DEPARTMENT OF ECONOMICS UNIVERSITY OF PESHAWAR …
147
i AN ASSESSMENT OF INLAND DESTRUCTIVE FISHING PRACTICES IN DISTRICT CHARSADDA, PAKISTAN SUBMITTED BY: MUHAMMAD QASIM (PhD Scholar) SUPERVISED BY: PROF. DR. MUHAMMAD NAEEM DEPARTMENT OF ECONOMICS UNIVERSITY OF PESHAWAR (SESSION 2014-2015)
Transcript of DEPARTMENT OF ECONOMICS UNIVERSITY OF PESHAWAR …
i
AN ASSESSMENT OF INLAND DESTRUCTIVE FISHING
PRACTICES IN DISTRICT CHARSADDA, PAKISTAN
SUBMITTED BY:
MUHAMMAD QASIM
(PhD Scholar)
SUPERVISED BY:
PROF. DR. MUHAMMAD NAEEM
DEPARTMENT OF ECONOMICS
UNIVERSITY OF PESHAWAR
(SESSION 2014-2015)
ii
Author’s Declaration
I Muhammad Qasim hereby state that my PhD thesis “AN ASSESSMENT OF
INLAND DESTRUCTIVE FISHING PRACTICES IN DISTRICT
CHARSADDA, PAKISTAN” is my own work and has not been submitted
previously by me for taking any degree from University of Peshawar, or anywhere
else in the country/world.
If my statement is found to be incorrect any time, even after my graduation, the
university has the right to withdraw my Ph. D degree.
Muhammad Qasim
Date: 15-04-2019
iii
Plagiarism Undertaking
I solemnly declared that research work presented in the thesis “AN ASSESSMENT
OF INLAND DESTRUCTIVE FISHING PRACTICES IN DISTRICT
CHARSADDA, PAKISTAN” is solely my research work with no significant
contribution from any other person. The complete thesis has been written by me, and
small contribution/help wherever taken has been duly acknowledged.
I understand the zero tolerance policy of the HEC and University of Peshawar
towards plagiarism. Therefore, I as an Author of the above titled thesis declare that
no portion of my thesis has been plagiarized and any material used as reference 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 Ph. D degree, the University reserves the rights to
withdraw/revoke my Ph. D degree and that HEC/University website on which names
of students are placed who submitted plagiarized thesis.
Student/Author Signature:_______________________________
Muhammad Qasim
Dated: 15-04-2019
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Acknowledgements
This dissertation would not have been completed in this form without the intellectual
guidance and constructive comments of all the faculty members of the author‘s advisory
committee and assistance from various institutions and individuals.
This dissertation is the result of enormous support provided by my advisor Prof. Dr.
Muhammad Naeem and members of the Graduate Studies Committee, Prof. Dr. Zilakat
Khan Malik, Dr. Amjid Amin, Dr. Naila Nazir and Prof. Dr. Himayatullah Khan. Without
their professional guidance, encouragement and inspiration, completion of this dissertation
would have been impossible. Thanks to Dr. Anwar Hussain, Assistant Professor, PIDE
University, Islamabad for sparing his valuable time and clear guidance throughout my
research. I am deeply indebted to my brother Dr. Said Qasim, Assistant Professor,
University of Baluchistan, who gave me very useful comments and suggestions that
facilitated shaping the present form of this research. I would like to express sincere
appreciation and gratitude to him for his invaluable guidance, critical comments, enormous
suggestions, great encouragement and constant support throughout the study period. I am
deeply grateful and indebted to him. Without his guidance, I would not have been able to
accomplish my studies.
I would like to thank Mr. Amir Hamza, Deputy Director, Fisheries Department, Khyber
Pakhtunkhwa, for his valuable time, provision of secondary data and arrangement of
meetings with fisheries watchers and fishermen. I am thankful to various government
departments in Khyber Pakhtunkhwa for providing the necessary data required in the
completion of this dissertation. In this regard, the data provided by Irrigation and Power
Department, District Charsadda, Population Census office Charsadda, Archives and
Libraries Department Khyber Pakhtunkhwa, is highly acknowledged. I am also thankful to
those students and colleagues in Government Postgraduate College, Charsadda, who not
only assisted me in field work but also provided field site accommodation during my data
collection period in the study area. Without their support, it would have been impossible
for me to carry out this research study. I pay my sincere thanks to all those fishers in the
study area, who agreed to provide their useful time and valuable information which helped
me complete my research work.
Finally, I would like to thank my friends and family for their continued support and
encouragement throughout my study period. It would be difficult to write the names of all
friends who supported me during field visits, data collection, and meeting respondents. I
would like to express my deepest gratitude to my family, who has provided support and
encouragement throughout my research work. I would not be what I am today without all
of them. I would like to thank my wife, daughters Maryam and Mahrosh and my son
Haroon for their patience due to lack of time for them. Last but not the least, I would like
to extend profound gratitude to my parents, brothers, sisters and other colleagues who
always remembered me in their prayers. Their strong moral support, during my study
period at the University of Peshawar gave me enormous encouragement for studies.
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Table of Contents
Chapter Title
Page
Title Page i
Submission Page ii
Approval Page iii
Acknowledgements iv
Table of Contents v
List of Tables vii
List of Figures ix
List of Acronyms and Abbreviations x
Abstract xi
1 Introduction 1
1.1 Background of the study 1
1.2 Statement of problem 3
1.3 Justification of the study 4
1.4 Research Questions 5
1.5 Aims and Objectives of the study 6
1.6 Hypotheses 6
1.7 Scope and limitations 7
1.8 Organization of the study 7
2 Literature Review 8
2.1 Destructive Fishing: Definition, concept & classification 8
2.2 The concept of common pool resources & tragedy of the
commons
12
2.3 Causes of destructive fishing practices 14
2.4 Impact of destructive fishing practices on fishermen
livelihoods
17
2.5 Factors affecting fish consumption 26
2.6 High vulnerability of fishery communities 28
2.7 Conceptual framework 29
2.8 Summary 32
3 Profile of the Study Area and Fishing Industry Scenario of
Khyber Pakhtunkhwa
34
3.1 Selection of the study area 34
3.2 Location and Boundaries 35
3.3 Aquatic Resources of Khyber Pakhtunkhwa 37
3.4 Fisheries regulations of KP 39
4 Research Design 50
4.1 Data collection 50
4.2 Research framework 51
4.3 Sample size 51
4.4 Data processing and analysis 55
5 Results and Discussions 68
5.1 Results of FGDs on DFPs 68
5.2 Socioeconomic Characteristics of fishermen for 2001 and
2016
68
5.3 Conservation measures 71
5.4 Causes of DFPs 74
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5.5 Impact of DFPs on fishermen livelihoods 80
5.6 Factors affecting fish consumption of selected
households
86
5.7 Hypothesis testing 94
5.8 Discussion 97
6 Summary, Conclusions and Recommendations, and
Limitations
101
6.1 Summary of the findings 101
6.2 Conclusions 103
6.3 Recommendations 107
6.4 Limitations or Recommendations for future research 109
References 111
Appendix A Questionnaire 128
Appendix-B Focused Group Discussion 133
Appendix-C Interviews with the officers of Fishery
Department, Khyber Pakhtunkhwa
135
Annexure-D Method of the calculation of sample size
136
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List of Tables
Table Title
Page
2.1 Rural livelihoods from micro perspective 19
3.1 Aquatic resources of Khyber Pakhtunkhwa 37
3.2 Summary of the small inland food fishes of river Swat/Kabul 38
3.3 Licensing and fee structure 39
3.4 Species of fish and prohibitions, (Schedule 1 of Fisheries Ordinance
1961)
40
3.5 Maximum amounts acceptable by way of composition for certain
offences
43
3.6 Number of Licenses issued 44
3.7 Fee Realized by Licenses 44
3.8 Legislation cases in different districts of Khyber Pakhtunkhwa 45
3.9 Leasing of dams 46
3.10 Departmental Income (Revenue) 47
3.11 Fish farm established 47
3.12 District Wise Non Trout Fish Production (Metric Tons) 48
3.13 Publicity information and research undertaken 49
4.1 Nature, source and purpose of data collected 50
4.2 Population Size and Statistical Sample 54
4.3 Justification for the DFPs variable 56
4.4 Fishing practices used in the construction of DFPs 57
4.5 Causes of DFPs 59
4.6 Justification of variables for fish consumption 62
4.7 Statistical techniques used for the analysis 67
5.1 Socioeconomic characteristics of fishermen in 2001 and 2016
(n=286)
69
5.2 Average years of formal education 71
5.3 Distribution of land holdings by type of fishers 71
5.4 Impact of licensing on access to water resources 72
5.5 Impact of fishery watchers on access to water resources 72
5.6 Impact of fishery litigation process on access to water resources 73
5.7 Fish size and amount 73
5.8 Correlation and other characteristics of explanatory variables
selected for the
75
5.9 Summary of the step wise regression model 77
5.10 ANOVA of the regression models 78
5.11 Coefficients of the explanatory variables included in the regression
model
79
5.12 Total value of livelihood assets from 2001 to 2016 for Type I
Households
82
5.13 Total value of livelihood assets from 2001 to 2016 for Type II
Households
83
5.14 Total value of livelihood assets from 2001 to 2016 for Type III
Households
85
5.15 Statistic results of Kruskal–Wallis test of livelihood capital
subcomponents
86
5.16 Comparison of Per capita fish consumption of different countries 88
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5.17 Reasons of fish consumption 89
5.18 Frequency of fish consumption 89
5.19 Preferences for fish species 90
5.20 Prices of different species of fish 90
5.21 Correlation and other characteristics of explanatory variables
selected for the regression model.
92
5.22 Table Summary of the regression model 92
5.23 Table ANOVA of the regression models 93
5.24 Coefficients of the explanatory variables included in the regression
model
94
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List of Figures
Figure Title
Page
2.1 Electrifishing 11
2.2 Undersized nets 12
2.3 A framework for comprehending characteristics of livelihood outcomes of
inland fisheries
21
2.4 The wheel approach of improving fishermen livelihoods 22
2.5 The sustainable livelihoods framework 23
2.6 Fishermen livelihoods assets in the current research 24
2.7 Vulnerability/risk analysis table 28
2.8 Conceptual Framework 31
3.1 Map of the study area 34
5.1 (a) Age structure of farming fishers 70
5.1 (b) Age structure of fishing farmers 70
5.1 (c) Age structure of occasional farmers 70
5.2 Fishermen perception on fisheries resources 73
5.3 Livelihood Assets for Type I Households 82
5.4 Livelihood Assets for Type II Household 84
5.5 Livelihood Assets pentagon for Type III Households 85
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List of Acronyms and Abbreviations
BC Before Christ
DI Khan Dera Ismail Khan
DCR District Census Report
DFID Department For International Development
DFPs Destructive Fishing Practices
DRL Daily Rod Line
FAO Food and Agricultural Organization
FGD Focused Group Discussion
FLIRES Fisheries Livelihoods Resilience Check
GDP Gross Domestic Product
GoP Government of Pakistan
GPA Global Program Action
HH Households
KG Kilogram
Km Kilometer
KP Khyber Pakhtunkhwa
LAs Livelihood Assets
LIFDCs Low Income Food Deficient Countries
M.A Malakand Agency
NGOs Non Government Organizations
NR Natural Resources
RAPFISH Rapid Assessment for Sustainability of Fisheries
SMEDA Small and Medium Enterprise Development Authority
SRL Seasonal Rod Line
UNEP United Nations Environment Programme
USA United States of America
WIOMSA Western Indian Ocean Marine Science Association
WWI World War First
WWII World War Second
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Abstract
Inland fishing is common in Pakistan and is a vital component of human diet, source of
food security, livelihoods and recreation. Despite being so much important, the freshwater
fisheries have not yet been given proper attention in Pakistan. The fish stock in the rivers is
continuously on the decline and destructive fishing practices on the increase, leading to
serious decline of fishes in the inland rivers of the study area. The monetary losses for the
neighboring communities and society resulting from such damage are more than the direct
individual benefits made by the users of these destructive methods.
Fishermen and people residing near water bodies are the main actors in fishery related
issues and their knowledge and perceptions about destructive fishing practices and
conservation of fishery resources are valuable. Therefore, this study was conducted in
district Charsadda Khyber Pakhtunkhwa province of Pakistan to pinpoint the major socio-
economic drivers of destructive fishing practices, and its impact on fishermen livelihoods
and fish consumption. Data was collected through a household survey from 286
households from nine fishermen concentrated villages of district Charsadda, using two
stage cluster sampling method. The households were divided into three groups (Type I,
Type II and Type III) in order to distinguish between households based on different
characteristics.
The fisher‘s socio-economic characteristics were analyzed through simple statistics such as
frequencies, percentages, averages and standard deviations. Stepwise multiple linear
regression models were used to identify the drivers of destructive fishing practices,
multiple regression for factors affecting fish consumption and Livelihood Asset Pentagon
for impact of destructive fishing practices on fishermen livelihoods. The stepwise multiple
linear regression model revealed that out of a total of seven variables five were negatively
and two positively correlated to DFPs. The results of livelihood asset pentagon revealed
that fishermen livelihood assets deteriorated in the last fifteen years due to reduction in the
size and amount of fishes in the rivers. The findings of this study led to specific
recommendations for combating the problems of DFPs and policy measures to reduce
pressure on fishery resources in the area, such as awareness and environmental education,
creation of alternative livelihoods opportunities and involvement of community in the
conservation of natural resources.
1
Chapter 1
Introduction
1.1 Background of the study
Small-scale inland fisheries are an important source of livelihoods for millions of poor
people (Stanford et al., 2017), particularly in developing countries. However, they are
extremely complex, and in many cases poorly understood (Welcomme et al., 2010). The
importance of the fisheries and aquaculture sector to the livelihoods of people living near
coastal areas is well documented (APFIC, 2010; Whittingham et al., 2003; Bene et al., 2007;
World Bank, 2004; World Bank, 2008), however, less is known regarding inland fisheries
(Bahadur et al., 2017). Some research studies have enumerated multiple ways in which fish
and fishing contribute to the livelihoods of rural people living in inland areas of developing
countries (Nasielski, et al., 2016), but small scale inland fisheries are vulnerable to global
and local stresses (Stanford et al., 2017). Inland fishing is common in Pakistan, taking place
in rivers, streams, lakes, ponds, dams, barrages and wetlands in almost all provinces and
districts (GoP, 2013a). Pakistan ranks 18th
in inland fisheries production in the world,
producing some 120,240 tonnes of fish in 2012 and 123,155 tonnes in 2013 (FAO, 2015).
The share of inland fisheries in total fish production in Pakistan has remained 21%, 30%,
23%, 30% in 1947, 1960, 1984, and 2009, respectively (GoP, 2013b). It is estimated that
some 180,000 people in the country, with almost 20,000 small craft are involved in inland
fisheries, mostly part-time, for their livelihoods (FAO, 2009; GoP, 2013a).
Fishing is a very old practice that dates back to at least the beginning of the Paleolithic period
about 40,000 years ago (Akhtar, 2015). There are various fishing practices, which include
hand gathering, spear fishing, netting, angling and trapping etc., however, recreational,
commercial and artisanal fishers use different techniques. Contemporary fishing practices
have grown out of the old practices, which are still used in artisanal fisheries but are different
by being less capital, vessel, and fuel-intensive than the current mechanized fishing methods
(Misund, Kolding, & Fréon, 2002). When the stock of fish in the rivers diminishes, fishing
methods become increasingly severe and the use of destructive fishing gears i.e. blasting, use
of small mesh nets, chemicals and electrofishing become attractive (Munyi, 2009). The
fishers are forced to adapt to or change fishing practices that can impact livelihoods. But
these human actions have persistently degraded freshwater fisheries resources worldwide.
2
Therefore, knowledge about the status and drivers of destructive fishing practices (DFPs) is
crucial for formulating sustainable fisheries management strategies.
Destructive fishing practices have been given tremendous attention worldwide and there are
varying explanations of what is meant by DFPs (Pet-Soede & Erdmann, 1998). DFPs are
methods that easily result in irreparable damage to aquatic habitats and ecosystem (Akhtar,
2015) or refers to the use of fishing practices in ways or in places such that one or more key
components of an ecosystem are damaged, eradicated, destroyed or cease to be able to offer
essential ecosystem functions (FAO, 2010). However, for the purposes of this study, a
practice is considered destructive which results in direct damage in the fingerling destruction.
Many fishing practices can be destructive if used inappropriately but some practices are
likely to result in irreversible damage. There are several cultural and socioeconomic forces
that have paved the way for the use of destructive fishing gears, which include increase in
settlements near water bodies, poverty, lack of alternative livelihood opportunities, open
access nature of rivers, and lack of rules and regulations to control destruction of fingerling
in inland water sources.
Small scale inland fishes are also very important as food and nutritional security and are
accessible source of high quality cheap animal protein crucial to balance diets in marginally
food secure communities because they are consumed whole with bones and easily absorbed
in human beings (Akpaniteaku et al., 2005). But despite being so much important in human
diet, the per capita fish consumption in Pakistan is 2 kg (Wasim & Parvez, 2007) against the
world average of 17 kg per year (York & Gossard, 2004; FAO, 2009; Garibaldi et al., 2004).
Globally fish meat provides three billion people almost 20 percent and 4.3 billion about 15
percent of animal protein (Garibaldi et al., 2004). Finances and earnings have a tremendous
influence on fish consumption and the consumption and nutritional status of fisher‘s family
members is their capacity to earn money which, in turn, depends on the nutritional health of
household members. Empirical evidence reveals that when income increases, fish is
consumed more than staple food (Ahmed & Lorica, 2002).
This research study investigated data on the proximate or direct drivers, i.e. human actions
that directly affect the loss of fisheries resource, and uses the word ‗driver‘ to specify
proximate drivers (Hosonuma & Liebeler, 2012). This is essential for the development of
strategies and policies that intend to improve current trends in fishing activities towards a
more environmental and biodiversity friendly outcome. Secondly, the study find out the
3
impacts of adapting fishing practices on fisher assets in different cohorts in the region, with a
focus on the impacts of Destructive Fishing Practices. Specifically, the study compares
changes in livelihood and households assets from 2001 to 2016. An understanding of
changes in socioeconomic condition of fishers will help inform policy makers and line
agencies to mitigate the impacts of decreased fish stocks. The study also investigated factors
affecting fish consumption of the fishermen communities.
We selected district Charsadda as the study site because it is considered as the most fertile
region of Khyber Pakhtunkhwa due to the presence of rivers, which has made it agrarian.
Secondly, fishing is very common in Jindi, Khiali and Kabul Rivers flowing in this area and
are the major tributaries of the Indus River System. Thirdly, fishing is one of the major
economic activities in this region, for example in 1998 almost 35% of all employed
population worked in the agricultural and fishery sectors (GoP, 2001).
1.2 Statement of the problem
The decline in inland fishery resources has become a major concern in many countries
worldwide. Due to the open access nature the past and current record of decline in fishery
resources is not a good omen. When there are no restrictions on fishers, they competitively
exploit the fishery resources quickly and inefficiently. The common pool nature of fishery
resources has made it a great challenge for fishery managers and conservationists to deal with
the continuous decline in fish stock. When individuals ignore the common property
externalities and overexploit the limited natural resources, resulting in the ‗tragedy of the
commons‘. In this competition and self interest fishers use destructive fishing methods. The
use of destructive fishing gears is one of the primary causes of fisheries decline globally
(Mozumder, Shamsuzzaman, Rashed-Un-Nabi, & Harun-Al-Rashid, 2018), and is the key
management concern to deal with. Freshwater fishery resources seem to be the most
persistently degraded worldwide, with approximately 20% of freshwater fish species is
becoming extinct, threatened, or endangered in recent decades (Revenga, 2000). Out of the
total 200 species of the Indus River system, a total of 32 fish species are known to be endemic
to Pakistan (GoP, 2013). For example, the famous game fish mahsheer (Tor putitora) which
is considered endangered by the International Union for Conservation of Nature (IUCN) is
becoming rare due to destructive fishing methods and overfishing (Rafique & Khan, 2012).
Similarly, a study conducted at the River Swat in district Charsadda, Khyber Pakhtunkhwa
Province of Pakistan, reports six species as missing in comparison with past records
4
(Yousafzai, Khan, & Hasan 2013). The problem of decreasing fish stocks is often
compounded for fishers dependent on fish productivity as both a source of food and income.
If the current trend of decline in freshwater fishery resources continues there will be no
sustainable fishery in the future. This may affect the lives of poor fishermen in terms of low
level of income and employment, reduced fish consumption and ultimately low level of
wellbeing. To avoid this inefficient exploitation of inland fishery resources and stop further
deterioration in the livelihood of rural poor, this study finds out the causes of destructive
fishing practices and its impact on fishermen livelihood. The government shall impose strict
ban on the sale, purchase and use of destructive fishing gears. Provision of alternative
livelihood opportunities, soft loans for aquaculture development, environmental education
and community participation for the conservation and sustainable use of fishery resources
may help reduce the use of destructive fishing gears and lessen its negative impact on rural
livelihoods.
1.3 Justification of the study
Human actions have rigorously affected the state of freshwater ecosystems worldwide
(Revenga, et al., 2005). Freshwater ecosystems represent valuable natural resources and
comprise of 0.01 percent of the total global water but are among the most globally threatened
(Dudgeon, 2014; Vörösmarty, et al., 2010; Sullivan et al., 2011). They are also very important
local food production in checking hunger and supporting rural development. However, studies
on fish fauna and fishing gears reveal that life on earth depends on water but the life within
water is ignored (Shumway, 1999). The fish market which has the potential of diversified
production, income generation, employment and recreation, has been overlooked in the past.
These important functions are endangered by the use of destructive fishing practices e.g. blast
fishing, cyanide fishing, electrofishing and use of small size nets, which continuously destroy
the fish habitat, reducing fish population in the rivers and affects livelihoods and fish
consumption. Destructive fishing methods, especially cyanide and blast fishing are highly
indiscriminate, killing juvenile. This research work focuses on three interlinked challenges of
finding out the drivers of destructive fishing practices, impact of destructive fishing practices
and reducing fish stock on fishermen livelihoods and fishermen fish consumption.
As compared to developed countries, livelihoods of majority of people in developing
countries depend on primary activities including fishing. We are not the first to attempt to
translate such broad concepts from small-scale fisheries and livelihoods policy into analytical
5
tools that fisheries managers and researchers can use, however, different communities have
different livelihood opportunities, lifestyles, fish consumption habits, fish catching techniques
and perceptions of fishing. Secondly, most of these studies are undertaken on marine waters
and coastal communities and limited research is available on inland water sources and
livelihoods of rural communities. Thirdly, inland fisheries are conducted on smaller scale,
where fishers are extremely poor as compared to marine fisheries. Fourthly, the decline of
fish in ocean and inland water bodies differ significantly and the use of livelihoods assets
pentagon for the analysis of fishermen livelihoods on current lines has never been undertaken
before and no evidence of such study is available regarding destructive fishing methods and
its impact on rural livelihoods in Pakistan and particularly in Khyber Pakhtunkhwa.
1.4 Research Questions
This study has investigated the causes and impacts of inland DFPs in district Charsadda,
Khyber Pakhtunkhwa. The fisheries sector has the potential to provide endless benefits in the
form of employment opportunities, income generation and important protein to local
communities if properly managed. So, there is certainly a need to study the causes and
impacts of DFPs. Given the current local and global depletion in river fisheries, it is no longer
acceptable to consider such high levels of mortality as unavoidable. The present study within
the context of the causes and impacts of DFPs is concerned with the following research
questions:
1. What are the major socioeconomic causes/drivers of destructive fishing practices in the
study area?
2. What is the impact of destructive fishing practices on fish populations/stock in rivers of
the study area?
3. What is the impact of destructive fishing practices on fish consumption and livelihoods of
fishermen in the study area?
4. Is there any regulatory framework available to deal with destructive fishing practices?
5. How the community, government and other agencies shall be motivated to mitigate the
negative causes of destructive fishing practices?
6
1.5 Aims and Objectives of the study
This research work is intended to find out the main reasons and impacts of Destructive
Fishing Practices and achieve the following objectives;
1. To find out the socioeconomic drivers of destructive fishing practices in the study area;
2. To determine the impact of destructive fishing practices on fishermen livelihoods in the
study area;
3. To find out fish consumption determinants of selected fishermen;
4. To discover the current regulatory structure for checking destructive fishing practices in
the study area.
1.6 Hypothesis
This research is based on the following hypotheses:
H1: Fishers with more years of formal education are less likely to adopt destructive fishing
practices than fishers with fewer years of formal education.
H1: Livelihood diversity has a negative effect on destructive fishing practices.
H1: Poor people conduct more destructive fishing practices than rich people.
H1: Low cost gears are more destructive than high cost gears.
H1: People living near water bodies conduct more destructive fishing practices than people
residing away from water bodies.
H1: The lower the supply of culture fish in the market, the higher the probability of use of
destructive fishing gears, the higher the supply of culture fish in the market, the lower the
probability of use of destructive fishing gears.
H1: The lower the fish stock in rivers, the higher the use of destructive fishing practices, the
higher the fish stock in rivers, the lower the use of destructive fishing practices.
H1: Destructive Fishing Practices lead to deteriorate fishermen livelihood in the long run.
H1: Fish consumption of the people conducting Destructive Fishing Practices is more than
non fishermen and people residing away from water bodies.
H1: Fisheries ordinance and regulation exists but lack proper implementation.
7
1.7 Scope and limitations
Empirical studies regarding freshwater fisheries economics and especially destructive fishing
practices are limited. For example, table 3.13 of chapter three provides publicity information
and research undertaken in Khyber Pakhtunkhwa, Peshawar on inland fisheries resources. A
total of twenty (20) publications have been undertaken so far only in the Upper Dir area of
Khyber Pakhtunhwa. This study attempted to investigate the socioeconomic drivers of DFPs,
using stepwise multiple linear regression models. The study also finds out the impacts of
DFPs on fish consumption and fishermen livelihoods and provides a base line data for
potential researchers, working on fisheries economics, destructive fishing practices and water
resources especially in Pakistan. The findings of this study provides guidelines for developing
appropriate policies and corrective mechanisms by relevant fisheries agencies, and other line
departments, which can help in the proper use and conservation of the fisheries resources in
Pakistan and particularly in Khyber Pakhtunkhwa. This can help in conservation of fisheries
resources in the rivers from further degradation. The conservation of fisheries resources can
solve problems of protein deficiency, food security and income inequalities in the future.
1.8 Organization of the study
The dissertation is divided into six chapters. The first chapter is introduction of the thesis, in
which the background of the study, justification of research, aims and objectives, hypotheses,
scope and limitations of this research is given. The second chapter provides description of the
DFPs conducted in the study area and in depth literature review on DFPs and its impact on
fishermen livelihoods and consumption. Chapter three is about selection of the study area,
location and boundaries including geography, demographic and economic characteristics, and
aquatic resources of Khyber Pakhtunkhwa with a summary of the small inland fishes of the
study area. This chapter also discussed the main features of fisheries regulations and
conservation measures in the study area. The fourth chapter is about research methodology
used in this dissertation, with detailed sampling procedures and techniques of data analysis.
Chapter five presents results and discussion of the study. This chapter highlight the socio-
economic characteristics of the fishermen, the impact of conservation measures on the
respondents, the causes of DFPs and impact of DFPs on fishermen livelihoods and
consumption. Chapter six discusses the summary, conclusions and recommendations for
combating DFPs in the study area.
8
Chapter 2
Literature Review
Freshwater fisheries resources sustain the welfare of millions of poor households across the
globe. However less attention has been given to the proper management of inland fisheries
resources. The topic is inadequately understood and documented in the overall fisheries
management debate locally and internationally. Considering these challenges and state of
affairs of inland fisheries and use of Destructive Fishing Practices (DFPs), it is essential to
investigate inland fisheries with respect to their significance, challenges and threats to water
bodies and organisms. This chapter clarifies concepts regarding DFPs and discusses different
destructive fishing gears being used in the study area, and reviews studies regarding causes
and impacts of destructive fishing practices around the globe and Pakistan. The focal point is
on the causes of destructive fishing practices and the association between DFPs and various
socio-economic factors of fishermen.
2.1 Destructive Fishing: Definition, concepts and classification
2.1.1 Definition
Fishery is defined as ―the exploitation of living aquatic resources held in some form of
common or open access property regime‖ (Smith et al., 2005). DFPs have been given
tremendous attention worldwide and there are varying explanations of what represent a DFP
(Pet-Soede & Erdmann, 1998). DFPs are methods that cause irreparable damage to water
bodies and ecosystem (Akhtar, 2015). It refers to the use of fishing practices in ways or in
places such that one or more key components of an ecosystem are damaged, eradicated,
destroyed or ceases to be able to offer essential ecosystem functions. However, for the
purposes of this study, a practice is considered destructive which results in direct damage to
the fingerling destruction. Different writers have identified different destructive fishing
techniques. Various fishing techniques are destructive if used wrongly but a few techniques
are liable to result in irreparable damage to the natural habitat. However following are some
of the DFP conducted in the study area.
2.1.2 Description of various destructive fishing gears used in the study area
Fishing is a very old practice and has developed during the years from traditional high cost,
low yield methods to low cost, more efficient methods. There are various fishing methods and
9
tactics, which include catching fish through bare hands, using pierce spear for fishing and
using different kinds of nets and trapping. Commercial fishers use costly and efficient
methods than recreational and artisanal fishers. Contemporary fishing practices have grown
out of the old practices and systems still used in artisanal fisheries but are different by being
less capital-, vessel-, and fuel-intensive than current mechanized fishing methods (Brandt,
1984). Recreational fishers fish for sports or pleasure; commercial fishers fish for income and
high profits, whereas artisanal fishers use traditional low-cost techniques for survival (Akhtar,
2015).
2.1.2.1 Dynamite or Blast Fishing
In this method the fish is stunned or killed by using explosives or blasting material (Akhtar,
2015). The dead or stunned fish is then collected after the blast but it also kills a lot of non-
targeted fingerling and other species. It was first introduced by the Japanese during WWII
(Pet-Soede & Erdmann, 1998), however this method was known prior to WWI, as this
activity is mentioned by Ernst Jünger in his book Storm of Steel (Akhtar, 2015). A variety of
materials including fertilizers (e.g. urea, ammonium and potassium nitrate -NH4NO3; KNO3)
are combined with kerosene in a bottle and ignited using waterproof fuses, illegally purchased
dynamite (often from civil engineering projects, home-made bombs, grenades and TNT are
used in blasting (Cesar, 2000; Pet-Soede et al., 2000; Haylor, 2003). Sometimes such
materials are obtained from police, military personnel or mining companies. Although it has
been banned in nearly all countries of the world including South East Asia (Cesar, 2000;
Haylor et al., 2003), but it is still carried out regularly in most of the countries as it is an
efficient, quick and easy way of catching fish (Hodgson & Liebeler, 2002; Haylor, 2003).
Blast fishing has resulted in decline of fish populations (Torell et al., 2004) and has affected
the livelihoods of poor fishermen.
2.1.2.2 Poison Fishing/Cyanide fishing
Cyanide is a very dangerous industrial chemical applied in gold mining, electroplating and
steel refining (Haylor et al., 2003). In the beginning cyanide was used to shock and capture
fish for aquariums but later this chemical was applied for catching fish used for eating
(Akhtar, 2015). It has been used since the 1980s for catching fish (Haylor et al., 2003),
because it is considered an effective, fast and relatively inexpensive, and easy method of
catching fish. Although the degree of damage vary based on a number of different causes
10
together with the type and quality of poison used, quantity of chemical and chemical mixed
with other items. Poison fishing is one of the dangerous methods as it kills every living thing
in the rivers. The suffocating effects finally cause the fish die and the fish then floats over the
surface of water and then fishers collect and sell or use them for sale or personal
consumption. The small fish are more susceptible to the effects of poison than the larger fish
(Munyi, 2009; Ochiewo, 2004). The income and profits from DFPs are higher than the
conventional fishing techniques (Cesar, 2003) but they exhaust the resources that shape the
basis of their income.
2.1.2.3 Electro fishing
Electric fishing is one of the most popular and easy method of catching fish in district
Charsadda. In this method electric field is produced in water to stun and gather fish. Electric
current is passed through a bare wire connected to steel net for collecting fish. A minimum of
two persons are needed to operate electrofishing, one to operate the electric current in water
and the second collects the stunned or dead fish with a small hand net. Initially it was used as
a general scientific assessment method to collect sample of fish for determining the total
population, density and space composition (Akhtar, 2015) and if this method is carried out
suitably, it results in no direct damage to fish and the fish go back to its natural position in
about two minutes after being stunned. This method is easy, less time consuming and fishers
use it as a recreational activity. It harms and kills the juvenile fish and due to its efficiency it
has reduced the size and number of fish in the rivers (Figure 2.1).
11
Figure 2.1 Electrofishin
Figure 2.1: 2.1a: show electrofishing, using electric generator for fishing.
2.1b: show fish that is injured with electric shocks produced by electric generator.
2.1.2.4 Small mesh size/Banned nets/Undersized nets
Due to technological advancement artisanal fishers have inclined towards using efficient but
DFPs, for example using small mesh-size nets that catch large quantities of fingerling, thereby
challenging sustainable use of fisheries resources (Munyi, 2009). The size and design of nets
applied is determined by the species targeted. The pervasive use of small mesh size nets is
due to its obvious effectiveness in catching small fish (Munyi, 2009; Ochiewo, 2004). The
popularity of destructive fishing gears, undersized mesh nets, together with rising number of
fishermen, are key management concerns to deal with (UNEP, 2007). Due to the open access
nature of fisheries there is limited mesh size limits or regulations on inland fisheries in the
province. Most of the fishers state that they use specific gears/nets for selective specie but the
reality is different, they focus on selective specie and consider the bycatch a blessing in
12
disguise, hardly ever a fisher will release the juvenile fish. In the study area environmentally
harmful nets, which are prepared from nylon and have a very small mesh are used to increase
fish catches (Figure 2.2).
Figure 2.2 Small mesh size nets and fish captured
Figure 2.2: The figure 2.2a on the left top shows the small net size. Figure 2.2b on top right
shows the small net with caught fingerlings. Figure 2.2c bottom left shows fishermen are
collecting fingerlings from the net. Figure 2.2d bottom right shows the fried fingerlings that
are available for sale near the river banks of Sardaryab.
2.2 The concept of common pool resources and tragedy of the commons
Managing natural resources that are held in common is a huge and serious challenge (Baden,
& Noonan, 1998). Fisheries and forests are examples of two common pool resources that are
13
currently of great concern in this period of major ecological challenges (Ostrom, 2008).
Common pool resources include those resources where rights are held by communities of
individuals, government and non-government organizations, and their use can be regulated in
a variety of ways by a variety of institutions (Common and Stagl, 2005; Libecap, 2008).
However, when they are owned or controlled by no one and anyone can enter or harvest they
are referred to as open access resources (Ostrom, 2008). With no rights to the unharvested
resources, users are under constant threat of ‗use it now or lose it‘ (Wills, 2006; Tietenberg
and Lewis, 2009), and individual interest undermine society‘s best interest (Baden, &
Noonan, 1998).
When individuals make decisions based on personal interests and ignore the common
property externalities that they cause to others, market failure occur leading to
overexploitation of the resources. Every individual is locked into a system that compels him
to increase his benefit without limit, in a world that is limited. Therefore freedom in a
commons brings ruin to all (Hardin 1968). At the stake is the prosperity and survival of both
the people and environment. This open access nature of resources is commonly but
incorrectly known as ‗tragedy of the commons‘ but in fact open access resources may be
overexploited but common property resources need not suffer overexploitation and their
allocation can be regulated in a way that avoids tragedy (Ostrom, 2008). The tragedy of the
commons was originally described by William Forster Lloyd in his 1833 two lectures on
population. Lloyd and later Hardin argued that when many individuals reap the full benefits
of a limited resource, whereas society shares the costs, the tragedy results (Baden, & Noonan,
1998). However, in his classic article, ―The Tragedy of the Commons,‖ leading ecologist
Garrett Hardin confused open access commons with commons that are the joint property of a
community. While Hardin correctly pointed out that valuable open access common pool
resources would be overharvested, his conclusion of an inevitable tragedy was too sweeping
(Ostrom, 2008). This clearly indicates that the problem of destructive fishing practices is due
to the common pool nature of the fisheries resources. Conflicts over the management of
common pool resources are not only material (Adams et al., 2003) but depend on the
perceptions, beliefs, myths and ideas of local people. Therefore the proper management of
common pool resources needs a profound understanding about the existing or potential
reasons of conflicts in resource use.
14
2.3 Causes of destructive fishing practices
Many research studies have acknowledged the fact that DFPs cause serious threat to the
fisheries. For example, Lampe et al., (2017) studied the key drivers and determinants that
influence the continuation of destructive fishing techniques and solutions for fisheries
conservation in a socio-cultural perspective. The study revealed that perseverance on the
accomplishment of economic needs, growing market demand, construction of settlements,
social composition of the working clusters of fishers, social and cultural perceptions regarding
water and its components as an open access, and poverty are the chief drivers that affected
behavior towards destructive fishing practices. The authors identified nine categories of the
main driving factors to destructive fishing practices through the ethnographic method in
South Sulawesi, Indonesia. The first three variables are related to fish catch and include
factors like, energy and time efficiency in catch, value of the quantity and quality of catch and
principles of maximizing current catches. Another three variables are related to fishermen
perception of the fishery resources including, confidence and feeling of compatibility with
some fishing practices, cultural perceptions in using destructive fishing practices and
considering water and its resources as the grace of God to be used by human. Another two
factors are related to fishermen social and cultural bonds and include the well-preserved
working group of traditional fishermen and existence of group relationship patterns between
fishermen and the law enforcement agencies and destructive fishing materials sellers. The
ninth category of variables includes the relative stability in demand for commodities and fish
prices in the region and adoption of technological innovation in fishing. The author however,
utilized perceived informal from fishermen and personal observations as primary data and did
not use any scientific methods for the gathering and interpretation of data.
The economic and social effects of DFPs on coastal fisheries and community livelihoods in
Kiribati Island were studied by (Ram-Bidesi, 2011). This research study applied different
techniques to gather primary and secondary data, including review of relevant literature,
personal observation for fishing gears and practices, household socioeconomic surveys and
interviews. The study also analyzed fisheries management regime by taking into
consideration the institutional arrangements, and an economic assessment of fishing methods
by examining destructive fishing, and an analysis of opportunity costs of other activities and
alternative livelihoods. The study found that the main reasons for the use of DFPs includes,
growing population, demand for resources, fish as the key supply of food and protein,
15
increased fishing pressure by different methods and intensity of fishing effort (Ram-Bidesi,
2011).
Gurumayum, (2009) studied that there is lack of new and more efficient and reliable fishing
gears due to which the old and outdated fishing gears are used. Mostly DFPs, like dynamiting,
poisoning and electric fishing is employed. According to this study selection of fishing gears
and practices depends on causes like physiography of the water source, nature of fish stock,
features of the raw material from which gears are made-up and living standard.
Khan & Khan (2011) finds out that the new fishing methods and technologies, indebtedness
of fishers, reduced catches, and failure of fishing policies are the main reasons for using
inappropriate fishing techniques. The main cause of illegal fishing practices is declining fish
stocks (Akhtar, 2015), which includes taking juvenile fish, fishing in waters closed for
fishing, or taking more fish than allowable. A research study was conducted on the
socioeconomic impacts of DFPs in Kenya (Munyi, 2009). The basic objectives of this study
was to observe the degree of occurrence of destructive fishing activities, the socioeconomic
determinants that reveal the continued occurrence of destructive fishing activities, and the
actions to discourage the DFPs in the area. The research reveals that 70% of the households
use destructive fishing techniques and 48% of them who apply DFPs are aged 18-35 years.
According to the author the most important drivers for applying destructive fishing techniques
were; seeming efficiency of DFPs, accessibility to economic but destructive devices in the
local market, the power of nomad fishermen and their lack of concern for fisheries resources,
younger fishers dominate use of DFPs, declining catches and fear amongst the fishers, passive
recognition of some destructive fishing methods at local level and lack of education among
the fishermen. The author further highlighted that majority of fishers population around the
world express a rising amount of insecurity due to being poor and highly dependent upon
natural resources, which insecurity is often accumulated by declining resources, growing
population, inadequate alternative livelihoods, inadequate access to land, unsound use and
preparation of land, rivalry and differences over natural resources (Munyi, 2009; Pomeroy
and Rivera-Guieb, 2006). According to the author DFPs have resulted in the dilapidation of
large areas of previously useful coral reef environment.
Fast population expansion and urbanization that is present in the Western Indian Ocean lead
to raise stress on conventional inshore fishery resources (Richmond, 2002). Ray (1968)
revealed that the growing consequence of destructive fishing techniques, particularly seine
16
nets and blasting may degrade the fishing resources of Tanga within a decade. Shumway
(1999) described that increase in population, poverty and the lack of alternative livelihoods,
extensive profit-making ventures with motives of maximizing temporary profits and
overfishing are the reasons of using destructive methods in fishing (Clark et al., 1992).
Another research study by (Cinner, 2009) find out that fisherman applying destructive fishing
techniques were younger, have low probability to make investment in the fishery, had lesser
fortnightly spending and were relatively poor. He based his analysis on two multivariate
material style of life indices model and find out that fishermen used destructive techniques
with almost 70% precision. This study used thirteen socioeconomic variables to test the
proposition that fishermen with beach seine nets are poor. Lack of environmental awareness
and education has undoubtedly led to the improper use of the environment through DFPs
(Wagner et al., 1999; Munyi, 2009). In Kenya destructive fishing methods is expressed as one
of the main setbacks facing the coral reefs (Munyi, 2009: McClanahan and Shafir, 1999;
McClanahan and Obura, 1995).
Suuronen, et al. (2012) identified that many fish stocks have declined due to excessive fishing
and the use of destructive fishing gears. Van Zalinge, Thuok, & Tana, (1998) examined
fisheries issues in the Lower Mekong Basin from a Cambodian perspective and identified that
Overfishing is certain, as the majority of fishes are caught before having a chance to
reproduce. Van Zalinge, (2002) further investigated the question that ―are the fish resources
over-exploited?‖ He found that generally fish catches may be higher today than in the earlier
period, but individual catch rates have declined, which is due to increase in human
population, larger fishing efforts and increase in the number of fishers. This study revealed
that there is a continuous reduction in fish size and the number of species has reduced in
catch. Similarly, Mangi, & Roberts, (2006) found that the size and maturity stage at first
capture for 150 of 195 species caught by different methods was well below the lengths at
which they mature. They collected data through different fishing techniques and found that in
almost all of the methods, 50.1 ± 22.7% of the catch comprised of fingerling, indicating
serious growth overfishing and use of destructive fishing gears. Eyo, & Ahmed, (2005) are of
the opinion that increase in effort leads progressive decline in the sizes of the fish species
caught. The use of destructive gears and outdated fisheries rules and laws results in declining
fish stocks (Ogutu‐Ohwayo, 2006). The socioeconomic and cultural causes of the use of
destructive fishing practices were also identifies by (Pet-Soede, 1998). This research finds out
17
that declining stocks and lack of enforcement, extreme mobility, lack of education and
poverty are the major reasons behind use of DFPs. In Tanzania it is believed that fishing
efforts have been doubled in less than twenty years (Fridah 2009; McClanahan and Shafir,
1999), and DFPs are common. The output of fisheries is even more reduced by the use of
DFPs and destruction of habitat mostly that of coral reefs (Munyi & Fridah, 2009; King &
Faasili 1999) described that overexploitation and use of destructive fishing practices are the
major reasons for the decline in fish catches. According to them overexploitation occurs due
to increasing population and use of destructive methods due to overly-efficient catches.
Inexpensive gears are related with maximum environmental degradation (Munyi, 2009),
which reveals that if the tendency of the use of low cost gears is high, fishers use highly
damaging techniques. For instance, in Tanzania blasting is considered as one of the major
destructive methods, and is practiced for the last more than sixty years (Wagner, 1999). It is
also a familiar method of fishing in the Comoros regardless of awareness campaigns
(UNEP/GPA and WIOMSA, 2004). Understanding the causes that trigger gear use is
important in finding out the connection between social and environmental change as argued
by (Munyi 2009; Stergiou et al., 1996).
2.4 Impact of DFPs on fishermen livelihoods
Numerous studies have hypothesized that destructive fishing practices, which can degrade
habitat, capture high amount of fingerling and finally lead to decreased yields, are mostly
employed by the poorer segments of society (Cinner, 2009). However, few studies have
empirically tested this relationship. It is an irony, that fishery which has enormous importance
in the livelihoods of a huge population of poor people, but limited research has been
undertaken especially in countries like Pakistan. It is important for the food safety of some
200 million people, particularly in the developing countries, where 1 in 5 individuals rely on
fish as their major source of protein (FAO, 2009). Following is a brief review of some of the
studies showing the importance of fishery sector in food security and livelihood.
The theory of livelihood starts with ―how different people in different places live‖ (Scoones,
2009) or it refers to the earnings in attaining a living, comprising livelihood potentialities,
physical and intangible capital assets (Ferse et al., 2012; DfID, 1999; Scoones, 1998;
Chambers, 1995; Chambers & Conway, 1992). The assets are required for livelihood in order
―to cope with stresses and shocks, and to maintain and enhance capabilities now and in future
18
for a long term well-being‖ (DfID, 1999). In this context, maintaining a living requires
livelihood assets and the fishermen livelihoods depend on the assets they hold. Many research
studies have acknowledged the fact that DFPs cause serious threats to fisheries. These
destructive activities have been expressed as one of the most important setbacks facing the
reefs (McClanahan and Obura, 1995; Munyi, 2009; McClanahan and Shafir, 1999; Ray,
1968). The use of destructive gears and overexploitation (King & Faasili, 1999), and outdated
fisheries rules and laws (Ogutu‐Ohwayo & Balirwa, 2006) results in declining fish stocks.
The livelihood concept has been described through sustainable livelihoods‘ approach (SLA),
which present livelihood as a link between capabilities, fairness and sustainability, and is
commonly recognized with the names of Chambers and Conway (1992). These approaches
try to promote sustainable development in a dynamic way that encircles the many dimensions
of human livelihoods. This concept was applied, adapted and criticized by numerous
researchers. The three components of sustainable livelihoods framework are sustainable
assets, vulnerability context and techniques and interventions (Murray & Ferguson, 2001).
These components are explained and used by (Allison & Ellis, 2001) as a micro policy
strategy for the rural poor and they applied it to understand the strategies of small scale
fishermen communities, faced with unpredictable fisheries resources. Smith et al., (2005)
described that inland fishers‘ livelihoods have been studied in a narrow and stereotyped way
which he calls an old paradigm and modified the livelihoods model presented by (Allison &
Ellis, 2001) combining the traditional livelihood model to the overall determinants of inland
fishery and developed a comprehending characteristic of livelihood outcomes of inland
fisheries. Andrew et al. (2007) used the concept of vulnerability to manage small scale
fisheries as he believes that economic system approaches are hard to operationalize. Glavovic
& Boonzaier (2007) adopted the sustainable livelihood framework to focus on approaches
that poor households employ to access fisheries interventions with the search for livelihood
outcomes. Ahmed (2009) used the concept of sustainable livelihood approach to support the
development of small indigenous species of fish farming in rural Bangladesh and attempted to
advocate the use of livelihoods approach as an analytical tool to facilitate getting a full
understanding of farmer‘s adaptive strategies into the policy field. Weeratunge et al. (2014)
and Voyer et al. (2017) applied the theory of ―lens of social wellbeing‖ and well being
respectively and discussed the social, economic and political dimensions of small scale
fishermen societies. However, these approaches only integrated well being and resilience into
small-scale fisheries but do not provide practical tools for evaluation of fishermen livelihoods.
A more recent study by Stanford et al. (2017) combined the principle of SLA with the
19
methodology of RAPFISH (a rapid assessment for sustainability of fisheries) to the FLIRES
(fisheries livelihoods resilience check) approach, which is used as a widely applicable tool to
evaluate resilience of fishermen livelihood and used six capital assets instead of the traditional
five.
2.4.1 The sustainable livelihoods approach
The sustainable livelihoods‘ approach (SLA) is commonly associated with the names of
Chambers and Conway (1992). Chambers and Conway presented SL as a bridge between
capabilities, fairness and sustainability. This concept was then applied, modified and
criticized by numerous researchers. These approaches try to promote sustainable development
(ecologically, socially, institutionally and economically) in a holistic, people centered and
dynamic way that capture the many dimensions of human livelihoods, and the opportunities
and threats that they are exposed to. The three components of sustainable livelihoods
framework are sustainable assets, vulnerability context and techniques and interventions
(Murray & Ferguson, 2001). These components are explained and used by (Allison & Ellis,
2001) as a micro policy analysis of rural communities.
Table 2.1 Rural livelihoods from micro perspective
Livelihood
Capitals
Access to
these assets is
tailored by
In a perspective
of
Outcome
in strategy
Possessing
actions of
With
outcomes in
terms of
Capitals
Natural
Physical
Human
Financial
Social
Resource
Endowments
Social contacts
Sex
Social group
Age
Ethnic origin
Styles Residents
Movement
Technological
variations
Comparative
prices
Aggregate policy
National
economic
tendency
World economic
trends
Livelihood
strategies
NR-based
behavior
Fishing
Farming
(food)
Farming
(non-food)
Livestock
Nonfarm NR
Livelihood
protection
Earnings level
Earnings
stability
Seasonal
variations
Degree of
threats
Institutions
Regulations
and norms
Land and sea
occupancy
Actions in
markets
Alarms
Storms
Recruitment
failures
sickness
Civil conflicts
Non-NR
based
Rural buy
and sell
Rural
produce
Remittances
Additional
transfers
Envl.
Sustainability
Soils and
earth quality
Water
Fish supply
Forests
Biodiversity
Organizations
Societies
NGOs
Local admin
State
departments
Source: adopted from Allison, E. H., & Ellis, F. (2001).
20
The notion of livelihood is about bringing together the important determinants that influence
the exposure and potency of a person and household strategies for livelihood. These include
the assets held by households, the practices they employ so as to create a satisfactory well
being and to guarantee other objectives such as reduction of risks, and determinants which
assist or restrain various households from getting access to capitals and activities (Table 2.1).
This framework brings together the necessary items that helps in defining the livelihood and
try to create a network between different aspects of livelihoods. The framework started with
the capital assets owned by individuals. Access to these assets is facilitated or hampered
through the policy and organizational aspects of livings. Possession of assets permit
households to form livelihood strategies, which are made of a collection of activities,
including natural resource based and ultimately this approach leads to the final results of
livelihood strategies.
Smith et al., (2005) noted the livelihood functions of inland fisheries and the consequences of
different fishery related policies in developing countries. According to Smith inland fisheries
make a significant input to rural livelihoods but its role has been ignored in developing
countries. He identified fishing as the only hope for the poor in developing countries, which is
semi subsistence livelihood, specialist occupation and part of diversified amassing strategy
(Smith et al., 2005). Smith described that inland fishers‘ livelihoods have been studied in a
narrow sense and a stereotyped approach, which he calls an old paradigm. He describes
fishermen livelihoods diversity as a comprehensive explanation of fishing activities and
modified the livelihoods model presented by (Allison & Ellis, 2001) given below. In this
model he has combined the traditional livelihood model to the overall determinants of inland
fishery and developed the following model:
21
Figure 2.3 A framework comprehending characteristics of livelihood outcomes of inland
fisheries:
Adopted from Smith et al., 2005
Stanford et al. (2017) combined the principle of Sustainable Livelihoods Approach with the
methodology of RAPFISH (a rapid assessment for sustainability of fisheries) to the FLIRES
(fisheries livelihoods resilience check) approach. The method of FLIERS is used as a widely
applicable tool to evaluate fishermen livelihood resilience. The method uses six capital assets
rather than the traditional five. An asset with the name of institutional is added and scaling
applied to check the resilience of fishermen in each of these assets.
Situational characteristics Patterns of relations Outcome
Tremendous
exploitation
of fishery
Low
Opportunity
cost of labour
Open access
nature
fisheries
As a last resort
opportunity
Fisher because
poor
Poor because
fisher
Low
household
income
derived
from
fishing
Economic determinants:
Vulnerability: seasonality, shocks and
trends
Labour market: farm and non-farm
employment
Population pressure: availability of land and
other common pool resources
Effective demand and access to markets
including credit
Fishermen determinants:
Household asset endowment
Livelihood objectives, food security,
nutrition, risk management, cash source,
social networks, recreation, last resort
Fishery determinants:
Seasonality and resilience to combined
yields
Scope for part time fishing, passive fishing
and economies of scale
Costs of fishing: human and financial
capital, , gear, skill etc.
Specific assets, isolation, preferences, social
factors, perverse incentives
Accessibility to markets and effective
demand for fish
Institutional determinants:
processes of discrimination: social
marginalization, class exploitation, political
disempowerment,
state and or community capacity for fishery
management, and governance structure
Envroment
al
unsustaina
bility
22
Figure 2.4: The wheel approach of improving fishermen livelihoods
Modified from Stanford et al. (2017), the wheel of improving fishermen livelihoods
We are not the first ones to attempt to translate broad concepts from small-scale fisheries and
livelihoods policy into analytical tools that fisheries managers and researchers can use.
Research regarding small scale fisheries and livelihoods policy is not limited, however
different communities have different lifestyles, perception of fishing, fish consumption habits,
and fish catching techniques. Ahmed (2009) used the concept of sustainable livelihood
approach to support the development of carp small indigenous species of fish farming in rural
Bangladesh. This study attempted to advocate the use of the livelihoods approach as an analytical
tool that can facilitate getting a full understanding of farmer‘s adaptive strategies into the policy
field. The study revealed that fish farming has contributed to social and financial benefits.
Improvement
in
Livelihoods
Physical
Capital
Financial
Capital
Social
Capital
Institutional
Capital
Human
Capital
Natural
Capital
Advice
Support
Sustainable
practices
Repayment
Loans
Cooperation Trust
within
group
Equipment
Repayment
Motivation
Hope
Strong
leadership Equipment
maintenance
/replacemen
t
Fish
stocks
23
Weeratunge et al. (2014) applied the concept of ―lens of social wellbeing‖ to describe the
socio economic and political aspects of traditional fishermen societies and evaluated its
contribution to fishermen livelihoods. Voyer et al. (2017) have used the well being approach
to evaluate the socioeconomic status of professional fishermen. The paper has used integrated
assessment of the fishing industry and a comprehensive evaluation of the value of fishery for
economic, social and environmental objectives. Thus, it evaluated whether the well-being
method facilitated researchers to react to and tackle the three barriers to effective triple
bottom line appraisal identified in this paper; they are 1) disciplinary obstacle, 2) lack of
social data and 3) practical obstacles in combining qualitative and quantitative data. Andrew
et al. (2007) used the concept of vulnerability to manage small scale fisheries as he believes
that economic system approaches are hard to operationalize. These approaches only
integrated well being and resilience into small-scale fisheries but do not provide practical
tools for evaluation of fishermen livelihoods.
Glavovic & Boonzaier (2007) adopted the sustainable livelihood framework to focus
concentration on approaches, poor households employ, to access fisheries, mediated by
governance organizations and social relations with the search of livelihood outcomes.
Figure 2.5: The sustainable livelihoods framework
Adopted from Glavovic & Boonzaier 2007.
Vulnerability
Context
Shocks
Trends
Seasonality
Livelihood Assets
H N S
F
P
Livelihood
Strategies
Livelihood
Outcomes
Contextual
Analysis Analysis of assets Analysis of
strategies
Analysis of mediating
institutions
Analysis of
outcomes and
tradeoffs
Influences and access
Policies, Institutions
and Processes
Levels of Government
Private sector
Laws
Culture
Policies
Institutions
Higher income
Increased well
being
Reduced
vulnerability
Improved food
security
More sustainable
use of natural
resource base
24
The livelihoods assets of this study are included in the following model (Figure 2.6), which is
adopted from Singh & Gilman (2000), and modified according to the current framework and
livelihoods assets of the study.
Figure 2.6: Fishermen livelihoods assets used in this research
Modified from Singh & Gilman (2000)
Cinner et al. (2011) postulated four situations of gradual severe decline in the mean catch of
Tanzanian fishermen, using redundancy analysis. The overall theme of the paper is on how
environmental change affects societies to adapt to different fishing situations i.e. either they
fish harder or reduce their efforts after change. The paper is an excellent contribution by
emphasizing what fishermen say about environmental change. So the paper is trying to
incorporate fishermen voices in policy making. Fishers were requested to answer questions
regarding successively increasing decline in fish catch. However, the results revealed that, on
the whole fishers change gears rather discarding fishing.
Kasulo & Perrings (2004) developed an excellent model of biodiversity in freshwater
fisheries. The impact of change in the variety of marketed fish species is captured by the
inclusion of biodiversity variables into the cumulative Gordon-Schaefer fishery model,
Physica
l Assets
Natural
Assets
Financia
l Assets
Social
Assets
Human
Assets
Fishermen
Livelihood Assets
Housing Income Membership
Union
council
Educati
on
Licensin
g
Litigatio
n Energy
Supply
Saving
Political
parties‘
membshp
Skill
Watcher
s
Fish size
&
amounnt
Transport
facility
Tools
Availabilit
y
Access
to
credit Law enforcement
agencies
membhp
Contacts with
village elders
Contacts with
other HHs
Kinship support
25
customized to embrace the effect of change in environmental circumstances. The model is
then applied to freshwater fishery in Lake Malawi. It revealed that the open access water
bodies are prone to larger pressure on its stocks at every level of biodiversity than it is in
profit maximizing models. In situations of profit maximizing models, the focus is on single
specie and catch and the output together are maximized, whereas in open access regimes
catches are maximized only at higher levels of bio-economic variety.
McManus et al. (1997) discussed the effects of some DFPs on coral reefs and possible speeds
of recovery. The study was conducted in Santiago Island. The findings of the research reveal
that blasting reduces the capability of growth of coral on the reef slope by about 1/3.
According to the authors blasting continues over time. However, it is supposed that blasting
would become less gainful with the passage of time as the quantity of fish would decline, and
extensive population decline would result in diminishing recruitment of fresh corals and thus
diminishing resilience. However, the study reveals that the use of cyanide is believed to be of
less harm to coral cover than blasting.
Pauly et al. (1989) questions the small-scale fishermen in third world countries. According to
the authors, the small scale fishermen are normally poor, especially their families are so poor
that they experience malnutrition. A very small number of them have alternative employment
opportunities. Pet-Soede, & Erdmann (1998) examined an overview of the DFPs in Indonesia
and then they compared different practices through a balance sheet method. They have
defined different DFPs used in Indonesia and have concluded that blast fishing is the most
destructive of all methods.
Akpaniteaku, et al. (2005) studied that increasing world population creates a threat of food
insecurity, particularly in developing countries. They also discussed fisheries resources and
find out per capita fish consumption and the need for aquaculture and the role of women in
fisheries in some developing countries. According to the authors, decline in fish catch lead to
increase poverty and food deficiency of women and children. Sadovy (2001) conducted study
on the reasons for the decline of wild fish supply in form of groupers in waters. According to
this study despite the enormous numbers of fish trapped compared with numbers of fish
grown out, there is a broadly known shortage of grouper seed and high signs that in several
areas wild seed supplies are waning, particularly those that have been long and catches in
large amount and one of the main reasons for this is the use of destructive fishing techniques.
26
Wasim (2007) explored the growth and instability in inland fish production for two different
periods [Period I (1975-1988) and period II (1989-2002)] of Sindh province of Pakistan. The
study discloses that in phase II, the inland fish production growth rate of six districts
positively and considerably increased, while that of two districts, considerably decreased. The
study also confirms that in phase I, a majority of districts have modest growth with less
volatility in inland fish production in contrast to phase II. The study also discloses that none
of the districts showed permanent increase in the comparative share in any period. Ayub
(2010) analyzed the impact of temperature and rainfall as factors of climatic change on fish
catch in Pakistan. The paper uses correlation technique to assess relation between these
variables. However, the paper shows a positive correlation number of fishing vessels and
catch. Overall, there was no considerable correlation between the fish catch and temperature
and rainfall.
The impact of aquaculture to food security and livelihood is evident from these studies but the
impact of DFPs on food security and livelihood has never been studied before. In Pakistan
and especially in the study area the use of such practices severely affecting not only the
natural habitat but affecting the consumption of many communities living near rivers and
streams. Empirical evidence regarding the link between destructive fishing practices and its
impact on fish consumption and livelihoods on the current lines has never been studied and
modeled before. However, limited research evidence is available in ocean fisheries on DFPs
and its impact on coral cover. For example, McManus, et al. (1997) discussed the effects of
some DFPs on coral cover and possible rates of recovery. Pet-Soede & Erdmann (1998)
examined an overview of the DFPs in Indonesia and compared different practices through a
balance sheet method. Pet-Soede et al. (1999) studied blast fishing in Indonesian coral reefs
from an economic perspective. Cinner et al. (2011) discovered the impact of variations in
environment on society‘s adoption of different fishing situations. These research evidences
reveal that there is tremendous research gap for studying the impacts of DFPs on fish
consumption and livelihoods.
2.5 Factors affecting fish consumption
Fish consumption is affected by a variety of social, economic, and environmental factors.
Research evidence (table 2.3) suggests that age, gender, family income, employment,
consumption season, urbanization, education, marital status, number of family members,
presence of children in family members, affect fish consumption. These variables were
27
aggregated into three major parameters: Economic, Social and physical or environmental
factors. The mean fish consumption of the world is 17kg per capita per annum in contrast to
Pakistan i.e. 2kg/capita per annum (Wasim & Parvez, 2007; York & Gossard, 2004; FAO,
2009; Garibaldi et al., 2004), which is one of the lowest in the region.
Global fish production is approximately 167.2 million tons per year of which total human
consumption is 146.3 million tones and 20.9 are non food uses of fish (FAO, 2016). Inland
fish represents a very important, often matchless source of high quality protein. Local food
production is important in checking hunger and supporting rural development in locations
where the poor do not have the capability to purchase food from the market (Corvalan et al.,
2005). Pakistan ranks 18th
in inland fishing in the world by producing 120,240 tonnes in 2012
and 123,155 tonnes in 2013 (FAO, 2015). The inland production of fish in Pakistan rose from
60,000 tons in the early 1980s to 284,000 tons at present (GoP, 2013b). The share of fisheries
sector to Gross National Product (GNP) for the period of 2014-15 was 5.8% (Ministry of
Finance, 2015). The share of inland fisheries in total fish production in Pakistan has remained
21%, 30%, 23%, 30% in 1947, 1960, 1984, and 2009-10 respectively (GoP, 2013a). It is
estimated that some 180,000 people (FAO, 2009; GoP, 2013b) mostly part-time, with almost
20,000 small crafts are involved in inland fisheries for their livelihoods. A number of
researchers have conducted studies relating to fish consumption. Majority of empirical studies
have based their investigation on the effect of social and demographic features on the fish
consumption (Nash and Bell 1969; Nayga and Capps1995; Capps 86; Perry 1982; Herath &
Radampola 2016; Gracia & Albisu 2001; Pippin and Morrison 1975; Keithiy 1987; Hu 1985;
Dellenbargcr et al. 1988; Cheng and Capps 1988; McGee et al. 1989; Israel et al. 1991). No
study has ever been conducted on the social and demographic factors of fishers and people
residing near water bodies in the study area and Pakistan. The current study will focus on
finding out the social, economic and demographic determinants of fish consumption in the
fishermen community, which is an important basis of protein, income generation and well
being.
The considerable expansion in fisheries and aquaculture production in the past 50 years,
mostly, in the past two decades, has improved the world‘s capability to consume diversified
and healthy food (FAO, 2016). However, the distribution of this increase in terms of per
capita fish consumption is unequal across the world. Per capita fish consumption has
increased in some countries while in others it has decreased. Fish consumption also
significantly varies between fishers or households residing near water bodies and people
28
residing, away from water bodies. In the study area no research has ever been conducted
documenting the fish consumption patterns of households.
2.6 High vulnerability of the fishery communities
The inland fishermen community of Charsadda is vulnerable to poverty due to the following
reasons:
Seasonal character of fishing activities: All the three types of fishermen (farming fishers,
fishing farmers and occasional fishers) are conducting fishing either as part time or combining
farming with fishing. Secondly, the weather conditions during winter seasons do not allow
fishermen to enter cold waters. The period from November to March are considered bad for
fishing activities which compel fishermen to abandon their livelihood activities during the
period, however during these days the flow of water is low due to which destructive fishing
methods especially blasting, use of cyanide, electric fishing and small mesh nets are adopted
by fishers. The months of April through October are regarded good fishing season due to high
flow of water, rains and warmth of water (figure 2.7).
Figure 2.7 Vulnerability/risk analyses
Months Bad season characterized by bad fishing,
scarcity of food and low income
Good season (good fishing, availability of
food and very high income)
January
February
March
April
May
June
July
August
September
October
November
December
Note: Adopted from Kebe, 2009
High cost of fishing inputs: Due to inflationary trends in the country, the prices of fishing
inputs, including fishing nets, fishing rods, and other related gears and materials, supplies,
fuel, oil, etc. are very expensive due to which the fishermen mostly rely on destructive fishing
methods which are less expensive and more efficient.
Lack of alternative livelihoods opportunities: There is shortage of alternative opportunities
for fishermen in the study area. Most of the fishers combine fishing with farming but they are
29
mostly subsistence farmers and that is the reason that they find enough time from farming to
fish.
2.7 Conceptual Framework
Freshwater comprise of 0.01 percent of total global water, which is 0.8 percent of the earth‘s
surface but sustain about 100,000 species out of about 1.8 million (Dudgeon et al. 2006).
Freshwater biodiversity represents a valuable natural resource but is extremely complex, and
in many cases poorly understood (Welcomme et al., 2010). The freshwater ecosystems on
which the river health depend on are among the most globally threatened (Dudgeon, 2014;
Vörösmarty, et al., 2010; Sullivan et al., 2011) with approximately 20% of freshwater fish
species becoming extinct, threatened, or endangered in recent decades (Revenga et al., 2000).
At present biodiversity of 65% of the world‘s river habitats is endangered by human caused
stressors (Sullivan et al., 2011). One threat to these systems is the use of DFPs, which fishers
can be driven to use under desperation (Munyi, 2009). For example, a study conducted at the
River Swat in district Charsadda, Khyber Pakhtunkhwa Province of Pakistan, reports six
species as missing in comparison with past records (Yousafzai, 2013). Similarly, out of a total
200 fish species of the Indus River system, 32 fish species are known to be endemic to
Pakistan (GoP, 2013).
Therefore, first of all this study identifies the driving forces of destructive fishing practices.
The dependent variable is destructive fishing practices, which is the variable of primary
interest, in which the variance is attempted to be explained by years of formal education,
number of alternative livelihoods, fish stock or population, cost of gear used, poverty,
distance from water bodies and amount of culture fish in the market. The level of education
affects fishing behavior of respondents. Level of education is usually described as the total
number of years of education a person has attained, based on the number of years it generally
requires to complete a particular level of education (Lowin, 2008; Shuttleworth-Edwards et
al., 2004). The less the education and environmental awareness, the greater is the probability
of destructive fishing practices. Similarly, lack of alternative livelihood opportunities may
lead fishers hang on to with the existing declining fishery, where they have no option but to
fish harder. Decline of fish stocks in the rivers and declining catches create fear among the
fishermen, leading them to intensify fishing because there is a constant threat of ‗use it now or
lose it‘ forcing them use destructive fishing practices. This study also hypothesized that the
higher the cost of gear, the higher the efficiency in catch and use of destructive fishing
30
practices. The poor the households, the greater the probability of conducting destructive
fishing practices. It is also believed that people living near water bodies are more attracted
toward fishing as compared to those living far away from water bodies. The more the
availability of culture fish in the market the lower the probability of conducting destructive
fishing practices.
Secondly, this study investigates the impact of adapting fishing practices on fisher assets in
different cohorts in the region, with a focus on the impact of destructive fishing practices.
Specifically, the study compares changes in livelihood and households assets from 2001 to
2016. DFPs have led to a decline in fish stock in rivers, which has a direct effect on fishermen
livelihoods through decline in fishing income, changes in the household fish consumption
patterns, increase in fishing efforts, which further intensify the destructive fishing practices.
These direct effects have indirectly affected the overall livelihood assets (indirect effect) of
fishermen, which result in reduced level of well-being and deterioration in livelihoods.
Therefore it is assumed that the more the destructive fishing, the higher the fish catch and
higher the profits of fishermen. Thirdly, this research assumes that fish consumption of the
people conducting destructive fishing practices is more than non fishermen and people
residing away from water bodies. In this model fish consumption is the dependent variable
and the variance is attempted to be explained by fishing income, distance to water bodies,
price of fish, family income, household size, age, education, and number of fishing gears. The
conceptual framework describing the interactions between the drivers of destructive fishing
practices, adaptive response of fishers, impacts on the biophysical fishery productivity and the
resulting consequence on fisher livelihoods (Figure 2.7).
31
Figure 2.8: Conceptual Framework
Destructive Fishing
Practices
Blast fishing
Cyanide
fishing
Electrofishing
Use of Small
mesh nets
Decline in
fish stocks
Direct Effects:
Changes in regular flow of income
Changes in the HH fish consumption patterns
(Determinants of fish consumption: Fishing
income, distance to water bodies, price of fish,
family income, HH size, age of HH head,
average years of formal education, number of
fishing gears)
Changes in fishing efforts/hardships
Intensify fishing/leave fishing
Deterioration in
livelihoods and
reduced level of
well-being
Indirect effects:
Changes in fishermen other livelihood
Assets:
Human: Education, Skill
Financial: Income, Savings, Access to credit
Physical: Housing, energy supply, transport
facility, Tools availability
Natural :licensing, litigation, monitors, fish
size and amount
Social assets: Membership in union council,
political parties membership, law
enforcement agencies, contacts with village
elders, contacts with other households,
kinship support
Situational Characteristics (Drivers of
Destructive fishing practices)
Economic Factors
level of income
Alternative livelihood opportunities
Cost of gear used
Supply of culture fish in the market
Level of savings
Social Factors
Level of education
Distance to water bodies
Age of fisher
Fishing experience
Environmental Factors
Environmental education
Decline in fish stocks/decline in catchers
and fear among the fishermen
Average fish catch/ day
Other Exogenous Factors
Networking and social bonds
32
2.8 Summary
The common pool nature of the fisheries resources has made it a great challenge for fisheries
managers and conservationists to deal with the continuous decline in fish stock. When
individuals ignore the common property externalities and overexploit the limited natural
resource, results in the ‗tragedy of the commons‘. Due to decline in fish stock and increasing
human population fishers either intensify fishing or amplify fishing methods leading to the
use of destructive fishing methods. The key drivers and determinants that influence the
continuation of destructive fishing techniques are socio-cultural and economic in nature.
These factors include, declining fish stocks (Akhtar, 2015), new fishing methods and
technologies, indebtedness of fishers, reduced catches, failure of fishing policies (Khan &
Khan, 2011), declining catches, lack of education among the fishermen (Munyi, 2009),
increase in population, poverty, lack of alternative livelihoods (Shumway, 1999), demand for
resources and fish as the key supply of food and protein (Ram-Bidesi, 2011) etc. These
practices not only reduce fish stocks in the rivers but severely affect poor fishermen in terms
of reduced economic activities, incomes, employment and fish consumption. The impact of
declining fisheries resources on fishermen livelihoods was initially studied by Allison & Ellis
(2001). Later Smith et al., (2005) modified the Allison & Ellis model and combined the
traditional livelihood model and developed a comprehensive model of livelihood outcomes of
inland fisheries. Andrew et al. (2007) used the concept of vulnerability to manage small scale
fisheries and Glavovic & Boonzaier (2007) adopted the sustainable livelihood framework to
comprehend the relationship between DFPs and livelihood outcomes. More recent studies
conducted by Weeratunge et al. (2014), Voyer et al. (2017) and Stanford et al. (2017) applied
the theories of ―lens of social wellbeing‖, RAPFISH and FLIRES respectively to discuss the
social, economic and political dimensions of small scale fishermen societies. Similarly, the
use of illegal fishing practices affect fish stocks, which result in reduced fish consumption.
Fish consumption is affected by social, demographic, economic and natural factors of fishing
community.
As compared to developed countries, livelihoods of majority of people in developing
countries depend on primary activities including fishing. We are not the first to attempt to
translate such broad concepts from small-scale fisheries and livelihoods policy into analytical
tools that fisheries managers and researchers can use, however different communities have
different livelihood opportunities, lifestyles, fish consumption habits, fish catching techniques
and perceptions of fishing. Secondly, most of these studies are undertaken on marine waters
33
and coastal communities and limited research is available on inland water sources and
livelihoods of rural communities. Thirdly, inland fisheries are conducted on smaller scale,
where fishers are extremely poor as compared to marine fisheries. Fourthly, the decline of
fish in ocean and inland water bodies differ significantly and the use of livelihoods assets
pentagon for the analysis of fishermen livelihoods on current lines has never been undertaken
before and no evidence of such study is available regarding DFPs and its impact on rural
livelihoods in Pakistan and particularly in Khyber Pakhtunkhwa.
34
Chapter 3
Profile of the Study Area and Fishing Industry Scenario of Khyber Pakhtunkhwa
This chapter presents key information regarding the area under consideration. The chapter is
divided into location and boundaries, natural features, demographic and economic features,
aquatic resources of Khyber Pakhtunkhwa and summary of the small inland fishes of the
study area. The chapter also discusses fisheries related regulations in Khyber Pakhtunkhwa.
3.1 Selection of the study area
The Indus plain starts from the foothills of the Himalayas and the Salt Range in the north and
continues to the Rann of Kutch and the Sea in the south (Mirza, 1975). The Indus River with
a total length of 2,750 km (GoP, 2013b) is the most important supply of surface water in
Pakistan and is thought out as the lifeblood for Pakistan. The huge Indus basin system
sustains the life and livelihoods of the bulk of population. The Indus water is mainly supplied
by glaciers. Its major tributaries in Khyber Pakhtunkhwa i.e., the Kabul River, Khiali and
Jindi (branches of Swat River) are passing from District Charsadda. The Swat River after
travelling from Swat and Malakand, enters the plains near Munda. After travelling for some
distance, it divides into river Khiali and Jindi, and then these river join in river Kabul near
Nisatta, after which there is one mighty Kabul River, commonly known as Landai. All the
three rivers and their tributaries from Munda to the place where they enter Kabul River
(Nisatta) and then the Kabul River from Nisatta to Nowshehra is the study area of this
research.
District Charsadda positioned between 34 -03‘ and 34 – 28‘ north latitudes and 71 -28‘ and 71
-53‘ east longitudes of Khyber Pakhtunkhwa is chosen as the area of study. The major reason
for the selection of Charsadda as the study area is that the three main rivers pass through this
region and over the years these are under severe threat due to the use of DFPs. The whole area
of district Charsadda is 996 square km/s. The climate of the district is extreme i.e. summer is
extremely hot with an average daily low of 27°C to an average daily high of 38°C in the
month of June, and winter is cold with an average daily low of 5°C to an average daily high
of 19°C. There are two rainy seasons in a year, winter rainfall in the months of March and
April, and summer rainfall in the months of July and August. The most important crops of
Charsadda are wheat, sugarcane, maize and a variety of vegetables. The Indus River with a
total length of 2,750 km (GoP, 2013b) is the most important supply of surface water in
35
Pakistan and is considered as the lifeblood for Pakistan. The major tributaries of Indus in
Khyber Pakhtunkhwa i.e., the River Kabul, River Swat (Khiali) and River Jindi pass through
District Charsadda. The Swat River after travelling from Swat and Malakand, enters the
plains near Munda. After travelling for some distance, it divides into river Khiali and Lower
Swat Canal. The rivers Khiali and Jindi fall into river Kabul near Nisatta, after which there is
one mighty River Kabul, commonly known as Landai. Fishermen concentrated villages were
identified from Munda to the place where they enter River Kabul at Nisatta. The common
fishing practices include use of hooks, spears, cast and drag nets, and rods.
3.2 Location and Boundaries
Charsadda district lies between 34 – 03‘ and 34 – 28‘ north and 71 – 28‘ and 71 – 53‘ east
(Figure 3.1). It is bounded by Malakand district on the north, Mardan district on the east,
Nowshehra and Peshawar districts on the south and Mohmand Agency of the Federally
Administered Tribal Areas on the west (DCR 1998).
Figure 3.1 Map of the Study Area
Figure 3.1 Location of the study area, showing main rivers and the selected villages/settlements
(circled).
36
3.2.1 Geography
Charsadda has an area of about 996 square kilometers (DCR, 1998). It is situated in the
central plain of Peshawar valley. Three main rivers and their tributaries flow through its
terrain, due to which its land is very fertile. The Kabul River enters Charsadda close to the
south west and demarcates the line between Charsadda and Peshawar. The Swat river enters
the district near Abazai village. The third River Jindi which is a tributary of the Kabul River,
flows near Charsadda zor bazaar and enters Kabul River near Nisatta. Later the three rivers
merge at Nisatta making a plain area called Doaba. After Nisatta there is one large river
commonly known as Landai. These three rivers are also the major source of irrigation water
in the district. The district is surrounded by Hills on three sides and the fourth side which is
not enclosed by any hills is where Kabul River flows out to form the Indus. The climate of the
district is extreme i.e. summer is extremely hot with an average daily low of 27°C to an
average daily high of 38°C in the month of June, and winter is cold with an average daily low
of 5°C to an average daily high of 19°C.
3.2.2 Demographic Characteristics
The total population of Charsadda was 1,022,364 according to Population Census conducted
in March, 1998 (DCR, 1998) with an inter-censal percentage increase of 62.0 since March
1981 when it was 630,811.
The total population of Charsadda was 94,243 according to the first Census conducted in
1868. It increased to 108,368 and then to 132,917 in 1881 and 1891 Censuses respectively
(Gazetteer of the Peshawar District 1897-98, 2004). The population density tremendously
increased from 633 persons per square kilometer in 1981 to 1,026 persons per square
kilometer in 1998. The urban population was 192,851 (18.9%) whereas 81.1 % of the people
lived in rural areas. The literacy ratio has increased from 13.3% in 1981 to 31.1% in 1998.
The literacy ratio is 46.9% for males as against 14.1% for females.
3.2.3 Economic Characteristics
According to the 1998 census the economically active population was 20.5% of the total
population or 30.8% of the population ten years and above. Of the total male population
38.6% were economically active, while 61.4% were not economically active. The
unemployment rate was 23.1%, while female unemployment rate was 9.6%, this small
37
proportion is out of the total economically active population, which means that a low
percentage of female are involved in the economic activities. In 1998 a larger part of the
economically active population was involved in agriculture (49.1%), followed by construction
industry (17.6%), and community, social and personal services representing 14.7%. Of the
total working population 93.6% were registered as employed in 1998, 44.7% were self
employed, 13.4% govt. employed and 30.0% private employees. Rafts and related trades
workers 4.4 percent. According to the 1998 census skilled agriculture and fishery workers
constitute 35.1 percent and crafts and related trade workers 4.4 percent. This means that the
present study contributes to more than 39.5 percent of the population, which is mostly
engaged in fishery and related activities.
3.3 Aquatic resources of the Khyber Pakhtunkhwa
Khyber Pakhtunkhwa has considerable Aquatic resources of cold, semi cold & warm waters.
Their detail is as under:
Table 3.1 Aquatic resources of Khyber Pakhtunkhwa
Water bodies Unit Cold water Semi-cold
water
Warm water Total
Rivers, Streams etc KM 1,718 2,757 1,627 6,102
Natural Lakes Hectare 2,216 402 3,744 6,362
Dams and
Reservoirs
Hectare 54,604.86 54,604.86
Source: Directorate of Fisheries, Agriculture Department, Govt. of Khyber Pakhtunkhwa
Table 3.2 summarizes the small inland food fishes of river Swat and Kabul, their prices,
maximum lengths and catch characteristics. Most of the high price fishes are rare and low
price fishes are frequent in catch. This is an evidence of the fact that most important fish
species have declined (rare), some are frequent in catch due to the reason that those fishes are
exotic in nature and are freed in rivers by the fisheries department. The very low quality
fishes are abundant and they are also at the mercy of DFPs by fishermen.
38
Table 3.2 Summary of the small inland food fishes of river Swat/Kabul
Family Order Family Species Local name Max
length
(cm)
Price/
Kg
(Rs.)
Catch
chara
cterist
ics
1 Cypriniformes Cyprinidae Barilius pakistanicus Pepal 7.6 180 F
2 Barilius vagra Pepal 13 200 F
3 Barilius modestus Pepal 10.8 180 F
4 Crossocheilus
diplocheilus
Button 11 230 A
5 Puntius sophore Tapaha 8.3 250 F
6 Puntius conchonius Tapaha 7.5 250 F
7 Puntius chola Tapaha 6 220 F
8 Puntius ticto Tapaha 6 220 F
9 Garra gotyla Kanesatt 13. 260 A
10 Schizothorax
plagiostomus
Swatay 14.5 270 R
11 Racoma labiata Swatay 13 270 R
12 Cirrhinus mrigala Torkay 33 350 R
13 Rasbora daniconius Sowage 12,.5 260 F
14 Tor macrolepis Mahasher 13.5 350 R
15 Cyprinus carpio (Exotic) China kub 13 350 F
16 Carassius
auratus(Exotic)
China kub 13.8 350 F
17 Salmophasia bacaila Spenkay 7.5 290 R
18 Salmophasia punjabensis Spenkay 12.8 300 R
19 Amblypharyngodon mola Spenkay 12.8 300 R
20 Labeo diplostomus Torkay 20.5 350 R
21 Nemacheilidae Schistura alepidota Sowa 7.6 280 R
22 Schistura prashari Sowa 6.2 260 R
23 Triplophysa naziri Sowa 12.2 300 R
24 Acanthocobitis botia Nai 6.5 280 R
25 Siluriformes Sisoridae Glyptothorax punjabensis Sulamani 11.7 420 R
26 Glyptothorax stocki Sulamani 9.5 400 R
27 Glyptothorax sufii Sulamani 11.5 450 R
28 Glyptothorax cavia Sulamani 9.7 320 R
29 Gagat cenia Taktake 7.6 300 F
30 Gagata pakistanica Taktake 7.7 300 F
31 Bagridae Mystus bleekeri Bretu 17.2 350 F
32 Schilbidae Clupisoma naziri Shermai 20 1200 R
33 Clupisoma garua Shermai 21 1400 R
34 Chaniformes Channidae Channa punctatus Asli katasar 16.5 300 F
35 Channa gachua Desi
katasar
15.8 300 F
36 Mastacembeli
formes
Mastacembelidae Mastacembelus armatus Marmahe 24 250 F
37 Beloniformes Belonidae Xenentodon cancila Kann mach 29 400 F
38 Perciformes Chandidae Chanda nama Shasha kub 13 400 F
Source: Yousafzai, 2013, R=Rare, A=Abundant, F=Frequent in catch
39
3.4 Fisheries regulations in KP
The organizational arrangement of fisheries sector in Khyber Pakhtunkhwa was initiated in
1958, under the management of Director Fisheries, West Pakistan Lahore, under the umbrella
of the ministry of agriculture and the same set up continued till June 1970. On the first of
July, 1987, the Fisheries section was acknowledged as an annexed section, under the
management of secretary forestry, fisheries and wildlife sector. Presently, at the provincial
level, the director fisheries is the general commanding officer of the fisheries wing and is
supported by four Deputy Directors, Fisheries and twenty one Assistant Directors, Fisheries,
in the province. These administrators are overseeing and managing the progressive as well
as communicational functions in their particular districts and hatcheries.
3.4.1 Licensing and fee structure
Fish stock in water bodies of the Khyber Pakhtunkhwa is administered by the provision
of fishing licenses and permits on day to day or seasonal basis to the anglers & fishermen,
under the Fisheries rules, 1976. The allowable types of licenses and rates are given in the
following table:
Table 3.3: Licensing and fee structure
S.No Types of licenses Rates (Pak Rupees)
1 Daily Trout angling license 100
2 General 500
3 Seasonal Rod and Line 100
4 Cast Net 300
5 Long Line 200
6 Daily Rod and Line 25
7 Seasonal Rod and Line (Special) 200
8 Daily Rod and Line (Special) 75
Sources: Fisheries Department, Khyber Pakhtunkhwa, Peshawar, Pakistan
3.4.2 Species of fish and prohibitions
The West Pakistan Fisheries Ordinance, 1961 is in practice today and this ordinance clearly
states the limits on different species and specific times of the year for fishing of each
category.
40
Table 3.4 Species of fish and prohibitions, (Schedule 1 of Fisheries Ordinance 1961)
S.No Species of
fish
Size (Inches) Period during which taking of the fish by any net,
cage, trap or fixed engine is prohibited.
1 Trout 09 10th October to 9th March
2 Mahasher 12 1st June to 31th August
3 Rahu 12 1st June to 31st August
4 Mori 12 1st June to 31st August
5 Thaila 12 1st June to 31st August
Sources: Fisheries Department, Khyber Pakhtunkhwa, Peshawar
Keeping in view the changing nature of fisheries resources and use of DFPs the West Pakistan
Fisheries Ordinance 1961 was amended from time to time. Different schedules of the
ordinance regarding DFPs are given below, some schedules are inserted through
(Amendment) Act, 1991 vide page-10-11 inserted through (Amendment) Ordinance, 1982
vide page-7-9.
3.4.3 Regulation regarding use of explosives.
Section six of the ordinance 1961, amendment 1991, damage of fish through explosives,
stated that ―no individual shall apply any blasting, electric current or other explosive
material‖ (Govt. of KP, West Pakistan Fisheries Ordinance 1961) in any water bodies
anywhere in the province with the intension thus to catch or destroy fish in the rivers of the
province. This ordinance clearly indicates that no person can use such destructive materials at
any river or water bodies.
3.4.4 Regulation regarding use of poison or chemicals in water.
Section seven described the ordinance rule regarding use of cyanide and the forms of poisons
states that, ―no person shall put any poison, lime or noxious material into any water with
intent thereby to catch or destroy any fish that may be therein‖ (Govt. of KP, West Pakistan
Fisheries Ordinance 1961).
3.4.5 Regulation regarding size of fish that shall not be taken
Section seven of the fisheries ordinance 1961 states that, ―no person shall kill, capture, or
possess any species of fish specified in the second column of the 1st schedule (table 3.4), of a
size less than that specified in the third column of the said schedule against such species‖
(table 3.4).
41
3.4.6 Regulations regarding nets, fixed engine and use of traps
The ordinance also has rules regarding nets, fixed engine and different forms of traps. It
prevents all persons from using any undersized mesh nets, cages, use of fixed engine,
entrapping fish through any other forms of fish catching devices which are prohibited under
section 1 above. However in private waters this rule does not apply and legal devices can be
used during the period permitted with regard to such species under the fourth column of the
said schedule (table 3.4) which is also specified in the license or permit provided through the
said ordinance. In the case of trout only the specified gears by the fisheries authorities shall be
used even in the permitted period.
Section ten of the ordinance describes that all those persons or fishermen who are possessing
fisheries licenses are liable to keep their licenses with them when fishing and the fisheries
authorities, watchers or the inspector of fisheries may demand licenses for fishing.
3.4.7 Rules regarding declaring water as sanctuary for fish
Section eleven of the fisheries ordinance declares that apart from this ordinance, the
government may announce or notify any water body as sanctuary for fish for any time period
as specified by the director of fisheries. During this period no individual shall catch, kill or
keep the said fish species without a particular license issued for this purpose.
3.4.8 Regulation regarding duties of different officers in different departments
Section 12 of the ordinance states that local officials of the land and revenue department
including irrigation canals patwari, irrigation canals watchmen at the village level, revenue
patwari and other officials are bound to provide information regarding use of illegal and
destructive practices of fishing in their specified revenue circles. Any delay in the provision
of such information shall be dealt strictly and the persons responsible shall be punished for
this offence. The ordinance further illustrates that if such case is put before a court of law and
if the magistrate believes that the persons responsible have committed or are likely to commit
negligence with reference to the Ordinance in the provision of necessary information, the
magistrate can issue a warrant for the investigation of all those places, where any undersized
fish, destructive materials e.g. cyanide, chemicals and other blasting materials, small mesh
nets, traps, or any other devices for catching and destroying fish are kept or hidden. Similarly,
the fisheries inspectors may search without a warrant from a magistrate all those individuals, their
42
boats, racks, automobiles, ships, boats, rafts, packages, in order to assure himself as to whether or
not the law has been violated with reference to the Ordinance (Govt. of KP, West Pakistan
Fisheries Ordinance 1961).
3.4.9 Regulation punishments
Section fifteen is about detaining a person without a warrant for offences in the ordinance. It
gives tremendous powers to the fisheries inspectors, which include;
A fishery inspector can apprehend an individual without may warrant if he thinks that the said
person has provided wrong addresses and other personal information, has refused to provide
his address and name, and if his personal information is doubtful and has violated the fishery
rules mentioned above and under section 6, 7, 8, 9 or 11 of the fisheries ordinance 1961. Such
a person shall remain under custody until he provides the necessary information correctly.
Section sixteen is about powers of seizure, which states that the fisheries inspectors or any
other person as authorized by the director of fisheries can seize small mesh size nets, traps,
cages, and any other destructive material or electric generator and other devices, which may
be used for fishing inaccurately (Govt. of KP, West Pakistan Fisheries Ordinance 1961).
Section seventeen is about different Penalties. This section states that all those persons
(a) Who disobey the orders of section 6 and 7 may be punished with precise detention of
either custody extending up to 6 months or with a monetary fine of Rs. 5000 or with both
fine and custody.
(b) Who disobey the orders of section 8, 9, 10 and 12 may be penalized with custody of
either account for up to 3 months or a fine of Rs. 1000 or with both fine and
imprisonment.
(c) Who disobey the orders of section 11 shall be may be penalized with jail of up to 6
months or fine of Rs. 5000 or with both.
Section 26 of the 1961 fisheries ordinance is about the power to formulate rules
(1) The Government shall formulate rules for the implementation of the above rules of this
Ordinance
(2) The government may implement the above mentioned rules without any discriminations.
These rules shall set down;
43
(a) The procedure of how a license or a permit may be issued, the conditions to be fulfilled
for having a license.
(b) Who has the authority to issue the permits?
(c) What shall be the possible fee for a specific license?
(d) The provisions on the basis of which the fishery authorities may grant the right of
catching fish.
(e) Rules regarding the different fish species and maximum number must be caught.
(f) Prizes, compensations and motivations to people rendering support to the fisheries
authorities regarding conservation of fisheries.
(g) The utilization of amounts recovered through the exercise of this ordinance.
(h) To ban or control all or any of the following issues: -
(i) the formation and utilization of fixed engines
(ii) the manufacture of weirs; and
(iii) the measurements & types of nets, traps or other means for taking fish
Table 3.5 Maximum amounts allowable as per certain violations
S.No. Description of violations Total amount which may be received
as compensation
1 Fishing without a license or Permit Rs. 200 or Rs. 25 per fish
2 Killing juvenile fish/fingerling Rs. 100 or Rs. 10 per fish
3 Illegal fishing Rs. 200 in for trout fish and Rs.100
in for other species.
4 Application of gears exceeding than the
permitted number in the rules Rs. 100 for each extra gear
5 Fishing with a undersized nets Rs. 100 for each net used.
6 License possessor using on-licensers‘ help in
fishing while using his gears Rs. 100 per person.
7 Presenting or placing fishes for price or barter
fish in breach of the rules under the ordinance Rs 100.
Source: Fisheries Department, Khyber Pakhtunkhwa, Peshawar, KP Fisheries Ordinance,
1961.
44
3.4.10 Number of licenses issued during 2015-16
Table 3.6 shows the number of licenses issued during 2015-16 by the fisheries department
Khyber Pakhtunkhwa. Data regarding other districts is omitted and only totals are given for
comparison. In district Charsadda during the financial year 2015-16 only 103 licenses were
issued. All the licenses were issued in general category except one which was issued for SRL.
The last row G. total shows the total licenses issued in Khyber Pakhtunkhwa.
Table 3.6 Number of Licenses issued
District Licenses Issued
Cooked/
Uncooked
Raft/
Boat/jala
General Cast
Net
Long
line
SRL
(season
al rod
line)
SRL
R. W
DRL
(Daily
rod
line)
DRL
(S)
DTA
(Daily
trout)
S. Total
Charsadda 0 0 102 0 0 01 0 0 0 0 103
G. Total: 10 0 1,451 968 656 1,553 0 389 0 2,808 7,835
Source: Directorate of Fisheries, Khyber Pakhtunkhwa, Peshawar
3.4.11 Fee Realized by Licenses
A total of Rs.51100 was realized by licensing during one year in district Charsadda. The last
low in table 3.7 shows the grand total of all the districts in Khyber Pakhtunkhwa.
Table 3.7 Fee Realized by Licenses
District Cooked/
uncooked
Raft/
Boat
/ Jala
General Cast
Net
Long
line
SRL SRL
R. W
DRL DRL
(S)
DTA S. Total
Rate 2000 5000 500 300 200 100 200 25 75 100
Charsadda 0 0 51,000 0 0 100 0 0 0 0 51100
G. Total:
20000
0
727000
296700
131200
159300
0
38900
0
280800
1653900
Source: Directorate of Fisheries, Khyber Pakhtunkhwa, Peshawar
45
3.4.12 Legislation
In district Charsadda a total of 86 cases were registered during one year, out of which 43 were
presented before office and 43 were registered, whereas 6 were filed by office.
Table 3.8 Legislation cases in different districts of Khyber Pakhtunkhwa
Peshawar Nowshera Charsadda Mardan Swabi Buner Kohat
B/F Office 21 0 43 142 0 39 0
Registered 145 32 43 35 106 59 47
Total (1+2) 166 32 86 177 106 98 47
Compounded 125 32 35 172 71 50 47
Comp: Fee Rs. 104100 12700 15500 75400 47700 37900 64300
To Court 27 0 0 0 4 24 0
B/F Court 0 14 0 253 0 0 04
Total (6+7) 27 14 0 253 4 24 04
Convicted 01 0 0 0 0 19 01
Fine Imposed 2000 0 0 0 0 40000 1000
Aqted/filed by
Court
0 0 0 0 0 0 0
C/F court 8+9+11 26 14 0 253 4 05 03
Filed by Office 02 0 06 1 0 0 0
C/F Office 3-
(4+6+13)
12 32 57 4 31 24 0
Total Bal: 12+14 38 46 57 4 35 29 03
Source: Directorate of Fisheries, Khyber Pakhtunkhwa, Peshawar
3.4.13 Leases of water bodies/dams
In district Charsadda only one dam with the name of Palay Dam, this is leased out for Rs.
3650,000 for three years period (table 3.9).
46
Table 3.9 Leasing of dams
District Neme of Water Body Lease Amount for the year
2015-16
Amount
Realized
Balance
Peshawar Azakhel Dam 1417500 1417500 0
Kohat
Karak
Hangu
Karak
1. Tanda Dam
2. Darwazai dam
3. Kandar Dam
4. Kandar Auxillary
5. Chanda Fateh Khan dam
6. Gandialy dam
7. Sharki Dam
8. Zaibi Dam
9. Changhoz Dam
10. Naryab Dam
11 Karak Dam Karak
12 loughar Dam Karak
2067000
716700
388400
435000
244400
708400
278300
466650
123300
80000
159000
162000
2067000
716700
435000
199700
244400
278400
278300
466650
0000
80000
159000
162000
0
0
0
0
0
0
0
0
0
0
0
0
Sub total 5829150 5087150 0
Bannu Baran Dam 402000 402000 0
D.I. Khan 1. River Indus Unit –I
2. River Indus Unit –II
3. River Indus Unit –III
4. River Indus Unit –IV
5. Chasma Dam
2003000
2547000
577000
2000000
0
2003000
2547000
577000
2000000
0
0
0
0
0
0
Sub total 0 0 0
Haripur 1. Khal dam
2. Mong Dam
3. Chatrri Dam
4. Khair Bara Dam
687000
537000
565000
672000
687000
537000
565000
672000
0
0
0
0
Sub total 2461000 2461000 0
T&K
Haripur
1. Tarbela dam
2. Khanpur Dam
16672669
3331000
16674000
3331000
0
0
Sub total 20003669 20004332 0
CH&TC
Pesh:
Portion II of CH&TC
Sherabad Peshawar 999620 452000 547620
Charsadda Palay Dam 3650000 3650000 0
Nowshera Jabba Khatak Dam 381667 381667 0
G. Total 42271606 40983317 547620
Source: Directorate of Fisheries, Khyber Pakhtunkhwa, Peshawar
3.4.14 Departmental Revenue
Total revenue to the fisheries department from district Charsadda amounted Rs.1283,100 for
the year 2015-16. Out of this Rs. 1216500 is the lease income per year and the remaining Rs.
51100 is license fee and Rs. 15500 is fine during litigation process (table 3.10).
47
Table 3.10: Departmental Income (Revenue)
Source: Directorate of Fisheries, Khyber Pakhtunkhwa, Peshawar
3.4.15 Fish farms established in selected districts of KP
Out of the total 112 fish farms established in Khyber Pakhtunkhwa fifty eight (58) farms were
established in district Charsadda (table 3.11).
Table 3.11 Fish farm established
Source: Directorate of Fisheries, Khyber Pakhtunkhwa, Peshawar
District Peshawar Nowshera Charsadda Mardan Swabi
Target 1500000
License Fee Trout 0 0 0 0 0
License Fee N. Trout 52200 20600 51100 63900 34600
Lease Money 945000 0 1216500 0 0
Comp: Fee 104100 12700 15500 75400 47700
Sale of Fish 4000 0 0 0 0
Sale of Fish Seed 0 0 0 1043535 0
Sale of Orn: Fish 0 0 0 0 0
Recovery of Over Payment 0 0 0 0 0
Miscellaneous 2000 0 0 0 0
S. Total 1107300 33300 1283100 1182835 82300
District Trout Farms Non Trout Farms Total
Nos. of Farms
Established YTD
Area (Acres) Nos. of Farms
Established
YTD
Area (Acres) Nos. of
Farms
Area (Acres)
Peshawar 0 0 25 20.625 25 20.625
Charsadda 0 0 58 68.5 58 68.5
Nowshera 0 0 26 26.5 26 26.5
Mardan 0 0 705 430 705 430
Swabi 0 0 46 79.625 46 79.625
Kohat 0 0 57 85.475 57 85.475
Bannu 0 0 61 29.04 61 29.04
D.I. Khan 0 0 43 834.6 43 834.6
Buner 0 0 20 4.0 20 4.0
Lower Dir 0 0 51 17.5 51 17.5
Upper Dir 1 0.14 0 0 1 0.14
Swat 12 2.5 17 5.25 29 7.75
Chitral 11 5.0 0 0 11 5.0
Shangla 04 0.85 0 0 04 0.85
Kohistan 18 1.125 0 0 18 1.125
Haripur 0 0 6 2.01 6 2.01
Mansehra 02 1.00 0 0 02 1.00
Batagram 1 0.25 0 0 1 0.25
CH&TC Pesh; 0 0 0 0 0 0
T&K Haripur 0 0 0 0 0 0
Madyan Swat 35 10 0 0 35 10
Thana M. A 0 0 5 6.5 5 6.5
Torghar 0 0 0 0 0 0
G. Total: 84 20.865 1120 1609.625 1204 1630.49
48
3.4.16 District wise non trout fish production
Table 3.12 shows the district wise non trout fish production in Khyber Pakhtunkhwa. From
district Charsadda 2.75 metric tons of fish was produced during the year 2015-16. This shows
the fish produced from Palai Dam in district Charsadda.
Table 3.12 District Wise Non Trout Fish Production (Metric Tons)
Source: Directorate of Fisheries, Khyber Pakhtunkhwa, Peshawar
3.4.17 Publicity information and research regarding fisheries
Table 3.13 shows general information regarding fisheries in the study area. The data revealed
that no such activities were undertaken in the study area. However a limited number of
research studies were undertaken in lower dir, but the level of research is also not known.
District Rivers/Dams
(Licenses)
Dams
(Leases)
Govt: Farms Private
Farms
S. Total
Peshawar 02.00 0.9 0 3.1 6.00
Charsadda 2.75 0 0 3.00 5.75
Nowshera 3.00 3.00 0 1.00 7.00
Mardan 0 0 0 0 0
Swabi 10.11 0 0 34.70 44.810
Kohat 15.057 28.334 0 0 43.391
Bannu 0 17.968 0 6.2 24.468
D.I. Khan 191.11 0 0 0 191.11
Buner 0 0 0 0 0
Lower Dir 11.5 0 0 8 19.5
Upper Dir 32.7 0 0 0 32.7
Swat 12.000 0 0 0 12.000
Chitral 5.951 0 0 0 5.951
Shangla 0 0 0 0 0
Kohistan 0 0 0 0 0
Haripur 0 31.307 0 0 31.307
Mansehra 9.637 0 0.008 8.532 18.177
Batagram 0 0 0 0 0
CH&TC Pesh: 0 0 0 0 0
T&K Haripur 0 167.196 0 0 167.196
Thana M.A. 73.29 0 0 0 73.29
Torghar 1.385 0 0 0 1.385
G. Total: 370.49 248.705 0.008 64.532 684.035
49
Table 3.13 Publicity information and research undertaken
District Training Publicity Research
Official Farmer NGOs Student TV/Radio
Talk
Hujra Talk Article
s
Papers Pu
bli
cat
io
n
Peshawar 0 0 0 0 0 05 0 0 0
Charsadda 0 0 0 0 0 0 0 0 0
Nowshera 0 0 0 0 0 02 0 0 0
Mardan 0 0 0 0 04 0 0 0 0
Swabi 0 0 0 0 0 0 0 0 0
Kohat 0 0 0 0 13 06 0 0 0
Bannu 0 0 0 0 0 0 0 0 0
D.I. Khan 0 0 0 0 0 0 0 0 0
Buner 0 0 0 0 0 0 0 0 0
Lower Dir 0 175 0 0 2 0 0 0 0
Upper Dir 0 4 0 85 0 5 0 0 20
Swat 0 0 0 0 0 0 0 0 0
Chitral 0 04 02 0 0 0 0 0 0
Shangla 0 0 0 0 0 0 0 0 0
Kohistan 0 0 0 0 0 03 0 0 0
Haripur 0 0 0 32 0 0 0 0 0
Mansehra 25 46 0 0 0 0 0 0 0
Batagram 0 0 0 0 0 0 0 0 0
PCH&TC 29 52 0 58 05 0 0 0 0
T&K Haripur 0 0 0 0 0 0 0 0 0
Madyan Swat 05 10 25 10 05 05 0 0 0
Thana M. A. 0 0 0 0 0 36 0 0 0
Torghar 02 11 0 0 0 0 0 0 0
G. Total
61 302 27
185 29 62 0 0 20
Source: Directorate of Fisheries, Khyber Pakhtunkhwa, Peshawar
50
Chapter 4
Research Design
This section comprises of the methodology applied in carrying outing this research. It shows
in detail the collection of primary data, research framework, sample size and techniques,
sampling frame and analytical techniques for data processing and analysis.
4.1 Collection of data
This dissertation is mainly based on primary data. However, secondary data regarding rules
regulations is also used for analysis. The secondary sources of data include reports, journals,
census and fisheries ordinance. The primary data are composed of the causes of DFPs, social
and economic features of the fishermen, fish consumption, fishing practices and conservation
methods used by the fishermen. Table 4.1 illustrates the nature and source of the data.
Table 4.1: Nature, source and reasons of data collected. Nature of data Data collected Year Source Reasons of use
Secondary data Boundary map of
the study area
- Irrigation Department,
Charsadda, Khyber
Pakhtunkhwa, Pakistan
Showing of the boundaries of
the study area for assistance
in the household survey
Census data 1998 Population Census
Organization, Pakistan
To identify the total
households data for selection
of sample households
West Pakistan
Fisheries
Ordinance1961/
(Amendment)
Ordinance, 1982.
1961 and
1982
Fisheries Department,
Govt. of KP,Pakistan
To know about the rules and
regulations regarding and
conservation measures in the
study area
Production of
inland fish and
fisheries in
Pakistan
2013 Zoological Survey of
Pakistan, 2013
To know about the total
production and share of
inland fisheries in Pakistan
and
Contribution of
fisheries in GDP
Various
years
Ministry of Finance
Pakistan, Economic
Survey of Pakistan
To identify the contribution
of fisheries to the national
income
District Census
Reports (DCR‘s) of
Charsadda
1998 Population Census
Organization, Statistics
Division, Islamabad,
Government of Pakistan
To have knowledge of the
socio-economic and other
features of the study area
Primary data Fisheries related
household and
Socioeconomic
data
2016 Households‘ survey knowing about the social,
economic and other features
e.g., fishing gears and
reasons used by the
households
51
4.2 Research framework
In this study Focused Group Discussion (FGDs), Key Informants‘ Interviews, household
survey and field observations are used for the collection of needed data. Before a detailed
questionnaire survey, a reconnaissance survey was carried out in the study area consisting of
field visits to major rivers and streams in the study area, to get an overview of the fishing
practices and livelihood activities. From the reconnaissance survey, it was revealed that
destructive fishing practices (DFPs) have severely affected the fisheries resources and
ultimately livelihoods of the fishermen. Interviews and group discussions with the community
leaders, elders, professional fishermen, government officers and fishery watchers were also
carried out. Sites were selected and a questionnaire to obtain essential information from the
household heads was developed. A reconnaissance survey based on the circumstances in the
area was undertaken; this survey helped in the pretesting of the questionnaire. The
questionnaire was modified. The selected household heads were then interviewed. Field
observation were also undertaken to watch the different activities in the area, e.g. fishing
gears adopted, fishing areas, meet fishery watchers and types and amount of fish caught. The
data collected were analyzed statistically using descriptive statistics, cross tabulations,
regression and livelihood assets pentagon. Findings and conclusions were drawn based on the
analysis. Finally recommendations were proposed for mitigating the destructive fishing
activities.
4.3 Sample size
Primary data in this research was gathered through household survey questionnaire,
observations, FGDs and Key informant interviews. The primary data were collected between
March and December 2016 through key informants interviews, focus group discussions
(FGDs) and household survey respectively. Firstly, in-depth interviews were conducted with
key informants including village heads (khans), elders and government officials. Secondly,
four FGDs were carried out to obtain key information regarding fishermen communities, their
socioeconomic characteristics and institutional set up. Thirdly, a detailed questionnaire is
administered to gather necessary data of the households. In this study, data was collected
from the male household heads due to their experience in fishing activities and decision
making power in the family. Females are not allowed to participate in income generating
activities outside homes. Therefore, only male household heads were interviewed. Secondary
52
data regarding licensing, litigation process, number of watchers, fisheries rules & regulations
was obtained from the provincial fisheries and irrigation departments.
In-depth interviews are very useful in giving a humane face (Mack et al., 2005; Boyce et al.,
2006), and achieving a holistic understanding (Berry, 1999) of research problems. In this
study a one on one in-depth interviews with key informants were conducted, which shared
their experiences and expectations on fisheries management and helped us explore the
people‘s perspective on DFPs, and the changes they perceived in the livelihoods of fishermen.
These in-depth interviews provided direction for further research and helped in the selection
of members and content of FGDs. The in-depth interviews revealed that DFPs have degraded
the fish fauna and badly affected livelihoods of fishermen in the study area.
Focus group interviews are commonly used for purposes of developing hypotheses that are
then verified with a survey of population or other kinds of research (Stewart et al., 1990; Reid
et al., 1981). To authenticate results of the in-depth interviews and get a deeper understanding
of the topic, four FGDs were carried out to obtain information regarding destructive fishing
gears, socioeconomic characteristics of fishermen communities and fishery regulations. A
single category design (Krueger & Casey, 2000) was used for professional fishermen, village
elders, and fishery officials and watchers consisting of 10, 7, and 8 members respectively.
However, for the fourth group multiple category design (Krueger & Casey, 2000) was used
with 10 mixed participants. Each group discussion remained from 60 to 80 minutes until
saturation was determined. During the focus group interviews questions regarding fishing,
use of DFPs, its effects on livelihoods, and other fishermen characteristics were asked. For
example; 1) think back over all the years that you've watched the fishing activities and tell us
the most enjoyable fishing memory you have 2) what comes to your mind when you think of
fishing? 3) why people mostly conduct DFPs? 4) what are the major reasons for not holding
fishery license? 5) how DFPs affect fishermen livelihoods? 6) and what can each one of us do
to reduce the use of DFPs?
4.3.1 Sampling Techniques
To choose a representative sample of respondents two stage cluster sampling was applied.
Cluster sampling simply requires a record of components in the clusters sampled (Anderson et
al., 1996). In the first stage, fishing communities with distinct fishing characteristics i.e.
location near water bodies, intensive fishing and presence of large number of fishermen labor
53
were purposively selected. In the second stage, sample households were selected from those
fishing communities. The survey was conducted with household heads (HHs) of each sample
household. Targeted villages were taken from households living near the three rivers in the
study area i.e. Swat, Kabul and Jindi. Fishing in Charsadda is seasonal with respect to
catches, which might be due to ecological and biological aspects. Although fishing is carried
out throughout the year but two main seasons with abundant fish catch by the fishermen are
Mid-February to April and July to October. The Mid-February to April has abundant fish
catch and is locally known as ―mainchal‖ (fish breeding season).
4.3.2 Sampling Frame
The total population of the study is the people living near rivers, streams, ponds, channels and
other water bodies in the study area. Three rivers and their channels in district Charsadda
which are the major tributaries of the Indus River System will be selected for this study. In
accordance with 1998 Census, the overall Population of district Charsadda is 1,022,000 (GoP.
2001). Due to non-availability of fresh population data, cluster sampling was applied, as it is
cost-effective and is appropriate for choosing due to the reason that the sampling frame of
individual components is not accessible.
In order to maximize validity of research, a comprehensive sampling frame was used to select
a better household sample for research. To find out a representative household sample size,
the following equation (Tryfos, 1996) was used:
n= (Equation 1)
Where n is sample size, N is population size, is ratio of a characteristic of interest in a
population (e.g. literacy rate, fishermen population, and mortality), C is ±error rate
(confidence interval), and Z a/2 is tabulated value for confidence level. Plugging the
proportion of 0.5 gives the maximum variance, 0.5*(1-0.5) = 0.25, error rate (confidence
interval) of ±8% and 1.96 tabulated value of Za/2 for 95% confidence level and number of
households of the above mentioned villages, sample sizes for each village were estimated.
The above method provided a sample size of 277 with error acceptance value of 6%, though a
sample size of 280 respondents was chosen for convenience of calculations (Annexure D).
54
Table: 4.2 Population Size and Statistical Sample
Rivers Village Name Population No. of HHs
Household types
Selected
Sample
Type I
30%
Farming
Fishers
Type II
30%
Fishing
Farmers
Type III
40%
Occasional
Fishers
Khiale
Abazai 2,978 190 85 26 25 34
Dawlat Pura 343 43 34 11 10 13
Jangal 131 16 15 5 4 6
Chitli Tapo 32 4 04 1 1 2
Sardaryab
Dogar 373 47 36 11 10 15
Doaba 356 45 35 10 10 15
Jala Bela 67 8 08 2 3 3
Jindi
Shahbara 495 62 44 13 14 17
Majoke 238 30 25 7 8 10
Total
5,013 445 286 86 85 115
For the fishermen livelihoods analysis households were divided into three categories of type I,
II and III. Type I is referred to as ―farming fishers‖ in this study and includes households
whose primary occupation is agriculture but they also catch fish to diversify their income
sources. Farming fishers have access to farm land but get less income from farming than
fishing farmers. This category of households is the least destructive in the study area. Type II
households are named as ―fishing farmers‖. They are poorer households getting almost equal
income from both fishing and farming. This category of households are more destructive than
type1 but less destructive than type III. Type III households are named as ―occasional
fishers‖. This category of households is the major threat to the fish fauna in the study area.
They occasionally go for fishing and use chemicals, blasting material (locally known as
khateen) and electric tools. This category of households mostly includes government officials,
businessmen, village khans (landlords), police and army and other law enforcement agencies
workers, who have not only access to these destructive methods but can use them anywhere
due to their contacts. The fishermen income was calculated on annual basis, excluding
personal consumption. The income was calculated as total average catch multiplied by
average market price. Type I, II and III accounts for 30%, 30% and 40% respectively of all
fishing households selected for this study. However, for the impact of DFPs on fish
consumption and causes of DFPs all the three data sets of the three types of households are
combined for the regression analysis.
55
4.4 Data processing and analysis
4.4.1 Identification of destructive fishing methods
From in-depth interviews and focused group discussions, the following fishing gears were
identified to be destructive:
1. Blast Fishing
2. Electrofishing
3. Small mesh size nets
4. Cyanide/Chemicals
Literature regarding the above destructive fishing practices were reviewed (Table 4.3).
Research evidence reveal that blast fishing reduces resilience to natural perturbations and is
more destructive than the use of chemical (McManus, et al., 1997; Pet-Soede, Cesar, & Pet,
1999; King, & Faasili, 998). The costs of blast fishing are more than its benefits (King, &
Faasili, 1998; Kunzmann, 2004; Fox, 1997) and it has serious health effects and many people
have got severe injuries while operating blasting materials (Fox, & Caldwell, 2006;
Gurumayum, & Choudhury, 2009). Blast fishing has extensive side kills of non-target and
juvenile fish and invertebrates (Gurumayum, & Choudhury, 2009; Bailey, & Jentoft, 1990).
Similarly, the use of cyanide severely affects juvenile fish and has negative effects on human
health (McManus, et al., 1997; Jones, Kildea, & Hoegh-Guldberg, 1999; Barber, & Pratt,
1997; King, & Faasili, 1998; Waqas, Malik, & Khokhar, 2012; Fox, 1997; Gurumayum, &
Choudhury, 2009; Chan, 2001; McCullough, & Hai, 2001). Gurumayum, & Choudhury
(2009) revealed that technology and introduction of new electric equipments have
tremendously increased the use of electrofishing methods. The use of environmentally
harmful nets are very efficient in catches but also result in by-catch and fingerling destruction
(Khan, & Khan, 2011; Watson, Revenga, & Kura, 2006).
56
Table 4.3: Justification for the DFPs variables
Measures and Sources Methods used Justification and impact of the
DF method with positive
negative signs
Explosives (Bomb
blasts/dynamite) (McManus, et
al., 1997; Pet-Soede, Cesar, & Pet,
1999 ;King, & Faasili, 1998;
Kunzmann, 2004; Fox, 1997;King,
& Faasili, 1999; Fox, & Caldwell,
2006; Gurumayum, & Choudhury,
2009; Bailey, & Jentoft, 1990).
Simple balance sheet
method, Survey,
Personal observations
Blast fishing reduces resilience to
natural perturbations and is more
destructive than cyanide, Blast
fishing costs are more than its
benefits, negatively affects on
human fish consumption
Extensive side kills of non-target
and juvenile fish and
invertebrates (+).
Chemicals (Poison, cyanide)
(McManus, et al., 1997; Jones,
Kildea, & Hoegh-Guldberg,
1999;Barber, & Pratt, 1997; King,
& Faasili, 1998; Waqas, Malik, &
Khokhar, 2012; Fox, 1997;
Gurumayum, & Choudhury, 2009;
Chan, 2001; McCullough, & Hai,
2001).
Simple balance sheet
method, Telephonic
survey, population
assessment surveys
Standardized survey
protocols.
Use of Cyanide affect health of
fish and humans, (+).
Electric Fishing (Gurumayum, &
Choudhury, 2009).
Survey Method Electric fishing increase with the
increase in electric equipments
used in fishing (+).
Banned nets (Khan, & Khan,
2011; Watson, Revenga, &
Kura, 2006).
Use the mapped
results to produce
maps of catches by
all gear types
annually since 1950.
Environmentally harmful nets
have been introduced in an effort
to increase fish catches (+).
Source: Literature Survey
4.4.2 Analytical Tools for Finding Causes of Destructive Fishing Practices
The growing number and size of human settlements in the neighborhood of these rivers is the
most important reason of high pressure on fisheries resources in the study area. Fishermen
reaction to degradation in local fish population in the rivers may include amplified effort,
targeting different stocks through fishing in other locations or changing equipment; reactions
that all have the capacity to successively reduce fish stocks.
57
4.2.2.1 Dependent Variable (Destructive Fishing Practices)
People residing near river bodies and fishermen have adopted several destructive fishing
methods and they employ it purposively based on their requirements and potential. Thus, the
practices employed differ among households. Through literature review, semi structured
interviews and focused group discussions with village elders and fishermen in the study area,
four destructive fishing practices (blasting, Cyanide/use of chemicals, electric fishing, and
banned nets) were identified, which were adopted by more than 10% of the people. A score of
―1‖was allotted to practices adopted by fishermen and ―0‖ to practices not adopted and an
index was created. Then, all scores were combined and divided by 4 to get a composite index
of adoption of DFPs. This index was used as dependent variable in this study. Similar method
for index construction and then using it as dependent variable has been used by Paudel, &
Thapa, 2004;Yila & Thapa 2008; Hair et al 1998; Mardia et al 1982. This index has revealed
the range of practices used but not the intensity of their use. The percentage of respondents
using different destructive methods is given in table 4.4 below.
Fisheries in district Charsadda is carried out using a few types of fishing gears. These gears
are used round the year, however only professional fishermen use specific nets for specific
specie. The most important fishing gears are cast nets with 0.5, 0.75 and 1 inch mesh size.
Fishing rods are not common due to high price and low catch, only recreational fishermen use
it for catching fish. Table 4.4 shows that most of the fishermen (78%) used electrofishing,
whereas 60 percent used small mesh size nets.
Table 4.4 Fishing practices that were used in the construction of the index of DFPs
Type of practice Adopted by number of households (f) Percentage (p)
Cyanide fishing 143 0.50
Blast fishing 153 0.53
Electrofishing 223 0.78
Small mesh size nets 172 0.60
f= frequency of households
P= percentage of n=286
58
4.2.2.2 Selection of Independent Variables
Destructive fishing practices are caused by a variety of factors. The main drivers of DFPs
were initially identified through literature review (Table 4.5). Then only those variables were
selected for the study which could be defined operationally and were measurable. Therefore
eleven variables were identified for the study, however after multivariate correlation analysis
only seven variables were identified for regression and the rest were dropped due to low
degree of correlation with the dependent variable. Then pearson correlation analysis is
conducted to choose the main factors to be used in the regression model. First of all we have
checked the data for the assumptions of partial correlation. That is the variables are
continuous variables, there are also control variables, linear relationship exists between
variables, there are no significant outliers and the data is normally distributed.
The variable availability of cultured fish in the market (table 4.5) is a very important
determinant of DFPs. Cultured fish availability can affect DFPs and can increase or decrease
the demand for catch fish (Fox, 1997; Chan, 2001). Amount of cultured fish was collected in
mounds (1 mound=40kg) from retailers in selected locations (table 4.5) through a market
survey. Due to a disorganized supply chain of culture fish in the market and lack of
recognition between wholesalers and retailers the data was collected from retailers only.
Another important variable is the fishing experience in years per respondent (household
head). DFPs require skills (Tol, 2006) and common people cannot undertake and can result in
health injuries. Distance to water bodies, which was measured in kilometers is another
important variable. It is commonly believed that people living far away from water bodies
normally are not attracted toward fishing (Tol, 2006) as compared to those living near water
bodies. Cost of gear used in fishing also affect fishing activities. Research evidence (Tol,
2006; Munyi, 2009) reveals that, the higher the cost, the higher the efficiency in catch and use
of destructive fishing practices. Research evidence reveals that decline in fish stocks in the
rivers, declining catches and fear among the fishermen (Akhtar, 2015; Munyi, 2009; Pomeroy
and Rivera-Guieb, 2006; Johnson, 1998; Khan & Khan, 2011) also leads to intensified
fishing. The level of education of respondents affects respondents fishing behavior. Previous
research evidence reveals that low level of education and environmental education or average
years of formal education (Munyi, 2009; Johnson, 1998; Wagner et al, 1999; Pet-Soede &
Erdmann, 1998; FAO. 2010) affect the use of destructive fishing practices. Age of fishermen
or the household head affect fishing activities as senior fishermen use techniques and skills
which can give them more yield and reduce the time and effort in fishing. Previous evidence
59
reveals that younger fishermen conduct more destructive fishing activities (Munyi, 2009;
Cinner, 2009). The average total household income affect fishing as those fishermen and
households with higher income can also purchase from market but the poor households have
no option but to catch in rivers and if the fish in river is low, they resort to DFPs. This was
taken as a proxy for poverty as research reveals that poor people conduct more DFPs due to
their low level of income, protein use and no alternative livelihoods opportunities (Lampe et
al, 2017; Munyi, 2009; Shumway, 1999; Clark et al., 1992; Cinner, 2009; Pet-Soede, 1998;
Pauly & Chua, 1988; Khan & Khan, 2011). Fishermen average catch per day can be an
important determinant of fishing activities. The variable was selected after an extensive
literature review. Research evidence reveals that decline in catch per unit effort leads to
intensified fishing (McManus, 1997; Fox, 1997; Odada, 2004; Cinner, 2011; McGinn, 1998;
Alcala, 1988). It can be estimated through average catch of respondents per day per effort
through different fishing gears. Availability of and number of alternative livelihoods can help
respondents adopt to other livelihood activities. Lack of alternative livelihoods (Munyi, 2009,
Pomeroy and Rivera-Guieb, 2006; Shumway, 1999; Clark et al., 1992; Johnson, 1998; FAO.
2010) is another cause of the use of destructive fishing practices. This was measured through
asking respondents regarding number of alternative livelihood options. Low level of savings
is also a factor in the use of destructive fishing practices (Johnson, 1998), because if
fishermen have lack of financial assets they conduct fishing so as to earn and maintain their
standard of living.
Table 4.5 Causes of DFPs (Literature cited with justification) S.No Variables and Sources Methods Used Hypothesized
relationship, Justification
and Impact of DFPs on
the variable with +, -
signs for Positive,
negative impact,
respectively
1. Supply of culture fish in the market
(Fox, 1997 ;Chan, 2001)
Amount of culture fish per day brought
for sale to the market
Higher culture fish
supply reduces risk to
wild caught (-).
2. Fishing experience in years (Tol,
2006).
Scoring method, Gear price surveys in the
market
The more the experience,
the more the use of DFPs
(+)
3. Distance to water bodies (Tol, 2006). Scoring method The lesser the distance
the more the use of DFPs
(-).
4. Cost of gear used (Tol, 2006; Munyi,
2009).
Gear price surveys in the market,
Ethnographic method- perceived informal
from fishermen and personal observations
Higher cost/price of gear
more efficiency in catch
and use of DFPs (+).
5. Decline in fish stocks, declining
catches and fear among the
fishermen (Akhtar, 2015; Munyi,
Observation, personal observation,
household socioeconomic surveys and
interviews; personal observation,
Decline in catch Per Unit
Effort leads to
intensified fishing (-).
60
2009; Pomeroy and Rivera-Guieb,
2006; Johnson, 1998; Khan & Khan,
2011)
household socioeconomic surveys and
interviews;
6. Level of education and
environmental education (average
years of formal education) (Munyi,
2009; Johnson, 1998; Wagner et al,
1999; Pet-Soede & Erdmann, 1998;
FAO. 2010).
Ethnographic method- perceived informal
from fishermen and personal observation
Lack of education more
DFPs (-).
7. Age of a fisher (Munyi, 2009;
Cinner, 2009)
Ethnographic method- perceived informal
from fishermen and personal observation,
Simple Balance Sheet Method
Younger people conduct
DFPs (-).
8. Poverty (Lampe et al, 2017; Munyi,
2009; Shumway, 1999; Clark et al
1992; Cinner, 2009; Pet-Soede, 1998;
Pauly & Chua, 1988; Khan & Khan,
2011).
Ethnographic method- perceived informal
from fishermen and personal
observations; multivariate material style
of life indices model (Cinner), Principal
Component analysis (Pauly); Personal
observations (Khan & Khan, 2011
poverty is not the cause of resource
degradation)
Poverty leads to the use
of DFPs (+, -).
9. Average Fish Catch Per Day
(McManus et al., 1997; Fox, 1997;
Odada, & Wandiga, 2004; King, &
Faasili, 1999; Cinner, et al., 2011;
McGinn, 1998; Alcala, 1988).
Fisheries Extension Program,
Semi-structured Interviews and
Redundancy Analysis, Field
Observations, Aerial Observations,
Surveys and Interviews with fishers,
Swimming Surveys, Simple Balance
Sheet Method Yields were estimated with
daily records of fish catches with
different gears and monthly samples of
catches.
Reduced catch leads to
using of DFPs (-)
10. Inadequate alternative livelihoods
(number of alternative opportunities),
(Munyi, 2009, Pomeroy and Rivera-
Guieb, 2006; Shumway, 1999; Clark
et al 1992; Johnson, 1998; FAO.
2010).
Ethnographic method- perceived informal
from fishermen and personal observation,
personal observation, household
socioeconomic surveys and interviews
Lack of alternative
livelihoods leads to
intensified fishing (-).
11. Low level of savings (Johnson,
1998).
Personal observation, household
socioeconomic surveys and interviews
Low savings more DFPs
(-).
12. Maximize catches/intensity of fishing
effort (Lampe et al, 2017; Munyi,
2009; Khan & Khan, 2011)
perceived informal from fishermen and
personal observations; direct observation,
KIIs, FGDs (Fridah);
The attitude to maximize
catches leads to the use
of DFPs (+).
13. Energy and time efficiency (Lampe
et al, 2017; King & Faasili, 1999).
Ethnographic method- perceived informal
from fishermen and personal
observations; Fisheries Extension
Strategy (King)
Low energy, less times
more DFPs (-).
14. Confidence and a feeling of
compatibility with some fishing
practices (Lampe et al., 2017)
perceived informal from fishermen and
personal observations, Ethnographic
method- perceived informal from
fishermen and personal observations;
More the confidence and
compatibility more the
use of DFPs (+).
15. Existence of group relationship
patterns between fishermen and the
law enforcement agencies and
destructive fishing materials sellers
(Lampe et al, 2017).
perceived informal from fishermen and
personal observations, Ethnographic
method
Good relations with law
enforcement more the
use of DFPs (+).
16. Taste of fish caught (Fox, 1997;
Chan, 2001).
Fish-taste comparison tests, Telephonic
Survey
Respondents preferred
wild caught instead of
farmed fish (+).
17. New fishing methods and Household survey, FGDs, stakeholder Efficiency in catches is
61
Technology (Khan, & Khan, 2011;
Odada, & Wandiga, 2004; Lampe et
al, 2017).
interviews, observation and interviews;
Ethnographic method- perceived informal
from fishermen and personal observations
maintained through
environmentally
damaging nets (+).
18. Regulations/ Ineffective rules/
incapacity to monitor rules and
regulations (Johnson, 1998; Satria, &
Matsuda, 2004; Khan & Khan, 2011;
Waqas, & Khokhar, 2012; Hossain,
et al., 2008; Odada, & Wandiga,
2004; King, & Faasili, 1998; FAO.
2010).
Personal observation, household
socioeconomic surveys and interviews;
Review of government records,
population assessment surveys
standardized survey protocols survey
scientific investigation of fish
Lack of law enforcement
leads to destructive
fishing (-).
19. To accomplish economic
needs/demand for resources (Lampe
et al 2017; Ram-Bidesi, 2011;
Shumway, 1999; Clark et al 1992;
FAO. 2010; Khan & Khan, 2011)
Ethnographic method- perceived informal
from fishermen and personal
observations, review, personal
observation, household socioeconomic
surveys and interviews, personal
observations, FAO general description
Higher demand for
economic needs more
the use of DFPs (+).
20. Construction of settlements/increase
in population besides major rivers
(Lampe et al 2017; Ram-Bidesi,
2011; Munyi, 2009, Pomeroy and
Rivera-Guieb, 2006; Richmond,
2002; Shumway, 1999; Clark et al.,
1992; Pauly & Chua, 1988; King &
Faasili, 1999).
Ethnographic method- perceived informal
from fishermen and personal
observations; literature
review, observation of fishing gear and
fishing practices,
and interviews (Ram), personal
observation, household socioeconomic
surveys and interviews; Principal
Component analysis (Pauly); Fisheries
Extension Strategy (King)
Increasing population
leads to the use of DFPs
(+).
21. Social and cultural perceptions
regarding water and its components
as an open access (Lampe et al,
2017)
Ethnographic method- perceived informal
from fishermen and personal observations
Depends upon social
norms (-, +).
22. Fish as the chief supply of food and
protein/ highly dependent upon
natural resources(Ram-Bidesi, 2011;
Munyi, 2009; Pomeroy and Rivera-
Guieb, 2006)
Literature review, observation of fishing
gear and fishing practices, and interviews
(Ram); personal observation, household
socioeconomic surveys and interviews
High dependence upon
natural resources lead to
the use of DFPs (+).
23. Economic and political
marginalization (Munyi, 2009;
Pomeroy and Rivera-Guieb, 2006)
Ethnographic method- perceived informal
from fishermen and personal observation
More marginalized
societies use DFPs (+).
24. Rivalry and differences over natural
resources (Munyi, 2009; Pomeroy
and Rivera-Guieb, 2006; FAO. 2010)
Ethnographic method- perceived informal
from fishermen and personal observation
Quest for food and
livelihood (+).
25. Urbanization (Richmond, 2002). (+).
26. Extreme mobility (Pet-Soede, 1998;
Munyi, 2009)
Ethnographic method- perceived informal
from fishermen and personal observation
More mobile fishers
conduct DFPs (+).
27. Seeming efficiency of destructive
fishing devices (Munyi, 2009)
Ethnographic method- perceived informal
from fishermen and personal observation
(+).
28. ―I don‟t care‖ attitude (Munyi, 2009) Ethnographic method- perceived informal
from fishermen and personal observation
Those who don‘t care for
nature uses DFPs (+).
29. inadequate access to land (Munyi,
2009; Pomeroy and Rivera-Guieb,
2006)
Ethnographic method- perceived informal
from fishermen and personal observation,
personal observation, household
socioeconomic surveys and interviews
No access to land more
use of DFPs (-).
30. Large Market (Johannes and Riepen
1995)
Personal observation, household
socioeconomic surveys and interviews
Larger the market more
the use of DFPs (+).
Source: Literature Survey
62
4.4.3 Analytical Tools for Finding Impact of DFPs on Fish Consumption
The consumption of fish people living near water bodies and fishermen is affected by a
variety of factors, including economic, social, natural, physical and environmental. Research
evidence (Table 4.6) reveal that family income, access to market, price, health, age, gender,
education, marital status, number of family members, presence of children in family,
employment, consumption season, urbanization etc. affect fish consumption of people. Per
capita fish consumption in Pakistan is 2 kg against the world average of 17 kg per year
(Wasim & Parvez, 2007; York & Gossard, 2004; FAO, 2009; Garibaldi et al., 2004).
However, the data is collected from fishermen or people living near water bodies having
higher access to fish than other people. Therefore, it is assumed that fish consumption of
respondents may be more than the per capita fish consumption in Pakistan.
Table 4.6: Justification of variables for fish consumption Variables and Sources Unit used Unit used in the
present study
Justification and Impact on
Fish Consumption with +, -
signs for Positive, negative
impact, respectively
Family income/fishing income (
Onurlubas, 2013; Nayga, & Capps,
1995; Verbeke, & Vackier, 2005; Can,
Günlü, & Can, 2015; Barberger-
Gateau, Jutand, et al., 2005)
Onurlubas
(amount in
different
currencies in
different rage)
Amount in Pakistani
Rupees
Family/fishing incomes
affect fish consumption
positively (+).
Distance to water bodies (Tol, 2006). Scoring
method
Distance to water
bodies(in Km)
The lesser the distance the
more the fish catch and
consumption
Price (Herath, & Radampola, 2016;
Lebiedzińska, Kostrzewa, et al., 2006)
Price of fish
Per kg
Price of fish Per kg in
Pakistani Rupees
Lower price leads to higher
fish consumption, +
Age (Onurlubas., 2013; Nayga, &
Capps, 1995; Can, Günlü, & Can,
2015; Perez-Cueto, Pieniak, &
Verbeke, 2011; Myrland, Trondsen,
Johnston, & Lund, 2000; Olsen, 2003;
Kull, Bergström, Lilja, Pershagen, &
Wickman, 2006)
Onurlubas (20-
21
22-23
24-25
>25)
Age of the
respondent in years
Age affect fish consumption
positively, +.
Education (Onurlubas, 2013; Verbeke,
& Vackier, 2005; Can, Günlü, & Can,
2015; Myrland, Trondsen, Johnston,
& Lund, 2000; Barberger-Gateau,
Jutand, et al., 2005)
Level 1-Level
V
Uneducated
Educated
Years of education Educated respondents
consume more fish than
uneducated,+
Household size(Onurlubas, 2013;
Nayga, & Capps, 1995; Myrland,
Trondsen, Johnston, & Lund, 2000)
˃3 person and
˂10 persons
per family
Total number of
family members
Higher the number of family
members, higher the level of
consumption, +
Fishing gears Technology (Khan, &
Khan, 2011; Odada, & Wandiga,
2004; Lampe et al, 2017).
Number of
fishing gears
Number of fishing
gears
Efficiency in catches is
maintained through
environmentally damaging
nets (+).
Source: Literature Survey
63
4.2.2.3 Models specification
4.2.2.4 Causes of Destructive Fishing Practices
The seven variables causing destructive fishing activities were analyzed using stepwise
multiple linear regressions (Hair et al 1998; Mardia et al 1982; Mehta 1998; Yila & Thapa
2008; Paudel and Thapa 2004). The dependent variable i.e. index of DFPs is numerical index
and changes from one respondent to another according to their use of different methods of
destructive fishing. This kind of investigation is an appropriate statistical method to detect the
effect of explanatory variables on the dependent variable (Yila & Thapa 2008; Paudel and
Thapa 2004; Hair et al 1998; Mardia et al 1982). Among the seven selected for regression
model one variable (stock of fish) is a dummy variable, all others are continuous variables.
This analysis has simple statistical procedure with high capability to integrate the impacts of
independent variables on the use of DFs. Initially all the sampled households were divided
into three types (farming fishers, fishing farmers and occasional fishers), in order to
differentiate between different households on the basis of various characteristics. However,
for finding the causes of DFPs the three datasets of fishers are pooled and included in the
regression model. To determine causes of DFPs the model is specified as following;
DFPs = α + β1Ed + β2Ln + β3Fs + β4Cg + β5Hp + β6Dw +β7 Cf +εi (Equation 2)
Where, DFPs is the dependent variable, α is the intercept, β1, β2 β3 β4 β5 β6 β7 are the
coefficients of explanatory variables Ed (average years of formal education of the household
head), Ln (number of alternative livelihoods), Fs (fish stock or population), Cg (cost of gear
used), Hp(average total household income, used as a proxy for poverty), Dw (distance to water
bodies), and Cf (amount of culture fish in the market). Stepwise multiple linear regression was
run on the above model and results were interpreted.
4.4.3.1 Determinants of fish consumption
There are many determinants of fish consumption, however keeping in view the local realities
and fishermen characteristics seven variables were selected for the multiple linear regression
and the model was specified as;
Fish_Cons = α + β1Fi1 + β2Dw2 + β3Pf3 + β4Fn4 + β5Hz5 + β6Ag6 + β7Ed7 ++ β8Fg8 + εi
(Equation 3)
64
Whereas Fish_Cons is the dependent variable i.e amount of fish consumed per household/year
(Kg), α is the intercept, and β1, β2 β3 β4 β5 β6 β7 are the coefficients of explanatory variables,
and Fi1, Dw2, Pf3, Fn4, Hz5, Ag6, Ed7, Fg8 are the explanatory variables, fishing income (Rs.),
distance to water bodies (Km), price of fish/Kg (Rs.), family income (Rs.), household size
(number), age of the household head (years), average years of formal education, and number
of fishing gears respectively.
4.4.5 Analytical Tools for Finding Impact of DFPs on Livelihoods
The building blocks of livelihoods are assets including social, human, physical, natural, and
financial that help to reduce vulnerability. In order to understand the significant changes in
the livelihoods of people residing near water bodies, two sets of data will be collected
regarding livelihood capitals, one for the current year 2016 and another for their assets level
in 2001.
4.4.5.1 Indicator design and analysis
Livelihood means the ―capabilities, assets and activities required for a means of living‖
(DFID, 2007; Serrat, 2008; Chambers and Conway 1992). The building blocks of livelihoods
are assets including social, human, physical, natural, and financial that helps to reduce
vulnerability of the communities to shocks. In order to understand the significant changes in
the livelihoods of the people residing near water bodies, two sets of data were collected
regarding livelihood capitals i.e., one for 2001 and another for the year 2016.
Indicators and variables have been widely used to assess livelihood assets (Chen et al., 2013;
Carney, 2003; Chambers and Conway, 1992; Thomas, 2008). In this study, we selected 19
variables to represent the five livelihood assets (table 3). The major reasons for the selection
of these variables for every kind of livelihood asset is related with the state of livelihood
conditions, fishing regulations and intensity of DFPs in inland waters by fishing communities
under consideration. The indices derived from the variables in this study were between the
range of 0 to 1, the higher values show better livelihood assets of the fishing community and
vice versa. These indices were then depicted in the livelihood asset pentagon, which is a
component of the sustainable livelihood framework (Shivakoti, and Shrestha, 2005).
65
Human capital relate to qualities, traits or situations that can improve or reduce the capacity
of fishermen and respondents in general to carry out their fishing activities. Variables
representing human capital assets include education, and skills. Education was considered as
a variable of human capital because literate people have greater awareness regarding the
disastrous impacts of destructive fishing practices (Verbeke et al., 2005; Leisher et al., 2012;
Pet and Djohani, 1998; Babulo et al., 2008; Cinner, 2009). Skill is an important determinant
for fishing because fishing needs knowledge of open waters and many individuals believe that
lack of skill would exclude them from entering the fishing sector (Chen et al., 2013; Peñalb
and Elazegui, 2011; Babulo et al., 2008; Allison and Ellis, 2001).
The financial assets were measured as indices of income earned through selling fish, savings
and access to credits (Babulo et al., 2008). The word regular inflow of money from fishing is
used in this study in order to exclude income from other sources as some of the respondents
were also related to farming occupations, part-time or seasonal fishermen.
Access to natural resources e.g. land, forest, water is considered as natural assets (DFID,
2007; Babulo et al., 2008). Full access to a capital assets assume the value of 1 and no access
assume the value of 0 (Shivakoti and Shrestha, 2005). Therefore anything that restricts one‘s
access to the natural resource is depriving one of the use of that natural resource. Access to
assets is allowed or hampered by the policy and institutional framework of livelihoods
(Allison and Ellis, 2001). Therefore, in this study the variables of the natural assets are
derived mostly from conservation efforts by the government i.e. licensing, number of
watchers, litigation process and fish size and amount. The respondents were asked whether
licensing, number of watchers and litigation has reduced their access to the water bodies or
not? The response was coded as yes=0, no=1, because these factors negatively affect the
amount of natural capital for the fishermen. Secondly, results of the FGD and interviews with
the key informants reveal that fish population and size has been significantly reduced over the
past 15 years. So within the natural assets the variable fish size and amount was included,
because this also affects their access to natural resource.
The indices for the physical capital assets include variables like housing, energy supply,
transport facility for taking fish to the market and availability of fishing tools (Babulo et al.,
2008). Both transport facility and fishing tools ownership increase their capacity to catch and
earn high level of income.
66
The social capital includes social networks and memberships (Peñalba and Elazegui, 2011;
Babulo et al., 2008). The social capital was calculated as indices of local union council
membership, membership in political parties, and networking with law enforcement agencies
i.e. police and courts, contacts with village elders, networking with other households and
kinship support. These variables were included because the participation and connections in
these associations help them in the conduction of DFPs (personal observation), besides the
provision of destructive fishing material. These livelihood changes are shown by livelihood
asset pentagon, which reveal the significant differences in the livelihoods of people between
2001 and 2016.
4.4.5.2 Measurement design
To measure the changes in livelihoods of fishermen and to develop a livelihood asset
pentagon, we adopted the indicator design used by (Chen et al., 2013) and modified it keeping
in view the social and sociological characteristics of the study area and nature of data.
Different scaling and indexing techniques are employed to make them comparable and to
draw meaningful explanations. The rating scale method with varying weights was used to
determine the variables. The livelihood index ranging from 0–0.33 is interpreted as poor; the
one with 0.34–0.66 as average and with 0.67–1 is interpreted as good. Furthermore, to carry
out the calculations expediently, three critical values: 0.33, 0.66 and 1 were selected to
replace poor, average and good performance, respectively (Muangkaew and Shivakoti, 2005;
Chen et al., 2013). The weighting method is designed in three ways. For answers to questions
in the form of numerical values, the ―mean value‖ is the important determinant in the design
of this type of technique. Less than the ―Mean‖ is considered ―Poor‖, with weight value of
―0.33‖; greater than the ―Mean‖ but less than ―1.5 × Mean‖ is considered ―Average‖, with a
weight value of ―0.66‖; and greater than ―1.5 × Mean‖ is considered as ―Good‖, with a weight
value of ―1‖(Chen et al., 2013).
I = (Mean) % × 0.33 + (Mean < Average < 1.5 × Mean)% × 0.66 + (> 1.5 × Mean)% × 1
(Equation 4)
For answers to questions in the form of good, average and poor, the index was developed as;
I = Good% × 1 + Average% × 0.66 + Poor% × 0.33. (Equation 5)
For answers to questions in the form of yes, no, the index was developed as;
I = Yes% × 1 + No% × 0 (Equation 6)
67
After calculations of the relevant indices for the concerned variables, a composite
measurement index for each type of asset is calculated as;
(Equation 7)
Where C= criteria score for each asset (0 ≤ C ≤ 1), n refers to the nth indictor of criteria (n =
1, 2, . . . n); I refers to indicator; and T refers to total number of indicators. Whereas, the
gross value of livelihood assets for each period is calculated as; LAs =
HA+EA+NA+PA+SA/5. LAs refer to livelihood assets; HA refers to human assets; EA
economic assets; NA natural assets; PA physical assets; and SA social assets.
Table 4.7: Statistical techniques used for the analysis Objectives
Parameters Major variables Statistical methods
To study the
socio-economic
characteristics
of the fishermen
Demographic
characteristics
Household size, age structure, educational attainment Descriptive statistics
Land holding size Area of land holding Descriptive statistics
Financial Assets Average annual fishing income, average savings,
average total household income
Descriptive statistics
Physical Assets Number of fishing gears Descriptive statistics
Natural Assets Average number of species caught, Impact of
licensing, number of watchers and litigation process
on access to fisheries resources, fish size and amount
Descriptive statistics,
Priority index
Social Assets
Membership in political parties, union council, law
enforcement agencies, village chiefs etc.
Descriptive statistics
Human Assets
Fishing experience Descriptive statistics
To compare
household
assets
Indicators of
households five
livelihood capitals
57 variables (subcomponents of livelihood assets) Kruskal-Wallis H test
To Know about
the causes of
DFPs
Fishermen
perceptions
Fishermen perceptions about DFPs and its causes. i.e.
average years of formal education of the household
head, number of alternative livelihoods, fish stock or
population, cost of gear used, average total household
income, distance to water bodies, and cost of gear
used.
Correlation, Stepwise
multiple linear
regression,
descriptive statistics
To determine
the impact of
DFPs on
fishermen
livelihoods and
consumption
Livelihoods assets
and fish
consumption
pattern and
socioeconomic
characteristics
For impact on fishermen livelihoods five assets with
nineteen variables.
For consumption the price of fish, distance to water
bodies, number of fishing gears, average years of
formal education, family income, household size,
fishing income
Livelihoods asset
pentagon,
Correlation, multiple
linear regression,
To investigate
the conservation
measures and
regulatory
framework
Conservation
measures
Number of licenses issued, income to fisheries deptt.,
farms established, fish production, publicity and
research undertaken
Descriptive statistics
68
Chapter 5
Results and Discussions
Knowing about the socio-economic characteristics of households of a particular study is
critical in their socio-economic improvement. DFPs are the result of many drives imbedded in
the socio-economic environment of the fishermen and hence it should be evaluated from the
socio-economic point of view. As DFPs are the outcome of the multifaceted relationship
between environment and society or in other words socio-economic characteristics of the
fishermen and DFPs have mutual association. Therefore the study of socio-economic features
of the households is essential. This chapter describes the results of the FGDs, socio-economic
features of fishermen, conservation measures, and causes of DFPs and impact of DFPs on
fishermen livelihoods.
5.1Results of FGDs on DFPs
The focus group interviews revealed that fishers mostly adopt destructive fishing methods due
to lack of awareness of natural resources and reduced fish population in rivers. Most people
don‘t hold licenses due to lack of proper implementation of fishery regulations or are being
influential people. Similarly, the use of DFPs is believed to be the underlying driver in
reduced levels of income and fish consumption for fishers. 89% of respondents compared
their present catch with the past and concluded that fish size and amount has considerably
reduced in the local rivers. 75% responded that the open access nature of fishery and the use
of electric generators are the major driving factors leading to reduced fishing stock in rivers.
Almost 80 percent respondents replied that DFPs can be reduced through implementation of
fishery rules, increase in the number of fishery monitors and community participation.
5.2 Socioeconomic characteristics of fishermen for 2001 and 2016
Table 5.1 shows general descriptive statistics of the sample households. The results reveal
that average annual fishing income was Rs. 27,235 in 2016 compared to Rs. 40,115 in 2001,
showing a 32% decline. This decline in fishing income is an evidence of reduced fishing
activity in this area. However average total household income has shown a slight increase
from Rs.234, 055 to Rs. 263,391, due to other sources of income. Similarly, average annual
saving from fishing income declined from Rs. 8400 to Rs. 4,400. Average household size is
about 8 to 10 persons per family illustrating the burden on meager family income. Average
69
number of species caught per day per effort in 2001 was about 6 which have reduced to about
4, supporting the results of FGDs and key informants interviews. Average age of the
respondent was about 40 and on average household heads have 20 years of fishing
experience. Respondents have on average 3 to 4 fishing gears and five years of fishing
experience. On average fishermen consume 30% and sell 70% of their catch. The results of
paired sample t-test (table 2) reveal that in almost all cases the 2 standard deviations are larger
than the difference between the means, so the hypothesis of equal means is not supported.
Results revealed that the size and stock of fish have reduced during the past 15 years. To cope
with the decrease in fish catch, some fishermen have either left the fishing occupation,
changed fishing gears or have reduced mesh size.
Table 5.1: Socioeconomic characteristics of fishermen in 2001 and 2016 (n=286)
Note: 95% confidence level. The amounts measured in Pakistani rupees, the average exchange
rate during 2016 was $1=Rs.104
S.No
.
Household Characteristics Year Fishing Households (n=286)
Mean
St. Deviation
t-test p-value
1. Average annual fishing income (Rs.) 2001 40,115±26,273 10.12 0.006
2016 27,325±16,933
2. Average total household income (Rs.) 2001 23,4055±14,8400 -5.44 0.000
2016 26,3391±16,5974
3. Average annual savings from fishing
income
2001 8,400±9,433 3.88 0.000
2016 4,400±6,415
4. Average household size (number) 2001 8.16±3.66 -5.97 0.000
2016 9.27±4.24
5. Average number of species caught 2001 5.96±1.44 29.91 0.000
2016 3.25±1.88
6. Average age of the HH (yrs) 2016 40.96±8.60
7. Fishing experience (years) of HH 2016 19.47±7.06
8. Average years of formal education of
HH
2016 5.09±5.00
9. Total value of fishing assets (Rs.) or
no. of gears
2016 3.94±1.75
10. Amount of fish consumed (%) 2016 30.84±27.71
11. Amount sold (%) 2016 69.23±27.62
70
5.2.1 Age structure
The total sample (286) was divided in three types of fishers. Type I (Farming fishers) and
type II (Fishing farmers) were 30% each respectively, while type III (Occasional fishers) was
40% of the selected sample. The average age of occasional fishers was lower (36 years) than
farming fishers (42 years) and fishing farmers (40 years). This high average age within all the
three groups reveals the fact that data was collected from household head. The age structure
of fishing farmers (86) and occasional fishers (85) is almost the same, with 41 and 42 percent
respondents belonging to 36-45 age group, respectively. Out of the total farming fishers 40
percent belonged to 36-45 years age group (Figure 5.1a). Similarly, 31 percent of the
households belonged to the age group 46-55. The fishing farmers have almost the same age
characteristics as farming fishers with 41 percent in the age group 36-45 and 35 percent in the
age group 26-35 (Figure 5.1b). 42 percent of the occasional fishers fall within the age group
of 36-45 and 32 percent in 26-35, while 19 percent in 46-55(Figure 5.1c). Only 7 percent
belong to the age group 56-65.
Figure 5.1(a) Age structure of farming fishers.
Figure 5.1(b) Age structure of fishing farmers Figure 5.1(c) Age structure of occasional farmers.
71
5.2.2 Educational attainment
Majority of the surveyed household heads were illiterate. However occasional fishers had
more than seven years of formal education, followed by fishing farmers with almost 6 years
and farming fishers almost 3 years (table 5.2). This reveals the fact that farming fishers and
fishing farmers who conduct fishing and farming as primary activities are mostly illiterate,
whereas occasional fishers fish either part time or as a recreational activity.
Table 5.2: Average years of formal education
Level Study area total (n=286)
Farming fishers
(n=30)
Fishing farmers (n=86) Occasional fishers (n=40)
%
Average years of
formal education
2.47±3.57 5.88±4.84 7.88±5.694
Note: Avg. years of formal education ± Standard Deviation
Source: Field Survey, 2016.
5.2.3 Land holding size
Farming fishers hold higher average land holding size (6.5 acres), followed by occasional
fishers with 4.6 acres and farming fishers 4.0 acres (table 5.3). The results indicate that
fishing farmers are the poorer households, holding lower land and fishing assets.
Table 5.3: Distribution of land holdings by type of fishers Type of fishers Average land holdings (area in acres)
Farming fishers 6.5±2.7 (86)
Fishing farmers 4.0±1.6 (85)
Occasional fishers 4.6±1.8 (115)
Note: Av. holding size ± Standard Deviation, Figures in parenthesis refer to the number of
observations.
Source: Field Survey, 2016.
5.3 Conservation Measures
Fishermen were asked simple questions in order to understand how conservation efforts have
affected fishermen access to fisheries resources.
Does licensing have restricted/reduced your access to fisheries?
Licensing allows people to use fisheries resources. In the study such licenses are issued on
seasonal basis. Those who don‘t have license are restricted from fishing activities. The
72
following data reveals that licensing was not a hurdle in fishing during 2001 as only 9 percent
of the farming fishers said licensing has restricted their access to fisheries but in 2016, 29
percent said that their access to water was affected due to licensing. Licensing has affected
farming fishers hardly due to their conduct of destructive fishing practices. 45 percent of
fishing farmers said their access to fisheries has restricted due to licensing (table 5.4).
Table 5.4: Impact of licensing on access to water resources Response 2016 2001
Farming
fishers
(N=86)
Fishing
farmers
(N=85)
Occasional
fishers
(N=115)
Farming
fishers
(N=86)
Fishing
farmers
(N=85)
Occasional
fishers
(N=115)
Yes 29 (33.7%) 45(53%) 42(36.5%) 09(10.5%) 08(9.4%) 08(9.4%)
No 57(66.3%) 40(47%) 73(63.5%) 77(89.5%) 77(90.6%) 107(93%) Total 100% 100% 100% 100% 100% 100%
Source: Field Survey, 2016
Do fishery watchers have restricted/reduced your access to fisheries?
Existence of fishery watchers also restricts those from fishing who don‘t have license and
conduct of destructive fishing practices. The results showed that in all the three groups in
2001 less than 10 percent of the respondent replied that watchers have restricted their access
to fishing, whereas in 2016 more than 30 percent replied that their access to fisheries resource
have been restricted due to the presence of watchers.
Table 5.5: Impact of fishery watchers on access to water resources Response 2016 2001
Farming
fishers
(N=86)
Fishing
farmers
(N=85)
Occasional
fishers
(N=115)
Farming
fishers
(N=86)
Fishing
farmers
(N=85)
Occasional
fishers
(N=115)
Yes 32(37.2%) 34(40%) 36 (31.3%) 05(5.9%) 05(5.9%) 09(7.8%)
No 54(62.8%) 51(60%) 79(68.7%) 80(94.1%) 80(94.1%) 106(92.2%)
Total 100% 100% 100% 100% 100% 100%
Source: Field Survey, 2016
Does fishery litigation process have restricted/reduced your access to fisheries?
Litigation and court cases also help in reducing not only illegal fishing but the use of
destructive fishing practices. In 2016 more than 20 percent in each type of fishers replied that
litigation has reduced their access to fisheries resources, whereas in 2001 more than 80
percent replied that litigation had no effect on their fishing activities (table 5.6).
73
Table 5.6: Impact of fishery litigation process on access to water resources Response 2016 2001
Farming
fishers
(N=86)
Fishing
farmers
(N=85)
Occasional
fishers
(N=115)
Farming
fishers
(N=86)
Fishing
farmers
(N=85)
Occasional
fishers
(N=115)
Yes 21(24.4%) 25(29.4%) 24 (20.9%) 06(7%) 03(3.5%) 08(7%)
No 65(75.6%) 60(70.6%) 91(79.1%) 80(93%) 82(96.5%) 107(93%)
Total 100% 100% 100% 100% 100% 100%
Source: Field Survey, 2016
Does fish size and amount has decreased over the past fifteen years?
Table 5.7 shows that the size and amount of fish has decreased tremendously over the past
fifteen years. More than 80 percent of the occasional fishermen and 73.3 percent farming
fishers and 84.7 percent of fishing farmers replied that they catch fish in lower size and
amount than they enjoyed catching over the past fifteen years (table 5.7).
Table 5.7: Fish size and amount Response 2016
Farming fishers
(N=86)
Fishing farmers
(N=85)
Occasional fishers
(N=115)
No 23(26.7%) 13(15.3%) 21 (18.3%)
Yes 63(73.3%) 72(84.7%) 94(81.7%) Total 100% 100% 100%
Source: Field Survey, 2016
Fishermen perception regarding fisheries resource degradation
Fishermen, village elders and fisheries officials revealed their views regarding the present
state of fisheries resources. This perception was verified with a household survey. Fishermen
were asked about their perception on the present fisheries resources in the rivers of district
Charsadda.
74
About 87% of fishers avowed that the fisheries resources are declining (Figure 5.2). The
fishers described it on the basis of declining catches of different varieties of fishes in the
study area. Only 4 percent of the fishermen said that the fisheries resources have increased,
which might be due to their younger age or lack of information. 9 percent replied that the
fisheries resource has remained stable during the past fifteen years. The results revealed that
there is severe decline of fisheries resources in the rivers of the study area.
5.4 Causes of destructive fishing practices
Knowledge about causes and status of DFPs is vital in the formulation of sustainable fisheries
management strategies. In this chapter the main drivers of destructive fishing practices were
identified. These practices have ruthlessly degraded the fish fauna in the rivers of the study
area. Due to the open access nature of rivers, increase in population near river banks,
poverty, lack of alternative livelihoods and many other cultural and socioeconomic forces
have paved the way for the use of destructive fishing practices. Initially through an in depth
literature review 30 variables were identified causing destructive fishing practices. These
variables were narrowed down to eleven variables due to measurement and model limitations.
After multicollinearity test only eight variables were found correlated with the dependent
variable, however due to weak correlation one correlation was dropped and seven explanatory
variables selected for the stepwise multiple linear regression analysis.
The results revealed that eight variables were found correlated with the dependent variable i.e
index of DFPs (table 5.8) and these variables have no multicollinearity with the other
independent variables. High negative partial correlation was found between DFPs and supply
of culture fish in the market (13.48±12.13), Inadequate alternative livelihoods (1.40±1.39),
distance to water bodies and (2.96±1.73 Km/s), and decline in fish stock (1.46±0.753),
whereas the partial correlation between level of education (7.73±6.155), and cost of gear used
(31941±30905) was positive. The partial correlation between Poverty (382624±179518 was
moderate negative and level of savings (3796±2779 in Rs.) was moderate and positive (r
(283) = 0.256, n = 286, p = .000). Among the independent variables selected for the model
include level of education (r= 0.684), number of alternative livelihoods (r= - 0.658), supply of
culture fish in the market (r= - 0.618), cost of gear used (r= 0.574), decline in fish stock (-
0.520), distance to water bodies (- 0.503), poverty or average household income (- 0.370) and
low level of savings (0.256). Among the eight variables significantly correlated with the
dependent variable index of DFPs, low level of savings was found significant at 0.05
75
confidence level, showing its weak correlation with the index of DFPs, while the other seven
variables were significant at 0.01 confidence level, therefore this variable was dropped from
the model and the model was run with only seven remaining variables.
Table: 5.8 Correlation and other characteristics of explanatory variables selected for the regression
model. Variable Variables
code
Description and unit
of measurement
Variable type Mean±S.D Pearson
correlation
value (r)
Low level of education and
environmental education (average
years of formal education)
Ed Average years of
formal education Continuous 7.73±6.155 0.684**
Inadequate alternative livelihoods
(number of alternative
opportunities)
Ln Number of
alternative livelihood
opportunities
-do- 1.40±1.39 -0.658**
Poverty (Low level of income) Hp Average total
household income
was taken as a proxy
for poverty level
-do- 382624±1795
18
-0.370**
Cost of gear used Cg Amount in Pak.
rupees -do- 31941±30905 0.574**
Distance to water bodies Dw Measured in Km -do- 2.96±1.73 -0.503**
Supply of culture fish in the
market
Cf Amount in tons Continuous 13.48±12.13 - 0.618**
Decline in fish stocks, declining
catches and fear among the
fishermen
Fs Dummy, taking a
value of 3 for
increase in fish stock,
2 for constant and 1
for decrease in fish
stock
Dummy, taking
a value of 3 for
increase in fish
stock, 2 for
constant and 1
for decrease in
fish stock
1.46±0.753 -0.520**
Low level of savings SL Measured in Pak. Rs. -do- 3796±2779 0.256*
Average Fish Catch Per Day Ac Amount of fish in Kg
per day per effort -do- 4.16±1.37 -0.078
Age of a fisher Af Age in years -do- 39.53±9.21 -0.167
Fishing experience in years
Ey Years
-do- 19.44±7.05 -0.088
Note: *, ٭٭, Correlation is significant at 99% and 95% confidence levels, respectively.
Two tailed test
5.4.3 Model specification for finding the causes of destructive fishing practices
The seven variables causing destructive fishing activities were analyzed using stepwise
multiple linear regression models (Hair et al., 1998; Mardia et al., 1982; Mehta 1998; Yila &
Thapa 2008; Paudel and Thapa 2004). The dependent variable i.e. index of DFPs is numerical
index and changes from one respondent to another according to their use of different methods
of destructive fishing. This type of analysis is a suitable statistical method to find out the
influence of explanatory variables on the dependent variable (Yila & Thapa 2008; Paudel and
Thapa 2004; Hair et al., 1998; Mardia et al., 1982). Keeping in view the objectives of research
76
i.e to find out the causes of DFPs in a simple way in order to recommend for effective policy
making, a simple analytical model like that of (Yila & Thapa 2008; Paudel and Thapa 2004)
was designed. The causes of DFPs were analyzed using stepwise multiple linear regression
models, which is effective for building of a model when both dependent and independent
variables are numerical (Paudel & Thapa 2004). Among the seven selected explanatory
variables for the regression model, one variable (stock of fish) is a dummy variable, all others
are continuous variables. This analysis has simple statistical procedure with high capability to
integrate the impacts of independent variables on the use of DFs. Initially all the sampled
households were divided into three types (farming fishers, fishing farmers and occasional
fishers), in order to differentiate between different households on the basis of various
characteristics. However, in finding the causes of DFPs the three datasets of fishers were
pooled and included into the regression model. To determine causes of DFPs on the DFPs the
model is specified as following;
DFPs = α + β1Ed + β2Ln + β3Fs + β4Cg + β5Hp + β6Dw +β7 Cf +εi (Equation 8)
Where, DFPs is the dependent variable, α is the intercept, β1, β2 β3 β4 β5 β6 β7 are the
coefficients of independent variables Ed (average years of formal education of the household
head), Ln (number of alternative livelihoods), Fs (fish stock or population), Cg (cost of gear
used), Hp(average total household income, used as a proxy for poverty), Dw (distance to water
bodies), and Cf (amount of culture fish in the market).
5.4.4 Results of the stepwise multiple linear regression
Prediction of the models
The explanatory variables were entered step by step in to the regression model. All of the
seven independent variables in the model have significantly influenced the destructive fishing
activities (Table 5.9).
77
Table 5.9 Summary of the step wise regression model
Model R R square Adjusted R
square
Standard
error of the
estimate
1 0.686a 0.47 0.469 0.15820
2 0.770b 0.593 0.590 0.13898
3 0.804c 0.646 0.642 0.12992
4 0.825d 0.681 0.677 0.12346
5 0.848e 0.720 0.715 0.11596
6 0.859f 0.738 0.733 0.11227
7 0.864g 0.747 0.741 0.11053
a. Predictors: (Constant), Average years of formal education
b. Predictors: (Constant), Average years of formal education, number of alternative livelihoods
c. Predictors: (Constant), Average years of formal education, number of alternative livelihoods, Fish stock
d. Predictors: (Constant), Average years of formal education, number of alternative livelihoods, Fish stock,
Cost of gear used
e. Predictors: (Constant), Average years of formal education, number of alternative livelihoods, Fish stock,
Cost of gear used, Average total HH income (proxy for poverty)
f. Predictors: (Constant), Average years of formal education, number of alternative livelihoods, Fish stock,
Cost of gear used, Average total HH income (proxy for poverty), Distance to water bodies
g. Predictors: (Constant), Average years of formal education, number of alternative livelihoods, Fish stock,
Cost of gear used, Average total HH income (proxy for poverty), Distance to water bodies, Amount of
culture fish available per day.
The results of the stepwise multiple regressions show that all of the variables that were
entered stepwise in to the model significantly explain the variation in the DFPs variable. Both
R and R square values have increased with the addition of explanatory variables from first
variable to the seventh. Similarly, both R and R square values have reasonable explanatory
power on the models. The last model, with seven explanatory variables, has significantly
high level of explanatory power, which was revealed in the adjusted R square value showing
74.1 percent variation in the use of DFPs has been explained by the model. The model is also
statistically significant with lower standard errors of the estimates.
Table 5.10 shows the F ratio of the independent variables in all the models is statistically
significant showing that the variables included in the model are correct and the overall model
is best fit.
78
Table 5.10 ANOVA of the regression models
Model Sum of
squares
Degree
of
freedom
Mean
square
F ratio Significance
1. Regression 6.327 1 6.327 252.819 0.000a
Residual 7.107 284 .025
Total 13.434 285
2. Regression 7.968 2 3.984 206.279 0.000b
Residual 5.466 283 .019
Total 13.434 285
3. Regression 8.675 3 2.892 171.317 0.000c
Residual 4.760 282 .017
Total 13.434 285
4. Regression 9.151 4 2.288 150.094 0.000d
Residual 4.283 281 .015
Total 13.434 285
5. Regression 9.670 5 1.934 143.827 0.000e
Residual 3.765 280 .013
Total 13.434 285
6. Regression 9.918 6 1.653 131.133 0.000f
Residual 3.517 279 .013
Total 13.434 285
7. Regression 10.038 7 1.434 117.366 0.000g
Residual 3.397 278 .012
Total 13.434 285
Note: see the note of above table 5.10 for the name of the variables.
Results of the regression model indicated that DFPs have been significantly influenced by the
seven explanatory variables. These variables are, average years of formal education of the
household head (Ed), number of alternative livelihood opportunities (LN), fish stock (Fs), Cost
of gear/s used for fishing (Cg), Poverty- measured by the total household income (Hp),
distance to water bodies (Dw) and supply of culture fish into the market (Ct). Out of the seven
significant explanatory variables the first variable, average years of formal education of the
household head), alone explains 47% of the total variation in the dependent variable (Table
79
5.9). The first three independent variables jointly explained 64% of the total variation, which
shows the importance of these factors in the DFPs. The rest of the four variables have less
explanatory power but are important due to its strong correlation with the dependent variable
and bear significant policy implications. The last model explains 74.7% combined
explanatory power, which reveals the fact that all the variables significantly influence
destructive fishing activities in the study area.
The regression results revealed that out of the total seven variables five variables have
negative effect on DFPs. These include number of alternative livelihoods, fish stock in rivers,
average total household income, distance to water bodies and amount of culture fish into the
market. With a unit increase in the number of alternative livelihoods, stock of fish in rivers,
average total household income, distance to water bodies and amount of culture fish into the
market, DFPs decrease by – 0.210, - 0.142, - 0.200, - 0.146, -0.125 units respectively (Table
5.11), which shows the importance of all these five variables in DFPs. However, average
years of formal education and the cost of gears have a positive effect on the dependent
variable. The higher ―t‖ values also reveal the fact that all the seven variables are significant
at 99% confidence level. The standard errors of the estimates also show a very small variation
which is not explained by the independent variables.
Table 5.11 Coefficients of the explanatory variables included in the regression model
Unstandardized
coefficients
Standardized
coefficients
t significance
B Standar
d error
(Constant) 0.727 .027 27.062 0.000
Average years of formal
education of the household head
0.010 .001 0.287 7.352 0.000
Number of alternative
livelihood opportunities
- 0.033 .006 - 0.210 -5.400 0.000
Fish stock or population in
rivers
- 0.041 .010 - 0.142 -4.072 0.000
Cost of gear used in fishing 1.426E-6 .000 0.216 6.060 0.000
Average total household income - 2.407E-7 .000 -0.200 -6.269 0.000
Distance to water bodies - 0.009 .002 -0.146 -4.418 0.000
Amount of culture fish into the
market
- 0.002 .001 - 0.125 - 3.137 0.002
80
5.5 Impact of destructive fishing practices on fishermen livelihoods
The problem of decreasing fish stocks due to destructive fishing practices is often
compounded for people whose incomes, food supplies and livelihoods are mostly based on
fish. Although fisheries is still a major source of livelihood in Charsadda but fish resources
are faced with declining fish stocks leading to changes in fishing practices and livelihoods of
fishermen. Therefore this chapter discusses the transformations in socioeconomic patterns of
fishermen due to the use of DFPs.
In order to understand the significant changes in the livelihoods of the people residing near
water bodies, two sets of data were collected from households regarding livelihood capitals
i.e., one for 2001 and another for the year 2016. Indicators and variables have been widely
used to assess livelihood assets (Chen et al., 2013; Carney, 2003; Chambers and Conway,
1992; Thomas, 2008). In this study, we selected 19 variables to represent the five livelihood
assets. The major reasons for the selection of these variables for every kind of livelihood asset
is linked with the state of livelihood circumstances, fishing regulations and intensity of DFPs
in inland waters by fishing communities under consideration. The indices derived from the
variables in this study were between the range of 0 to 1, the higher values show better
livelihood assets of the fishing community and vice versa. These indices were then depicted
in the livelihood asset pentagon, which is a component of the sustainable livelihood
framework (Shivakoti, and Shrestha, 2005). To measure the changes in livelihoods of
fishermen and to develop a livelihood asset pentagon, we adopted the indicator design used
by (Chen et al., 2013) and modified it based on the reality of the study area and data
characteristics. Different scaling and indexing techniques are employed to make them
comparable and to draw meaningful explanations.
5.5.1 Changes in fishermen livelihood assets from 2001 to 2016
Changes in livelihood assets from 2001 to 2016 are obvious from tables 5.12, 5.13, 5.14 and
figures 5.3, 5.4, and 5.5 for farming fishers, fishing farmers and occasional fishers
respectively. Changes in livelihood assets vary across different types of households and are
discussed below;
81
5.5.1.1 Farming Fishers
The total figure for livelihood assets is 0.40 in 2001 and 0.33 in 2016 for farming fishers. The
farming fishers were already very poor due to index value of 0.40 but their economic
conditions worsened (index value of 0.33) due to reduced amount and size of fish in rivers.
The deterioration in the livelihood conditions is the product of the combined impact of all
types of livelihood assets. However, variations in different kinds of assets show varying
results and characteristics.
The value of financial capital in 2001 is 0.53, and it dropped to 0.35 in 2016. Although there
is a decrease of 18%, both these values still belong to the range ―0.33-0.66‖, which shows that
in the past 15 years, the change in financial assets is not very significant. However, the
change in financial assets has now reached the lowest bottom of average category. The value
of physical capital in 2001 is 0.38, and it fell to 0.28 in 2010. There is a decrease of 10%,
dropping this value from average to the poor category, representing a significant deterioration
in physical assets because these fishermen have lost, destroyed or discarded some of the
fishing tools due to reduced fishing activity or using specie specific gears.
Natural assets in this respect are with reference to fishermen livelihoods, i.e. access to natural
assets improves fishermen livelihoods but on the other hand overexploitation of the natural
assets deteriorates the natural environment. For example, fishermen were asked whether
licensing, number of watchers and litigation has reduced their access to water bodies. In this
study we have assumed that anything that restricts fishermen access to water bodies will
negatively affect their livelihoods and improve the conservation efforts. The value of natural
assets is 0.23 in 2001 and it increased to 0.27 in 2016. The value in both 2001 and 2016
belong to the interval ―0–0.33‖, which shows that although conservation efforts have
improved but has at the same time affected the livelihoods of people conducting destructive
fishing practices.
The value of social capital in 2001 is (0.50), fell to (0.35) in 2016. Both of the figures fall
within the ―average‖ range, but the decrease of 15% in the past fifteen years is significant.
Fishermen contacts and networking has been severely affected in the past fifteen years. The
value of human capital for farming fishers has remained the same from 2001 to 2016 (0.38),
which belong to ―average‖ range. These changes in the livelihoods are depicted in the
82
livelihoods asset pentagon (figure 5.3), showing decline in financial, physical and social
assets and an improvement in natural assets.
Table 5.12: Total value of livelihood assets from 2001 to 2016 for Type I Households
Capitals Variables 2001 2016
Weight Capital
Value
Weight Capital
Value
Economic
Assets
Fishing income
Savings from fishing income
Access to credits
0.53
0.49
0.58
0.53 0.45
0.41
0.20
0.35
Physical
Assets
House ownership
Energy Supply
Transport facility
Fishing tools ownership
0.69
0.23
0.17
0.43
0.38 0.32
0.25
0.18
0.37
0.28
Natural
Assets
Licensing
Watchers
Litigation
Fish size and amount
0.07
0.08
0.06
0.69
0.23 0.36
0.31
0.21
0.21
0.27
Social
Assets
Union Council membership
Membership in political parties
Networking with law enforcement
agencies
Contacts with village elders
Networking with other households
Kinship support
0.40
0.37
0.60
0.50
0.58
0.57
0.50
0.63
0.22
0.23
0.30
0.26
0.51
0.35
Human
Assets
Education
Skill
0.25
0.51
0.38 0.39
0.37
0.38
Livelihood
Assets
0.40 0.33
Figure 5.3: Livelihood Assets for Type I Households
83
5.5.1.2 Fishing Farmers
For fishing farmers, the sum value of livelihood assets is 0.36 in 2001 and 0.38 in 2016,
showing a 2% increase. A small decrease in financial, physical and social assets is witnessed
during 2001 to 2016 (Table 5.13). However, human assets have gained 7% during the period.
Natural assets (conservation) have improved by 9% but this restriction has negative effect on
the livelihoods of fishermen. Figure 5.4 shows changes in livelihoods assets through the
livelihood asset pentagon, showing improvements in natural and human assets, and a small
increase in social assets. The figure shows decrease in financial and physical assets for fishing
farmers. The decline in financial and physical assets reveals that fishing activities of farming
fishers have been severely affected over the study period.
Table 5.13: Total value of livelihood assets from 2001 to 2016 for Type II Households
Capitals Indicators 2001 2016
Indicator
Weight
Capital
Value
Indicator
Weight
Capital
Value
Economic
Assets
Fishing income
Savings from fishing income
Access to credits
0.47
0.40
0.29
0.39 0.45
0.36
0.21
0.34
Physical
Assets
House ownership
Energy Supply
Transport facility
Fishing tools ownership
0.23
0.29
0.21
0.54
0.32 0.19
0.34
0.30
0.33
0.29
Natural
Assets
Licensing
Watchers
Litigation
Fish size and amount
0.10
0.13
0.07
0.56
0.22 0.35
0.37
0.24
0.27
0.31
Social
Assets
Union Council membership
Membership in political parties
Networking with law enforcement
agencies
Contacts with village elders
Networking with other households
Kinship support
0.70
0.41
0.24
0.57
0.49
0.57
0.50 0.77
0.53
0.13
0.65
0.30
0.49
0.48
Human
Assets
Education
Skill
0.36
0.43
0.40 0.46
0.48
0.47
Livelihood
Assets
0.36 0.38
84
Figure 5.4: Livelihood Assets for Type II Household
5.5.1.3 Occasional Fishers
The overall value of livelihood assets for occasional fishers is 0.44 in 2001 and it increased to
0.49 in 2016 (Table 5.14). Although there is an increase of 5%, but both of these values lie in
the average range. The major contributors to this increase are the natural (18%) and human
assets (12%). Financial, social and physical assets decreased by 4%, 2% and 1% points
respectively. These changes in livelihoods assets between 2001 and 2016 for occasional
fishers are also shown on livelihoods assets pentagon (figure 5.5).
85
Table 5.14: Total value of livelihood assets from 2001 to 2016 for Type III Households
Capitals Indicators 2001 2016
Indicator
Weight
Capital
Value
Indicator
Weight
Capital
Value
Economic
Assets
Fishing income
Savings from fishing income
Access to credits
0.49
0.47
0.47
0.48 0.54
0.41
0.36
0.44
Physical
Assets
House ownership
Energy Supply
Transport facility
Fishing tools ownership
0.33
0.65
0.54
0.67
0.55 0.27
0.75
0.58
0.56
0.54
Natural
Assets
Licensing
Watchers
Litigation
Fish size and amount
0.09
0.05
0.04
0.46
0.16 0.52
0.40
0.29
0.15
0.34
Social
Assets
Union Council membership
Membership in political parties
Networking with law enforcement
agencies
Contacts with village elders
Networking with other households
Kinship support
0.45
0.19
0.41
0.41
0.29
0.69
0.41 0.62
0.33
0.26
0.48
0.15
0.52
0.39
Human
Assets
Education
Skill
0.60
0.63
0.62 0.71
0.76
0.74
Livelihood
Assets
0.44 0.49
Figure 5.5: Livelihood Assets pentagon for Type III Households
86
Comparison of all the three types
The overall livelihood assets of type I households (farming fishers) showed deterioration with
an index value ranging from 0.40 in 2001 to 0.33 in 2016. However, the index values showed
improvement from 0.36 to 0.38 and from 0.44 to 0.49 for type II (fishing farmers) and type III
(occasional fishers) households respectively. Results showed that the economic, social and
physical assets of farming fishers showed deterioration from 2001 to 2016. The economic,
social and physical assets of fishing farmers have also deteriorated but most of these
households have amplified their fishing gears to suit declining fish stocks. The natural assets
have improved in all the three groups from 2001 to 2016 which shows that licensing, number
of fishery watchers and litigation processes have led to some improvement in conservation of
fishery resources. However, more efforts in conservation of these resources may further
improve the situation. The three types of fishers were tested on 19 homogeneous indicators
using the Kruskal-Wallis H test. Results of the Kruskal-Wallis H test showed that there was a
statistically significant difference in livelihood assets between the different types of fishers,
χ2(2) = 5.489, p = 0.064, with a mean rank livelihood asset of 22.97 for Farming fishers,
28.47 for Fishing farmers and 35.55 for Occasional fishers (Table 5.15).
Table 5.15: Statistic results of Kruskal–Wallis test of livelihood capital subcomponents
Descriptive
statistics
N Mean Std. deviation Minimum Maximum
Value
Variables
57
57
0.387
2.0
0.16395
0.824
0.13
1
0.77
3
Ranks Variables N Mean Rank
Value 1 19 22.97
2 19 28.47
3 19 35.55
Total 57
Test statisticsa,b
Chi-square df Asymp.sig.
Value 5.489 2 0.064
5.6 Factors affecting fish consumption of selected households
Fish consumption is affected by a variety of social, economic, and environmental factors.
Research evidence suggests that age, gender, family income, employment, consumption
season, urbanization, education, marital status, number of family members, presence of
children in family members, affect fish consumption. These variables were aggregated into
three major parameters: Economic, Social and physical or environmental factors. The per
87
capita fish consumption in Pakistan is 2kg per year compared to the world average of 17kg
per year (Wasim & Parvez, 2007; York & Gossard, 2004; FAO, 2009; Garibaldi et al., 2004),
which is one of the lowest in the region. In this study fish consumption within the fishermen
community and people residing near water bodies, or the households that mostly conduct
DFPs for fish consumption.
Global fish production is approximately 167.2 million tons per year of which total human
consumption is 146.3 million tones and 20.9 are non food uses of fish (FAO 2016). Inland
fish represents a very important source of low-priced meat essential to balanced diet in
marginally food secure communities (Akpaniteaku et al., 2005). Local food production is
important in checking hunger and supporting rural development in locations where the poor
do not have the capability to purchase food from the market (Corvalan et al., 2005). Pakistan
ranks 18th
in inland fishing in the world by producing 120,240 tonnes in 2012 and 123,155
tonnes in 2013 (FAO, 2015). The inland production of fish in Pakistan rose from 60,000 tons
in the early 1980s to 284,000 tons at present (GoP, 2013b). The share of fisheries sector to
Gross National Product (GDP) for the period of 2014-15 was 5.8% (Ministry of Finance,
2015). The share of inland fisheries in total fish production in Pakistan has remained 21%,
30%, 23%, 30% in 1947, 1960, 1984, and 2009-10 respectively (GoP, 2013a). It is estimated
that some 180,000 people (FAO, 2009; GoP, 2013b) mostly part-time, with almost 20,000
small crafts are involved in inland fisheries for their livelihoods. A number of researchers
have conducted studies relating to fish consumption. Most of these studies have based their
analyses on the effect of socio-demographic factors on the consumption of fish products
(Nash and Bell 1969; Nayga and Capps1995; Capps 86; Perry 1982; Herath & Radampola
2016; Gracia & Albisu 2001; Pippin and Morrison 1975; Keithiy 1987; Hu 1985;
Dellenbargcr et al., 1988; Cheng and Capps 1988; McGee et al., 1989; Israel et al., 1991). No
study has ever been conducted on the the social and demographic factors of fishers and people
residing near water bodies in the study area and Pakistan. The current analysis of factors of
fish consumption was therefore, constructed, and based on the previous research efforts, to
find out the socio-demographic factors of fish consumption in the fishermen community.
Fisheries and aquaculture is an essential source of protein, nutrition, income and well being
for numerous people around the world and supply more than 3.1 billion households with
about 20 percent of their average per capita intake of animal protein. Moreover, fish is one of
the most-traded food commodities worldwide with more than half of fish exports by value
originate in developing countries (FAO, 2016).
88
Table 5.16: Comparison of Per capita fish consumption of different countries
Source:* FAO. 2016; ** Wasim & Parvez, 2007; York & Gossard, 2004; FAO, 2009;
Garibaldi et al., 2004, *** FAO, 2016; Herath & Radampola 2016
Fish consumption also significantly varies between fishers or households residing near water
bodies and people residing away from water bodies. In the study area no research has ever
been conducted documenting the fish consumption patterns of households. The major aim of
the present fish consumption model is to obtain information on fish consumption levels of
fishermen and people residing near water bodies, and to find out the link between the
socioeconomic and demographic features of the households and their fish consumption
preferences. The primary data was collected from 286 fishermen and household heads
residing near water bodies in the study area using two stage cluster sampling method. Data
collected through questionnaires was analyzed through descriptive statistics and multiple
linear regression.
5.6.2 Reasons of fish consumption
Fish is consumed due to variety of reasons, some consume it due to being nutritious and
healthy, others consume it because it is fresh and easily available in the market or caught. The
S.No. Country and Region Consumption of fish/Capita/Year(Kg)
2013-16
1. Worldwide* 20.2
2. European Union* 24
3. Developed countries* 22.7
1. Japan 50.2
2. Canada 22.5
3. USA 23.7
4. North America 23.6
4. Developing countries* 19.6
1. Africa 10
2. Egypt 20.9
3. Nigeria 11.8
4. Sub-Saharan Africa 8.9
5. Developing region * 18.8
6. Asia*
1. China 39.5
2. Pakistan** 2.0
3. India 6.0
4. Indonesia 35.0
5. Philippines 31.2
6. Thailand 27.5
7. Sri Lanka*** 10.8
7. Low income
food-deficit countries (LIFDCs *
7.6
89
reasons of fish consumption in the study area include; non availability in the market, which
means that fishermen wait on river banks for customers, to sell their catch, however if their
wild caught fish is not sold then they take it home for personal consumption. About 35
percent of the respondents responded that they consume fish when it is not sold in the market.
The reasons for the high amount of fishermen response that they take home if not sold are;
most of them are small fishermen, using inefficient gears, and decline of fish population in
rivers. More than twenty percent responded that they consume fish at home if they are not
offered a better price for their fish. Taste of the fish was not found to be much important for
fishermen but freshness mattered (15%).
Table 5.17: Reasons of fish consumption
Variable Frequency Percentage
Not sold in the market 98 34.27
Lower price in the market(cheaper) 60 20.98
Nutritive value 38 13.29
Easily available 29 10.14
Taste of fish 18 6.29
Freshness 43 15.03
total 100 100
Source: Field Survey
5.6.3 Pattern of fish consumption
Table 5.18 shows that more than 38 percent of respondents consume fish once a month, this
also shows that these are people who are either fishermen or part time fishermen or people
residing near water bodies. The fish consumption shall be lower for people who are not
fishermen or don‘t fish for recreation or do not reside near water bodies.
Table 5.18: Frequency of fish consumption
Variable Frequency Percentage
Once a month 111 38.81
2 to 3 times a month 93 32.52
Four times a month 59 20.63
More than four times a month 23 8.04
Total 286 100
Source: Field survey
5.6.4 Preferences for fish species
The results reveal that in the study area people prefer to consume china kub, although the
most delicious and tasty fish is shermahe but its supply is inadequate to meet the market
90
demand and therefore most people (40.21%) prefer to consume China Kub (Table 5.19).
Secondly, most wild caught fish in the rivers of the study area is a low quality fish named
Marmahe, most people (17.82%) prefer to consume this fish due to its taste and availability.
Table 5.19 Preferences for fish species
Local name Fish Specie Frequency Percentage
China kub Cyprinus carpio (Exotic) and Carassius
auratus(Exotic)
115 40.21
Shermahe Clupisoma naziri and Clupisoma garua 39 13.64
Mahasher Tor macrolepis 34 11.89
Marmahe Mastacembelus armatus 51 17.82
Sulaimani (Fauji) Glyptothorax punjabensis, Glyptothorax
stocki, Glyptothorax sufii, Glyptothorax
cavia
21 7.34
Sole (Katasar) Channa punctatus, Channa gachua 26 9.10
Total 286 100
Source: Field survey
5.6.5 Prices of different fish species
Table 5.20 shows the average prices of different fish species sold in the market. These prices
are average and vary slightly on the basis of size, weight, season and farmed or capture.
Among the above types ―Shermahe‖ which is considered as the trout of Charsadda has the
highest price due to being specific to river Kabul in district Charsadda. Farmed shermahe is
sold in the market but the taste and prices are different. Wild fish stocks in the Khyber
Pakhtunkhwa are declining, while the causes for this decline cannot be ascertained, increased
fishing pressure, pollution, and construction of dams, which block the movement of migratory
fish species, are all strongly suspected of having adverse effects on fish stocks (Directorate of
Fisheries, 1995).
Table 5.20 Prices of different species of fish
Local name Fish Specie Prices (Rs.)
China kub Cyprinus carpio (Exotic) and Carassius auratus(Exotic) Farmed 280-350
River 350-420
Shermahe Clupisoma naziri and Clupisoma garua Farmed 800-1200
River 1200-1400
Mahasher Tor macrolepis Farmed 240-270
River 300-350
Marmahe Mastacembelus armatus Farmed 250-300
River 350-370
Sulaimani (Fauji) Glyptothorax punjabensis, Glyptothorax stocki,
Glyptothorax sufii, Glyptothorax cavia Farmed 280-300
River 400-450
Sole (Katasar) Channa punctatus, Channa gachua Ricer 270-300
Source: Field survey
91
5.6.6 Results of the multiple linear regression model for fish consumption
There are many determinants of fish consumption, however keeping in view the local realities
and fishermen characteristics eight variables were selected for the multiple linear regression
and the model was specified as;
Fish_Cons = α + β1Fi1 + β2Dw2 + β3Pf3 + β4Fn4 + β5Hz5 + β6Ag6 + β7Ed7 ++ β8Fg8 + εi
(Equation 9)
Whereas Fish_Cons is the dependent variable amount of fish consumed per household/year
(Kg), α is the intercept, and β1, β2 β3 β4 β5 β6 β7 are the coefficients of the independent
variables, and Fi1, Dw2, Pf3, Fn4, Hz5, Ag6, Ed7, Fg8 are the explanatory variables, fishing
income (Rs.), distance to water bodies (Km), price of fish/Kg (Rs.), family income (Rs.),
household size (number), age of the household head (years), average years of formal
education, and number of fishing gears respectively.
The results show that out of the selected eight variables only seven are correlated with the
dependent variables (Table 5.21), therefore only seven were used in the final regression. All
the selected seven variables have high correlation with the dependent variable and no
correlation with the other explanatory variables. The results show that out of the selected
seven variables only three variables have negative correlation and the rest of the four have
positive correlation with the dependent variable. The results of the partial correlation shows
that high negative correlation was found between price of fish and amount of fish consumed,
distance to water bodies number of fishing gears, and average years of formal education.
However the correlation between fish consumption and family income and household size
was moderate. The correlation between fish consumption and household was low. However
the correlation between fish consumption and average age of the household head is very low
and therefore it is dropped from the final model.
92
Table 5.21: Correlation and other characteristics of explanatory variables selected for the regression
model.
Variable and description Variable type Mean Pearson correlation
value (r)
Price of fish (in Kg), price of fish was
considered at retail level
Continuous 218.63±48.31 - 0.713**
Distance to water bodies, distance was
taken from each respondent in Km
-do- 3.03±3.19 -0.427**
Number of fishing gears -do- 3.92±1.76 0.416**
Average years of formal education -do- 7.74±6.17 0.407**
Family income -do- 384748±182435 0.361**
Household size -do- 9.42±4.43 - 0.278*
Fishing income -do- 27482±16934 0.354*
Age of the household head -do- 40.96±8.60 -0.023
Note: *, ٭٭, Correlation is significant at 99% and 95% confidence levels, respectively.
Two tailed test
Prediction of fish consumption model
The explanatory variables were entered in to the regression model. All of the seven
explanatory variables in the model have significantly influenced fish consumption in the
study area.
Table 5.22 Table Summary of the regression model
Model R R square Adjusted R
square
Standard
error of the
estimate
Durbin
Watson
1 0.815a 0.664 0.656 33.60 1.26
b. Dependent Variable: Fish_amount_consumed a. Predictors: (Constant), Fishing_Income,
Distance_to_waterbodies_km, HH_Size, Family_Income, Avg_years_formal_Educn_HH_head,
price_fish_1kg, Number_fishing_gears
Table 5.22 shows that both R and R square values have reasonable explanatory power on the
models. The adjusted R square value of (65.6) shows high level of explanatory power of the
variables on the fish consumption. The model is also statistically significant with lower standard
errors of the estimates.
Table 5.23 shows the F ratio of the independent variables in the model and shows that the model
is statistically significant showing that the variables included in the model are correct and the
overall model is fit.
93
Table 5.23: Table ANOVA of the regression models
Model Sum of
squares
Degree
of
freedom
Mean
square
F ratio Significance
1. Regression 620761 7 88680 78.550 0.000a
Residual 313850 278 1129
Total 934612 285
a. Predictors: (Constant), Fishing_Income, Distance_to_waterbodies_km, HH_Size,
Family_Income, Avg_years_formal_Educn_HH_head, price_fish_1kg, Number_fishing_gears
b. Dependent Variable: Fish_amount_consumed
The regression results showed that out of the total seven variables three variables have negative
effects on consumption. These include price of fish, distance to water bodies, and household
size. With a unit raise in the fish price, distance to water bodies, and household size fish
consumption decrease through -0.508, - 0.207 and -0.137 units correspondingly (Table 5.24),
which shows the importance of all these five variables in fish consumption. However, the
number of fishing gears, average years of formal education, family income and fishing income
have a positive effect on the dependent variable. Increase in the number of gears, average years
of formal education, family income and fishing income increases fish consumption. The higher
―t‖ values also reveal the fact that all the seven variables are significant at 99% confidence level,
except fishing income. The reason is that these are poor fishermen and when their fishing income
increases they try to cover other expenses instead of consuming fish. The standard errors of the
estimates also shows a very small variation which is not explained by the independent variables.
94
Table 5.24: Coefficients of the explanatory variables included in the regression model
Unstandardized
coefficients
Standar
dized
coeffici
ents
t significance
B Standard
error
(Constant) 181.80 14.52 12.52 0.000
Price of fish (Kg) -0.602 0.05 -0.508 -12.55 0.000
Distance to water bodies (Km) -3.715 0.67 -0.207 -5.59 0.000
Number of fishing gears 4.542 1.39 0.109 2.55 0.011
Average years of formal
education of the household head
1.944 0.34 0.209 5.65 0.000
Family income 2.990 0.00 0.095 2.46 0.015
Household size -1.774 0.466 -0.137 -3.81 0.000
Fishing income 0.000 0.00 0.037 0.88 0.382
Summary of the factors affecting fishermen fish consumption pattern
Most of the fishermen (34.27%) consume fish because it is not sold in the market either due
to lower price or lack of access to market. All of the selected households consume fish and
39% consume fish once a month whereas 32% consume fish 2 to 3 times and 20 percent
consume four times a month. More than forty percent of the consumers consume China fish
and 14 percent consume Shermahe. Shermahe is considered the most delicious fish in the
study area and it is caught and sold as fresh which are the reasons of its high price.
According to fishermen when the price of fish rises, they consume less not because the price
is high but because they sell more when the price rises. The results of correlation and multiple
regression reveals that the price of fish in the market, distance to water bodies, and household
size has negative effect of fishermen fish consumption whereas the number of fishing gears,
average years of formal education, total family income and fishing income has a positive
effect on fishermen fish consumption.
Hypotheses Testing
Based on the analysis of data the following hypotheses were tested:
H0: Fishers with more years of formal education are less likely to adopt destructive fishing
practices than fishers with fewer years of formal education.
95
Results of the regression model (Figure 5.12) show a positive relationship between average
years of formal education and DFPs i.e. with a unit increase in average years of formal
education, DFPs increase by 0.287units.
The analysis shows a positive relationship between education and use of destructive fishing
practices. But the unit of education in this case is years of formal education of the household
head. The average years of education of the respondents is less than ten years, means most of
them have very low level of education. Therefore in this case the results are not contrary to
the previous findings but it is due to other exogenous factor i.e. the fishermen have strong
social bonds and affiliations in political parties, which have resulted in higher use of
destructive fishing materials. This was also obvious from the result of focus group interviews,
which revealed that fishers mostly adopt destructive fishing methods due to lack of awareness
of natural resources and reduced fish population in rivers.
H0: Livelihood diversity has a negative effect on destructive fishing practices.
Results of the regression model (Figure 5.12) show a negative relationship between number
of alternative livelihoods and DFPs i.e. with a unit increase in the number of alternative
livelihoods, DFPs decrease by – 0.210 units.
H0: Poor people conduct more destructive fishing practices than rich people.
Results of the regression model (Figure 5.12) show a negative relationship between average
total household income (poverty), and DFPs i.e. with a unit increase in average total
household income, DFPs decrease by - 0.200 units.
H0: Low cost gears are more destructive than high cost gears.
Results of the regression model (Figure 5.12) show a positive relationship between cost of
gear and DFPs i.e. with a unit increase in the cost of gear, DFPs increase by 0.216 units.
H0: People living near water bodies conduct more destructive fishing practices than people
residing away from water bodies.
Results of the regression model (Figure 5.12) show a negative relationship between distance
to water bodies and DFPs i.e. with a unit increase in distance to water bodies, DFPs decrease
by - 0.146 units.
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H0: The lower the supply of culture fish in the market, the higher the probability of use of
destructive fishing gears, the higher the supply of culture fish in the market, the lower the
probability of use of destructive fishing gears.
Results of the regression model (Figure 5.12) show a negative relationship between amount
of culture fish into the market and DFPs i.e. with a unit increase in distance to water bodies,
DFPs decrease by -0.125 units.
H0: The lower the fish stock in rivers, the higher the use of destructive fishing practices, the
higher the fish stock in rivers, the lower the use of destructive fishing practices.
Results of the regression model (Figure 5.12) show a negative relationship between stock of
fish in the river and use of DFPs. i.e. with a unit increase in the stock of fish in the rivers,
DFPs decrease by - 0.142 units.
H0: Destructive Fishing Practices lead to improve the livelihood of people in the study area.
The overall livelihood assets of type I households (farming fishers) showed deterioration with
an index value ranging from 0.40 in 2001 to 0.33 in 2016. The economic, social and physical
assets of fishing farmers have also deteriorated but most of these households have amplified
their fishing gears to suit declining fish stocks. The natural assets have improved in all the
three groups from 2001 to 2016 which shows that licensing, number of fishery watchers and
litigation processes have led to some improvement in conservation of fishery resources. The
three types of fishers were tested on 19 homogeneous indicators using the Kruskal-Wallis H
test. Results of the Kruskal-Wallis H test showed that there was a statistically significant
difference in livelihood assets between the different types of fishers, χ2(2) = 5.489, p = 0.064,
with a mean rank livelihood asset of 22.97 for Farming fishers, 28.47 for Fishing farmers and
35.55 for Occasional fishers (Table 5.15).
H0: Fish consumption of the people conducting Destructive Fishing Practices is more than non
fishermen and people residing away from water bodies.
The regression results showed that out of the total seven variables three variables have
negative effects on consumption. These include price of fish, distance to water bodies, and
household size. i.e. with a unit increase in fish price, distance to water bodies, and household
size fish consumption decrease by -0.508, - 0.207 and -0.137 units correspondingly (Table
5.22). However, the number of fishing gears, average years of formal education, family
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income and fishing income have a positive effect on the dependent variable. Increase in the
number of gears, average years of formal education, family income and fishing income
increases fish consumption. The higher ―t‖ values also reveal the fact that all the seven
variables are significant at 99% confidence level.
H0: Fisheries ordinance and regulation exists but lack proper implementation.
Fisheries Ordinance 196, Govt. of KP, West Pakistan revealed that regulations exists
regarding use of explosives, use of chemicals, small mesh nets and electric currents but there
are hurdles in proper implementation of these rules. The law enforcement agencies, fishery
monitors and destructive material sellers are responsible for the breach of law.
Discussion
Fish stocks are renewable resources and have to be scientifically managed because
unscientific exploitation of stocks, lead to their depletion and ultimate disappearance
(Alagaraja, 1984). Fish stock is defined as a group of fishes of the same specie or subspecies
which are spatially, genetically, or demographically separated from other groups (Pope,
Lochmann, & Young, 2010; Wells & Richmond 1995). There are various approaches for
assessing fish stocks, which are broadly classified into virgin stocks and exploited stocks.
The present research report has identified fish stocks through fishermen perception.
Discovering exact fish stock is not only difficult and costly but is not the primary purpose of
the current research. The current research has focused on whether fish stock has declined? and
the impact of declining fishery on fishermen livelihoods. Finding the magnitude of this
declining fishery need further research investigation. Decline of the stock of fish in the rivers
intensify fishing efforts and make destructive fishing practices more attractive. Numerous
research studies have acknowledged the fact that the use of destructive fishing gears and
excessive fishing efforts have lead to a decline in fish stock and reduced the number of fish
species in catch (Suuronen, et al., 2012; Munyi & Fridah, 2009; Mangi, & Roberts, 2006;
Ogutu‐Ohwayo, 2006; Eyo, & Ahmed, 2005; Van Zalinge, 2002; King & Faasili 1999; Van
Zalinge, Thuok, & Tana, 1998). Results of the Focused Group Discussions and interviews
with the key informants revealed that fish stock and size has been significantly reduced over
the past 15 years. Therefore, the finding of the qualitative data on the fish size and amount is
consistent with the results of earlier studies.
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The variable, level of education of the household head was taken because in the study area the
cultural values are strong and household head can influence and shape the behavior and
outlook regarding use of destructive fishing practices. Previous research evidence reveals that
level of education or average years of formal education (Munyi, 2009; Johnson, 1998;
Wagner et al., 1999; Pet-Soede & Erdmann, 1998; FAO, 2010) negatively affect the use of
destructive fishing practices positively. That is lower the level of education, higher the use of
destructive fishing gears. The findings of the study are not consistent with the previous
research observations and investigations and have proved that education does not play a
pivotal role in reducing the use of destructive fishing practices. The present analysis shows a
positive relationship between education and use of destructive fishing practices. But the unit
for the measurement of education in this case was average years of formal education of the
household head. The results of this study shows that average years of formal education of the
household head is less than ten years, which means that most of them have very low level of
education. Therefore, when this aspect is taken into consideration the results are not contrary
to the previous findings. However fishermen have strong social bonds, and affiliation with
political parties, which support their illegal fishing practices. The availability of alternative
livelihood opportunities can reduce the pressure on the river resources (Munyi, 2009,
Pomeroy and Rivera-Guieb, 2006; Shumway, 1999; Clark et al., 1992; Johnson, 1998; FAO,
2010). Analysis of the education and livelihoods opportunities in the study area reveal that
over the past 15 years the number of schools has been increased and due to education many
fishermen have got jobs in police and law enforcement agencies. The stock of fish in the
major rivers of the study area has been reduced over the past two decades. Finding the stock
of fish is a difficult job, however this variable was figured out through interviews with
fishermen and during focused group discussions and field visits to the study area. The
fishermen revealed that fish stock has been reduced which has led them to fish harder or use
destructive fishing and small mesh size so as to sustain their living standard. Research
evidence also supports the fact that decline in fish stocks in the rivers, declining catches and
fear among the fishermen (Akhtar, 2015; Munyi, 2009; Pomeroy and Rivera-Guieb, 2006;
Johnson, 1998; Khan & Khan, 2011) lead to intensified fishing. Results show that the cost of
gear is also positively correlated with the DFPs which support the previous research evidence,
showing the higher the cost, the higher the efficiency in catch and use of destructive fishing
practices (Tol, 2006; Munyi, 2009). In the study area the cost of destructive materials has not
only increased but its supply has been reduced due to ban and punishment on its use.
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However, those fishermen who have contacts with the law enforcement agencies not only get
these materials but can use it anywhere in the study area.
Poverty is multidimensional but the average total household income was used as dummy for
poverty. Low level of income and demand for protein (Lampe et al., 2017; Munyi, 2009;
Shumway, 1999; Clark et al 1992; Cinner, 2009; Pet-Soede, 1998; Pauly & Chua, 1988; Khan
& Khan, 2011) induce people DFPs. Reduction in poverty will lead people use other protein
sources more than fish and will reduce the pressure of the limited river fisheries. The results
have also shown significant relationship between distance to water bodies and use of DFPs. It
is commonly believed that people living far away from water bodies normally are not
attracted toward fishing (Tol, 2006) as compared to those living near. The people residing
near water bodies mostly use destructive fishing because people living distant to water bodies
not only have to travel to water bodies but carry the destructive material which is difficult
owing to the present security situation in the Khyber Pakhtunkhwa. The supply of culture fish
to the market has also increased tremendously which has reduced dependence on river fish
and use of destructive fishing.
Small-scale fisheries are important for the livelihoods of over 120 million people (Allison, &
Ellis, 2001) but are exposed to global and local stresses (Stanford, et al., 2017). Another key
area of the present research was to show the impact of DFPs on fishermen livelihoods. This
study provides insights into fisher livelihoods through livelihood assets pentagons. This study
has made a number of important observations in this regard. It has been observed that the
livelihood assets of farming fishers severely deteriorated from total index value of 0.40 to
0.33, due to the reason that they have access to land but getting less income from farming
than fishing, which is an evidence of reduced amount of fish and fishing activity in the rivers
by these fishers. The overall livelihood assets of fishing farmers have improved from 0.36 to
0.38 with human and natural assets as contributor to this increase and deterioration in the rest
of the capitals, indicating the hardships fishers facing due to decline in economic, physical
and social assets. Considerable deterioration in physical assets among all the three types
reveals that these fishers have lost, destroyed or discarded some of their fishing gears due to
reduced fishing activity. Savings from fishing income and fishing tools ownership has
reduced among all the three groups. The increase of fishing income only among occasional
fishers reveals the fact that they catch more due to the use of DFPs. Natural assets here refer
to fishers‘ livelihoods, i.e. access to natural assets improves livelihoods but on the other hand
overexploitation of the natural assets causes deterioration of the natural environment. For
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example, fishers were asked whether licensing, number of monitors and litigation has reduced
their access to water bodies. In this research it is assumed that anything that restricts fisher‘s
access to water bodies will negatively affect their livelihoods and improve conservation
efforts. The conservation efforts show improvement in number of licensing, fisheries
monitors and litigation cases but have negative effect on the livelihoods of fishermen. There
are many causes of fisheries degradation not covered in the present paper and research gap
exists in this regard. These include competition and conflicts over natural resources,
construction of settlements besides major rivers, social and cultural perceptions regarding
water and its components as an open access, new fishing methods and technology, taste of
fish caught, ineffective rules or incapacity to monitor rules and regulations, intensity of
fishing effort, energy and time efficiency, existence of group relationship patterns between
fishermen and the law enforcement agencies and destructive fishing materials sellers and fish
as the main source of food etc. Similarly, there are many other processes that may have
impact on fishermen livelihood assets, not covered under the present research. For example,
alternative livelihood opportunities, access to land and Economic and political
marginalization etc.
The considerable expansion in fisheries and aquaculture production in the past 50 years,
especially, in the last two decades, has improved the world‘s capability to consume
diversified and healthy food (FAO, 2016). However, per capita fish consumption is unequal
across the world. The study revealed that almost 35% of the fishermen consume fish because
it is not sold in the market either due to lower price or lack of access to market. There is no
organized market for their catch to sell. They wait besides the rivers with their catch until a
consumer come and take their catch with a price. If nobody is there to purchase then they take
it home for self consumption. All of the selected households consume fish and 39% consume
fish once a month whereas 32% consume fish 2 to 3 times and 20 percent consume four times
a month. More than forty percent of the consumers consume Common Carp and only 14
percent consume Shermahe. According to fishermen when the price of fish rises, they
consume less not because the price is high but because they sell more when the price rises.
This reveals that fishermen in the study area are mostly poor and rely on fish sale for their
livelihoods.
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Chapter 6
Summary, Conclusion and Recommendations
This chapter summarizes the conclusions and recommendations emanating from this study. It
begins by looking at a summary of the major findings. It includes a brief discussion presented
according to each of the main research questions followed by the outcomes of this study. The
conclusions of this study are also covered in this section. It concludes with a list of policy
recommendations and limitations of the study or recommendations for future research.
6.1 Summary of the findings
6.1.1 Socio-economic characteristics
In the study area type III households (occasional fishers) had on the average 7.8 years of
formal education but on average 15 years of fishing experience, revealing the fact that the
sample households have mostly low level of education. As mentioned earlier this category of
households mostly includes government officials, businessmen, village khans (landlords),
police and army and other law enforcement agencies‘ workers, who have not only access to
destructive materials but can use them anywhere being influential. Fishing farmers and
farming fishers both have more than 20 years of fishing experience and lower than 6 years of
formal education. Average annual fishing income of the farming fishers is (Rs.47626),
followed by fishing farmers (Rs. 22674) and occasional fishers (Rs. 13800). This shows that
fishing farmers are the poorest fishers whereas farming fishers are average due to availability
of farming land. The lowest fishing income of occasional fishers reveals that occasional
fishers mostly consume, rather than selling. The average annual savings are also high in case
of farming fishers. On the other hand, the average total household income of occasional
fishers is highest among the three groups, revealing the fact that they are a richer group and
mostly have paid jobs. Fishing farmers are the poorest among the three groups. The farming
fishers have on average 5 or more fishing gears, in case of occasional have it is 4 and fishing
farmers 2. Farming fishers hold higher average land holding (6.5 acres), followed by
occasional fishers with 4.6 acres and farming fishers 4.0 acres. Occasional fishers catch more
species of fish than other fishers due to the reason that they use more destructive fishing
material than the other groups. The occasional fishers also consume on the average more than
68 percent of the fish caught than selling it in the market. The fishing farmers sell more than
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88 percent of fish in the market due to the reason that fishing is the source of income and
livelihoods for them.
6.1.2 Conservation measures and fishery rules and regulations
The results also revealed that over the past fifteen years the conservation measures have
improved. The impact of licensing, numbers of watchers, and fishery regulations, have
reduced the access of illegal fishers to water bodies. However the representation of fishers‘ in
different social and community groups and political parties help them in the conduction of
DFPs. The description of the fishery rules and ordinance shows that laws exist but need
amendment in line with modern fishing technology, structure of fishing gears and fishing
methods. The fee of license is Rs. 500 per season, which is very low and many fishermen fish
without licenses. In 2015-16 only 103 people got licenses which is a very small amount
keeping in view the three major rivers and population, and it reveals that many people go
fishing without licenses. The fishery department shall observe fishing without licensing. The
prohibition on the size of different fishes is hardly observed and very small size fishes which
are few inches in size (figure 2.2) are caught. The ordinance puts tremendous responsibility
over many sections of society but none of them is aware of their responsibilities. The
ordinance states that ―Every Lambardar, Village Watchman, Canal Patwari, P.W.D. Darogha,
Zilladar, Revenue Patwari, Tapedar, Supervising Tapedar and Qanungo shall be bound in the
absence of reasonable excuse to give to an inspector of fisheries or any other person
authorized in this behalf by the director of fisheries, information in respect of any
unauthorized netting, killing or other offence under this ordinance committed within the limit
of his village or circle, as the case may be, as soon as the commission of such offence comes
to his knowledge‖, however, the community and these offices scarcely comply to the
ordinance.
6.1.3 Causes of DFPs
Among the selected causes of DFPs in the study area, findings reveal that education has a
positive relation with DFPs, which is not consistent with the previous research observations
and investigations and have proved that education does not play any role in reducing the use
of DFPs. Analysis of the education and livelihoods opportunities in the study area reveal that
in the past fifteen years the number of schools have been increased and due to education
many fishermen have got jobs in police and law enforcement agencies. The stock of fish in
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the major rivers of the study area has been reduced over the past two decades. The fishermen
revealed that fish stock has been reduced which has led them to fish harder or use destructive
fishing and small mesh size so as to maintain their well being. Results show that the cost of
gear is also positively correlated with the DFPs which support the previous research evidence,
showing the higher the cost, the higher the efficiency in catch and use of DFPs. In the study
area the cost of destructive materials has not only increased but its supply has been reduced
due to ban and punishments on its use. However, those fishermen who have contacts with the
law enforcement agencies not only get these materials but can use it anywhere in the study
area. Reduction in poverty will lead people use other protein sources more than fish and will
reduce the pressure of the limited river fisheries. The results have also shown significant
relationship between distance to water bodies and use of DFPs. It is commonly believed that
people living far away from water bodies normally are not attracted toward fishing as
compared to those living near. The supply of culture fish to the market has also increased
tremendously which has reduced dependence on river fish and use of destructive fishing.
6.2 Conclusions
District Charsadda is endowed with water resources, providing rich and diverse fishing
opportunities. However, over the past more than two decades the fish fauna in rivers is
continuously on the decline and the size and amount of fish is decreasing. Being concerned
with the adverse effects of DFPs the fisheries department have taken various steps like
increase in the number of watchers, putting ban on the use of cyanide and blasting materials.
However, destructive fishing is still undertaken and poses serious threat to the fisheries
resources in the study area. The decline in inland fishery resources has become a major
concern because; it is a source of livelihood, protein and recreation for poor people.
One of the basic objectives of this of this research was to find out the major socioeconomic
causes/drivers of destructive fishing practices in the study area or find out why people
conduct destructive fishing. Based on the correlation (Table 5.9) and regression analysis
(Table 5.10, 5.11 and 5.12) we conclude that two factors, namely, cost of gear and years of
education of the household head had a positive impact on DFPs, while the remaining five
variables namely, number of alternative livelihoods, decline in fish stocks, poverty, distance
to water bodies and supply of culture fish to the market had a negative impact on DFPs. Cost
of gear is positively correlated with destructive fishing. The higher the cost of gear the higher
the destructive fishing practices. Due to recent conservation measures the cost of blasting
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material and cyanide has increased. The results are also supported by the previous research
findings (Tol, 2006; Munyi, 2009), showing a positive relationship between cost of gear and
destructive fishing practices. In order to determining the impact of level of education on
destructive fishing practices, the relative number of years of education of three different kinds
of respondents was taken in to consideration. Occasional fishers on the average hold 7.8 years
of education (Table5.2; 5.5). But such a low level of average is not a good indicator of being
educated. It was observed that occasional fishers have more contacts and networking with law
enforcement agencies due to which they not only have access to destructive materials but can
use them anywhere in the rivers. This result is also supported by the results of FGDs in
section 5.1 as; The focused group interviews revealed that occasional fishers mostly conduct
destructive fishing methods due to lack of awareness regarding natural resources and reduced
fish population in rivers. Most of the people don‘t hold licenses due to lack of proper
implementation of fishery regulations and are being influential people. This fact was also
mentioned in section 5.2.2 educational attainment as; ―Majority of the surveyed household
heads were illiterate. However occasional fishers had more than seven years of formal
education, followed by fishing farmers with almost 6 years and farming fishers almost 3 years
(Table 5.2).‖ Fishing activities in the study area are mostly concentrated in villages near water
bodies. Those who fish have strong contacts with influential people and are mostly under the
influence of village ―Khans‖, and the police and fisheries monitors do not catch them due to
the support of influential people. Alternative livelihood opportunities may help poor
fishermen switch over easily between professions, rather than amplify fishing methods, fish
harder or use destructive fishing practices. Previous research evidence also supports the
findings of the present study (Munyi, 2009, Pomeroy and Rivera-Guieb, 2006; Shumway,
1999; Clark et al., 1992; Johnson, 1998; FAO. 2010). Therefore, if the government wants to
reduce destructive fishing, poor fishermen shall be facilitated through, provision of soft loans,
skill development and awareness regarding water resources. Similarly, when fish stock in the
rivers decline, fishers intensify fishing and in this competition destroy the fishery resources.
Therefore when fish stock in the rivers decreases, fishers increase the use of destructive
fishing practices. Akhtar, 2015; Munyi, 2009; Pomeroy and Rivera-Guieb, 2006; Johnson,
1998; Khan & Khan, 2011, revealed that decline in catch per unit effort lead to intensify
fishing and the use of destructive fishing. Poverty may or may not lead to the use of
destructive fishing (Lampe et al., 2017; Munyi, 2009; Shumway, 1999; Clark et al 1992;
Cinner, 2009; Pet-Soede, 1998; Pauly & Chua, 1988; Khan & Khan, 2011). The present study
shows a negative relation between poverty and destructive fishing practices. Due to poverty
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they have no option but to fish in order to support their families. Secondly, poor people fish in
order to exploit the open access fishery resources and meet the protein demands of their
family. The present study postulated a negative relation between distance to water bodies and
the use of destructive practices. The results revealed that the lesser the distance the more the
use of DFPs (Table 5.12). Tol, 2006 also find out a similar relation between the two
variables. Supply of culture fish to the market had a negative impact on DFPs, and it reduces
risk to wild caught (Fox, 1997 ; Chan, 2001). When the supply of culture fish increases, most
people purchase from the market, which reduce the pressure on the limited natural resource.
Another major research question the study has attempted to answer was to find out the impact
of destructive fishing practices on fish populations/stock in rivers of the study area. The
common pool nature of fishery resources has made it a great challenge for fishery managers
and conservationists to deal with the continuous decline in fish stock. Finding fish stock in the
rivers is a difficult task and not the primary objective of the current study. Results of FGD
and interviews with the key informants reveal that fish population and size has been
significantly reduced over the past 15 years. Section 5.1 results of the FGDs cited ―Almost
90% of the respondents compared their present catch with past and concluded that fish size
and amount has significantly reduced in the local rivers‖. Similarly, section 5.2
socioeconomic characteristics of fishermen for 2001 and 2016 cited; ― average number of
species caught per day per effort in 2001, was about 6, which have reduced to about 4,
supporting the results of FGDs and key informants interviews‖. Secondly, table 5.7 fish
amount and size and figure 5.2 highlights fishermen perceptions regarding fisheries resource
degradation. Fishermen, village elders and fisheries officials revealed their views regarding
the present state of fisheries resources. This perception was verified with a household survey.
About 87% of fishers avowed that the fisheries resources are declining (Figure 5.2). Thirdly,
the variable fish size and amount was also found out for the analysis of livelihood asset
pentagon through survey (Table 5.13, 5.14, 5.15 and Figure 5.3, 5.4 and 5.5).
Fishery resources make a significant contribution to rural livelihoods. Destructive fishing
practices have not only declined fish stock and size in the rivers but have negative effects on
fishermen livelihoods. This study shows insights into fishermen livelihoods through
livelihood assets pentagon. Maintaining a living requires livelihood assets and the fishermen
livelihoods depend on the assets they hold. Analysis of the livelihood assets revealed that in
all the three types of households, only natural assets have shown some improvement from
2001 to 2016 (Table 5.13, 5.14, 5.15 and Figure 5.3, 5.4 and 5.5). The improvement in natural
106
assets in this context shows the fact, that the recent conservation efforts of the fisheries
department in terms of licensing, watchers, and litigation process may have reduced the
disastrous impacts of DFPs. However, its tremendous use in the past has resulted in reduced
livelihood assets of fishermen. The average amount and size of fish over the past fifteen years
for all the three groups has been reduced tremendously. The watchers are hired on temporary
or seasonal basis and they check only seasonal fishing activities. Cyanide and chemicals are
banned, but is still available at many locations in the study area. A fertilizer with the name of
―thyodine‖ has been extensively used in the past for fisheries, which is actually for pesticides;
however its production is stopped but many other local methods of combining different
chemicals and pesticides are still in use. The study showed that influential people, hereby
called occasional fishermen in this study still use destructive fishing practices due to their
status, influence and contacts with the law enforcement agencies. Section 5.1 discussed
results of the focused group interviews, which, revealed that occasional fishers mostly
conduct destructive fishing methods due to lack of awareness regarding natural resources and
reduced fish population in rivers. This is also shown in conceptual framework (Figure 2.8),
and in the livelihood assets of respondents which affect DFPs. The networking and contacts
variables are included in social capital of the livelihood assets. These include; Union Council
membership, Membership in political parties, Networking with law enforcement agencies,
Contacts with village elders, Networking with other households, and Kinship support.
The fish consumption pattern shows that fish 98 percent of fishermen consume fish, because
it is not sold in the market (Table 5.18). The plausible reason for low catch is that, output is
low and cannot be taken to the market due to cost of transportation. But their output is low,
due to continuous use of destructive fishing practices. Destructive fishing practices increase
current catch of fishermen at the expense of future output. On average fishermen consume
only 30 percent of their catch and sell 70 percent (Table 5.1). 38 percent consume fish once a
month (5.19). The regression results showed that out of the total seven variables three
variables (price of fish, distance to water bodies, and household size) have negative effects on
consumption (Table 5.25). However, the number of fishing gears, average years of formal
education, family income and fishing income have a positive effect on fish consumption.
Analysis of the regulatory framework reveals that laws governing water bodies exists, but
need changes due to change in technology and fishing methods. For sustainable use of fishery
resources, community, government and other agencies shall be motivated to alleviate the
negative causes of destructive fishing practices. in order to create awareness, lessons
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regarding sustainable use of fishery resources and conservation should be included in
textbooks at school and college level in order to create awareness.
6.3 Recommendations
6.3.1 Policy implications
The results of this dissertation offer significant policy implications in reducing the intensity of
DFPs. The results discovered that most of the household heads in the area were illiterate.
Literacy was found positively correlated with DFPs. Literacy considered on the basis of
number of years of formal education of household head. The results revealed that the average
years of formal education was about 7-9 years, which is a very low level and might not be
considered a reasonable literacy level. Observations of textbooks at school and college level
also reveal that no lessons regarding conservations and environmental education were
included. Education will fail until awareness and environmental education is added to the
curriculum. There is need for awareness regarding the use of natural resources. The fishers
and other people residing besides rivers shall be made aware regarding the sustainable use of
fisheries resources. There is open access to fisheries in the study area, and have become the
employer of the last resort, attracting people who have no other means of survival.
Due to recent conservation measures by the government and ban on the sale and purchase of
cyanide and blasting material, the prices of these materials have increased. But increase in
price of destructive materials is not solution for decrease in destructive fishing practices.
Concrete steps should be taken to reduce the entry of occasional fishers and destructive
material sellers. The results reveal that farming and fisheries were the key livelihood
opportunities of the bulk of male population in the study area. A variety of alternative
occupations is a key attribute of rural existence, unnoticed by policy makers, and is strongly
connected to flexibility, resilience and stability (Ellis, 1999). This shows that diverse
livelihood systems are more sustainable and less vulnerable than un-diversed ones because
they permit for positive adaptation to changing circumstances. Therefore, alternate income
sources and livelihood opportunities should be provided to the population in the area. This is
also evident from the fact that families with high average total household income conduct less
DFPs. So the provision of alternative opportunities will reduce pressure on fisheries
resources. The government and other nongovernmental organizations should provide credit
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facilities and trainings to the local people as there are many latent opportunities but the people
cannot opt due to lack of finances and necessary trainings.
The decline of fish stock in the rivers could be increased through artificial fish breeding in
hatcheries and release in the rivers. Figure 2.1 shows how thousand of juvenile fishes are
captured by small mesh nets. Small mesh nets shall strictly be prohibited especially in
breeding seasons. The reliance of poor fishermen on water resources shall be decrease
through, provision of alternative livelihood opportunities, teaching sustainable use of fishery
resources and awareness regarding conservation of fishery resources. The results revealed that
the farther the distance to water bodies, the lesser the intensity of the use of DFPs. Keeping in
view this finding, the government should check the construction trend alongside the major
rivers; this will serve two purposes; 1) it will reduce the current trend of water pollution in the
rivers, affecting water bodies, 2) in addition it will reduce the intensity of the use of DFPs.
Local people should be encouraged through provision of loans, training and skill for
aquaculture development. Increase in the amount of culture fish in the market may reduce the
pressure on declining fishery resources.
The fisheries rules and regulations are adequate for the protection and sustainable exploitation
of fisheries resources but these policies are not implemented properly. Strict ban should be
imposed on the use and transfer of chemicals and blasting materials, and if the fishery
officials, law enforcement agencies and influential individuals are found guilty of using
destructive fishing materials, they should be dealt with strictly. The results also revealed that
increase in the cost of destructive gears has reduced their use, therefore the fisheries
department with the support of police should check the size of nets and other destructive gears
in the local market and impose ban its supply to the local market. The fishery watchers
should visit the rivers more frequently for helping fishermen in sustainable use of fisheries
resources, and should arrange seminars and workshops on proper use of fishery resources for
the local people and fishermen. The role of community cannot be ignored in the conservation
and sustainable use of fishery. Community leaders, village elders, village khans, union
council officials, local political parties‘ leadership should be encouraged to help the fishery
department and government in achieving the goals of sustainable use of fishery resources.
The government should give property rights of the rivers to community or some other specific
groups for specific times to conserve fisheries, and if the community is successful in
increasing the amount and size of fishes in the rivers, they should be rewarded and such
activities should be properly monitored and advertised.
109
To improve livelihoods of the fishermen as well as to conserve local fishery resources from
DFPs immediate actions must be taken. In this regard, the government and line departments
should strengthen local institutions and make arrangements for awareness of local people.
Awareness should be created through local radio and television networks regarding negative
impacts of DFPs, local residents and community elders should be encouraged to discourage
destructive fishing practices. The number of watchers should be increased and the nature of
their employment should be made permanent. Promoting the use of selective gears and
discouraging the use of DFPs should be pursued through a system of incentives and penalties.
The pressure on wild stocks may be moderated through increased reliance on farmed fish and
public education and awareness. Stocking of water bodies may also help increase the supply
of wild caught fish with less pressure on natural stocks. The future fisheries management
initiatives should be directed towards reducing the intensity and use of DFPs and enhancing
awareness regarding conservation of fisheries resources for future generations.
6.3.2 Limitations /Recommendations for future research
The present study has captured only those causes which can be measured and analyzed
through the selected regression models. However, tremendous research gap still exists in
finding the causes of destructive practices empirically. Destructive fishing methods have
many reasons, not explained by the present model. For example rivalry and differences over
natural resources (Munyi, 2009; Pomeroy and Rivera-Guieb, 2006; FAO. 2010) is a major
cause of fisheries resource degradation in developing countries. Similarly, construction of
settlements/increase in population beside major rivers (Lampe et al., 2017; Ram-Bidesi, 2011)
and social and cultural perceptions regarding water and its components as an open access
(Lampe et al, 2017) is also a major threat to fisheries resources and needs further
investigation, especially in developing countries. Similarly, technology and new fishing
methods (Khan & Khan 2011; Odada & Wandiga 2004; Lampe et al., 2017), energy and time
efficiency (Lampe et al 2017; King & Faasili 1999), and ineffective rules or incapacity to
monitor rules & regulations (Johnson, 1998; Satria & Matsuda 2004; Khan & Khan 2011;
Waqas & Khokhar 2012; Hossain et al., 2008; Odada & Wandiga 2004; King & Faasili 1998;
FAO 2010), are also the major causes of destructive fishing practices. It is generally believed
that wild catch is tastier than farmed fish, therefore, taste of fish caught (Fox 1997; Chan
2001), and intensity of fishing effort (Lampe et al., 2017; Fridah 2009; Khan & Khan 2011),
may also lead to destructive fishing practices. Due to continuous use of some fishing gears
fishers feel confidence and a feeling of compatibility with some fishing practices (Lampe et
110
al., 2017), which may be destructive in nature. In most of the cases fishermen, employees of
law enforcement agencies and destructive fishing material sellers create group relationship
patterns (Lampe et al., 2017, leading to degradation of fisheries resources due to DFPs. Many
poor people rely on fish as the chief supply of food and protein or are high dependence upon
natural resources (Ram-Bidesi 2011; Munyi 2009; Pomeroy and Rivera-Guieb 2006) mat
trigger the use of DFPs. However the present study have focused on only seven causes of
destructive fishing g practices, including; average years of formal education, livelihood
diversity, poverty, cost of gear used, distance to water bodies, supply of culture fish in the
market and fish stock in the rivers.
(a) The dissertation discovered the drivers of DFPs, and the impact of destructive methods on
fishermen livelihoods and consumption. There is further need to conduct empirical research
on the causes of DFPs as this research has focused on a few pertinent causes. Many other
avenues still remain unanswered.
(b) This research also investigated that the application of DFPs is widespread and frequent, in
the study area adding to the sufferings of small scale fishers and leading to economic and
social distress. However, this study investigated the effect of DFPs on only afew assets of
fishers that were affected due to reduced fishing activity in the study area. There is
tremendous research gap in applying the sustainable livelihood approach to the fishing
practices in the study area, as the present research only covered a small component of the
SLA.
(c) Research on the impact of population and construction of settlements, water pollution,
competition and conflicts over natural resources, urbanization, social and cultural perceptions
regarding water and its components as an open access , new fishing methods and technology,
taste of fish caught, ineffective rules or incapacity to monitor rules and regulations, existence
of group relationship patterns between fishermen and the law enforcement agencies and
destructive fishing materials seller, on water resources needs proper attention of researchers,
which will improve the situation of current fishing activities to a great extent. However,
tremendous research gap still exists in finding the above mentioned causes of destructive
practices empirically.
111
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Appendix-A. Questionnaire No. of Interview: __________
Questionnaire on
AN ASSESSMENT OF INLAND DESTRUCTIVE FISHING PRACTICES
IN DISTRICT CHARSADDA, PAKISTAN
Note:
The Purpose of this study is to collect information on the above topic as a requirement of PhD
Degree from University of Peshawar. All the responses will be treated confidentially.
Researcher Scholar: Mr. Muhammad Qasim
Village Name: _______________________________
Date of Interview: _______________________________
Respondent‘s Name: _______________________________
Department of Economics
University of Peshawar, Pakistan
129
I. Respondent’s Personal and general information:
Q.1 Age of the Respondent: __________
Q.2 Age group 26-35 36-45 46-55 56-65 >66
Q.3 Education Status: Educated Illiterate
Q.4 Skills Type: Expert/Seasoned Fishermen Medium level Beginner
Q.5 Type of tools used in fishing:
i. Fishing using boat
ii. Fishing using tube and fishing gears
iii. Electric appliances (generator etc.)
iv. Other _____________________________
Q.6 What is your primary occupation?
Q.7 What is the household size in your family (number of households) ____________
Q.8 What is your average total household income besides fishing? _____________
Q.9 What is your total fishing experience in years? ___________________
Q.10 Please mention the number of fishing gears you own? _________________
Q.11 What is the average land size you hold? __________ Acres
Q.12 What percent of the caught fish is Consumed Sold
II. Adoption and causes of Destructive Fishing Practices
Q.13 Which practice or practices you conduct for fishing among the following? You can choose
more than one option.
DFP Adopt Do not adopt
Blast Fishing
Cyanide/Chemical Fishing
Electric Fishing
Banned Nets/Traps
Other Fishing Farming
130
Causes of Destructive Fishing Practices
Variable Measurement Amount/
Response
Q.14 Average catch/day/effort or trip Kg/day
Q.15 Please mention your average years of formal
education
Years
Q.16 How many alternative livelihood opportunities
do you have?
Number
Q.17 What is your average total household income? Amount (Rs)
Q.18 What is the cost of gear/s you use in fishing? Amount (Rs)
Q.19 Please tell me the distance to water body from
your residence?
Km
Q.20 How much culture fish is brought for selling in
this local market?
Amount in tons
Q.21 What is your opinion about the fish stock in
the water bodies?
Increase d=3
Constant=2
Decreased=1
Q.22 How much do you save from your monthly
fishing income?
Average annual
savings =
average monthly
savings × 12 =
Q.23 Years of experience in fishing Years
Q.24 Licensing Hold license=1
Don‘t hold
license=0
III. Impact of DFPs of fish consumption
Q.25 What is the most important reason of fish consumption among the following?
(tick one option only)
Not sold in the market
Lower price in the market(cheaper)
Nutritive value
Easily available
Taste of fish
Freshness
Q.26 What is the frequency of fish consumption in your family?
Once a month
2 to 3 times a month
Four times a month
More than four times a month
131
Q.27 Which fish species among the following you consume mostly? (tick
one option only)
Response
Local name Fish Specie
China kub Cyprinus carpio (Exotic) and Carassius auratus(Exotic)
Shermahe Clupisoma naziri and Clupisoma garua
Mahasher Tor macrolepis
Marmahe Mastacembelus armatus
Sulaimani
(Fauji)
Glyptothorax punjabensis, Glyptothorax stocki,
Glyptothorax sufii, Glyptothorax cavia
Sole (Katasar) Channa punctatus, Channa gachua
Q.28 Please mention the average amount of fish consumed (in KG) in your
family per month? (a)
Q.29 Total Number of Households (b)
Q.30 Per Capita fish consumption per year (a/b)×12
Q.31 Price of fish /Kg (in Rs)
Q.32 Please mention who consume more fish
among the following age groups?
(prioritize from 1 to 5)
0-5
6-10
11-15
16-20
Above 20
Q.33 Please mention who consume more fish in the family? Educated (1),
Uneducated (0)
Q.34 Season you consume more fish? Summer Winter
Q.35 Amount of fish sold/day/trip
Q.36 Please mention the number of species you caught in
IV. Impact of DFPs on livelihoods: (Note: please indicate the level of assets in the two periods)
Assets
Scale Time Period
Financial
Assets
2001 2016
Q.37 Regular inflow of money
(income/wages/earnings)/month
Rupees
Q.38 Savings from income earned from
fish
Rupees
Q.39 Access to credits Rupees
Physical
Assets
Q.40 Housing (shelter)-rented or personal Yes=1
No=0
Q.41 Energy supply- UPS, Generators Yes=1
No=0
Q.42Transport facility for fish to market-
motorcycle/car
Available=1
Not available=0
Q.43 Tools availability (Boat, nets, tube,
etc. )
Owned=1
Not owned=0
2001= 2016 =
132
Natural
Assets
Q. 44 Number of fish species caught
Q.45Does licensing have restricted/
reduced your access to fisheries?
Q.46Do fishery watchers have
restricted/reduced your access to
fisheries?
Q.47Does fishery litigation process has
restricted/reduced your access to
fisheries?
Q.48Does fish size and amount has
decreased over the past fifteen
years?
Q.49Do fisheries resources in your area
has
Number
Yes=1 No= 0
Yes=1 No=0
Yes=1 No=0
Yes=1 No=0
Increased=2
Constant=1
Decreased=0
Social
Assets
Q.50 Local union council members
Q.51 Membership in political parties
Q.52 Law enforcement agencies (police,
courts)
Q.53 Contacts with village elders
Q.54 Networking with other households
or fishermen
Q.55 Kinship (Family members support)
Yes=1 No= 0
Yes=1 No=0
Yes=1 No=0
Yes=1 No=0
Yes=1 No=0
Yes=1 No=0
Human
Assets
Q.56 Education: Avg. years of formal
education
Years
Q.57 Years of experience of household
head in fisheries related activities
Years
Q.58 Please mention the number of
household engaged in fishing
Number
Q.59 Time spent in working Hours
Thank You
133
Appendix-B. Questionnaire No. of Discussion: __________
Questionnaire for
FOCUSED GROUP DISCUSSION
1. Name of respondent:
2. Location:
3. Profession:
4. What major destructive fishing practices are conducted in your area?
5. Which fishing method is intensively used among the following methods?
Cyanide
Blasting
Electrofishing
Small mesh nets
6. Which method is the most destructive among the above mentioned practices?
7. Why people conduct destructive fishing?
i. Due to lack regulation
ii. No community control
iii. Easy access to destructive fishing gears
iv. Lack of education regarding conservation of natural resources
v. Catch rate is high with destructive fishing
vi. Due to poverty
vii. Other ________________________
8. Why most of the fishers don‘t hold licensing?
9. Who mostly conduct the destructive fishing practices in your community?
i. People who have more fishing experience
ii. People with no fishing experience
iii. People with more social and political contacts
iv. Any other ___________________
10. Destructive fishing is mostly conducted by
i. Fishermen
ii. Non-fishermen
11. Destructive fishing practices mostly conducted by
i. Farming fishers
ii. Fishing farmers
134
iii. Occasional fishers
12. Does destructive fishing improve people‘s livelihoods? Yes/No
13. Do fishers hold licenses? If no then why?
14. What is the impact of DFPs on the livelihood of fishermen?
15. What is the impact of DFPs on fishermen fish consumption?
16. When you compare your present catch with the past, do you think that fish size has
increased or reduced?
17. When you compare your present catch with the past, do you think that amount of fish in
the rivers has increased or reduced?
18. If the fish stock in the rivers have reduced? What are the underlying causes for this
reduction?
19. If the fish stock in the rivers have increased? What are the underlying causes for this
increase?
20. How can we reduce the use of destructive fishing practices?
135
Appendix-C. Interviews No. of Interview: __________
Interviews with the officers of Fishery Department, Khyber Pakhtunkhwa
1. What is the process for obtaining license for fishing?
2. Is there any expiry on fishing license?
3. What is the license fee for fishing?
4. Which fishing methods/gears are highly destructive.
5. How do you watch fishing activity in the rivers?
6. What is the control mechanism for reducing the intensity of destructive fishing practices?
7. If a person is found guilty of conducting destructive fishing, what are the penalties?
8. Do you think fish population in the rivers has declined?
9. If yes, then what strategy/s the fishery department is adopting to control the use of DFPs?
10. Is there any campaign or awareness program organized by the fisheries department to
control the decline of fish stocks in rivers?
136
Annexure D: Method of the calculation of sample size
Formulae for the sample size n= source: (Tryfos, 1996)
Nominator C/z (C/z)2 Denominator sample
Water body
type
Settlement
/Village
name and
number
Population
size census
1998 Male pop
persons/HH
unit #of HHs ∏
∏(1-
∏) N∏(1-∏) N-1 0.040816327 (.05/1.96)2
Sardaryab(River
Kabul)
Dogar 373 209 8 47 0.5 0.25 11.65625 46 0.040816327 0.001665973 0.32601 36
Doaba 356 203 8 45 0.5 0.25 11.125 44 0.040816327 0.001665973 0.3224698 35
Jala Bela 67 33 8 8 0.5 0.25 2.09375 7 0.040816327 0.001665973 0.2622865 8
Khiale (River
Swat)
Abazai 2978 1518 8 190 0.5 0.25 47.4375 189 0.040816327 0.001665973 0.5644523 85
Dawlat Pura 343 187 8 43 0.5 0.25 10.71875 42 0.040816327 0.001665973 0.3197626 34
Jangal 131 73 8 16 0.5 0.25 4.09375 15 0.040816327 0.001665973 0.2756143 15
Chitli Tapo 32 21 8 4 0.5 0.25 1 3 0.040816327 0.001665973 0.2549979 4
River Jindi
Shahbara 495 261 8 62 0.5 0.25 15.46875 61 0.040816327 0.001665973 0.3514161 44
Majoke 238 238 8 30 0.5 0.25 7.4375 29 0.040816327 0.001665973 0.2978967 25
Total sample 286
