The impact of climate change on wetland resources along lake wamala, mityana district, uganda

Table 4-1: Percentage of respondents for each area………..22 Table 4-2: Relative Proportion of the impact of climate change on livelihood………27 Table 4-3: Relative Proportion of the impact

MINISTRY OF EDUCATION AND TRAINING

NHA TRANG UNIVERSITY

MINISTRY OF EDUCATION AND TRAINING

NHA TRANG UNIVERSITY

BAKER MATOVU THE IMPACT OF CLIMATE CHANGE ON WETLAND RESOURCES ALONG LAKE WAMALA, MITYANA DISTRICT, UGANDA

MASTER THESIS

KHANH HOA-2018

Management and Climate Change Code:

Topic Allocation Decision

Decision on establishing the

Committee:

Defense Date:

Supervisors:

1 Dr Nghia Ngo Dang

2 Dr Pradeep Kumara Terney

Chairman of the Committee:

Faculty of Graduate Studies:

ACKNOWLEDGEMENT

I would like to express the deepest appreciation NORAD/NORHED Project in conjunction with Nha Trang University for helping and giving me the best platform and conditions to write and finish my studies and Master’s thesis

Special thanks go to Dr Nghia Ngo Dang and Dr Pradeep Terney Kumara for not only supervising my research but also the continuous support during my study, patience, motivation, enthusiasm, immense knowledge and insights you gave me I must say it was

a cornerstone in polishing up my thesis and developing new ideas that made this work a fruition

Special gratitude to my academic mentors and counselors notably; Dr Jerome Sebadduka Lugumira of Washington, USA, Thomas Russell Cummins of Calgary, Canada and Russ Harvey; I am always indebted to you as you have been the drivers of this journey to date

I hope I have not disappointed you

Lastly but not least, I would like to thank my family; my parents, brothers and sisters and relatives for the financial, moral and spiritual support in all my endeavors even during the times of trial I have to assure you that I hope to reciprocate such selflessness

DATE: …… /………… /…………

SIGNATURE: ………

Matovu Baker

Contents

CHAPTER ONE: INTRODUCTION 1

1.2 Statement of the problem 5

1.3 Justification of the study 6

1.4 Objectives 6

1.4.1 Overall objective 6

1.4.2 Specific Objectives 7

CHAPTER TWO: LITERATURE REVIEW 8

2.1 Climate Change/Global Warming and Manifestation 8

2.2 Uganda and climate change vulnerability 12

2.3 Lake Wamala, changes in wetland resources and its surrounding environment 14

CHAPTER THREE 15

3.0 Research Methods and Materials 15

3.1 Study Area 15

3.2 Study methods 17

3.3 Study Design 18

3.3 Data Acquisition 19

3.4 Data synthesis and Analysis 20

3.4.1 Temperature 20

3.4.2 Rainfall 20

3.4.3 Water Balance changes 20

CHAPTER FOUR: RESULTS 21

4.1 Demographic Characteristics of Households 21

4.2 Local Communities’ Perception on Climate Change 23

4.3 Water Level changes 24

4.4 Climate Variability and Livelihood 24

4.5 Climate change and wetland resources 25

4.6 General causes of wetland resource loss 26

4.7 Main Risks associated with wetland resource loss 28

4.8 Mitigation and Adaptation measures 28

4.8.1 Local Communities Adaptation 28

4.8.2 Government interventions or adaptation strategies 30

CHAPTER FIVE: DISCUSSION 32

5.1 Climate Trend Analysis and Perception 32

5.1.1 Impact of climate change on wetland resources 32

5.2 Climate variability and livelihoods .35

5.3 Climate Variability and wetland resources 36

5.4 Causes of Wetland Resources Loss 37

5.5 Risks associated with illicit wetland resource degradation and loss 38

5.6 Mitigation and Adaptation Strategies 39

5.7 Relationship between Lake Wamala’s Demographic Characteristics and Climate change adaptation 41

CHAPTER SIX: CONCLUSIONS AND RECOMMENDATIONS 44

6.1 Conclusions 44

6.2 Recommendations 45

Implementation plan and estimated budget .48

REFERENCES 49

Appendices 66

Appendix 1 Semi structured questionnaire for data collection 66

Appendix 2 Data entry and analysis format 74

Appendix 3 Selected Demographic Characteristics of Uganda 74

Appendix 4 Annual minimum and maximum Temperatures (OC) extracted from Mubende Station, data from 1990-2012 75

Appendix 5 Annual Rainfall pattern (mm) recorded at Mubende Weather Station around Lake Wamala, 1990-2011 76

Appendix 6 Monthly Average Rainfall (mm) for Mubende Weather Station near Lake Wamala, 1990-2012 77

Appendix 7 Decadal average temperature (OC) from Mubende Station around Lake Wamala, 1990-2012 77

Appendix 8 Historical Monthly Temperature (OC) variations for Mityana District 77

Appendix 9 Annual mean minimum and mean maximum temperature anomalies (OC) time series analysis for Mubende weather station near Lake Wamala 1990-2012 78 Appendix 10 Annual average rainfall anomalies (mm) and Standard

Precipitation Indexes (SPI) for Mubende Weather Station near Lake

Wamala from 1990-2012 79 Appendix 11 Relative proportion of gender in the study areas around Lake Wamala 80 Appendix 12 Relative percentage of marital status of the sampled

respondents around Lake Wamala 80 Appendix 13 Relative Proportion of the education level of the respondents around Lake Wamala 81 Appendix 15 Relative proportion of community adaptation strategies in each sampled zone around Lake Wamala 82 Appendix 16 Relative proportion of government strategies to mitigate and adapt to climate change in each specific zone around Lake Wamala 83

LIST OF ACRONYMS

COP: Conference of Parties

CPUE: Catch per Unit Effort

FAO: Food and Agriculture Organization

GHGs: Green House Gases

GNF: Global Nature Fund

GoU: Government of Uganda

ICBD: Increased Cost of Doing Business

INC: Intergovernmental Negotiating Committee

IPCC: Intergovernmental Panel on Climate Change

IUCN: International Union for the Conservation of Nature

KEA: Kikandwa Environmental Association

LVFO: Lake Victoria Fisheries Organization

MAAIF: Ministry of Agriculture, Animal Husbandry and Fisheries MWE: Ministry of Water and Environment

NaFIRRI: National Fisheries Resources Research Institute

NAPA: National Adaptation Program for Action

NEMA: National Environment Management Authority

NWP: National Wetlands Program

SPI: Standard Precipitation Index

UBOS: Uganda Bureau of Statistics

UNDP: United Nations Development Program

UNEP: United Nations Environment Program

UNFCCC: United Nations Framework Convention on Climate Change USAID: United States Agency for International Development

WMD: Wetlands Management Department

LIST OF TABLES

Table 4-1: Percentage of respondents for each area……… 22

Table 4-2: Relative Proportion of the impact of climate change on livelihood………27

Table 4-3: Relative Proportion of the impact of climate change on specific area wetland resources………29

Table 4-4 Relationship between wetland resource losses on livelihoods due to climate change….……… 29 Table 4-5: Proportion of community adaptation strategies………33

Table 4-6 Proportion of critical areas in need of government support for adaptation……34

Table 4-7 Proportion of critical occupations in need of government support for adaptation……… 35

LIST OF FIGURES/GRAPHS

Figure 2-1: Current and Projected Temperature changes in Uganda……….…13

Figure 3-1: Spatial extent of Lake Wamala and the sampled villages ………17

Figure 3-2: Climate change impact assessment……… 18

Figure 4-1: Relative Percentage of households in the sampled areas……… 22

Figure 4-2: Relative proportion of community occupation (s) in the sampled areas… 23

Figure 4-3: Relative percentage of local people perception on climate change……….24

Figure 4-4: Frequency of wet and dry months along Lake Wamala………25

Figure 4-5: SPI Series assessing the drought occurrence in relation to the probability of observed total annual rainfall changing from average………25

Figure 4-6: Relationship between Lake Depth and inter-decadal annual rainfall……….26

Figure 4-7: Impact of climate change on community occupation……… ….27

Figure 4-8: Relative proportion of the effect of climate change on wetland resources…28 Figure 4-9: Relative proportion of the causes of increased wetland resources loss… 30

Figure 4-10: Relative proportion of the risks associated with climate change on local communities……… 31

Figure 4-11: Relative impact of climate vagaries on specific occupation……….32

Figure 4-12: Proportion of community adaptation strategies……… 33

Figure 4-13: Relative proportion of government strategies to help local communities’ adaptation and mitigation……… 35

Figure 5-1: Lake Wamala and its changing spatial extent……… 37

Figure 5-2: Variations in Lake Wamala Water Levels……… 38

Figure 5-3: Exposed Water gauges due to reducing water level……… 39

Figure 5-4: Exposed Lacustrine swamp beds due to drought……….41

Figure 5-5: Inter-relationship and alternative strategies for sustainable wetland resource management and livelihood ………48

LIST OF APPENDICES

Appendix 1 A semi-structured questionnaire for data collection………72

Appendix 2 Data entry and data analysis sheet and format……….81

Appendix 3 Selected demographic characteristics of Uganda………82

Appendix 4 Annual minimum and maximum Temperatures (OC) extracted from Mubende Station, data from 1990-2012……… 83

Appendix 5 Annual Rainfall pattern (mm) recorded at Mubende Weather Station around Lake Wamala, 1990-2011……… 84

Appendix 6 Monthly Average Rainfall (mm) for Mubende Weather Station near Lake Wamala, 1990-2012……….84

Appendix 7 Decadal average temperature (OC) from Mubende Station around Lake Wamala, 1990-2012……….…84

Appendix 8 Historical Monthly Temperature (OC) changes for Mityana District…… 85

Appendix 9 Annual mean minimum and mean maximum temperature change (OC) time series analysis for Mubende weather station near Lake Wamala from 1990-2012…….86

Appendix 10 Annual average rainfall changes (mm) and Standard Precipitation Indexes (SPI) for Mubende Weather Station near Lake Wamala from 1990-2012……… 87

Appendix 11 Relative proportion of gender in the study areas around Lake Wamala…88

Appendix 12 Relative percentage of marital status of the sampled respondents around Lake Wamala………88

Appendix 13 Relative Proportion of the education level of the respondents around Lake Wamala………89

Appendix 14 Relative percentage of the impact of climate change on wetland resources around Lake Wamala……… 89

Appendix 15 Relative proportion of community adaptation strategies in each sampled zone around Lake Wamala……….90

Appendix 16 Relative proportion of government strategies to mitigate and adapt to

climate change in each specific zone around Lake Wamala……… 90

Appendix 17: Annual rainfall trends around Lake Wamala……… 92

Appendix 18: Inter-decadal changes in temperature around Lake Wamala………… 92

Appendix 19: Selected Demographic characteristics of Mityana district……… 93

Appendix 20: Mityana District sub-counties demographic statistics……… 94

Appendix 21: Mityana District; counties and sub-counties………95

ABSTRACT

It is common knowledge that global coastal wetlands are critical natural resource zones that avail many benefits to threshold environs and local communities However, wetlands are facing catastrophic degradation severely putting at risk their noteworthy ecological goods and services that determine human functions Surprisingly, the underlying causes

of such appear subjective! The coastal wetland zones of Lake Wamala are experiencing a noticeable shoreline retreat that has led to loss of wetland resources This henceforth calls for sustainable wetlands resource management by clearly dissecting and understanding the prime cause of such losses This research used community based participatory surveys/interviews to capture individual stakeholder perceptions and knowledge on wetland resources, what causes their degradation, impacts and mitigation strategies in order to assess areas of consensus and diverging interests amongst stakeholders to develop feasible and sustainable management options The research focused on 6 local areas along Lake Wamala to generate information on the impact of climate change on wetland resources Results point out that increased climate change and some anthropogenic drivers have grossly affected wetland resources and livelihoods The study also highlights that there is a disjointed and ineffective framework to cope up or mitigate risks from wetland resource loss This calls for immediate and comprehensive remediation strategies such as co-management, developing of shared management and interests through local community and government partnership and collaboration in line with practical national frameworks so as to boost awareness and knowledge sharing on the ecological-human benefits of wetlands in the face of climate change

CHAPTER ONE: INTRODUCTION

1.1 Introduction to the study

Currently, there is increasing consensus that climatic change poses a great challenge not only to livelihoods but also wetland resources’ conservation, management and restoration (Erwin, 2009), both at local, regional and macro mega-watershed levels and surrounding environments (Wheeler, 2013) This has made global climate change models and projections regard anthropogenic drivers as the main threat to the removal

of species, integrity and interlinks of ecosystems both marine and terrestrial (Hulme, 2005) This is irrespective of the fact that habitat responses to different stressors vary

at various levels It’s apparent that the increasing temperatures for instance will affect coastal wetland biota due to changes in rainfall and sea level especially in the tropics (Day et al, 2005) Despite the existence of literature on wetland resources, ecological niches and their interdependence with climate conditions, wetland responses to climate change is still poorly understood as most climate change impact models focus

on anthropogenic stressors (Clair et al., 1997) The critical role and functioning of such ecosystems is inaccurately and minutely predicted in case of extreme climate change scenarios; making it prevalent to assess the relationship by which climate changes affect wetland resources (McAllister , 1997) The Inter-Governmental Panel

on Climate Change (IPCC, 2014)and Conference Of Parties (IPCC, 2013) highlight the urgency at which such ecosystems are likely to be threatened This has coincided with a significant degradation of marine and fresh water resources and biota with far-reaching impacts on ecosystem functioning, human health and welfare(IPCC, 2007) Though historical natural variability has made species and biota adapt to such evolutionary patterns (Harley and Miner, 2006), current trends project high level proximal impacts which could adversely alter feedback cycles making the future of wetland resources and ecosystems precisely difficult to predict (Larsen, 2005) The simulated linear temperature trend (1905-2005) of 0.74oC (0.56-0.92) is two times larger than that of the past century (1800-1900) which threatens ecosystems, atmospheric functioning and human livelihoods (IPCC, 2007)

Current climate change projections predict an increase in temperature by 1.5-2oC and

no doubt, increasing temperature and precipitation changes are increasingly

considered as the main threats to wetland functioning and distribution (Ludena et al.,

2015) This means that components of wetlands that are resources for human consumption directly or indirectly are at risk as they provide water for drinking, fish, fruits, weaving and thatching raw materials, peat and fuel wood as their availability relies on the health of wetland ecosystems (Abila, 2002) Statistics estimate that wetland resources (goods and services) are valued at 15.5 trillion USD/year (Costanza

R., 1997)

However, current trends in wetland cover and degradation and the less attention given

to wetlands has availed impetus and a decisive knock-down effect to increasing vulnerability of wetland resources and communities therein to adverse climate change impacts (Abila, 2002) This sporadic loss is likely to accelerate global terrestrial carbon as wetlands will not be able to sequence and absorb the previous range of 10-20% of the sequential cycle (Sahagian, 1998) as well as the sustainable continuity of living earths systems (IPCC, 2014) The main parameters that have been identified as great drivers of climate change are temperature and precipitation (especially rainfall) variations such as in the tropics (Shresta et al., 1999)as such parameters speed up natural/environmental losses to biota, water and vegetation (Harley, 2006) This has not only increased socio-economic losses but also the frequency of natural disasters along coastal and shoreline zones The sporadic temperature increase has not only affected micro-climate dynamics and increasing risks to local community livelihood but also ecosystems therein like wetlands Johnson et al (2005) anecdotes that,

“Current and future climate changes will affect wetlands in two fundamental ways: the number of functioning wetlands (and their functional capacity) within most eco- regions will decline and the geographic location of certain types of wetlands will shift.’’

This is in tandem with simulations and studies around Lake Wamala that showcase a gradual shift in lake waters and surrounding wetlands by about 80 meters since 1960’s (Musinguzi et al., 2016) The semi-permanent wetlands in such coastal/shore land

zones function based on water levels and any increase in temperature will likely lead

to water loss, vegetation and peat land loss as well as the living species like mudfish (Wiles, 2005) The losses are projected to be indifferent across the spectrum of resources depending on spatial location and adaptability (Root et al., 2003) Some areas are likely to experience positive temperature and precipitation shifts than others which will also determine the quality and quantity of wetland resources (Day et al., 2005) depending on the type of wetland based on the Ramsar categorization (Ramsar, 1971) Irrespective of the spatial extent of the impact, it’s apparent that climate change will affect wetland resources especially in the developing world where adaptation is low Coincidentally, most research and literature subjectively considers anthropogenic aspects as the main drivers of coastal wetland loss (Seguin et al., 2006)

The United Nations Framework Convention on Climate Change Report (UNFCCC,

2010) relates climate change directly or indirectly to anthropogenic activities that alter the composition of the global atmosphere The vulnerability of coastal zones and resources to climate change is accelerated by human populations therein that increases exposure and sensitivity (Ludena et al., 2015) especially in areas below 1-1.5 meters from the shorelines (Fussel, 2010)

Despite the long held belief and literature relating extreme wetland resource loss to anthropogenic factors, recent analysis indicates that climate change parameters are the most likely threats to wetland resource losses (Fischer, 2016) Ecological effects on coastal ecological systems are increasingly apparent due to climate change This is

highlighted by several literature that;

“Changes in climate will lead to the intensification of the global hydrological cycle,

shifts in the geological distribution of wetlands, altered tidal ranges in bays and estuaries, changes in sediment and nutrition transport, increased coastal flooding and

in turn increased vulnerability of some coastal populations” (IPCC, 2014)

This means that though there is increasing understanding of wetland management systems, such systems will be impractical without taking into account climate change Today, developing countries are more vulnerable to climate change especially in rural areas of Uganda due to few alternative activities and adaptation strategies

(Environmental Alert, 2010) Local communities and people are at a face-off with the direct impacts of climate change, owing to their reliance upon and close relationship with the environment and its resources that exacerbates the difficulties already faced

by vulnerable communities (UN Permanent Forum on Indigenous Issues, 2007)

This is commensurate with the Ugandan scenario that coincides with increased vulnerability of ecosystems and livelihoods due to climate change The (USAID,

2012) report for the past 35-25 years highlights that the magnitude of observed

warming since 1980’s is large and unprecedented indicating a 2+ deviation from the past climate norm This is in tandem with the (National Wetlands Program, 2008) report that observed a fall in rainfall totals from 1960-2009 and a projected increase in temperature by 1-1.5oC; with devastating impacts on uni-modal rainfall distribution of less than -150 to -50 mm between 2010-2039 across the country and this is projected

to increase the mean temperatures between 1-3.1oC by 2060 The (USAID, 2012)

report acknowledges that changes in climate have increased on vulnerability of environmental resources and livelihoods This has not only increased on catastrophic hazardous events like flash floods, landslides, and decline in water levels but also affected wetland cover and resources therein Since 1994, Uganda has lost about 11,268 square kilometers of wetlands down from 37,575 square kilometers-a 15% decrease of the nation’s land area (199,810 square kilometers) to about 26,308 square kilometers in 2009,(Turyahabwe et al., 2013) representing a 30% loss in wetland

cover (WMD, 2009) Recent studies about wetland loss and perception to change in

Uganda indicate a correlation between wetland resource loss and associated risks and hazards to climate change (UNDP/UNEP, 2009)

Around lake Wamala, the unpredictable climate changes manifested by precipitation shifts, floods, and drought have coincided with increase in floating vegetation, decrease in fish stocks, size and quantity, increase in wetland fires, reduction in sea level and seasonal drying and flooding of swamplands like in Magongolo, Nkonya and Naama villages (NEMA, 2013) Since 1990, about 80 meters of Lake Wamala coastal waters have been lost due to progressive drying (Global Nature Fund, 2013) and despite the historical perceptions about the lake retreats and advances in water

levels, the lake and resources therein might be lost if current climate change scenarios are not mitigated (National Wetlands Program, 2008) It’s upon this background that the study will identify the impact of climate change parameters especially rainfall and temperature variations on coastal wetland resources around lake Wamala, identify the causes and associated impacts so as to come up with coping and mitigating measures that tame such impacts that devastate the already fragile resources and local communities therein This is also based on the fact that there are limited vulnerability assessments done in Uganda and around lake Wamala to communicate urgent and immediate adaptation interventions necessary to mitigate adverse effects of climate

change (Twinomugisha, 2005)

1.2 Statement of the problem

Currently, it is no longer theoretical that the impacts of climate change are the pinnacle to the increase in ecosystem and livelihood vulnerability and if the trend continues unabated, most resources are predicted to become extinct Unfortunately, most current literature and scientific researches focus on predictions of impacts at a macro-level ignoring micro-levels where most resources and livelihoods are more prone to risks of climate change due to their direct reliance on local resources especially in environmentally sensitive areas for survival Conversely, though some eco-assessment research has been carried out around Lake Wamala; most of the reports focus on people’s perception, water and food security in relation to climate change This has made it imperative to interlink climate change impacts to coastal wetland resources as most local communities therein rely directly or indirectly on wetland resources around the lake for their livelihood

Global studies and reports underline the impact of anthropogenic drivers in increasing greenhouse gas concentrations that scale up environmental disasters which has expectedly increased the cost of natural disasters with a 15 fold increase from 1950-

1990’s (IFRC, 2001) However, this analysis practically ignores the direct impact of

climate change on coastal resources that greatly determine human activity and welfare hence creating an avenue for more insightful local community research to synthesize the impact of climate change on coastal wetland resources onto which local

communities derive livelihood to foster feasible discussions that try to reduce vulnerability and usher in adaptive and mitigating measures for sustainable socio-environment management

This is envisaged from the fact that climate change is a complex phenomenon that highly impacts local ecosystems and livelihoods This avails a pivot upon which research on coastal wetland resources loss can be undertaken to reduce on impacts accruing from climate change like: increasing temperatures, rainfall reduction and variability, flooding, sea level changes, and coastal wetland sedimentation that have adverse impacts on wetland health and peoples livelihoods This is evidenced in this footage http://www.worldbank.org/en/news/video/2014/03/04 The changing ecosystem in Lake Wamala has been classified as one of the climate change hotspots

in Africa (UNEP, 2009)

1.3 Justification of the study

Wetland resources and habitats are a prime source of livelihood to coastal communities (Armitage, 2017); however, changing climate and its variability in Uganda is currently affecting the availability of wetland resources where people derive income and sustenance (Sewagudde, 2009) This dilemma forms part of this thesis on the impact of climate change on wetland resources and specifically examines how such changes have affected local livelihoods along Lake Wamala The information from this study will act as a benchmark for devising strategies to cope up with climate change along coastal areas of closed inland water bodies such as Lake Wamala This will help in guiding local, regional, national and international policy makers in clearly devising strategies that promote sustainable wetland resource management and climate change adaptation

1.4 Objectives

1.4.1 Overall objective

• The general objective of the study was to examine the impact of climate change

on wetland resources and livelihoods along Lake Wamala in Mityana District, Uganda

CHAPTER TWO: LITERATURE REVIEW

Most climate change impact scientific research reports and studies on ecosystems focus on anthropogenic drivers to such change This fosters the need to continuously synthesize climate change analyses to relay its impact on coastal wetland resources that are a home to several vulnerable ecosystems as well as human beings and their livelihood

2.1 Climate Change/Global Warming and Manifestation

Though there is consensus about global warming, the definition of climate change, its frequency and magnitude and perception varies

The United Nations Framework Convention on Climate Change (UNFCCC, 2010) defines climate change as:

‘The change in climate attributed directly and indirectly to human activity that alters the composition of global atmosphere and which is in addition to natural variability, observed over comparable time periods’

To highlight the urgency of climate change and its threats, UNFCCC in partnership with the Intergovernmental Negotiating Committee (INC) in 1992 adopted the need to mitigate climate change as a priority stipulated in Article 1 of the convention

(Twinomugisha, 2005) Though the definition mainly highlights anthropogenic drivers

as the main pivot to climate vagaries, there is increasing oversight that climate change represents significant variation in micro and macro weather patterns and variability maybe due to natural processes or drivers that alter the functioning of the atmospheric

and terrestrial land-use patterns (IPCC, 2001); (Sharma, 2009)

Current global temperatures are increasing at an estimated rate of 0.30C to 0.60C since the late 1800’s and it has sporadically increased since the 1960’s by about 0.20C to 0.30C (Xiaodong & Baode, 2000) making the sustainability of ecosystems and livelihoods more vulnerable

Current literature acknowledges that there is and has been unprecedented warming since the 1950’s (IPCC, 2014) with current estimates being nearly 0.4-0.80C than the last century and current projections predict that there is a likely increase by a further

1.50C and highs of over 40C in some areas (USAID, 2012) This warming has implications on several additional abiotic variables for example ocean expansion and sedimentation in fresh water areas as warming trends are predicted to be stronger over continental interiors than over the oceans; that will increase pressure gradients (Harley and Miner, 2006)

This corroborated by the observed increase in global temperature due to increase in greenhouse gas emission and concentrations from 280 Parts Per Million (PPM) in 1850’s to 379 PPM and if current carbon emissions continue unabated, emissions might reach 970 PPM by 2100 This concern is highlighted in the Kyoto Protocol accord (2005) that urges countries to reduce GHGs to 5.2% or less to achieve sustainable development (UNFCCC, 2007) This outcry is supported by a myriad of studies that draw conclusions that climate change sensitivity indices indicate a remarkable increase in temperature and negative and uncertain precipitation variations (Ludena et al., 2015) and summarize that poor countries are more vulnerable than developing countries (Tol et al, 2002) though some literature predicts drastic outcomes that developed countries might be more vulnerable and sensitive to climate variability than developing countries in terms of inherent resistance to damage and other calibration parameters like along the East Coast of USA (Diffenbaugh et al., 2007) Irrespective of the extent and magnitude of change, its prevalent that climate change will have drastic impacts on the earth’s systems and the impact of global warming is widespread (Meehl et al., 2005) These effects; though they might vary in distribution and abundance over space and time, are having and will continuously have great effects on human populations, environmental resources and communities (Harley, 2006) Some of the implications include sea level change, increased atmospheric carbon concentrations, loss of marine and terrestrial ecosystems and potential changes in the biogeochemical feedback cycles of organisms (IPCC, 2001, Larsen, 2005) The potential impacts of climate change on wetland resources are drastic as wetlands avail critical values that aid sustainable development (Bergkamp and Orlando, 1999) Wetland resources perform a myriad of ecosystem functions in form of goods and services that satisfy human needs(De Groot, 1992) These services are grouped as: regulation, provision of habitats, production and provision of

information (Bergkamp, 1999) Maintaining wetlands and capitalizing on such values can be a valuable incentive and alternative to disruption activities that degrade wetlands and ecosystems (Costanza, 1997) Unfortunately, climate change and its impacts will degrade such services and goods as they hamper with waterfowl that are dependent on wetlands, habitats therein and desertification processes irrespective of the fact that such projections have some degree of uncertainty (Frederick, 1997) The ability of wetland ecosystems to adapt will be highly reliant on the rate and extent of changes in precipitation, evaporation, run off, as well as the intensity and frequency of events like droughts, fires, floods and sedimentation (Murkin et al, 1997)

Continuous changes in climate are off-setting and are likely to off-set increased risks, and hazards making people and resources therein more vulnerable The conceptualization of vulnerability to climate change is controversial making its description difficult

Watson (1996) relates vulnerability to the extent to which climate change may damage

a system (its sensitivity) and its ability to cope with new conditions On the contrary, (Cutter et al, 2000) identify a three (3) factor typology to highlight vulnerability including: risk of exposure to hazards, capability for social response and attributes of places including geo-location Nevertheless, consensus exists that vulnerability is a function of exposure, sensitivity and adaptive capacity of a system to climate change and its associated threats Future vulnerability will not only depend on climate change but also the type of development path of a given country that must be commensurate with sustainable development to minimize negative environmental impact and socio-economic lifestyles

The UN Permanent Forum on International Issues Report (2007) reports that climate change is a function of:

• Exposure to climate vulnerability and change; which refers to the degree of climate vulnerability and change that an entity (country, community, individual

or ecosystem) experiences like temperature rise vis-à-vis drought

• Sensitivity to climate shocks and stresses; which are an assessment of the amount of impact climate factors have on an entity like land-use and geographical conditions

• Adaptive capacity, which describes the ability of the entity to manage the negative impacts and take advantage of any opportunity that, arises Adaptive capacity depends on physical resources, access to technology and information, varieties of infrastructure, institutional capacity and capability and the distribution of resources (Tol, 2007)

The above tenets underscore the focus of UNFCCC (2002) that tries to identify the most vulnerable countries to climate change (Yohe, 2002) Article 17 of the Marrakesh accords concludes that most countries are now vulnerable to climate changes and this calls for adaptive capacity

This principle envisions the development of practical models and measures to avert the diverse and adverse impacts of climate change and has led to the development and formulation of scientific tools to address broad implications of land surface interactions within the climate system for policy making However, despite such tools, some micro and extensive adaptation options are not still fully understood (IPCC, 2006), despite the fact that adaptation and mitigation can reduce vulnerability In fact, current observations correlate that climate changes are likely to off-set uncommon losses in terrestrial wetland resources(Kates, 2000)

Climate change is one of the main natural challenges today especially in the developing economies in Africa and Asia (IPCC, 2014) Most recent studies in open water lakes and main water bodies in Africa have indicated increased warming of lakes such as Lake Victoria and Albert in Uganda (Sitoki et al.2010) However, most

of the study focus was on the physiology and chemical conditions of such lakes for example circulation dynamics, nutrient loading and recycling and less on wetland resources such as fishes The fact that climate elements especially rainfall and temperature change lead to alteration of the physical-chemical dynamics of freshwater lake ecosystems means that such changes can influence aquatic life and habitats, productivity, and fishes with their related characteristics (Badjeck et al 2009)

Several studies on Ugandan lakes such as Victoria have concluded that ecosystem productivity and wetland resource abundance/change is directly correlated to changes

in climate conditions For instance, a recession in water levels on Lake Wamala has coincided with a fall in fish yield (Musinguzi et al 2015) Life- history of fishes and wetland ecosystems directly interacts with environmental-ecosystem parameters implying that the size and age of wetland resources and species is correlated with temperature (Robertson et al 2005) Increase in temperature increases on feeding and metabolic demands of wetland ecosystems such as fishes implying that low food availability reduces fish growth (Cochrane et al 2009) This means that rising temperatures directly and indirectly determine fish yield especially in small water bodies (Armitage et al 2017) In the Mekong Delta, increased discharge with increased flooding has boosted the growth of some species though it is associated with death and suffocation of young fish (Perry and Barange, 2009) However, this will depend on how a given fish adapts to such changes For instance, less adaptive species might disappear well as fishes adaptive to oxygen deficiencies will thrive (Allison et

al 2007)

2.2 Uganda and climate change vulnerability

The country’s capacity to adapt to climate change; its related risks, hazards and stress

is a function of its wealth, resources and governance direction (Kates, 2000) This is related to how a country manages catastrophic events like landslides, floods, ecosystem losses among others To assess and determine such concerns, it’s prudent to understand micro-scale dynamics to assess variability in natural phenomenon and vulnerability (Tunner, 2003) Uganda; being a small land locked country with varied geo-physical environments and climate conditions, avails a ripe basic foundation onto which research by which climate change has impacted coastal wetland resources can

be done This is envisaged from the fact that climate patterns in Uganda are sporadically changing due to global warming drastically affecting freshwater and wetland resources onto which most local people derive livelihood

In each decade since 1950, the average minimum and maximum temperatures in Uganda have been increasing creating extreme torrential rainfall accentuated with

floods, severe droughts, receding water levels in rivers and lakes, receding ice caps on Mountain Ruwenzori and increasing incidences of malaria in places such as Kabale where it was not prevalent before (Environmental Alert, 2010) It’s estimated that the 1975-2009 warming has been more than 0.8 degrees Celsius for Uganda during both the march-June and June-September rainy seasons (USAID, 2012) This represents a 1.5 degree Celsius increase across the country with typical rates of warming around 0.2 degrees Celsius per decade (Environmental Alert, 2012) This is projected to amplify the impact of decreasing rainfall and periodic droughts with a significant impact on food resources and environmental assets

Figure 2.1 Observed inter-decadal temperature changes in Uganda

Source: USAID, 2012

Climate change is likely to have off-putting effects on economic growth despite the fact that Uganda has made strides in macro-economic stability and social conditions (Twinomugisha, 2005) The government underlines that socio-economic transformation can be achieved with enabling environment conditions (Environmental Alert, 2010), and this is envisaged from the fact that Uganda is ranked among the Highly Indebted Poor Countries (UNDP/UNEP, 2009) Such a gap makes local people and communities apparently more vulnerable to climate change due to low adaptive capacity, access to information and knowledge to cope with the adverse impacts of such changes

With such overt prospective and perceived risks, adaptation to climate change is imperative in Uganda and action has to be taken to sustainably utilize and manage constrained resources like coastal wetland resources Currently, Uganda has developed and inventory of GHGs; to mitigate GHG emissions at national level but there is still a lacuna in vulnerability assessments especially in wetland resources (Twinomugisha, 2005) This creates an avenue to adapt and adopt non-structural measures that are not only feasible but also cost effective in building livelihood capacity to disaster preparedness and resource management These measures include:

developing land-use zoning policies, developing updated vulnerability maps, training, participatory rural approaches, public awareness, development of early warning systems and others

This makes it imperative to study the impact of climate change on coastal wetland resources around important lakes and basins as most people in Uganda directly or indirectly rely on resources therein for survival (UNEP, 2013) Though the overall value of coastal wetlands has not been quantified, the purification function of wetlands like Nakivubo along lake Victoria is estimated at 1.3 million US dollars per year (Emerton&Malinga, 1999) with increasing valuation arising from water treatment, cultivation, papyrus harvesting, brick making, fish farming and artisanal fishing, creating a potential total economic value at 1.56 million US dollars per year (Ministry of Finance, 2008) In rural areas like Naama and Nkonya, wetland resources along rivers and lakes are estimated to contribute 200 US dollars each year towards household income (WID/IUCN, 2005)

2.3 Lake Wamala, changes in wetland resources and its surrounding environment The history of Lake Wamala anecdotes that the lake was a biodiversity hotspot with variety of fish species such as African catfish, and Haplochromines (Okaronon, 1989)

In 1960s, there was restocking of the Lake with 3 species of tilapia such as Nile

Tilapia, Tilapia zillii and Oreochromis leucosticus which boosted stocks and

production (NaFIRRI/NARO, 2016) However, since the late 1990s, fishery stocks started to decline in size and length (Kimbowa & Kaganga, 2011) reducing the commercial value of stocks (MAAIF, 2014) This was partly due to climate variability

as a result of increase in temperature, drying out of swamps due to drought that led to low water levels and increase in the number of fishers and resource users by 50% by

2005 (GoU, 2008) and dominance of catfish that efficiently adapted to the increasing temperatures in adjacent wetlands despite the fall in water levels (Goulden, 2006)

Lake Wamala has gradually been experiencing variations in water levels and resources therein but current trends are alarming that the Lake is designated as ‘a climate change hotspot (UNDP/UNEP, 2009) Despite initially covering 250 km2 , the surface area of the Lake reduced by half due to increasing temperatures from 1980’s

to 1990s (Uganda Wetlands Atlas, 2016) By 2012, formerly submerged coastal land was exposed-a sign of receding water levels partly accounted for by increase in temperature and evaporation in lieu of water gain (Sewagudde, 2009) With the current global and national climate change projections, it is projected that such a paradox will increase furthering a decline in water levels, wetland resources and ecosystem loss affecting livelihoods (USAID, 2012) This is because most of the coastal communities around Lake Wamala are demographically and socially poor, unemployed with relatively low levels of education which characteristics partly impact the level of adaptation to climate change (Branch et al 2002) Education and awareness increases information access, utilization of information and easy adaptation

to new technologies (Armitage et al 2017) This analysis exposes a gap and avails a platform for academic inquiry that; what is the impact of climate change on wetland resources? Are local people vulnerable to such changes and what can they do to adapt and mitigate such changes? This study therefore tried to examine the impact of climate vagaries to create a foundation for the understanding of how wetland resources are affected and what impacts has it caused on local communities so as to devise appropriate strategies to manage such climate change

Kibimba and it surrounded by swamp vegetation like papyrus, ambatch trees and Hippo grass with peat soils (Okaronon, 1989) The lake has undergone periods of alternating water levels In the 1960s, it covered 250 km2 with a wetland zone of 60km2 and a maximum depth of 4.5 meters though this area reduced to a half by 1999; partly due to climate vagaries (GoU, 2008) The lake has continuously shrunk since

1995 irrespective of the fact that there is minimum obstruction in the water of the lake-a pattern which partly explains that variations in climate patterns accounts for the changes in the physiology of Lake Wamala

Lake Wamala in Mityana covers two counties-Mityana Municipality and Busujju; where Naama and Nkonya coastal sites are found in Busimbi Division, Mityana Town

in Central Division, Buzibazi and Lusalira areas are found in Banda sub-county and

Mpongo village in Maanyi Sub-County (UBOS, 2016) (Appendix 21) The local

communities in such areas have distinct demographic characteristic both at household

and zonal level (See Appendix 19, 20)

Figure 3-1 Spatial Extent of Lake Wamala and the main villages/landing sites

3.2 Study methods

The research used both quantitative and qualitative methods focusing on the Climate Change Vulnerability Assessment paradigm (Desanker and Nasef, 2003); where existing scientific data as well as local people experiences and ideas were used to assess the vulnerability of wetland resources so as to improve on the understanding of what causes such vulnerability and the type of vulnerability The main vulnerabilities that were taken into consideration were be: wetland resource vulnerability, physical vulnerability and local socio-economic livelihood vulnerability

Figure 3-2: Climate Change Impact Assessment Approach

Source: United Nations Permanent Forum on Indigenous Issues report, 2007

This helped in determining vulnerability using the equation;

V= I- A where, V is vulnerability, I is impact and A is adaptation

3.3 Study Design

Primary and secondary data was used for the study Primary data was collected using semi structured questionnaires, field observations and key informant interviews from August to December 2017 Questionnaires we administered to 100 household heads /local people that were randomly selected using snowball due to financial constraints from six coastal villages along Lake Wamala: Mityana Town, Naama, Nkonya, Buzibazi, Mpongo and Lusalira The questionnaire covered local communities’ views

on climate change, its effects on wetland resources and their livelihood, main causes

of such changes and associated risks and coping up or mitigation strategies in place These areas were considered as they have a history of flooding as they lie near river mouths of rivers: Nyanzi and Mpamujugu and drowned valleys/wetlands, have important habitats and easily accessible

Secondary data covered data on climate aspects, and all literature that was not captured in the questionnaire Rainfall and air surface temperature data was obtained from Uganda National Meteorological Mubende weather station archives, respondents’ views and Mityana District Environment department; which are the main stations located nearest to Lake Wamala Mubende weather data was used since before 2005, Mityana District was part of Mubende; henceforth, preceding data before

2005 was imperative in reflecting what weather records Mubende station has (See Appendices 4-10) This was tested to analyze periods of variations in climate

parameters These periods traced variations since 1998 during which acute changes in climate parameters were being felt (Natugonza and Ogutu-Ohwayo, 2015) Based on the seasonal weather classifications of Uganda, these seasons were described as short dry season (December-February), long wet season (March-May), long dry season

(June-August) and short wet season (September-November) (Komutunga and Musiitwa, 2001) Due to a historical data gap on wetland resources, the period for examining overt losses or gains in such resources was 2007-2017 to ease comparison with the few existing literature and research on selected wetland resources like fish around Lake Wamala To collect a lot of data, contact was made with local parish/village leaders in each sampled village from where weekly visits were made to targeted households with knowledge on climate changes, wetland resources and livelihoods around Lake Wamala

3.3 Data Acquisition

Annual and monthly rainfall totals and air temperature data were obtained from archives and excerpts from Ministry of Water and Environment (MWE), UNMA, NaFIRRI, Mubende and Mityana District Weather Records, and a few research reports

and findings around Lake Wamala (See Appendices 4-10)

Historical data on Lake Wamala wetlands and resources like fish catches especially from 1990 to 2015 was obtained from archives of NaFIRRI (though unpublished) through the Mityana District Fisheries and Environmental Officer as there was 1 frame survey and 2 Catch Assessment Surveys that were conducted in 2012 and experimental fish sampling is carried out in the Lake every 3 months since 2011 (Natugonza et al., 2015) Such biometric data was used to determine the length-weight relationships, conditioning factors and other characteristics in relation to mainly temperature changes (Lake Victoria Fisheries Organization, 2007)

Data on the impacts of climate change on other wetland resources like vegetation, water level and soils was obtained through a set of well-designed questionnaires that

were be sent to respondents (See Appendix 1) The respondents were chosen based on the demography of the area, their proximity Lake Wamala, knowledge about the wetland resources and climate change, source of livelihood and willingness to respond

to the questions in the questionnaire

Data on the causes of wetland loss, associated impacts and adaptation and mitigation strategies was obtained using questionnaires and formal interviews with Mityana District Environment officers For easy data acquisition amongst the less literate

grassroots communities, 12 research assistants (2 assistants for each area) were recruited to traverse the 6 sites on a weekly basis and enumerate data and make critical observations The swampy coastline deterred accessibility to threshold islands and hence, respondents were chosen form easily accessible zones

3.4 Data synthesis and Analysis

3.4.1 Temperature

The study employed descriptive statistics and illustrations to analyze and understand the long-term mean of temperature; mean of the maximum, average and minimum temperature inter-annual and inter-decadal temperature variations around Lake Wamala Temperature data from Mubende Meteorological Station was compared using Analysis of Covariance (ANCOVA) and the average change in temperature was

determined using SAS JMP 10 Software (See Appendices 4-10 and 18)

3.4.2 Rainfall

Rainfall totals (monthly and annual) were summed up for the identified periods to determine the Standardized Precipitation Index (SPI) obtained as standard variations between annual rainfall and long-term average (Tumbo, 2007) Variability in rainfall was determined using the coefficient of variation (CV) calculated as a ratio to the

mean and expressed as a percentage (See Appendices 5, 6, 7, 10, 17) The inter-link

between rainfall and lake depth was examined with the Pearson Product-Moment Correlation Analysis

3.4.3 Water Balance changes

Data was on water inflows and outflows was obtained from the Directorate of Water Resource Management (DWRM) and data on Lake Depth was obtained from NaFIRRI (1990-date) This was supplemented with satellite images of UNEP (2012) and field observations This was envisaged from the fact that since there are less large scale water abstractions in Lake Wamala, water levels are expected to be normal and high (Sewagudde, 2009) and its location in the Lake Victoria basin makes interactions and complementarity between ground water and surface water flows less paramount (Krishna-Murthy and Ibrahim, 1973)

The historical, demographic and all other data obtained via questionnaires was analyzed using a computer program of Excel All the collected data was entered in Excel spreadsheets

Data analysis was done using pivot tables and pivot charts/graphs after getting summaries of all data Such pivot tables ease comparison and area specific analysis; a touchstone in understanding which area/s or wetland resources have been immensely

or minimally affected by climate change hence helping in generating pathways in coping to and adapting to such changes

CHAPTER FOUR: RESULTS

4.1 Demographic Characteristics of Households

The demographic characteristics of the six sites vary as it is in Uganda (see Appendix 3), Mityana District and the sub counties and sampled areas along Lake Wamala

Mityana district is a Local Government administrative unit/district in Central Uganda that was set up in 2005; prior to that, it was under Mubende District Local government administration (UBOS, 2016)

All the respondents from the sampled villages had distinct demographic characteristics based on sex, marital status, education level and occupation

Table 4.1 Percentage of respondents for each area

Area Mityana Buzibazi Naama Mpongo Lusalira Nkonya Sex

Generally, the proportion of households varied from area to area

Figure 4-1 Relative Percentage of Households sampled during the Survey

There was an almost identical sex ratio of 52:48 irrespective of the fact that Naama had the largest proportion of male respondents (14%) and Mityana town had the most

female respondents (10%) (See Appendix 11) Majority of the local people are single

households with the largest proportion of married households in rural areas The

largest proportion of married households was in Buzibazi (10%) (See Appendix 12)

There was a comparatively high literacy level across all zones as 79% of respondents reported to have attained secondary school education especially in Mityana

(Appendix 13) Virtually, all respondents are engaged in some form of income

generating activity However, there is a continuous dominance of traditional livelihood activities such as small holder farming even though many respondents reported that they are shifting to secondary activities such as in Naama This highlights a paradigm shift from fishing as 30% of the respondents indicated that they have diversified and engaged in other activities such as teaching, poultry, apiculture and quarrying to enhance their income The source of livelihood varies amongst the six areas from where households were interviewed although most households are engaged in other activities Also activities like fishing and trade have been neglected

in some areas like Nkonya and Mpongo respectively

Figure 4-2 Relative Proportion of community occupation in the sampled areas along Lake Wamala

4.2 Local Communities’ Perception on Climate Change

All communities were alarmed by the sporadic changes in climate elements and patterns For instance, most of the local people (70%) reported that the frequency of rainfall patterns, extended drought, reduced rainfall and extremely hot conditions have increased and become less predictable over the years especially in Naama and Nkonya where 5% of the households are affected by reducing rainfall

Figure 4-3: Relative Percentage of the perception of local communities on climate change around Lake Wamala

The perception on the frequency of increased changes in climate events is alarming especially in Naama were 4% of households reported sporadic changes synonymous with data from Mubende Weather Station that shows gross anomalies and unpredictable frequencies in some months

Figure 4-4: Frequency of Wet and Dry months along Lake Wamala

Source: Mubende District Meteorological Archives

Such climate change alarms acknowledged by local households in Buzibazi concur with the analyses of rainfall data that confirmed that, irrespective of the fact that average rainfall were above average rainfall anomalies since 1988 by 8.03 mm, SPI values indicated that there were high inter-annual rainfall variability Also, the severity of drought is progressively increasing since 2010 based on the probability of the observed total annual rainfall

Figure 4.5 SPI series assessing the drought occurrence in relation to the probability of observed total annual rainfall changing from average (1980-2010)

(Source: Uganda National Meteorological Authority, Entebbe)

There is a variation in temperatures with extremes of 31OC and lows of 150C especially in Jan-March with a mean of (≥22.6±0.17OC) There was a higher variation

in temperature after 1990 (C.V=1.9%) than before (C.V=1.7%) with average temperature being 22.1±0.320C and the average change in temperature was slightly different from the past regimes (F=30.2, p˃0.05) (Appendix 4-10)

Analysis of weather information indicated a linear increase in minimum temperature (R2=0.145), maximum (R2=0.09) and average temperature (R2=0.2) even though minimum and maximum temperature showed significant increase (Appendix 20)

4.3 Water Level changes

Historical data indicated that there was a positive correlation between rainfall and lake depth till 2000s (r=0.83, n=6, p<0.05) However, the Lake depth receded since 2005 with exposed water gauges (Figure 5-1)

Figure 4-6: Relationship between Lake Depth and inter-decadal annual rainfall (Source NaFIRRI, National Meteorological Authority, 2013)

4.4 Climate Variability and Livelihood

Most respondents (97%) reported that the continuous vagaries in climate elements have had a ripple effect on livelihood activities such as small scale farming Households in Buzibazi (18%) observed that an increase in temperatures has had direct impact of crop yields, fish catch and stocks Such changes have affected farm produce, increased the cost of doing business, increased the incidence of pests and diseases, have led to floods and soil degradation For instance, 6% of respondents in Lusalira experienced a decline in Household income due to climate changes

Table 4-2 Relative Proportion of the impact of climate change on livelihood

Decline in household income 23%

Reduced agricultural produce 14%

Increased cost of doing business (ICDB) 9%

Increased coldness and fog 8%

Increased occurrence of pests and

diseases

7%

Destruction of infrastructure 6%

Figure 4-7: Impact of climate change on community occupation

4.5 Climate change and wetland resources

All households reported that climate variability has led to negative impacts on wetland

resources onto which they derive their livelihood (See Appendix 14) For instance,

4% of respondents in Mpongo experienced a decline in fish stocks and catch, well as 8% of wetland soils in Nkonya have been affected Generally, there is a direct correlation between changing climate events and wetland resources that pre-determine the source of livelihood of people therein Small scale farming that predominates the coastlands of the lake have been directly affected by the changes in rainfall and temperature trend and associated weather events like floods and drought

Figure 4-8: Relative Proportion of the effect of climate change on wetland resources

The effect of climate variability on specific resources vary for each area In Nkonya, 8% of the respondents reported that wetland soils have been affected well as 10% of respondents in Mityana town highlighted that the main affected resource is swamp vegetation

Table 4-3: Relative Proportion of the impact of climate change on specific area wetland resources

Resource Wetland Soil Water Quality

and Quantity

Swamp Vegetation

Table 4-4 Relationship between wetland resource losses on livelihoods due to climate variability

Livelihood Farming Others Trade Fishing Total

4.6 General causes of wetland resource loss

There is a symbiosis between anthropogenic and natural factors in accounting for what causes wetland resources degradation However, specifically, respondents highlighted that 20% of such loss is attributed to swamp cultivation and increasing population which accounts for 16% Natural phenomenon of drought and low rainfall account for 15% of the total loss of wetland resources It is also imperative to note that the causes