Vulnerability of fishery based livelihoods to impacts of weather and climate events

PATTEN VULNERABILITY OF FISHERY-BASED LIVELIHOOD TO IMPACTS OF WEATHER AND CLIMATE EVENTS: A CASE STUDY OF ROBERTSPORT, GRAND CAPE MOUNT COUNTY, LIBERIA MASTER THESIS KHANH HOA - 201

MINISTRY OF EDUCATION AND TRAINING

NHA TRANG UNIVERSITY

ERIC T.S PATTEN

VULNERABILITY OF FISHERY-BASED LIVELIHOOD TO IMPACTS OF WEATHER AND CLIMATE EVENTS: A CASE STUDY OF ROBERTSPORT, GRAND CAPE MOUNT

COUNTY, LIBERIA

MASTER THESIS

KHANH HOA - 2019

MINISTRY OF EDUCATION AND TRAINING

NHA TRANG UNIVERSITY

ERIC T.S PATTEN

VULNERABILITY OF FISHERY-BASED LIVELIHOOD

TO IMPACTS OF WEATHER AND CLIMATE EVENTS:

A CASE STUDY OF ROBERTSPORT, GRAND CAPE

MOUNT COUNTY, LIBERIA

MASTER THESIS Major:

Topic allocation Decision

Decision on establishing the

ACKNOWLEDGEMENT

My sincere gratitude to the Administration and Faculty of the Nha Trang University, especially the program faculty of the NORHED International Masters Program on Marine Based Ecosystem Management and Climate Change, for their support and mentorship in completing this work

I am also profoundly grateful to Prof Curtis M Jolly for his motivational support, experienced and knowledge based supervision as well as great enthusiasm for the completion of my study and Masters Thesis

My esteemed appreciation to the Administration of the University of Liberia, for their immense financial support towards my study and research work; moreover, the support from the Department of Economics during my time of study and research is highly applauded

Finally, I would like to appreciate my family and friends whose support meant the world to me, especially my wife and kids

Thank you!

This work is dedicated to mama

TABLE OF CONTENTS

UNDERTAKING i

ACKNOWLEDGEMENT i

APPENDICES vi

LIST OF ABBREVIATIONS vii

LIST OF TABLES i

LIST OF FIGURES iii

Abstract 17

CHAPTER 1: INTRODUCTION 1

1.1 Problem Statement 2

1.2 Significance of the study 3

1.3 Limitations of the study 4

1.4 Research questions 4

1.5 Objectives of the study 4

CHAPTER 2: WEATHER, CLIMATE AND CLIMATE CHANGE 6

2.1 Temperature 6

2.2 Rainfall 6

2.3 Weather and Climate conditions in Liberia 7

2.3.1 Climate 8

2.3.2 Rainfall, Temperatures and Extremes 9

2.3.3 Natural Hazard Occurrence 10

2.4 Vulnerability of fishery-based Livelihoods to impacts of Weather and climate events 12

2.5 Sustainable Livelihood Approach (SLA) 12

CHAPTER 3: RESEARCH METHOD 17

3.1 Focus Group Discussion 17

3.1.1 First Focus Group Discussion 19

3.1.2 Second Focus Group Discussion 19

3.1.3 Third Focus Group Discussion 20

3.2 QUESTIONNAIRE 20

3.2.1 QUESTIONNAIRE DEVELOPMENT 20

3.2.2 MODIFICATION/FINALIZATION OF QUESTIONNAIRE 20

3.3 Households survey/interview 21

3.4 Mode of data entry 21

3.4.1 Data Analysis 22

3.5 Secondary Data 22

CHAPTER 4: RESULTS 23

4.1 FOCUS GROUP DISCUSSION 23

4.1.1 First Focus Group Discussion 23

4.1.2 INSTITUTIONAL ANALYSIS 25

4.1.3 Weather and Climate Impacts on Fisher-folks livelihood resources 25

4.2 Second Focus Group Discussion 26

4.2.1 INSTITUTIONAL ANALYSIS 28

4.3 THIRD FOCUS GROUP DISCUSSION 29

4.4 ASSESSMENT OF LIVELIHOOD ASSETS 29

4.4.1 HUMAN CAPITAL (ASSESSMENT OF HOUSEHOLD INFORMATION) 29

4.4.2 Occupational analysis 30

4.4.2.1 ASSESSMENT OF SOCIAL CAPITAL 30

4.4.2.2 House and Land ownership social capital 31

4.4.2.3 House Structural, Roofing and Floor Types- Social Capital 31

4.4.2.4 Organization membership and Type of Affiliation 33

4.4.2.5 Availability of Gov’t organization and Fishing regulatory law 34

4.4.2.6 Availability of Relatives and help from Relatives and Community 35

4.4.3 Assessment of Access to Natural Capital 36

4.4.3.1 Households years of being involved in fishing or fishing activities Error! Bookmark not defined 4.4.3.2 Household access to fishing and earnings from fishery-based activities Error! Bookmark not defined 4.4.3.3 Average catch of households currently and in the past 10 yearsError! Bookmark not defined 4.4.3.4 Coastal Flooding and Coastal Erosion weather & climate effects and Impacts 42

4.4.3.5 Sea Level Rise and Wind Strength effects on households and their Impacts on fishing activities 44

4.4.3.6 Rainfall Impacts on fishing activities and the impact of marine pollution on household fishing activities 46

4.4.4 Assessment of Physical capital 38

4.4.4.1 Access to roads Error! Bookmark not defined 4.4.4.2 Access to Water & Sanitation 38

5.4.4.3 Access to Schools Error! Bookmark not defined 4.4.4.4 Access to Technology Error! Bookmark not defined 4.4.4.5 Access to Hospitals Error! Bookmark not defined 4.4.4.6 Access to Toilets Error! Bookmark not defined 4.4.4.7 Access to Markets for Producer goods Error! Bookmark not defined 4.4.5 Assessment of climate change knowledge and perception 47

4.4.5.1 Assessment of Knowledge about Climate change (CC) 47

4.4.5.2 Assessment of perception of climate variables changing 48 4.4.5.3 Assessment of households’ perception of climate variables changing 49 4.4.5.4 Assessment of Impact of current trend of climate change 50

4.4.5.4.1 Household perception of Climate Change impact on livelihood & fresh water quality 50

4.4.5.4.2 Households (HH) perception of climate change Impact on infrastructure and sea level rise (SLR) 51

4.4.5.4.3 Household perception of climate change impact from increased emperature and Coastal Flooding 52

4.4.5.4.4 Households perception of climate change impact on coastal erosion and environmental pollution 53

4.4.5.4.5 Households perception of climate change impact on salt water intrusion and loss of fishing grounds 54

4.4.5.5 Households rating of climate events impacts on their livelihood 55

4.4.5.5.1 Households rating of the impacts of loss and damage of infrastructure due to

climate events Error! Bookmark not defined

4.4.5.5.2 Households rating of coastal floods and coastal erosion impacts due to climate events 56

4.4.5.5.3 Households rating of SLR and Temperature Change (TC) impacts due to

climate events Error! Bookmark not defined

4.4.5.5.4 Households rating of wind strength and rainfall impacts due to climate events

Error! Bookmark not defined

4.4.5.6 Household perception of what is responsible for climate change 58

4.4.5.6.1 Perception of cutting of trees and burning of solid fuelError! Bookmark not

defined

4.4.5.6.2 Perception of volcanic eruption and carbon emission from transportation Error!

Bookmark not defined

4.4.5.6.3 Perception of carbon emission from energy production and industries pollution

Error! Bookmark not defined 4.4.5.6.4 Perception of burning of waste being responsible for climate change Error!

Bookmark not defined

4.4.5.7 Household perception of what can reduce climate change impacts 61

4.4.5.7.1 Perception of re-planting of tress and sustainable forest useError! Bookmark

not defined

4.4.5.7.2 Perception of increase use of public transport and use of appliances with low

energy consumption Error! Bookmark not defined

4.4.5.7.3 Perception of renewable energy sources and coastal defenses and sea walls

Error! Bookmark not defined 4.4.5.7.4 Perception of building durable structures and climate change awareness Error!

Bookmark not defined

4.4.5.7.5 Perception of mangroves replanting and support from government 63

4.4.5.7.6 Perception of support from NGOs and alternative skills training Error!

Bookmark not defined

4.4.5.7.7 Perception of increased level of education and employmentError! Bookmark

not defined

4.4.5.7.8 Perception of loans and support from communityError! Bookmark not defined

4.4.5.8 Household mode of coping with weather and climate events 66

4.4.5.8.1 Household mode of coping with coastal flooding, coastal erosion, SLR and other climate events 66

4.4.6 Correlation analysis of weather and climate events impact on fisheries

dependents income Error! Bookmark not defined

CHAPTER 5: DISCUSSION CONCLUSION & RECOMMENDATION 69

5.1 Discussion 69

5.2 Conclusion 72

5.3 Recommendations 72

References Error! Bookmark not defined

APPENDIX A 79

APPENDICES

Appendix A: Questionnaires

APPENDIX B: Excel Spreadsheet Setup

LIST OF ABBREVIATIONS

AAT – Annual Average Temperature

AR5 – Annual Report 5

CC – Climate Change

CE – Coastal Erosion

CF- Coastal Floods

CMA- Collaborative Management Association

EPA – Environmental Protection Agency

EJF – Environmental Justice Foundation

FBLs – Fishery based Livelihoods

FDA – Forestry Development Authority

FGD – Focus Group Discussion

GAC – General Auditing Commission

GCM – General Climate Models

GDP – Gross Domestic Product

GHGs – Green House Gas Emissions

HH – Households

IPCC – Inter-governmental Panel on Climate Change

ITCZ – Inter-Tropical Convergence Zone

LMS – Liberia Meteorological Service

NaFAA – National Fisheries and Aquaculture Authority

PRA – Participatory Research Appraisal

RCM – Regional Climate Models

viii

SLA – Sustainable Livelihood Approach

SLR – Sea Level Rise

TC – Temperature Change

UNDP – United Nations Development Programme

UNFCC – United Nations Framework on Climate Change

USAID – United States Agency for International Development

WA – West Africa

WS – Wind Strength

i

x

LIST OF TABLES

Table 4.1: Frequency of First Focus Group Discussion 23

Table 4.2: Fanti town households rating of weather & climate impacts on fishing activities 26

Table 4.3: Frequency from Second Focus Group discussion 27

Table 4.4: Household Demographic Information Analysis on Sex and Education 29

Table 4.5:Occupational Analysis of Fanti Town and Kru Beach fishing villages’ respondents 30

Table 4.6: Sex Specific Social Relationship Status 31

Table 4.7: Age Specific Social Relationship Status Error! Bookmark not defined.

Table 4.8: Households monthly earnings 36

Table 4.9: Weather and climate events that have affected households fishing activities 43

Table 4.10: Impacts of Coastal Floods and Coastal Erosion on household fishing activities 44

Table 4.11:Impacts of Storms and Seasonality on household fishing activities 46

Table 4.12: Impacts of Rainfall and Marine pollution on Household fishing activities 47

Table 4.14:Perception of replanting of trees and sustainable forest use 61

Table 4.15: Household perception of increase use of public transport and use of appliances with low energy consumption 62

Table 4.16: Household perception of renewable energy sources and coastal defenses and sea walls 62

Table 4.17: Household perception of durable structures and climate change awareness 63

Table 4.18: Household perception of mangroves replanting and support from government 64

Table 4.19: Household perception of support from NGO and alternative skills training 65

Table 4.20: Household perception of increased level of education and employmentError!

Bookmark not defined.

Table 4.22: Correlation output of income, coastal flooding, sea level rise and rainfall

Error! Bookmark not defined.

LIST OF FIGURES

Figure 2.1: Map of West Africa 7

Figure 2.2: Average monthly Temperature and Rainfall for Liberia, 1901-2015; Source: WORLD BANK GROUP – Climate Knowledge Portal, Accessed 2/14/19 9

Figure 2.3: Average annual Precipitation of Robertsport from 2008 – 2016 Source: Liberia Meteorological Service (LMS) 10

Figure 2.4: Annual average hazard occurrence for Liberia, Source (World Bank climate knowledge portal, Liberia Dashboard; Accessed 15/02/2019) 11

Figure 2.5: Conceptual framework adopted and modified from DFID-1999 13

Figure 3.1: Focus Group Discussion Pair-wise matrix and ranking 18

Figure 4.1: Pair-wise Comparison Matrix of Fanti town Fishing Village 23

Figure 4.2: Pair-wise comparison matrix profile from Focus group Discussion 1 24

Figure 4.3: Fanti Town Fishing village institutional Analysis 25

Figure 4.4: Pair-wise Comparison Matrix of Kru beach Fishing Village 27

Figure 4.5: Institutional Analysis by Fisher-folks in Kru Beach Fishing Village, Robertsport 28

Figure 4.6: House Wall Structural types 32

Figure 4.7: House floor Types 32

Figure 4.8: House roofing Type 33

Figure 4.9: Organizational memberships (L), and Type of Affiliation (R) 34

Figure 4.10 Availability of Government organization (L) and Fishing activities regulatory law (R) 34

Figure 4.11: Availability of relatives and help from relatives and community 35

Figure 4.12: Household years of involvement in fishery related activities 37

Figure 4.13: Household current monthly average catch/ton and average monthly

catch/ton in the last decade 38

Figure 4.14: Effect of SLR and WS on household fishing activities in the past 10 years 45 Figure 4.15: Household access to road infrastructure in both Fanti Town and Kru beach 38

Figure 4.16: Household access to water and sanitation in Fanti town and Kru beach 39

Figure 4.17: Household access to Schools in Fanti town and Kru beach 40

Figure 4.18: Household access to Technology in Fanti town and Kru beach 41

Figure 4.19: Household in Fanti town and Kru beach access to hospitals 41

Figure 4.20: Households access to markets for producer goods 42

Figure 4.21: Households Knowledge about climate change 48

Figure 4.22: Households in Fanti town and Kru beach Perception of Climate change 49

Figure 4.23: Household perception of climate variables changing 50

Figure 4.24: Households in Fanti town and Kru beach perception about climate change impact on livelihood (L), and Fresh water quality (R) 51

Figure 4.25: Households perception of climate change impact on temperature (L), and coastal flooding (R) 53

Figure 4.26: Households perception of climate change impacts on coastal erosion and environmental pollution 54

Figure 4.27: Household Perception of climate change impacts on salt water intrusion and loss of fishing grounds 55

Figure 4.28: Household perception of climate change impacts on fishing tools 55

Figure 4.29: Household rating of the impact of infrastructure loss and damage due to climate events 56

Figure 4.30: Household rating of the impact of coastal floods and coastal erosion due to climate events 57

Figure 4.31: Household rating of SLR and TC impacts on fisheries dependents of Robertsport 57

Figure 4.32: Household rating of WS and Rainfall impacts on fisheries dependents of Robertsport 58

Figure 4.33: Household perception of cutting of trees and burning of solid fuel as a cause

of climate change 59

Figure 4.34: Household perception of volcanic eruption and carbon emission from transport as a cause of climate change 60

Figure 4.35: Household perception of industries pollution and carbon emission from

energy production as a cause of climate change Error! Bookmark not defined.

Figure 4.36: Household perception of burning of waste as a cause of climate change

Error! Bookmark not defined.

Figure 4.37: Household mode of coping with coastal floods and coastal erosion 67

Figure 4.38: Household mode of coping with WS and rainfall 67

Abstract

Liberia is a small Tropical West African country, located along the gulf of Guinea with a population of approximately 3.5 million persons As a country that is natural resource dependent, fisheries, iron ore, gold, diamond and timber contribute immensely

to its Gross Domestic Product There is high reliance on fisheries as a source of nutrition for many along the coast in Liberia

However, most of the coastal fishing communities, including inhabitants of Robertsport have been affected one way or the other by some climatic events such as coastal erosion and inundation as well as storm surges, precipitation and floods in the last decade Fishery is the primary source of livelihood and employment in Robertsport These coastal fishing communities and its dependent population could face severe impacts of weather and climate events, thus making them vulnerable to climate change impacts In assessing the vulnerability of Fishery-Based Livelihoods of coastal communities in Robertsport, Grand cape Mount County to impacts of weather and climatic events, this study sought to understand reasons and recommend strategies to reduce vulnerabilities of fishery-based livelihoods to weather and climate events in Robertsport, Grand Cape Mount County

By this, the impacts of weather and climate events on fishery-based livelihood resources, knowledge of climate change and local adaptive measures were assessed The hypothesis was to determine if respondent’s perception on level of income to these selected environmental hazards/variables and its associated risks make significant impact

on their livelihoods In order to pursue this assessment, a Participatory Research Appraisal (PRA) including Pair- wise ranking and institutional analysis were approaches adopted to conduct this valuation Focus Group Discussion was conducted separately in two (2) fishing villages in Robertsport, namely, Fanti Town and Kru Beach This FGD brought together fishermen, fish driers (processors/fish mongers), who are mostly women

as well as co-management officers both from the NaFAA

A Pair-wise ranking is a PRA tool that is used to outline hazards or priorities and compare them and then later ranked In our use of the pair-wise ranking, the two fishing villages’ inhabitants were gathered in separate forum to list and rank weather and climate events that impacted their livelihood resources The exercises enabled the identification the effect of these climate hazards on the livelihood resources and methods of adaptation and their effectiveness as well as available institutions in their areas of fishing and whether these support or regulate their fishing activities Following the listing of these weather and climate events, a pair-wise matrix of the weather and climate events was developed and the fishermen, fish driers (processors) and co-management officers were asked to compare each weather and climate event The correlation analysis suggests that there is negative relationship among variables such as income, sea level rise, coastal flooding and rainfall Also, the findings reveal low climate change knowledge, inadequate and ineffective local adaptation measures as well as low level of education Thus, households’ livelihood resources could be impacted in case of an increase in weather and climate events and render them vulnerable to these weather and climatic stressors

Key Words: Coastal flooding, coastal erosion, rainfall, Robertsport, participatory research appraisal, correlation, artisanal fishermen, weather and climate, climate change

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iv

CHAPTER 1: INTRODUCTION

Liberia is a small Tropical West African country, located along the gulf of Guinea with a population of approximately 3.5 million persons (LISGIS, 2009) It bears ownership to a coastline of 565km long, and maintains property or right to 12 nautical miles of exclusive economic zone as well as an aerial/regional belt consisting

of 200 nautical miles (USAID-DAI, 2008)

As a country that is natural resource dependent, fisheries, iron ore, gold, diamond and timber contribute immensely to its Gross Domestic Product (GDP) Fisheries are, however, tipped to be one of the sectors that have high potential for growth and contribution to National GDP Fisheries contribute about 10% of the country’s GDP

(Hughes, S et al, 2012)

The Small scale Fisheries sector employs over 33,000 persons, of which, 60% are women (GoL & FAO, 2012) The small scale (Artisanal fisheries) is an important component of Liberia’s marine fisheries, with over 3,300 registered canoes and more than 11,000 active fishermen who operate from 114 fish landing sites Artisanal fisheries provide food (65% of animal proteins) and livelihoods to people living along the coast (USAID-USDA, 2014)

An approximated 58% of Liberia’s 3.5 million persons live within 40 miles of the coast, with fisheries related activities being their major source of livelihood (USAID-DAI, 2008) A 2009 report outlined that coastal communities’ livelihoods are

vulnerable to poverty (Kebe, M et al, FAO-Report, 2009)

In Liberia, cases of disasters related to weather and climate events that encompass coastal flooding, coastal erosion, strong winds, pollution, and other climate related events occurring in especially the nine (9) coastal counties have heralded radio and television talk shows, newspapers and other main-stream and social media outlets and platforms Government institutions have attributed these situations to climate change as well as poor sanitation management A recent marine ecosystem audit report

by the General Auditing Commission (GAC) (GAC, 2018) outlined the lack of marine ecosystem management policy by institutions involved with the Marine space This, the report GAC lamented, posed serious threat to the achievement of the United Nations sustainable development goal 24 by the Government of Liberia

These conditions have not isolated fisheries-based livelihoods from the impacts

of the results of climate and weather events that continue to rampage the coast of Liberia

Coastal ecosystems in Liberia are reportedly at risk as a result of Sea Level Rise (SLR) (USAID-USDA, 2014), with a projected 1m SLR leading to a loss of over 95 Km2 of land due to coastal erosion and inundation (USAID-DAI, 2008) Climate Change (CC) is projected to put strain on fisheries (Brander, 2006) SLR, increasing temperatures, fluctuating rainfall patterns and ocean acidification present severe consequences to marine and other ecosystems as well as fish populations (IPCC, 2007;

Cheung et al., 2009; Islam, M et al, 2013; Essam, M., et al, 2013) Experiences of these are already visible in some fishery-dependent coastal communities (Perry et al,

2009) These reports/publications coincides with heightened global concerns over the scale of changes occurring in our climate., attributable to an upshot of Greenhouse Gas emission (GHGs) in our atmosphere, leading to observed fluctuations in rainfall patterns, rising global atmospheric temperatures (land & Sea), droughts, coastal erosion, SLR, and other extreme weather and climate change events (IPCC, 2007)

Coastal floods, coastal erosion and coastal storms may accentuate these consequences on fishery-based livelihoods (FBLs) and increase their sensitivity by rendering on-shore infrastructures and other land-based installations damaged

(Westlund L et al, 2007)

Assessing the vulnerability of FBLs of coastal communities in Robertsport, Grand cape Mount County to impacts of weather and climate events set out a foundation to identify and suggest proposals to reduce the consequences

as well as storm surges, precipitation and floods leading to 10 deaths in 2012 (Richard, 2012), especially FBLs However, most coastal residents in Robertsport refuse to relocate citing lack of alternative livelihood (IRIN, 2007)

Robertsport, the capital of Grand Cape Mount County, is a fishery dependent community The level of education among fisheries dependent households was observed to be very low, with many of those involved in fisheries related activities as a

means of livelihood having no or very limited alternative training ((Kebe, M et al

FAO-Report, 2009) A United Nations Development Program (UNDP) 2016 Human Development Report estimated Liberia’s Human Development Index score at 0.427 (UNDP & United Nations, 2016) The per capita GDP estimate of US$900.00 was outlined in this report (US-CIA, 2015) As fishery is the primary source of livelihood and employment in Robertsport (FAO, 2007;USAID, 2015), these coastal fishing communities and the dependent population could face severe impacts of weather and climate events, thus making them vulnerable to climate change impacts (EPA, 2013)

An EPA report to the United Nations Framework on Climate Change (UNFCC), highlighted low climate change knowledge and perception in Liberia thus raising concerns about the adaptability of affected communities (EPA, 2013)

While there are reports assessing fisheries based livelihood vulnerability to poverty (Kebe et al., 2009), these reports however have not focused on the vulnerability of fishery-based livelihood to impacts of weather and climate events This study sought to understand reasons and recommend strategies to reduce vulnerabilities of fishery-based livelihoods to weather and climate events in Robertsport, Grand Cape Mount County

1.2 Significance of the study

The fishery sector of Liberia has a major role to play in employment and food security in Liberia With the high dependence of Liberians on fishery resources, it plays a major role contributing significantly to the growth of the Economy Climate change would likely pose serious threats to over 1,925 (LISGIS, 2009) urban households, most of whom reside in Robertsport along the coast in fishing communities (USAID-DAI, 2008) The National Disaster Management Agency estimates losses of over US$100,000 yearly to coastal communities The level of

adaptation for most coastal inhabitants is very low Proposals have been advanced through the EPA’s National Adaption Plan (NAP) and the NaFAA to remedy some of the difficulties faced by these coastal residents

The study aimed to provide detailed information to institutions and policy makers

in Liberia on;

1 The impact of weather and climate variability on fishery-based livelihoods

2 Perception of fishing community of weather and climatic events in relation to their activities

3 Local adaptation strategies and their effectiveness in minimizing dangers on continuous extreme weather events

1.3 Limitations of the study

We had hoped to interview 128 households in our survey; however, only 70 households were willing and available to be assessed We could not have waited until all 128 expected interviewees were available due to limited time and resources

1.4 Research questions

 What are the impacts of weather events on fishery-based livelihood resources?

 What does fishing community know about climate change?

 What are the local adaptation measures used and their effectiveness?

1.5 Objectives of the study

The overall objective of this study was to assess variables that determine the vulnerability of fishery-based livelihood to weather and climate events The specific objectives were:

 To assess the impacts of weather events on fishery-based livelihood resources

 To assess fishing community’s (Robertsport) knowledge of climate change

 To evaluate local adaptation measures used in Robertsport, Grand Cape Mount County and their effectiveness

1.6 Hypothesis

 Ho: Weather and climate events have impacts on Household’s income level

 H1: weather and climate events do not have impact on Household’s income level

CHAPTER 2: LITERATURE REVIEW WEATHER, CLIMATE AND CLIMATE CHANGE

Climatic conditions in West Africa (WA) include high temperatures, uneven distribution of rainfall with heightened precipitations in some countries and contracted

rains in others These climatic conditions also cause SLR and sharp “oscillation” of

high precipitations (USAID, 2018) According to the United States Agency for

international Development (USAID) (2018) publication, a “south-western moist wind”

that forms from atop the Atlantic Ocean is engulfed with short periods of high

precipitations

West Africa (WA) climate trend has generally educed in recent decades as a reaction to human induced GHG activities These variabilities and CC pose

consequences for fisheries, agriculture, and human health, etc (J.O Riede et al, 2016),

and the livelihood that depend on them (USAID, 2018)

2.1 Temperature

According to the Inter-Governmental Panel on Climate Change (IPCC) Annual Report 5 (AR5) (2013), global annual average temperatures (AAT) have risen since the 1950’s and this trend is expected to continue to the end of the century Many areas

in Africa, including WA, have endured a rise in AAT by 0.50C and above during the

last 50 – 100 years (IPCC, 2013;J.O Riede et al, 2016); AAT in WA orbit within the

range of 26 - 300C, however, variations lie in nighttime temperatures and

close-to-earth wetness (humidity) during the rainy season (J.O Riede et al, 2016) Regional

Climate Models (RCM) estimates AAT over WA to rise by 30C to 60C up to the close

of the 21st century (THE WORLD BANK GROUP, Accessed 2019) According to this dashboard, estimates for the frequency of “hot” days and nights, projected by the General Circulation Models (GCM) navigate towards rises in these climate events with coastal regions to be mostly affected

2.2 Rainfall

The magnitude of rainfall considerably diminishes from the WA coast along the Atlantic Ocean, that lies in the South of the Sahara situated in the north; where the level of rainfall is observed to have a powerful “South-North” inclination As a result

WA is sub-divided into 3 climate regions (Sahel, Sudan and the Tropical-humid

Guinea Coast) (J.O Riede et al, 2016)

According to J.O Riede et al (2016), the Sahel region which lies at 12.5 0N, experirnces an annual precipitation that does not surpass 500 mm, with a high degree happening in August The Sudan region that lies between 90 and 12.50 N, notes a yearly rainfall of less than 200 mm in Northern Nigeria to 1000 mm in northern Mali Lastly, the Tropical-Guinea coast region situated along the Gulf of Guinea sees an average yearly precipitation of more than 1500mm

Estimates from the GCM show little rise in 5-day utmost rainfall by the years

2046 – 2065 and the latter years of 2081 – 2100 “under low, medium and high

emissions scenario” GCM projects “low medium confidence” as it relates to high

precipitation within the WA region by the close of the 21st century However, RCM shows rises in the frequency of days with high levels of precipitation in this region in May and July (THE WORLD BANK GROUP, Accessed 2019)

2.3 Weather and Climate conditions in Liberia

Liberia is a small West African country that lies along the banks of the Atlantic Ocean as figure 2.1 below shows

Figure 2.1: Map of West Africa 1

Bordered in the north by the Republic of Guinea, in the east by the Republic of

La Cote D’Ivoire and on the west by Sierra Leone; it is situated at latitudes 4O 20’ to

8O 30’ North and longitudes 7O 18’ to 11O 30’ west The total land area space is 11,

370 Square Kilometers (Sq km) (G Cape Mt.-CDA, 2012) Its physical and geographical features encompass flat to rolling coastal hills that provide a platform for gold, iron ore, diamond, water as well as forests (GoL-NHDR, 2009;G Cape Mt.-CDA, 2012)

Climate change could pose a major problem, most notably to “public health”,

coastal zones and coastal counties as well as to the agriculture sector (THE WORLD BANK GROUP, Accessed 2019) Grand Cape Mount County is located in the western region of Liberia, with its county capital as Robertsport It is situated 70 15’ N, 110 00’

W in the South-Western region of Liberia, bounded by the Republic of Sierra Leone

on the West, Gbaporlu County on the North-east and adjoined by Lake Piso and Bomi County on the East as the Atlantic Ocean sits on the South Its population is sparsely distributed with much reliance on commerce, mining and fishing (G Cape Mt.-CDA, 2012)

2.3.1 Climate

Liberia is a country with a tropical climate that encompasses one major rainy

season, even though most months endure precipitations “the wet season runs from

May to October, with a short break in rains from mid-July to August as the Inter Tropical Convergence Zone (ITCZ) oscillates between the equator and the Tropic of Cancer.” (THE WORLD BANK GROUP, 2019 Accessed 2/14/19;LMS, 2017) The

dry season runs from November to April with the average temperatures ranging from

24 – 27OC February and March endure the topmost temperatures as shown by figure 2.2 below (THE WORLD BANK GROUP, 2019 Accessed 2/14/19)

Robertsport, Grand Cape Mount County’s weather is a humid and tropical climate with the wet season and the dry season as the two major different seasons The wet (Rainy) season runs from May to October, averaging rainfall of approximately 400cm, while the dry season runs from November to April (6 months each) The average minimum and maximum temperatures of Robertsport, Grand Cape Mount County falls within the range of 28 to 34 degree Celsius (G Cape Mt.-CDA, 2012)

2.3.2 Rainfall, Temperatures and Extremes

Liberia endures a precipitation gradient from its inland terrain to the coastal zones

The precipitation cycles in Liberia have featured “drier” and “rainier” course during the 1960’s and beyond The 1960’s and the latter years of the 1970’s saw specific wet periods while the early years of the 1970’s and 1980’s saw specific dry periods (THE WORLD BANK GROUP, 2019) Accordingly, the World Bank group climate knowledge portal, Liberia dashboard (year), postulates observed gradual change in the dry and precipitation seasons over the last three (3) decades The (2019) dashboard indicates that the average annual oscillation of “cold” nights by year has contracted by 18 days from 1960 – 2003 From 1961 – 2003, the frequency of West

African cold days and cold nights have contracted As a coastal county, Grand Cape Mount has high average annual rainfall as a result of a coastline that spans approximately from South – East to north – West

The rainfall data below recorded and obtained from the Liberia Meteorological Service (LMS) for Robertsport, covering the years 2008 - 2016 show the month of

0 500

August recording the highest amount of rainfall with an average annual rainfall of approximately over 400 cm over the nine years July – September notably share the highest annual rainfall during the wet season The year 2008 recorded the lowest average annual rainfall according to this data, as noticeable fluctuations in the rainfall are observed among various months and years However, August 2015 recorded the highest average monthly rainfall of 462 cm among these years according to this data

Average annual temperature, according to the climate change knowledge portal dashboard for Liberia has risen by 0.8OC from 1960 – 2006 The average frequency of

“hot” nights by year has risen by 57 nights from 1960 – 2003 From 1970 – 2010, West African temperatures have increased by higher degree in the last 20 years from

1970 – 2010 than the previous as shown by figure 2.3 below

Figure 2.3: Average annual Precipitation of Robertsport from 2008 – 2016

Source: Liberia Meteorological Service (LMS) 2.3.3 Natural Hazard Occurrence

Floods are an alternating natural hazard in Liberia and are anticipated to grow even worse with CC, notably with severe impacts on coastal counties due to SLR Severe heavy precipitation was responsible for floods in 2007, which posed implications for human health, infrastructure, and basic livelihood activities like fisheries and agriculture Figure 2.4 shows annual average natural hazard occurrence that could be exacerbated by CC:

Figure 2.4: Annual average hazard occurrence for Liberia, Source (World Bank climate knowledge portal, Liberia Dashboard; Accessed 15/02/2019)

Projected rise in sea levels is anticipated to heighten along the Liberian coast and could occasion additional and repeated flood situations in coastal counties (THE WORLD BANK GROUP, 2019), notably coastal counties including Robertsport, Grand Cape Mount County

An estimated 1.0 meter (m) in SLR would result to an estimated 230,000 persons being put at risk with a projected loss of 2,150 sq km of land and infrastructure along the coast worth an estimated value of US$250 million Even more so, this situation would exacerbate the occurrence of epidemics on the population such as Cholera, Malaria, as well as Diarrhea (THE WORLD BANK GROUP, 2019)

Lassa fever which mostly occurs during wet seasons would also increase due to

SLR “Schistosomiasis, yellow fever, hepatitis A, lymphatic filariasis and intestinal

worms” are anticipated to rise due to climate change (THE WORLD BANK GROUP,

2019) February and March are the driest months of the dry season and the occurrence

of drought This period is occasioned by the shortage of safe drinking water supply especially for household use, and water demand for agricultural purpose would increase by 2020 and 2050, as the Regional Climate Models (RCMs) over Liberia has projected an average annual temperature increase by 0.60 in the 2020’s and by 1.30 by the year 2050 (THE WORLD BANK GROUP, 2019)

2.4 Vulnerability of fishery-based Livelihoods to impacts of Weather and climate events

The IPCC (Intergovernmental panel on climate change) (2007) outlines vulnerability of a fishery-based livelihood to impacts of extreme weather and climate

events as: “The degree to which a fishery-based livelihood structure/system is

susceptible, or unable to cope with adverse/negative effects/impacts of climate change, including climate variability and extremes, and vulnerability is a function of the character, magnitude and rate of climate variation to which a system is exposed, its sensitivity, and its adaptive capacity”

In other words, the extent, disposition or weightiness to which a livelihood system/structure dependent on fishery is exposed, sensitive, and to which its adaptive capacity is low is regarded as vulnerable (IPCC, 2007)

Livelihood includes one’s capabilities, asset and endeavors of existence Its sustainability is attained if it can cope and rebound from shocks and stress by enhancement of one’s capabilities and assets at present and in the future (DFID, 1999;DFID, 2008; UNDP-IRP, 2009)

In order to assess the impacts of weather and climate events faced by fishermen and other fishery-based livelihoods in Robertsport, there are a number of methods through which they can be pursued to understand the scale of their vulnerabilities Thus, in my approach to assess the vulnerability of fishery-based livelihoods to impacts of weather and climate events, the conceptual framework below would be used as a basis of my analysis This framework highlights the relationship/interaction between the elements of vulnerabilities and fishery-based livelihood (Islam et al., 2013)

2.5 Sustainable Livelihood Approach (SLA)

The SLA is an effective tool for assessing and understanding vulnerabilities of livelihoods to extremes and climate change (DFID, 1999) SLA is a framework which seeks to transcend conventional descriptions and methods to reduce vulnerabilities (Krantz-SIDA, 2001) Figure 2.5 below displays a conceptual framework adopted and modified to show factors influencing vulnerability and coping mechanisms of households in Robertsport, Liberia

Figure 2.5: Conceptual framework modified from DFID-1999

Vulnerability is the extent/degree to which people are likely or susceptible to the impacts of climate change (IPCC, 2007; Groot, Singh, & Riel, 2013;Rahman, 2015) Fisheries dependent households in Robertsport and other coastal communities could be sensitive to weather and climate events depending on their skill set and property ownership

Changes in these livelihood contexts due to weather and climate events tend to influence livelihood prospects and shape its outcome Households in Robertsport employ several means (livelihood strategies) in pursuit of livelihood outcomes (Krantz-SIDA, 2001) However, inadequate or restricted access to available livelihood assets as a result of environmental or socio-politico factors have the propensity to undermine the achievement of these livelihood outcomes Thus, these livelihoods may become vulnerable (UNDP-IRP, 2009)

It is noteworthy to emphasize that these vulnerable livelihoods have a tendency of livelihood interdependence with one another as is the case with the artisanal fishermen, fish- mongers, processors and traders in Robertsport, Grand cape Mount County (UNDP-IRP, 2009) People residing in rural coastal communities in Liberia are reliant

on fishing activities that are sensitive to climate change Small fishing communities such

as Robertsport, where small-scale fisheries are the main occupation, fishery-based livelihoods are involved in different activities which include fishing, processing, trading and other fisheries related activities such as materials repairs (OECD, 2001)

Coastal floods, coastal storms, result in the death of coastal households, including fishermen or relatives and friends of these fishermen (IPCC, 2007) Some of these deaths have recently been recorded in Robertsport (Richard, 2012) These climate

events and other extremes also cause health complications (Kovats RS, et al, 2003), and

destruction to infrastructure such as housing, health facilities, roads, educational facilities and other fishing implements such as boats, nets, gears as well as landing sites

(Westlund L, et al, 2007;USAID-USDA, 2014) Basic social services in these areas are

often not available or accessible (MRAG & Group, 2011) Early warning systems (for example, technology to inform people on weather and climate situations) and prompt disaster response, if lacking, could expose the livelihood resources of these fisheries reliant communities to severe impacts of weather and climate

There are variations in the levels of impacts on fishery-based livelihoods as a result of weather and climate events Hence, the poor may be heavily affected due to low adaptive capacity (for example land ownership, house ownership, access to loans,

etc) (Roncoli C, et al, 2001), more particularly, fisher folks who are heavily dependent

on the fishery resource (Coulthard, 2008) Coulthard (2008) and Roncoli (2001) further indicated that fishery-based livelihoods are likely to be affected in varied ways

by weather and other climate extremes Therefore, assessing the vulnerability of fishery-based livelihoods to impacts of weather and climate events particularly in Liberia (Robertsport) would require an extensive analysis (Islam et al., 2013)

2.6 Review of climate change using livelihood concepts

According to (Ziervogel, G & Calder, 2003), livelihood analysis concepts have been used as a basis to assess and provide understanding on climate variability and change in Lesotho Furthermore, this concept has been used to understand hurricane

impacts on households in rural Honduras (Morris, S S et al., 2002), agrarian households social vulnerability in Vietnam (Adger, 1999) as well as (Knutsson, et al.,

2006) put it, different vulnerability levels among villages in China (Allison, E H &

Ellis, 2001) enforced that the SLA approach is an important livelihood assessment tool

in fisheries Thus, (Ferrol-Schulte, et al D., 2013) further emphasized that SLA is

effective in assessing fisheries based livelihoods in Tropical coastal communities, to which, Robertsport is of no exception

In this study, the SLA is used as the tool to assess fishery-based livelihoods (FBLs) assets, impact and knowledge and/or perception about climate change and their coping mechanisms The SLA is a bridge that inter-links livelihood assets to households’ livelihood strategies and adaptive capacity

Few research studies have assessed vulnerability and climate change effects in

impoverished communities such as Robertsport for instance (Cheung et al., 2009; Essam M., et al, 2013; Rahman, 2015) However, most studies conducted in Liberia as well as ongoing studies are centered on forestry, agriculture, mining (eg (Wallace, et

al, 2008;LISGIS, 2009;GoL-NHDR, 2009;EPA, 2013) and broad based fisheries

regulation and livelihood analysis of Liberian fisheries While livelihood analysis of Liberian small scale fisheries has been assessed, this assessment excluded weather and climate impacts on these livelihood assets and did not address the threats of climate change faced by fishery-based livelihoods in Liberia Consequently, this research aims

to address the gaps in the assessment of the impacts of weather and other climate extremes on fishery-based livelihoods in Robertsport, Grand Cape Mount County, Liberia

2.7 Data collection and Data analysis tools

The use of both quantitative and qualitative methods is being employed in this research In assessing the vulnerability of FBLs to weather and climate events in Robertsport, this study employed the use of Participatory Research (Rural) Appraisal (PRA) as a tool for household to outline weather and climate hazards that have impacted their livelihood and rank the climate variability/hazards which has impacted them the most Also, household interviews, using questionnaire will be conducted The PRA will include three (3) focus group discussions (FGD) which will see households identifying/outlining climate variabilities or hazards that have impacted their livelihoods both in Kru Beach and Fanti Town separately The third FGD will be to assess HH understanding of the questionnaire

The PRA assessment will be presented by HH using a Pair-wise comparison matrix which allows them to pair each climate variability or hazard with the other and determine which one has the most impact and to identify methods of adaption and their effectiveness The PRA was also used to identify relevant institutions in the fishing communities using institutional analysis using Venn diagram and profiling A pair-wise comparison matrix allows participants in a FGD to compare one item with the other According to (Hibar & Thompson, 2018), a pair-wise comparison matrix is an easy task in which one or two variables should be chosen based on the closeness of some physical or memorable reference This tool relied on household experience of historical experiences to be able to carry on this assessment

Three (3) FGD were held because in the two (2) fishing villages that households were assessed, their locations were different and the thus the impact could vary Furthermore, there existed two (2) groups of households, the local Kru fishermen and the Fanti fishermen from Ghana The questionnaire was used objectively to obtain credible information about weather and climate variability or hazards (Babbie, E and Mouton, 2001) using purposive sampling methods that targeted households depending

on fisheries

In this research, the questionnaire is drawn and modified from previous

publications (Kebe et al., 2009), government documents and pilot exercises at the

study site The questionnaire is designed into seven (7) sections (General information, Sec.(0); Assessment of human capital, Sec (1); Assessment of Social capital, Sec (2); Assessment of Natural capital, sec (3); Assessment of Financial capital, Sec (4); Assessment of physical capital, Sec (5); and Assessment of climate change knowledge/perception)

CHAPTER 3: RESEARCH METHOD

3.1 Focus Group Discussion

In our quest to investigate the vulnerabilities of fishery-based livelihoods to impacts of weather and climate events, a focus group discussion (FGD) was organized

at the study site of Robertsport, Grand Cape Mount County To assess how weather and climate events have impacted the livelihoods resources; knowledge of climate change and the effectiveness of local adaptation measures I employed the participatory research appraisal (PRA) technique

In order to pursue this assessment, PRA methods such as Pair- wise ranking and institutional analysis as approaches were used The FGD was conducted separately in two (2) fishing villages in Robertsport, namely, Fanti Town and Kru Beach This FGD brought together fishermen, fish driers (processors/fish mongers), who are mostly women as well as co-management officers both from the NaFAA and the fisher folks

A Pair-wise ranking is a PRA tool that is used to identify hazards or priorities for comparisons and ranking In the use of the pair-wise ranking, the inhabitants of the two fishing villages’ were gathered in separate groups to list and rank weather and climate events that impacts their livelihood resources, and to identify methods of adaptation and their effectiveness as well as available institutions in their areas of fishing that support or regulate their fishing activities Following the listing of these weather and climate events, we developed a pair-wise matrix of the weather and climate events and asked the fishermen, fish driers (processors) and co-management officers to compare each weather and climate event (figure 3.1)

Figure 3.1: Focus Group Discussion Pair-wise matrix and ranking

Consequently, we counted the appearance of the weather and climate events and created the rank

In the same vein, villagers in the two fishing villages in Robertsport were asked how their livelihood resources impacted as a result of these weather and climate events

as high, moderate, low, and no impact After assessing the impacts of these weather and climate events on the livelihood resources of the fisher folks, participants were asked about what local adaptation measures they use as a means of adapting to the impacts of these weather and climate events The measures were then ranked by the participants of the FGD as most effective, moderately effective or not effective

Institutional analysis was another PRA method used to conduct the FGD in Fanti Town and Kru Beach An institutional analysis approach involves analysis of institutions that impact the livelihood activities of the participants when their livelihood activities are affected by weather and climate events In this venture, participants listed institutions and organizations that they thought impacted their activities This process allowed participants to discuss among themselves and agree on relevant institutions and organizations that affected their activities and to also indicate the levels of importance of these institutions

A Venn diagram was used as a method to outline the significance of the services

of each of these institutions and the degree of significance of their interactions As

such, the arrows of the Venn diagram indicated the significance of the interactions while the size of the circle reflected the significance of the services rendered

3.1.1 First Focus Group Discussion

The first focus group discussion was conducted in the Fanti Town fishing village This FGD brought together 12 persons that included the Fanti Governor, the Town Chief, 1 representative of the Co-management officers, 5 fish processors (dryers/fishmongers) who were all women and 4 fisher men They were gathered with the assistance of the local authorities through the help of the NaFAA local office in the community This group which is situated along the banks of the Lake Piso identified weather and climate events which impacted their livelihood resources The participants were asked how their livelihood resources impacted as a result of these weather and climate events as high, moderate, low, and no impact and what local adaptation measures they use as a means of adapting to the impacts of these weather and climate events Each participant identified local methods of coping with the weather and climate hazards and rated the effectiveness of the measures The livelihood resources that were affected as a result of this weather and climate hazards were also outlined

3.1.2 Second Focus Group Discussion

The second FGD was held in the Kru Beach Fishing village in Robertsport, approximately 45 minutes’ walk from the Fanti Town Fishing village This discussion brought together 13 persons including the Kru Town chief, 1 co-management official representation, 7 fish processors (dryers) who were all women and 4 men All of these persons were selected randomly with the help of the NaFAA and community leadership

to participate in the discussion The Kru Town Beach fishing village is located along the banks of the Atlantic Ocean and the by-mouth of the Lake Piso During the FGD, the participants outlined weather and climate events as well as their hazards which impact their livelihood resources The participants were asked how their livelihood resources impacted as a result of these weather and climate events as high, moderate, low, and no impact and what local adaptation measures they use as a means of adapting

to the impacts of these weather and climate events They identified local adaptation measures for coping with weather and climate hazards They further indicated local livelihood resources that are affected as a result of these weather and climate events

3.1.3 Third Focus Group Discussion

The third FGD was conducted and held in Robertsport with a random selection of

25 persons (10 and 15 persons each) from the two (2) fishing villages (Fanti Town and Kru Beach) This FGD was conducted to test the relevance of the designed questionnaire which was used in the survey The participants were assessed based on the designed questionnaire and their views were gauged to ascertain the relevant application of each of the questions in the survey questionnaire

3.2 QUESTIONNAIRE

As a means of assessing the impact of weather and climate events on based livelihoods resources, fishing community’s knowledge about climate change as well as local adaptation measures for climate change and their effectiveness, we developed a survey questionnaire as a simple tool to evaluate local fisher folks in Robertsport, Grand Cape Mount County

fishery-3.2.1 QUESTIONNAIRE DEVELOPMENT

The questionnaire was developed using qualitative (Perception, impacts, adaptations and effectiveness) and quantitative information (age, income and education level) as a result of interactions with the locals during the focus group discussions in line with the research objectives The questionnaire had three (3) basic parts divided into seven (7) sections so as to address the research objectives The first section of the questionnaire contained general identification information The second section assessed human capital information/assets

The third section assessed social capital and the fourth section assessed natural capital/assets The fifth section of the questionnaire investigated financial capital /assets while the sixth section investigated physical capital/assets The seventh section

of the questionnaire assessed FBL’s climate change knowledge/perception, adaptation and effectiveness

3.2.2 MODIFICATION/FINALIZATION OF QUESTIONNAIRE

Once developed, the questionnaire was tested in a pre-survey technique at the study site to test its relevance and simplicity Twenty-five persons were selected randomly both from the two (2) fishing villages during this process This process was