
Are there any institutions in the community for decision making/management of
common resources e.g. forest land, pasture land if any, water bodies?
What is the role of women and men in these institutional arrangements?
Do you have any access to community loans? How do you get the loans?
Are there any groups or arrangements in the community to help u resolve any
problems?
Can you please describe these people groups or arrangements?
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Coping strategies
(This section should be done after getting responses from seasonal and livelihood
mapping and after identifying hazards in area)
In asking following questions, provide examples like timing of sowing/planting or
harvesting, change varieties, irrigate the land
If there is too little rain than expected, what you do with your crops?
If there is too much rainfall than expected, what you do with your crops?
If the weather is hotter than expected for longer time period, what you do?
If the weather is extremely cold for longer time period, what you do?
Your area faces landslides mostly after rains, so how you deal with it?
What you do with crops, animals etc. in landslides?
Have you tried introducing any new crop or left planting some old ones?
Describe the change (why)?
Do you get any help from the community groups/ institutions or any other to
overcome challenges in coping?
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ANNEXURE-4 Definitions and Description of VCA Tools
Tool Type Definition and Description
Participant
observation
It is the method of field investigation in which an investigator or a
researcher collects information about people, processes, and practices of a
particular place or a region. It is the process of learning through exposure
to or involvement in the day-to-day or routine activities of participants in
the researcher setting.
Transect Walk It is a tool in which a researcher walks with the community men or
women along a given transect to get an overview of the village and
villagers daily life. It is to develop an understanding of the site, location,
seasons, severity of hazard, resource distribution, landuse and landscape
of the area. Such walk can be of two to three hours in the beginning of the
field survey separately with men and women.
Focus Group
Discussion
(FGD)
It is a method of collecting data in a group of 6-12 people guided by a
facilitator. The group should be comprised of young and old as well as
men and women for gathering diverse data.
FGDs can be conducted through the following five methods.
Community
historical
timeline
This tool gathers data about the events and changes that have occurred in
a community in last 10/20 years. Such changes and events have a major
impression on the community‟s livelihood and their daily activities. It is
important to include older people of the community in this method.
Seasonal
timeline
It is a tool which maps regular cyclic periods and events of a year. It
helps in documenting the major climatic and environmental hazards of a
year in a calendar which has influenced the community‟s livelihood.
Livelihood
seasonal
monitoring
calendar
It is a method of assessing income earning period as well as key
production time throughout the year which have significant effect on the
community‟s livelihood due to food availability. (USAID 2010).
Community
ranking of
hazard severity
It is a tool which identifies hazards in a community according to local
people‟s perception. After identification of the major hazards, a radar
chart is used to rank which hazard has higher or lower severity.
Venn diagram
of the institution
It is a tool which develops a diagram of different institutions of a
community like government organizations, non- government
organizations, community representatives.
Semi-Structured
Interview
It is a method of inquiring data from a person using a planned
questionnaire with open ended responses. This allows a greater in-depth
response on a particular topic of interest.
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ANNEXURE-5 Frequency Table of Questionnaire Data collected
from Households
Variables
Response Frequency Percentage
Children are going to schools Yes 107 53.5
No 93 46.5
Children are in private schools Yes 29 14.5
No 171 85.5
Adults are in
colleges/universities
Yes 11 5.5
No 189 94.5
Owner of business Yes 11 5.5
No 189 94.5
Job at main districts Yes 22 11.0
No 178 89.0
Involved in tourism-based job Yes 39 19.5
No 161 80.5
Involved in agriculture Yes 88 44.0
No 112 56.0
Owner of land Yes 20 10.0
No 180 90.0
Rented land for agriculture Yes 31 15.5
No 169 84.5
Labor at someone‟s land Yes 72 36.0
No 128 64.0
Surplus food available Yes 47 23.5
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No 153 76.5
Storage of food for six months Yes 11 5.5
No 189 94.5
Change in agricultural
production and techniques
Yes 150 75.0
No 11 5.5
don‟t
know
39 19.5
Use medicinal plants for any
treatment
Yes 187 93.5
No 13 6.5
Collection for firewood from the
forest
Yes 185 92.5
No 15 7.5
Working outside Pakistan Yes 13 6.5
No 187 93.5
Seasonal migration to main
districts
Yes 44 22.0
No 156 78.0
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ANNEXURE-6 Field Survey (prevue)
During Focus group discussion with Men (above) and Women (Below).
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In-depth interview with Labor Councilor
Mountains slopes used for agricultural activities
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A small land used for cultivation in front or back of houses
Overview of Balakot community in foothills
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Big herds of rich families were reared by poor daily wage labors
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A view from river bank community having patch of cultivated land and river
kunhar flowing in front
View of mountain pine forest
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During data collection of carbon sequestration
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A Panoramic view of River Kunhar flowing through the mountainous valley
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List of Publications
Assessing the impacts of the changing climate on forest ecosystem services and
the livelihood of Balakot mountainous communities.
Laila Shahzad*1, Arifa Tahir
2, Faiza Sharif
3, Ikram Ul Haq
4 And Hamid
Mukhtar.5
Pakistan journal of Botany (manuscript no:18-168 accepted).
Ecosystem Vulnerability Assessment under Climate Crisis: A Review.
Shahzad et al., 2017. 12: 54-64. Journal of Environmental and Agricultural
Sciences (ISSN: 2313-8629) Open access
Assessing the community vulnerability to natural disasters and climate change in
the mountainous region of Pakistan
Laila Shahzad1*, Arifa Tahir
1, Faiza Sharif
2 and Muhammad Waqas Ijaz.
2
International Journal of Biosciences Vol. 13, No. 3, p. 132-143, 2018
http://dx.doi.org/10.12692/ijb/13.3.132-143/ Open access
Understanding the community‟s perception of climate change and adaptations in
the Mid Hills of Pakistan
Laila Shahzad*1, Arifa Tahir
2 and Faiza Sharif
3
Biologia-Pakistan (under review)
Livelihood adaptations, poverty and climate change: Evidence from the Balakot
mountainous community of Pakistan (Submitted)
Quantifying livelihood vulnerability of rural mountainous communities to
climate and land use change: A case of Balakot Pakistan (Submitted)
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