CHARACTERIZATION OF FISHERY RESOURCES AND IMPACTS OF

ARTISANAL FISHING ON SEAGRASS MEADOWS OF GAZI BAY, SOUTH

COAST, KENYA

MUSEMBI PETER MWANZIA

A Thesis is submitted partial fulfilment of the requirements for the Degree of Masters of

Science in Fisheries of Pwani University

September, 2019

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DECLARATION

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DEDICATION

I dedicate this thesis to all those who have helped and supported me in following the path of marine ecology and conservation. iv

ACKNOWLEDGEMENT

Foremost, I would like to thank the Almighty God for the good health that enabled me to undertake this work. I am grateful to my supervisors Dr Bernard Fulanda and Dr James

Kairo for their mentorship during the study period. I thank Dr Michael Njoroge for his assistance and guidance in designing the study, data collection, analysis and writing. I am also grateful to the PUNGUZA HEWA KAA project under the Blue Carbon Unit funded by Newton Fund. which funded the fieldwork. To Gazi Beach Management Unit

(BMU), particularly, the Chairman, Mr Juma Mkuu; a huge appreciation for linkage with fishers, the logistics for the field surveys with the Gazi BMU, and to all fishers and the wider community in Gazi for your acceptance to take part in this research. I would also like to thank my family for their financial and emotional support during the study period. v

ABSTRACT

Fisheries resources are critical to coastal communities livelihoods, providing food and income. The exploitation of fisheries resources in the tropics is mainly small-scale in nature characterized by being multi-species and multi-gear and conducted over the entire seascapes, from mangroves, seagrass meadows to coral reefs using low technology crafts such as dug-out canoes. There has been biased attention of tropical marine fisheries towards coral reef-associated fisheries with little attention to other habitats such as seagrass meadows. Large amounts of fisheries are also associated with seagrass meadows which contribute substantially to small-scale fisheries through the provision of nursery, breeding and feeding grounds for numerous marine species that are exploited by coastal communities. However, critical information on some aspects of seagrass associated fisheries such as species assemblages and exploitation are limited. Using

Creel survey and Underwater Visual Census (UVC) this study characterized the fisheries resources associated with seagrass meadows, their exploitation patterns and fishing impacts in Gazi Bay. Catch composition, species diversity, catch trends and threats to seagrass meadows and associated fisheries were evaluated over one year. Five fishing gears were observed in the seagrass meadows; basket traps (75.1%), hook and stick (10.8%), nets (7.8%), handline (4.9%), and speargun (1.4%). Overall a total of 113 species belonging to 55 families were recorded from catch assessment and Underwater

Visual Census (UVC). A total of 85 species were observed from the creel survey while

Underwater Visual Census recorded 33 species. Despite the high diversity in creel survey, only seven species accounted for 72.8% of the total catch by number dominated by Leptoscarus vaigiensis (30.8%). Others included, Scarus ghobban (10.2%), Lutjanus fulviflamma (10.1%), Lethrinus lentjan (7.6%), Lethrinus nebulosus (6.1%), Plotosus lineatus (4.3%) and Siganus sutor (3.6%). The catch rate was highest in the basket trap vi gears, at 3.5 ± 1.7 kg/fisher/trip (± SD) while handline recorded the lowest catch rate at

2.6 ± 1.2 kg/fisher/trip (± SD). There was significant variation in catch rate among the fishing gears (Kruskal-Wallis, p = 0.0187). The seven dominant species L.vaigiensis, S. ghobban, L.fulviflamma, L. lentjan, P. lineatus, L. nebulosus and S. sutor recorded mean lengths of 16.8 cm, 16,1 cm, 16.7 cm, 15.5 cm, 18.3 cm, 13.3 cm and 19.3 cm respectively. Forty-one percent (41%) of individuals from the top seven dominant species were immature. All gears recorded a proportion of immature individuals from the dominant species indicating the impact of gears on the fishery. There is a need for effective gear-based management measures for the seagrass fishery in the bay to protect key species such as the dominant observed in this survey for the sustainability of the fishery and ecosystems as well as protect livelihoods of the community depending on the fishery.

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TABLE OF CONTENTS

ACKNOWLEDGEMENT ...... iv

ABSTRACT ...... v

LIST OF FIGURES ...... ix

LIST OF TABLES ...... xi

LIST OF ABBREVIATIONS AND ACRONYMS ...... xii

CHAPTER ONE: INTRODUCTION ...... 1

1.1 Background ...... 1

1.2 Statement of the Problem ...... 5

1.3 Significance of the study ...... 6

1.4 Scope of the study...... 6

1.5 Objectives of the study...... 7

1.5.1 General Objective ...... 7

1.5.2 Specific Objectives ...... 7

1.6 Research Questions ...... 7

CHAPTER 2: LITERATURE REVIEW ...... 8

2.1 Global seagrass distribution...... 8

2.2 Seagrass meadows and Ecosystem services ...... 8

2.3 Seagrass and Climate change...... 9

2.4 Seagrass in the Western Indian Ocean ...... 10

2.5 Seagrass meadows in Gazi Bay ...... 11

2.6 Tropical marine artisanal fisheries ...... 12

CHAPTER THREE: MATERIALS AND METHODS ...... 16

3.1 Study Area ...... 16

3.1.1 Geographical location ...... 16 viii

3.1.2 Climatic Conditions ...... 17

3.1.3 Socio-economic activities ...... 18

3.2 Sampling and Data Collection ...... 19

3.2.1 Fishery Creel Surveys ...... 19

3.2.2 Underwater Visual Census ...... 21

3.3 Data Analysis and Statistical Tests ...... 21

CHAPTER FOUR: RESULTS ...... 24

4.1 Species Diversity...... 24

4.1.1 Catch Assessment Survey ...... 24

4.1.1.1 Fishing gear composition ...... 26

4.1.1.2 Seasonal variation ...... 31

4.1.2 Underwater Visual Census (UVC) ...... 34

CHAPTER FIVE: DISCUSSION ...... 42

CHAPTER SIX: CONCLUSION AND RECOMMENDATIONS ...... 48

6.1 Conclusion ...... 48

6.2 Recommendations ...... 48

REFERENCES ...... 50

APPENDICES ...... 64

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LIST OF FIGURES

Figure 1: Map showing Gazi Bay with areas of seagrass meadows, corals and mangroves.

...... 17

Figure 2: The relative abundance of dominant families (accounting for >1% of relative abundance) observed in the catch assessment survey...... 25

Figure 3: Relative abundance of dominant species (accounting for >1% of relative abundance) observed in the catch assessment survey ...... 26

Figure 4: Species catch composition by fishing gears observed in the seagrass meadows showing dominant species with the relative abundance of > 5% by numbers ...... 29

Figure 5: Non-Metric MDS showing the separation of species by different fishing gears .. 30

Figure 6: Non-Metric Multi Dimensional Scaling (nMDS) showing the separation of species by seasons...... 31

Figure 7: The relative abundance (%) of the fish species caught during the Northeast monsoon (NEM)...... 32

Figure 8: The relative abundance (%) of the fish species caught during the southeast monsoon (SEM)...... 33

Figure 9: Total family density (number of individuals per 1000m2) recorded in the

Underwater Visual Census Error bars are standard errors...... 35

Figure 10: Total species density (number of individuals per 1000m2) recorded in the

Underwater Visual Census Error bars are standard errors...... 36

Figure 11: The relative abundance of different functional groups observed in the catch assessment survey and underwater visual census...... 37 x

Figure 12: Median catch rates (with 25%, 75% quartiles) of fishing gears during both SEM and NEM used in the seagrass meadows with Kruskal-Wallis test. Black dots indicate outliers...... 38 xi

LIST OF TABLES

Table 1: Species diversity, the proportion of catch and catch rates of different fishing gears

...... 27

Table 2: Relative abundance and species richness of finfish and shellfish captured by different fishing gears ...... 28

Table 3: Proportion (%) of individuals under the length at first maturity (Lmat) of the most dominant species by fishing gear. ND - no data in the catch ...... 41 xii

LIST OF ABBREVIATIONS AND ACRONYMS

ANOSIM Analysis of Similarity

BMU Beach Management Unit

CAS Catch Assessment Survey

CPUE Catch Per Unit Effort

Lmat Length at first maturity

KIIs Key Informant Interviews

NEM North-East Monsoon nMDS Non-Metric Multi-Dimensional Scaling

SD Standard Deviation

SEM South-East Monsoon

UVC Underwater Visual Census

WIO Western Indian Ocean

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CHAPTER ONE: INTRODUCTION

1.1 Background

Seagrasses are marine flowering plants that live and complete their lifecycle submerged in seawater (Bjork et al., 2008). They are found in the photic zones of marine environments extending from the intertidal zone to sub-tidal zone with soft bottoms forming extensive monospecific or multispecies meadows (Gullstrom et al., 2002).

Seagrass meadows are distributed throughout the world except in Antarctica (Green &

Short, 2003) and form one of the most productive coastal ecosystems in the world

(Duarte & Chiscano, 1999). The spatial distribution of seagrass meadows is influenced by various factors such as light, temperature, salinity, nutrient availability and wave action (Hemminga & Duarte, 2000). There are up to 76 known species of seagrass worldwide (Green & Short, 2003) with the indo-pacific region having the highest diversity (Short et al., 2007). The seagrass meadows of the tropics form part of the mangrove-seagrass-coral reefs interconnected ecosystems and among the most productive shallow marine system (Moberg & Ronnback, 2003).

Seagrass meadows are highly productive ecosystems and their structural complexity is of significance to fisheries, providing refugia against predators, sites for attachment especially of settling eggs and food for various species (Gullstrom et al., 2008; Farina et al., 2009). Their connectivity with other adjacent ecosystems enhances cross-habitat utilization by species and thus supports the productivity of adjacent habitats (Heck et al.,

2008). Consequently, seagrass meadows are critical foraging, refugia and nursery grounds for numerous species of finfish and invertebrates that are exploited for subsistence, recreational and commercial purposes (Jackson et al., 2001; Orth et al.,

2006; Unsworth & Cullen, 2010; Cullen-Unsworth & Unsworth, 2013). The location of

2 seagrass meadows in shallow nearshore waters make them easily accessible for exploitation with minimal gear requirement (Unsworth et al., 2018). For example, gleaning (the use of simple gears or hand collection to exploit invertebrates in the intertidal zone during low tide) is a dominant activity in tropical and subtropical regions and a source of food to coastal communities (Unsworth & Cullen, 2010; Nordlund et al.,

2011). However, such fisheries are rarely monitored nor are the catches reported (De la

Torre-Castro et al., 2017). Generally, data and information on fisheries associated with seagrass meadows such as species assemblages and the exploitation methods are limited.

Furthermore, the majority of the seagrass associated fisheries are usually categorized as coral reef fisheries limiting reporting on the value of seagrass ecosystems in supporting fisheries. Consequently, these critical ecosystems have continued to receive little attention, more often being neglected in fisheries management plans.

Seagrass meadows are also important in the provision of other ecosystem services. They form one of the most efficient carbon sinks by capturing and storing huge stocks of carbon and have been suggested to have the potential for mitigating the impacts of climate change (Duarte et al., 2013; Hejnoiwcz et al., 2015; Githaiga et al., 2017).

Seagrass meadows contribute to nutrient cycling in coastal waters through their uptake from the water column, and storage in biomass and sediment. Through dissipating the energy of waves and currents, they stabilize sediments and prevent erosion (Potouroglou et al., 2017).

Globally, seagrass meadows are rapidly declining and facing increasing threats from both natural and anthropogenic disturbances. They have been mentioned as among the most threatened ecosystems comparable to mangroves, coral reefs and tropical forests

(Duarte, 2002; Orth et al., 2006). Seagrass meadows are estimated to have decreased at a

3 rate of 110 km2 per year in the last three decades and approximately 29% of the areal seagrass extent has been lost in the last century (Waycott et al., 2009). The location of seagrass in shallow nearshore areas make them particularly vulnerable to overexploitation and other human and land-based disturbances (Waycott et al., 2009).

The continued decline in seagrass meadows is a cause of concern on their ability to continue providing critical ecosystem services to coastal systems.

Despite their significance and the threats they are facing, seagrass meadows have received very little research attention especially in East Africa (Samoilys et al., 2015) with more focus directed towards other marine habitats such as mangrove forests and coral reefs (De La Torre-Castro, 2004, Nordlund & Gullstrom, 2013). The biased focus has been attributed to the high species diversity in coral reefs and intense exploitation in both coral reefs and mangrove forests (Nordlund & Gullstrom, 2013). Although this is currently changing with increasing scientific attention on seagrass ecosystems in East

Africa (Nordlund & Gullstrom, 2013, Githaiga et al., 2016), there are still critical components of seagrass that have not been studied especially regarding their faunal species diversity, fisheries and exploitation patterns and livelihood support to coastal communities. Understanding these issues in seagrass habitats is important to inform and strengthen existing coastal habitats management strategies.

Fisheries resources are important to millions of coastal communities providing food and income enhancing coastal livelihoods (McClanahan et al., 2005a; 2013). Fisheries resources include traditional finfish fisheries that inhabit shallow marine habitats such as common families like Lutjanidae, Lethrinidae and Scaridae as well as shellfish which include invertebrates’ species that may have shells in place of backbones and including molluscs and crustaceans (Nordlund and Gullstrom, 2013).

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Small-scale fisheries dominate marine fisheries in the majority of developing countries.

In most parts of the Western Indian Ocean (WIO) region, small-scale fisheries contribute 93-98% of the marine catch, comprises the main income-generating activity and a major source of protein for local communities (Samoilys et al., 2015; Tuda et al.,

2016; Rehren et al., 2018). These fisheries are characterized by open access, low technology, multi-species and multi-gear, with catches landed in multiple sites and fishing carried out throughout the entire seascape of mangroves, seagrass meadows and coral reefs (Kaunda-Arara et al., 2003; McClanahan & Mangi, 2004; De la Torre-Castro et al., 2014). These characteristics, coupled with high dependence on marine resources by adjacent communities make small-scale artisanal fisheries particularly complex to assess and manage.

Small scale artisanal fisheries in Kenya and the WIO region have been extensively studied. Their contribution to local food security and livelihoods, catch composition, catch rates, trends and management interventions have been widely discussed (Kaunda-

Arara et al., 2003; McClanahan & Mangi, 2004; McClanahan et al., 2008; Fulanda et al.,

2009; Tuda et al; 2016; Samoilys et al., 2017). Similar to global and regional trends, local catch rates indicate declining catches due to additive and synergistic effects of overfishing, habitat degradation, use of destructive fishing methods and emerging phenomena such as climate change, consequently harming peoples’ source of food and livelihoods (McClanahan, 2008; Samoilys et al., 2017). Although efforts have been made to address these challenges in the WIO, their impacts on the ecosystems, fisheries and livelihoods remain insufficient threatening coastal systems and peoples’ livelihoods

(Samoilys et al., 2017).

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Studies on tropical marine fisheries have historically focused on coral reef-associated fisheries (Nordlund et al., 2010) despite evidence that the fisheries are carried out throughout the whole of the coastal seascape of coral reefs, mangrove forests and seagrass meadows (Unsworth & Cullen, 2010; Nordlund et al., 2017). Seagrass fisheries are widespread, contribute significantly to small-scale fisheries catches and support coastal livelihoods, especially in the Indo-Pacific which has the greatest seagrass species diversity (Gullstrom et al., 2002; De la Torre-Castro & Ronnback, 2004; Nordlund et al.,

2010; Unsworth & Cullen, 2010; De la Torre-Castro et al., 2014; Nordlund et al., 2017).

However, information on seagrass fisheries and their contribution to small-scale fisheries are still limited as is information on the impacts of these fisheries on the ecosystem. It is important to understand these aspects to inform effective management actions.

1.2 Statement of the Problem

Small-scale artisanal fisheries are important sources of livelihoods to coastal people providing food and income. Numerous studies have been conducted on small-scale fisheries highlighting different aspects of the biology of species, ecology and socio- economics. However, the focus of these studies has been biased towards coral reef and mangrove associated fisheries. Small scale fisheries, especially in the tropical coastal, are exploited in the entire seascape from mangroves forests, seagrass meadows and corals reefs. Substantial fisheries are associated with seagrass meadows and are critical in supporting small-scale fisheries and the livelihoods of coastal communities. Although few studies have highlighted the importance of seagrass meadows for fisheries production, information on important aspects of these fisheries such as exploited

6 species, exploitation methods, impacts of exploitation to the habitats are limited and therefore few management actions have been implemented.

1.3 Significance of the study

Seagrass meadows and their fisheries resources are important to coastal communities, it is predicted their exploitation will increase as human and natural pressure on adjacent habitats such as coral reefs through climate change-related mass bleaching and associated mortalities increase. This is because fishing communities will shift and exploit seagrass more as fisheries productivity in adjacent habitats declines.

Additionally, seagrass meadows are part of the tropical coastal seascape. Understanding the contribution and dynamics of different habitats within the coastal seascape to fisheries productivity and local livelihoods is critical to inform effective governance and management for the sustainability of fisheries and their habitats especially within the ecosystem-based management framework. This study provides a comprehensive assessment of fish and shellfish assemblage associated with seagrass meadows, their exploitation patterns, and community perception on catch composition, trends and threats to the fisheries and seagrass meadows.

1.4 Scope of the study

This study focusses on abundance and biomass of finfish and shellfish in the seagrass meadows of Gazi Bay. The work was carried out over a one year and sampling was conducted twice weekly. Landed catches and Underwater observation were employed to achieve the objectives. The sampling of fish catches was voluntary and the results are only from fishers that accepted their catches to be sampled that included 167 fishing trips. Underwater Visual Census was limited by the horizontal visibility and only observations made when visibility was 6 m or more were retained.

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1.5 Objectives of the study

1.5.1 General Objective

The general objective of this study was to characterize the fishery resources and fishing impacts of artisanal fishing on the seagrass meadows of Gazi Bay, South Coast, Kenya.

1.5.2 Specific Objectives

i. To determine diversity, abundance and biomass of fish and shellfish

exploited from the seagrass meadows in Gazi Bay.

ii. To assess exploitation patterns of fish and shellfish within the seagrass

meadows in Gazi Bay.

iii. To assess the maturity composition of most abundant species landed from the

seagrass meadows in Gazi Bay

1.6 Research Questions

1. What species of finfish and shellfish are exploited in the seagrass meadows of

Gazi bay?

2. What fishing gears are used in the exploitation of finfish and shellfish in the

seagrass meadows of Gazi bay.

3. What species are exploited by each of different fishing gears used in the seagrass

meadows of Gazi bay?

4. Is there a seasonal difference in the species that are exploited in the seagrass

meadows of Gazi bay?

5. What is the size structure of the dominant species exploited from the seagrass

meadows of Gazi bay?

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CHAPTER 2: LITERATURE REVIEW

2.1 Global seagrass distribution

Seagrasses are diverse marine angiosperms that are widely distributed in temperate and tropical coastlines and are found throughout the world except in Antarctica (Green &

Short, 2003). Seagrass meadows occur between the depths of 0 – 30 m although they can grow at greater depth depending on the light availability (Duarte, 2002). Seagrasses are physiologically, morphologically and economically adapted to cope in the wide range of environments they inhabit. Spatial distribution of seagrasses is driven by light, temperature, salinity, nutrient availability, and wave action among other factors

(Hemminga & Duarte, 2000; Orth et al., 2006). An estimated cover of between 300,000 and 600,000 km2 by area has been recorded (Fourqurean, 2012). Seagrasses have a relatively low taxonomic diversity compared to terrestrial angiosperms with over

250,000 recorded species (Orth et al., 2006). The distribution range of seagrasses is, however, wider compared to other marine habitats such as mangrove forests and coral reefs that are restricted to tropical and subtropical regions and salt marshes and kelps beds in the temperate areas. Seagrasses predominantly occur as single species although in the tropics mixed stands are common. The tropical Indo-pacific region has the highest seagrass diversity with up to 14 species recorded in one locality (Short et al., 2007).

2.2 Seagrass meadows and Ecosystem services

Seagrass meadows are important socio-ecological systems that provide numerous ecosystem services that are vital to coastal communities and their livelihoods (De

Torres-Castro & Ronnback, 2004). The role of seagrass meadows in fisheries productivity, biodiversity support, carbon sequestration and sediment stabilization has been documented (Green & Short, 2003).

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Seagrass meadows support higher densities of flora and fauna than adjacent unvegetated areas (Hemminga & Duarte, 2000, De la Torres-Castro & Ronnback, 2004). The seagrass physical and biological structures contribute to high biodiversity (Gullstrom et al., 2008). The structural complexity provides sites for attachment and refugia from predators. The physical structure also dissipates water energy from incoming currents and waves allowing early life stages to settle in the relatively calm water (De Torres-

Castro & Ronnback, 2004). High productivity provides energy sources to both resident and transient species enhancing cross-habitat utilization and connectivity by species.

Seagrass meadows have been recorded as the main feeding grounds for numerous fish species that have subsistence, recreational and commercial value (Duarte, 2002;

Dorenbosch et al., 2006).

2.3 Seagrass and Climate change.

Seagrass meadows have recently been recognized as one of the most efficient carbon sinks in the world and contributing to the mitigation of climate change. Although they occupy only 0.2 % of world’s ocean area they are estimated to sink 27.4 Tg C yr-1 representing about 10% of global oceanic carbon burial and about twice as much carbon per unit area than buried in productive temperate and upland tropical forests

(Fourqurean, 2012). Carbon in seagrass meadows is derived from aboveground materials comprising of both standing biomass as well as epiphytes that the seagrasses support.

Below ground materials such as dead roots and rhizomes and organic carbon stored in sediments also contribute substantial amounts to the total seagrass carbon. Additionally, seagrass trap materials from other sources that are buried increasing their carbon storage

(Duarte et al., 2010; 2013). The information on carbon storage of seagrass meadows is biased with more research carried out in North America, Western Europe and Australia

10 and limited information on South America and Africa. It is likely therefore that the estimated amount of carbon buried by seagrass is underestimated (Fourqurean, 2012;

Githaiga et al., 2017) especially based on the fact that the regions with limited information mostly lie within the tropical Indo-pacific with the highest seagrass diversity. The high capacity of seagrass to store carbon has been attributed to high primary productivity and their ability to filter out particles from the water column and deposit them in the soil (Kennedy et al., 2010). The conservation of seagrass meadows is therefore critical for mitigating the impacts of climate change.

2.4 Seagrass in the Western Indian Ocean

The Western Indian Ocean region harbour among the world richest seagrass communities with 13 known species recorded in the region some in mixed stands of up to 8-10 species (Gullstrom, et al., 2002). Seagrasses are ecologically and socio- economically valuable resources in the region. Numerous commercial, subsistence and recreational fish and invertebrates’ species are associated with seagrasses in the Western

Indian Ocean (WIO). Important fish families such as Lethrinidae, Lutjanidae and

Siganidae are found in seagrass meadows in Kenya, Tanzania, Mozambique and

Madagascar (Van der Velde et al., 1995; Gell & Whittington, 2002; Gullstrom et al.,

2002). Other commercially valuable fisheries species such as cowries, octopus, sea urchins, sea stars and sea cucumber are exploited in seagrass meadows in the region

(Gullstrom, et al., 2002). Seagrass associated fisheries have been suggested to contribute substantially to the local artisanal fisheries in the WIO (Nordlund & Gullstrom, 2013).

Research on seagrass habitats in WIO has received limited attention compared to other coastal habitats such as mangrove forests and coral reefs. Most of the studies have investigated seagrass diversity and ecology and limited studies have looked at the socio-

11 ecological context of seagrass meadows (De la Torre-Castro, 2006; Cullen-Unsworth et al., 2014). Furthermore, fish as seagrass associated fauna and their linkage with coastal communities have been studied more than other associated fauna (Gullstrom et al.,

2002)

2.5 Seagrass meadows in Gazi Bay

There are twelve species of seagrass in Gazi Bay with four dominant species;

Thalassodendron ciliatum, Thalassia hemprichii, Enhalus acoroides and Syringodium isoetifolium occurring as monospecific or multispecies stands from the intertidal zone to the subtidal (Githaiga et al., 2017). Various studies on seagrass at Gazi Bay have focused on carbon dynamics and storage (Hemminga et al., 1994; Marguilier et al.,

1997; Bouillon et al., 2007; Githaiga et al., 2017), associated macroalgal communities

(Coppejans et al., 1992) productivity, growth and population dynamics (Duarte, 1996).

Seagrass meadows of Gazi Bay have been reported as important habitats with several organisms of commercial importance such as blacklip pearl oysters, fish and invertebrates recorded in the bay (Kimani and Mavuti, 2002; Van der Velde, 1995). De

Troch et al., (1996) found a high correlation between the diversity of fish and the density and diversity of seagrass though this varied between Eastern and Western creeks of the bay. While these studies have been vital in contributing to the knowledge of seagrass meadows in the bay most of them have focused on fauna either as specific species (black pearl oyster and taxa (fish). Important invertebrate groups such as large crustaceans and molluscs have been not been studied despite them forming a significant part of the local artisanal fishery. The interaction of socio-economic activity and the status of seagrass and associated fauna in the bay is unknown neither is the contribution of their fisheries to the community wellbeing. The current study aims to have a comprehensive

12 assessment of fish and shellfish assemblage associated with seagrass meadows, their exploitation patterns and evaluate the size structure of the dominant species.

2.6 Tropical marine artisanal fisheries

Small-scale fisheries are important to coastal communities supporting local livelihoods through provision of food and income especially in tropics where there is a high-level dependency on marine resources (McClanahan & Maina, 2004; McClanahan et al.,

2013; De la Torre-Castro et al., 2014). Small scale fisheries are characterized by low technology, multi-species exploited using multi-gears and landed at multiple landing sites. In Kenya 14 fishing gears (Samoilys et al., 2011) and 163 species (McClanahan &

Mangi, 2004) have been reported. In tropics, small-scale artisanal fisheries are carried out within the interconnected marine habitats of coral reefs, seagrass meadows and mangroves.

The artisanal fishery in Kenya has been widely studied. Like most of the tropical marine fisheries, it is predominantly small-scale using traditional fishing methods. Common gears include basket traps, gillnets, handlines, fence traps, beach seines and spearguns that are deployed in the near-shore coral reef, seagrass and mangroves areas using dug- out canoes and a few motorized boats. Long-term trends are indicating a decline in landings and change in catch composition that has been attributed to synergistic effects of overfishing, habitat degradation, use of destructive fishing methods as well as natural drivers such as climate change (McClanahan, 2008; Tuda & Wolff, 2015; Samoilys et al., 2017).

Similarly, shallow marine habitats that support these fisheries productivity such as coral reefs, seagrass meadows and mangroves are deteriorating due to combined

13 anthropogenic and natural pressures. Mass coral bleaching and associated mortality due to increasing sea surface temperature has affected more than 50% of the global coral reefs in the last three decades and raising concerns on the future of coral reefs in a rapidly changing global climate (Hoegh- Guldberg et al., 2007; Pandolfi et al., 2011).

Consequently, these changes have been reported to cause a reduction in the size structure of reef fish assemblage (Graham et al., 2007). Predicted frequent bleaching events and other local disturbances such as overfishing, pollution and destructive fishing are likely to have more impacts on the coral reef systems. Over-exploitation of wood products, conversion to aquaculture and agriculture, pollution effects, and reduction in freshwater flow through damming of major rivers, increased sedimentation, and coastal development has also caused widespread degradation of mangrove forests. Globally, between 20% and 35% of mangrove area has been lost in the last three decades

(Polidoro et al., 2010). Seagrass meadows are also severely impacted by coastal development and growing human populations as well as by the impacts of climate change (Waycott et al., 2009). Overall these critical marine habitats deterioration is threatening coastal communities’ food security and livelihoods.

The exploitation of biodiversity in seagrass meadows is common in different regions of the world and support coastal livelihoods through provision of food and income

(Nordlund et al., 2010; Unsworth et al., 2010; Cullen-Unsworth et al., 2014). Cullen-

Unsworth et al., (2014) observed that 82% of invertebrate harvesting in Wakatobi in

Indonesia was being carried out in shallow intertidal and subtidal seagrass meadows while Unsworth et al., (2010); approximated that 70% of households in the same area consumed fish from seagrass compared to just 20% from coral reefs. In East Africa, seagrass meadows are critical to the livelihoods of local communities through the

14 provision of fishing grounds, a substrate for seaweed culture, local medicine as well as aesthetic values. (De Torre-Castro & Ronnback, 2004). Gell and Whittington (2002) reported that the value of fisheries associated with seagrass meadows in Mozambique was 120,000 USD per year while De Torre-castro & Ronnback (2004) recorded much higher fisheries value at Chwaka Bay in Zanzibar of 240,000 USD per year.

The location of seagrass from intertidal to shallow subtidal make them easily accessible by humans, opening them to multiple human uses (Cullen-Unsworth et al., 2013) and exposing them to different forms of exploitation (Orth, et al., 2006). In the Western

Indian Ocean (WIO) region, for example, the seagrass meadow resources are exploited by fishing and hand-collection (De Boer et al., 2001). Collectors usually target invertebrates such as cowries, crabs, octopus, squids and sea urchins using spears or harpoons as well as collecting sessile species at low tide. Other forms of exploitation include gill nets, traps, fishing lines, beach seines and trawl nets to capture finfish.

Invertebrate exploitation within seagrass areas is a common activity around the world.

High levels of invertebrates harvesting have been recorded in Chwaka Bay Zanzibar,

Tanzania (Nordlund et al., 2010) and Inhaca Island in Mozambique (Nordlund et al.,

2013). According to Unsworth and Cullen, (2010), invertebrate fishery is largely unquantified and its impacts to biodiversity, ecosystem functioning, and local community livelihoods is little known especially in WIO where they form an important source of protein for rural coastal populations (Nordlund et al., 2010; Cullen-Unsworth et al., 2013). Additionally, the overall contribution of invertebrate fisheries to coastal marine fisheries is poorly documented with more attention given to coral reef-associated fisheries arguably due to their high species diversity and intensive use levels (Nordlund et al, 2010).

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The ecosystem services provided by seagrass meadows are varied depending on seagrass species, geographical location as well as the socio-economic and cultural context of the local communities (Rotherham & West, 2002; Fourqurean et al., 2012; Nordlund et al.,

2018). The distribution and use of the seagrass meadows by the associated fauna is known to vary with depth, species and seagrass stand, proximity to other structurally complex habitats as well as geographical location (Jackson et al., 2001, Heck et al.,

2008). Subsequently, their ecology, exploitation and provision of ecosystem services and their response to exploitation pressure vary at geographical and climatic scale. It is important to understand these aspects at local and different scales.

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CHAPTER THREE: MATERIALS AND METHODS

3.1 Study Area

3.1.1 Geographical location

The study was conducted for 12 months from September 2017 to August 2018 in Gazi

Bay, southern coast, Kenya. The bay is a shallow, tropical coastal water system at 4° 25'

S, and 39° 30' E, with extensive mangrove forests fringing the landward side, coral reefs sheltering the bay from the eastern seaward side, and extensive seagrass meadows in the continental reef shallow waters (Figure 1). The bay is relatively shallow with a mean depth of 5m and 8m at its deepest part. It stretches approximately 1.75–3.5 km wide and

3.25 km long and covers a surface area of about 17 km2 (Bouillon et al., 2007). The bay has a semi-diurnal tide with a tidal range of between 1.4m during neap tide and 3.2m during spring tide (Kitheka, et al., 1996).

The bay has two freshwater inlets, River Kidogoweni that flows through a creek on the northwest of the bay and River Mkurumuji situated on the southwestern side that flows from Shimba hills. The bay also has another creek on the eastern side that lacks a freshwater inflow (Githaiga et al., 2017).

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3.1.2 Climatic Conditions

The main climatic drivers are the Southeast monsoons (SEM) and the Northeast monsoons (NEM) The SEM runs from April to September and is characterized by strong winds and rough sea conditions. The NEM runs from October to March and is characterized by calmer sea conditions. The mean annual rainfall in Gazi ranges from

1000–1500 mm and occurs during two distinct periods; the long rains run from March to

May while the short rains are experienced during October to December (Kitheka et al.,

1996).

Figure 1: Map showing Kenya (inset) showing the location of Gazi Bay with areas of seagrass meadows, corals and mangroves.

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3.1.3 Socio-economic activities

Fishing is the main economic activity in the bay. Gazi bay has one of the most active landing sites on the south coast, supporting a small-scale artisanal multi-gear and multi- species fishery (Kimani et al., 1996). Other economic activities include small-scale businesses, ecotourism ventures such as the Gazi Women Mangrove Boardwalk and farming.

Fishing activities are influenced by the SEM and NEM seasons. During the SEM season fishing is concentrated within the inshore waters and sheltered areas of the bay because it is too rough to venture in the ope n ocean outside the bay. During NEM the ocean is calm allowing fishers to go further offshore exploiting the deeper waters and fisheries resources of the outer reefs

(McClanahan, 1988; Tuda et al., 2016). A greater area of the bay is exposed during low spring tide allowing local fishers to harvest fish and invertebrate resources by foot using sticks and hand collection (Githaiga et al., 2017). In the past four decades, there has been immigration by fishers from Pemba in Tanzania that have introduced small-scale purse-seine fishing (Ochiewo, 2004). Occasionally, resource conflicts occur between migrants and local fishers about fishing grounds, market access as well as conflicts with fishery managers on licenses. Generally, there has been concern about a substantial decline in the fisheries due to overexploitation and use of destructive gears in the area

(McClanahan et al., 2008; Tuda 2018).

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Twelve seagrass species reported in the eastern coast of Africa have been recorded in the bay occurring either as monospecific or mixed stands in both the subtidal and intertidal zone up to a depth of 8m (Coppejans et al., 1992; Githaiga et al., 2017; Harcourt et al.,

2018). Four of these species are dominant namely Thalassodendron ciliatum, Thalassia hemprichii, Enhalus acoroides, and Syringodium isoetifolium, accounting for about 70% of the seagrass cover in the bay (Coppenjans et al., 1992; Githaiga et al., 2017). The other species are Cymodocea rotundata, Cymodocea serrulata, Holodule wrightii,

Halophila minor, Halophila ovalis, Halophila stipulacea and Zostera capensis. The seagrass meadows in Gazi bay are reported to be some of the largest and almost contiguous meadows along the Kenya coast, covering an estimated area of 8 km2

(Bouillon et al., 2007; Samoilys et al., 2015).

Gazi bay hosts the first community-based project to trade on mangrove carbon credits;

Mikoko Pamoja. The project provides long-term incentives for mangrove protection and restoration through community involvement and benefits based on mangroves ability to sequester huge amounts of carbon in their biomass and sediments (Wylie, Sutton-Grier

& Moore, 2016; Plan Vivo, 2015 ).

3.2 Sampling and Data Collection

The study employed two approaches for the field surveys and data collection; (i) fishery creel survey or catch assessment surveys and (ii) Underwater Visual Census (UVC) for one year (Harmelin-Vivien & Francour, 1992; English et al., 1997; Samoilys, 1997)

3.2.1 Fishery Creel Surveys

A sampling of landed catches was done twice weekly from all fishers conducting their fishing in the seagrass meadows of the bay from September 2017 to August 2018 to

20 cover both NEM and SEM season. Sampling was done 10 days every month spread over the neap and spring tides. Sampling was carried out at Gazi landing site except for some fishers using hook and stick do not land their catch in the landing sites and therefore they were followed where they were fishing and their catch measured. A total of 167 fishing trips were completed over the one year study period.

At the landing site landed catch was sorted and identified to species using identification keys and field guides such as Anam and Mostrada, 2012. Catch data including total weight (TW, kg), the number of individuals of each species, fishing gear used, fishing grounds visited and crew size for each fishing trip was recorded. Additional information such as total length and weight of individuals was obtained from a random subsample of the catch. The total length of individual fish was measured to the nearest 0.1 cm from the tip of the snout to the tip of the caudal fin using a standard marked ruler fixed on a flat board. Total weight for each species was weighed to the nearest 0.1 g using a hand- held portable electronic weighing balance (Weiheng, W40 kg / 10 g, Japan).

A functional group comprises species with similar life history that respond to environmental fluctuations in a similar way within a given habitat (Ladds et al., 2018).

Functional groups can describe the way energy or materials are transferred or stored within the system and can be defined based on feeding behavior. Functional structure of species assemblage is a key indicator of the status or resilience of an ecosystem hence important in describing the structure of species assemblage in relation to their habitat and help in understanding species diversity (Choat and Clements, 1998). In this study all species were categorized into seven functional groups based on FishBase, Choat and

Clements (1998), Choat, Clements and, Robbins (2002) and Samoilys et al., (2019).

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3.2.2 Underwater Visual Census

Underwater Visual Census (UVC) was carried out using visual techniques as described by Harmelin-Vivien & Francour, (1992) and English et al., (1997). Transects measuring

50 x 5 m were deployed in seagrass meadows. Each transect was deployed as the assessment of species was carried out such that the investigator pulled the transect tape behind them to avoid disturbing fast-moving species. Underwater Visual Census was carried out by snorkelling. All individuals within the transect were identified to species level and enumerated. Species that could not be identified in the field from both creel surveys and Underwater Visual Census were photographed using a GoPro® Hero3+ camera for subsequent reference identification.

3.3 Data Analysis and Statistical Tests

Data were analyzed using R statistical programs (R Core Team, 2018). For analyses catch data was organized into two matrices in Microsoft excel. One with effort data that included crew size, area fished, period fished, fishing gear and the total weight of the catch. The second matrix included information of species and functional groups abundance by gear, total lengths and weight of the individual specimen. For all analysis by gears, cast net, monofilament net, gillnets and reef seine were pooled into the category "nets".

The nominal catch rates by gear were calculated as kg/fisher/trip by dividing the total catch weight by the number of fishers in a boat.

Catch rate (by gear) =

Total Catch (kg) by gear or vessel (i) Catch rate = Total Number of fishers (Nos.) per gear or vessel

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Relative abundance was estimated as a ratio of the total number of each species and the total catch.

푁푢푚푏푒푟 표푓 푖푛푑푖푣푖푑푢푎푙 푝푒푟 푠푝푒푐푖푒푠 (ii) 푅. 퐴 = 푋 100 푇표푡푎푙 푁푢푚푏푒푟 표푓 푖푛푑푖푣푖푑푢푎푙 표푓 푎푙푙 푠푝푒푐푖푒푠

The multivariate non-Metric Multidimensional Scaling (nMDS) technique was then used to visualize catch composition by fishing gears and by seasons. Analysis of Similarity

(ANOSIM) test was used to statistically determine if catch compositions were significantly different by fishing gears and seasons.

Six dominant species; that contributed over 70% of the total catch abundance were selected for size-frequency distribution. Sexual maturity was determined using the length at first maturity (Lmat). This is the length at which fish of a given population become sexually mature for the first time. This value is important to determine juvenile retention rates (Tuda et al., 2016). Juvenile retention rates were determined by calculating the proportion of landed individuals below length at first maturity (Lmat).

Values for Lmat were obtained from Mangi & Roberts (2006) and Froese & Pauly

(2000).

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The UVC data was organized into species and functional group numerical density standardized into the number of individuals/1000m2. Descriptive analysis was conducted to show the density by species and families. Due to rough conditions and poor visibility during SEM, few transects were carried out during this period and therefore no species and functional comparison by seasons was carried out. Survey was carried out when underwater horizontal visibility of more than 6 m to ensure species within the transects could be observed and enumerated.

Data were tested for normality and homogeneity of variance using Shapiro-Wilk statistic. The data did not meet the assumptions of normality even after subjecting it to transformation. The non-parametric test Kruskali-Wallis to test the difference in catch rate among the different fishing gears. The significance level of all statistics was set at

0.05 (Dytham, 2011).

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CHAPTER FOUR: RESULTS

4.1 Species Diversity

A total of 113 species belonging to 55 families were observed from both catch assessment and Underwater Visual Census (UVC) over the study. This comprised 87 species of finfish belonging to 38 families and 26 species of shellfish representing 17 families. Twelve species were recorded from both UVC and catch assessment namely;

Leptoscarus vaigiensis, Lutjanus fulviflamma, Caranx heberi, Cypraea tigris, Lethrinus harak, Parupeneaus barberinus, Parupeneaus indicus, Chicoreus ramosus, Siganus sutor, Cheilio inermis, Lactoria cornuta, Holothuria scabra.

4.1.1 Catch Assessment Survey

Catch Assessment Survey was dominated by finfish with 90.9 % of the recorded individuals being finfish while only 9.1 % were shellfish. A total of 85 species from 41 families were recorded from the catch assessment survey consisting of 70 species of finfish belonging to 31 families and 15 species of shellfish belonging to 10 families

(Appendix 1). Scaridae (43.4%), Lethrinidae (15.7%) and Lutjanidae (10.4%) were the most dominant families cumulatively accounting for 69.5% of the total catch by number

(Figure 2). The most abundant shellfish family was Sepiidae that contributed 2.4% of the total catch and 28.2% of the shellfish catch. The family Haemulidae was the most speciose finfish family as well as overall with 9 species sampled. Portunidae was the most speciose shellfish with 3 species observed.

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Figure 2: The relative abundance of dominant families (accounting for >1% of relative abundance) observed in the catch assessment survey. *Shellfish families

Seven species of finfish accounted for 72.7% of the total catch by abundance namely;

Leptoscarus vaigiensis (30.8%), Scarus ghobban, (10.2%), Lutjanus fulviflamma

(10.1%), Lethrinus lentjan (7.6%), Lethrinus nebulosus (6.1%) Plotosus lineatus (4.3%) and Siganus sutor (3.6%). The most abundant shellfish species was Chicoreus ramosus that contributed 2.1% of the total catch and 2.4% of the shellfish catch (Figure 3).

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Figure 3: Relative abundance of dominant species (accounting for >1% of relative abundance) observed in the catch assessment survey *Shellfish species

4.1.1.1 Fishing gear composition

Five fishing gears are used for the finfish and shellfish exploitation in the seagrass meadows of the bay; basket traps, hook and stick, handlines, nets and spear guns

(Appendix 3). The basket trap was the most dominant gear contributing 75.1% of the total catch by abundance. Basket traps also recorded the greatest richness with 44 species and caught over 90% of the top seven (7) dominant species. Nets recorded 32 species, hook and stick caught 24 species, spear gun caught 17 and handline caught the least number 13 species (Table 1).

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Table 1: Species diversity, the proportion of catch and catch rates of different fishing gears

Gear type Number of Proportion of total Catch rates

species catch (%) (kg/fisher/trip) (± SD)

Basket traps 44 75.1 3.5 ± 1.6

Hook and 24 10.8 3.2 ± 1.7

stick

Spear gun 17 1.4 3.0 ± 2.5

Handlines 13 4.9 2.8 ± 2.6

Nets 32 7.8 3.0 ± 1.9

Taxa composition varied by gears. Overall 91% of total recorded species by abundance were finfish while 9% were shellfish. All gears except hook and stick were dominated by finfish. Basket trap has the highest proportion of finfish individuals (99%), gillnet, handline, speargun recorded 92%, 87% and 86% respectively. Sixty-nine per cent of individuals recorded from hook and stick were shellfish (Table 2).

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Table 2: Relative abundance and species richness of finfish and shellfish captured by different fishing gears

Gear type Relative abundance Species richness

Finfish Shellfish Finfish Shellfish

Basket traps 99.7 0.25 43 1

Nets 92.8 7.2 28 4

Handline 87.1 12.9 12 1

Hook and stick 31.1 69.0 13 11

Spear gun 86.7 13.3 15 1

All gears 91.0 9.0 74 10

Species composition varied by gear, however, same species appeared in several of the fishing gears such as L.fulviflamma that appeared in basket traps, handline and nets and

L.lentjan appeared in basket traps and handline. L. vaigiensis dominated basket traps followed by S.ghobban and L.fulviflamma. C.ramosus, M.cinereus and S.latimanus dominated hook and stick. Handlines were dominated by L. fulviflamma, L.lentjan and

L.harak. Catches from nets were dominated by P.lineatus, S.sutor and L.fulviflamma while the speargun was dominated by S.psittatus, O.vulgaris and M.cinereus (Figure 4).

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Figure 4: Species catch composition by fishing gears observed in the seagrass meadows showing dominant species with the relative abundance of > 5% by numbers

The non-Metric Multidimensional Scaling (nMDS) plots by fishing gears showed three distinct groupings of species; The first group comprised of basket trap, the second comprised of gillnets and handline and the third group comprised of speargun and hook and stick (Figure 5). The plot by season showed a separation of species by seasons

(Figure 6). ANOSIM results showed no significant difference in species composition by seasons (R = -0.08544, p > 0.05) but a significant difference by fishings gears. (R =

0.697; p < 0.05).

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Figure 5: Non-Metric Multi-Dimensional Scaling (nMDS) showing the separation of species by different fishing gears

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Figure 6: Non-Metric Multi-Dimensional Scaling (nMDS) showing the separation of species by seasons.

4.1.1.2 Seasonal variation

A total of 1473 individuals representing 46.2% of the total individual landed from 63 species were observed during NEM while 1714 individuals accounting for 53.7% of all individuals landed and representing 76 species were observed during SEM. Species composition varied by seasons although, in both NEM and SEM Leptoscarus vaigiensis was the most abundant accounting for 48.5% and 15.6 % respectively. Five of the top seven species during both NEM and SEM were similar but with different relative abundance (Figure 7 & 8).

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Figure 7: The relative abundance (%) of the fish species caught during the Northeast monsoon (NEM).

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Figure 8: The relative abundance (%) of the fish species caught during the southeast monsoon (SEM).

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4.1.2 Underwater Visual Census (UVC)

A total of 675 individuals from 33 species representing 24 families were observed with

UVC in a total area of 5000 m2 (Appendix 2). Finfish comprised 52.7% of the total number of individuals from eighteen species observed while 47.3% were shellfish representing fifteen species. The most abundant families were Diadematidae and

Toxopneustidae recording densities of 17.6 ± 12.9 (SD) and 17.6 ± 8.5 (SD) individuals/1000 m2 respectively. Other abundant families included Labridae and

Scaridae recording densities of >10 individuals/1000 m2. The families Fistularidae,

Hexabranchidae and Holothuriidae recorded the lowest density all with 0.2 ± 0.2 (SD) individuals/ 1000 m2 (Figure 9). Tetraodontidae was most diverse family recording 5 species; Arothron hispidus, Arothron immaculatus, Arothron nigropunctatus

Canthigaster compressa, Canthigaster solandri. Diademantidae was the second most speciose recording 4 species. Mullidae, Oreasteridae and Strombidae recorded two species each. All the other families recorded one species each.

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Figure 9: Total family density (number of individuals per 1000m2) recorded in the Underwater Visual Census Error bars are standard errors.

Tripeustes gratilla was the most common species observed with a mean density of 17.6

± 8.5 SD individuals/1000 m2 while Astryuga radiata recorded the lowest density (0.2 ±

0.2 SD individuals/1000 m2) (Appendix 2). Other common species observed included

Diadema setosum (14.6 ± 12.0 SD), Thalassoma amblycephalum (11.8 ± 4.8 SD ),

Leptoscarus vaigiensis (10 ± 3.0 SD), Lutjanus fulviflamma (8 ± 3.5 SD) and Siganus sutor (7.6 ± 3.1 SD) (Figure 10).

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Figure 10: Total species density (number of individuals per 1000m2) recorded in the Underwater Visual Census Error bars are standard errors.

Herbivore was most dominant functional groups for both Catch Assessment Survey

(CAS) and Underwater Visual Census (UVC) accounting for 48% of total catch and

52% of the total observed individuals respectively. Omnivores were the second most dominant by abundance accounting for 43% and 19% for CAS and UVC respectively.

Other functional groups recorded included carnivores, piscivores, invertivores and detrivores recorded in both CAS and UVC and planktivores recorded in UVC only

(Figure 11).

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Figure 11: The relative abundance of different functional groups observed in the catch assessment survey and underwater visual census.

Species of conservation interests Several species of conservation concern listed in the IUCN Redlist of threatened species were recorded in the catch assessment survey. Four species of groupers: Cephalopholis boenak, Epinephelus coioides, Epinephelus longispinis, Epinephelus malabaricus were observed in basket trap catches. Speargun captured three species of rays and one species of grouper; Himantura gerrardi, Neotrygon kuhlii, Pastinachus sephen and Epinephelus malabaricus. Nets captured one species of ray; Himantura gerrardi and one species guitarfish Rhynchobatus djiddensis.

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Catch rates The overall catch rate across all gears was 3.3 ± (1.8 SD) kg/fisher/trip. The catch rate was highest in basket traps; 3.5 ± 1.6 kg/fisher/day while handline recorded the lowest catch rate; 2.8 ± 2.6 kg/fisher/day (Table:1). There was significant variation in catch rate among the fishing gears (Kruskal-Wallis, p < 0.05) (Figure 12). Posthoc pairwise comparison revealed significance between basket trap and handline, basket traps and nets and basket traps and spear gun.

Figure 12: Median catch rates (with 25%, 75% quartiles) of fishing gears during both

SEM and NEM used in the seagrass meadows with Kruskal-Wallis test. Black dots indicate outliers.

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Size structure The length distribution of the four abundant species; L.vaigiensis, S. ghobban,

L.fulviflamma, and L.lentjan (Figure 13), sampled ranged between 8.8 cm and 32.6 cm.

L. vaigiensis individuals sample ranged between 11.3 cm and 23.3 cm with a mean of

16.8 ± 2.3 cm, S. ghobban ranged between 10.7 cm and 32.6 cm with a mean of 16.1 ±

5.3 cm, L. lentjan ranged between 8.8 cm and 29.7 cm with a mean of 15.8 ± 6.9 cm while L. fulviflama ranged between 10.0 cm and 25.1 cm with a mean of 16.7 ± 3.3 cm.

The mean lengths of L. lentjan and S. ghobban were below length at first maturity.

The proportion of juvenile retention varied by species and fishing gears. Overall, 41.5% of the seven most abundant species landed were immature. All individuals from S. ghobban and L. nebulosus landed were immature while L. lentjan recorded 71.4% L. vaigiensis recorded, 24.5%, L. fulviflamma, 29.3 %, S. sutor 70.0 %. All individuals from P. lineatus landed were mature. Three gears; basket trap, handline and nets caught immature indivuals of the dominant species with a proportion of 41.9%, 37.3% and

37.7% respectively. In basket traps 5 of the 7 dominant species caught had proportion of immature individuals. These species were L.vaigiensis, S.ghobban, L.fulviflamma, L. lentjan and L.nebulosus and recorded 24.5%, 110%, 28.4%, 96.2% and 100% of immature individuals respectively. All individuals of S.ghobban and 69% of S. sutor caught by gillnet were immature while handline captured immature individuals of

S.ghobban, L.fulviflamma and L.lentjan at 100%, 50% and 16.7% (Table 3).

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Figure 13: Size frequency distribution of four dominant species with Length at first maturity (Lmat) (blue line) for L.vaigiensis (15.1 cm), L.lentjan (20.3 cm), L.fulviflamma (15.6 cm), S.ghobban (40.0 cm), A, B, C, D respectively. Lmat values were obtained from Mangi & Roberts (2006) and FishBase.

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Table 3: Proportion (%) of individuals under the length at first maturity (Lmat) of the most dominant species by fishing gear. ND - no data in the catch

Basket trap Gillnet Handline Leptoscarus 24.5 ND ND vaigiensis Scarus ghobban 100 100 100 Lutjanus fulviflamma 28.4 ND 50 Lethrinus lentjan 96.2 ND 16.7 Lethrinus nebulosus 100 ND ND Plotosus lineatus 0 ND ND Siganus sutor 0 69.0 ND All species 41.9 37.7 37.3

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CHAPTER FIVE: DISCUSSION

Using catch assessment surveys and underwater visual survey this study recorded 113 species of finfish and shellfish of which 87 were finfish and 26 were shellfish in the seagrass meadows of Gazi bay. Despite of recorded species, the results revealed that a few species dominate catch in the catch assessment survey. The study also recorded five different fishing gears used in the exploitation of finfish and shellfish in the seagrass meadows of the bay. The fishing gears catch are not selective in the size of target species capturing both mature and immature individuals. The relatively high number of species recorded in this study is due to the physical and biological structure of seagrass meadows. The high productivity of seagrass and epiphytes that attached to them act as a source of food of various species within the tropical seascape (Heck et al., 2008,

Nordlund & Gullstrom, 2013). The structural complexity of seagrass meadows offers sites for attachment providing refugia and hiding places for finfish and shellfish to avoid predation (Farina et al., 2009). Most of these species are of commercial and subsistence value and are exploited by adjacent communities for food and livelihood as observed in the study. The capture of taxa such as butterflyfishes of the family Chaetodontidae that are coral reef residents indicates that seagrass meadows support biodiversity from the adjacent habitats and emphasizes their linkage with other coastal habitats.

This study recorded the dominance of herbivores such as L.vaigiensis and S.ghobban in both catch assessment survey and Underwtaer Visual Census highlighting the importance of seagrass meadows to directly provide food to herbivores and indirectly to other functional groups such as carnivores and piscivores that were also observed in this study. These results support other observations that have shown seagrass meadows harbour a diverse range of herbivores that influence and mediates different ecological

43 process within the seagrass habitat (Scott et al., 2018). Herbivory is important in structuring seagrass habitats. For example, overgrazing by any form of herbivores can reduce productivity in tropical seagrass meadows (Unsworth et al., 2017). In contrast, mesograzers have been shown to substantially reduce seagrass epiphytes leading to increase in seagrass biomass (Myers and Heck, 2013).

The multispecies exploitation observed in this study is common in tropical marine fisheries and has been previously reported (Kimani et al., 1996; McClanahan & Mangi,

2002; Samoilys et al., 2017). Although this is beneficial to the species assemblage as the fishing pressure is spread over many species, the results of this study showed only seven species accounted for over 70% of the total catch. This has also been previously reported in the country (Hicks & McClanahan, 2012; Samoilys et al., 2017). This pattern of a few species dominating catch, indicates that there may be selective pressure on the few species that might lead to their overexploitation. Some species such as Leptoscarus vaigiensis, Lethrinus lentjan and Siganus sutor which were dominant in this study have earlier been reported as overexploited (Hicks and McClanahan, 2012).

This study found that common fishing gears employed in small-scale fisheries in the country are used in the seagrass meadows of Gazi bay. Four of the dominant gears recorded in this survey; basket traps, nets, handline and spear gun are among the most dominant fishing gears along the Kenyan coast targeting reef species (Gomes et al.,

2014; Samoilys et al., 2017). This finding demonstrates that gears used in other shallow marine fisheries are also employed in seagrass meadows. Additionally, handline, gillnets, hand collection and spear gun observed in this study have also been recorded in a global analysis of major fishing methods in seagrass meadows (Nordlund et al., 2017) further suggesting some similarity in seagrass exploitation worldwide.

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The fishing gear with the highest proportion of catch the basket trap a dominant gear in the south coast of Kenya deployed in coral reefs and seagrass areas. Although it is considered as a traditional fishing method it has been reported to capture immature fish

(Tuda et al., 2016). This was also observed in this study.

The hook and stick fishing method recorded the second-highest proportion of the total catch by abundance. The method recorded unique invertebrate species such as Chicoreus ramosus, Sepia latimanus, Loligo duvaucelli, that are rarely reported in small scale fisheries. The presence of a large seagrass meadow exposed during low spring tides enables accessibility of the meadows to the small-scale fishermen with limited investments such as using hook and stick or bare hands a method has has been commonly referred as gleaning. Hook and stick in seagrass ecosystems is widely carried out in the region (Unsworth & Cullen, 2010, Nordlund et al., 2010) and elsewhere in the world (Anderson et al., 2011) and is acknowledged as an easy and cheap exploitation method and important in the provision of food and income to the local communities.

However, it is usually unreported, unregulated and its contribution to small-scale fishery mostly ignored (Unsworth et al., 2018). This was also observed in this survey as some of the fishers did not take their catch at the landing sites. The results of this study highlighted that hook and stick is an important part of the small-scale fishery yielding catch rates comparably to or more than other common fishing gears such as basket traps and handline.

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The results of nMDS and total catch indicated distinct separation by season and higher proportion of total catch by abundance (53.7%) during SEM compared to NEM that recorded 63 species and 46.2% of total catch This could be due to reduced fishers effort within the bay during NEM compared to SEM as most fishers venture out of the bay to offshore fishing grounds during the calm NEM season. The non-Metric

Multidimensional Scaling (nMDS) showed distinct separation of species assemblage by fishing gears. This may be as a result of differences in selectivity and operation of the fishing gears as previously reported by Mangi et al., (2007).

Results on size composition of the catch showed that three gears, basket traps, handline and nets caught immature individuals indicating recruitment overfishing; the harvesting of too many fish before they have matured, so that the replenishing potential is restricted

(Pauly, 1988). Similar results have been reported by Hicks & McClanahan (2012) and

Tuda et al., (2016) suggesting that common fishing gears used in small-scale have an impact on the size structure of the exploited species. The capture of immature individuals may be rekated to the fact that, seagrass meadows act a nursery grounds for numerous tropical fish families such as Lethrinidae, Lutjanidae, Mullidae and Siganidae

(Gell & Whittington, 2002). There is, therefore, a need for gear restrictions within the seagrass areas to protect the juvenile individuals. Several gear-management interventions have been recommended in small-scale fisheries in the country. Gear- restrictions are effective management tools with both ecological and socio-economic benefits (Hicks & McClanahan, 2012). They can be adapted for different fisheries management context to protect particular key species based on their life history and body sizes. For example, modification of basket traps to include an escape gap or increasing the mesh size has been found to significantly increased the mean length of

46 captured fish reducing the proportion of immature individuals (Gomes et al., 2014, Tuda et al., 2016). However, neither gated traps or increase in the mesh size have been adopted at Gazi bay. One possible explanation for this is that, although these measures may have positive impacts in the long term, they may have some short-term loss in revenue for fishers (Tuda et al., 2016). This might suggest social-economic factors should be considered in recommending the adoption of fishing methods even when there is evidence of their environmental sustainability. Additionally, concerns on the effectiveness of some of these measures such as the increase in mesh sizes in managing a multispecies fishery have been raised. For example, it’s difficult to come up with the optimum size of the mesh as the exploited species have a range of sizes (Munro, 1996).

The study recorded catch rates of 3.5 ± 1.6 (SD) kg/fisher/day and 3.0 ± 0.5 (SD) kg/fisher/day respectively for basket trap and speargun which was slightly higher compared to 2.0 ± 0.1(SD) kg/fisher/day and 3.2 ± 0.1 (SD) kg/fisher/day recorded by

Tuda et al., 2016 in the same area. This might indicate that seagrass meadows had high catch rates that average of all other habitats as sampled by Tuda et al., 2016. Generally, catch rates in artisanal fisheries in Kenya have declined over the last decades (Samoilys et al., 2017). This has been suggested to indicate declining fisheries resulting from high fishing pressure, the use of destructive fishing methods and habitat deterioration (Mangi

& Roberts, 2006; Tuda & Wolff, 2015; McClanahan & Abunge, 2014).

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The Underwater Visual Census recorded 675 individuals from 48 species representing

32 families lower than a previous study investigating fish diversity within the creeks of the bay that recorded 75 species from 40 families (De Troch et al., 1996). The difference in diversity may be due to the different sampling methods used. This study employed

Underwater Visual Census using snorkelling and this might have affected the behaviour of species towards the observer. Species may initiate a flight response in the presence of the observer and move away from the observer and not be counted (Watson et al., 1995).

Additional the structural complexity of seagrass meadows provide areas where individuals can hide and avoid detection by the data collector. De Troch et al., (1996) employed a beach seine which is efficienct in capturing all the fauna within a transect.

This study recorded the sea urchin species Tripnesutes gratilla as the most abundant species in Underwater Visual Census. This species is a macroherbivore and common in seagrass meadows grazing on seagrass and associated macroalgae (Eklof et al., 2006). A high abundance of this species can be related to several factors with overfishing of sea urchin predators such as balistids (triggerfishes) and lobsters suggested as one of the main drivers. Other factors such as pollution, diseases and the life-history of sea urchins as r-selected species also cannot be overlooked (Eklof et al., 2006).

48

CHAPTER SIX: CONCLUSION AND RECOMMENDATIONS

6.1 Conclusion

This study highlighted that seagrass meadows of Gazi bay supports a diverse assemblage of finfish and shellfish that support small-scale fisheries. The seagrass meadows also support species from other adjacent habitats therefore enhacing cross-habitat utilization of species within the seascape. The results also show that fishing is widely carried out in the seagrass meadows evidenced by the diverse gears that are used. The different fishing gears have catch rates higher than what has been reported for the small-scale fishery in the country. The different exploitation methods are catch species of a wide range of sizes including immature individuals. This can have an impact on the size structure of the species assemblages that are targeted.

6.2 Recommendations

This study showed that various fishing gears capture immature individuals from the seagrass meadows. It is critical to develop sound management action and restrictions on the fishing gears that are used in the seagrass meadows to protect the habitat and the exploited species. Seagrass meadows are usually included in management measures as nursery grounds however, this study showed that they are also important fishing grounds and therefore it is critical to include them in the seascape management as a nursery, breeding and fishing ground within the ecosystem approach. The study was carried out in a relatively small bay in the south coast of Kenya, however, seagrass meadows are distributed throughout the Kenyan coast, future research should focus on a larger geographical scale to capture different socio-ecological aspects of exploitation in seagrass meadows. This study reported the hook and stick fishing method that

49 contributes substantially to fisheries productivity. Future research work should be conducted to understand the impacts on this fishing method to the habitat and exploited species.

50

REFERENCES

Anam, R. & Mostrada, E. (2012). Field identification guide to the living marine

resources of Kenya. FAO. Species Identification Guide for Fishery Purposes.

Rome: FAO.

Anderson, S. C., Mills, F. J., Watson, R. & Lotze, H. K. (2011). Rapid global expansion

of invertebrate fisheries: Trends, drivers, and ecosystem effects. PloS ONE, 6,

e14735.

Bjork M., Short F., Mcleod, E. & Beer, S. (2008). Managing Seagrasses for Resilience

to Climate Change. IUCN, Gland, Switzerland. 56pp.

Bosire, J.O., Okemwa, G. & Ochiewo, J. (2012). Mangrove linkages to coral reef and

seagrass ecosystem services in Mombasa and Takaungu, Kenya. London:

Ecosystem Services Poverty Alleviation Programme.

Bouillon, S., Dehairs, F., Velimirov, B., Abril, G., & Borges, A. (2007). Dynamics of

organic and inorganic carbon across contiguous mangrove and seagrass systems

(Gazi Bay, Kenya). Journal of Geophysical Research, 112, 1–14.

Choat, J. H., & Clements, K. D. (1998). Vertebrate herbivores in marine and terrestrial

environments: a nutritional ecology perspective. Review of Ecology and

Systematics, 29, 375–403.

Choat, J. H., Clements, K. D., & Robbins, W. D. (2002). The trophic status of

herbivorous fishes on coral reefs. I: dietary analyses. Marine Biology, 140, 613–

623.

51

Cinner, J. E., McClanahan, T.R., MacNeil, A.M., Graham, N.A.J., Daw, T.M.,

Mukminin, A. et al., (2012). Co-management of coral reef social-ecological

systems. Proceedings of the National Academy of Sciences 109 (14), 5219–5222.

Coppejans, E., Beeckman, H., & De Witt M. (1992). The seagrass and associated

macroalgal vegetation of Gazi Bay (Kenya). Hydrobiologia. 247, 59–75.

Cullen-Unsworth, L. C., Nordlund, L. M., Paddock, J., Baker, S., McKenzie, L. J. &

Unsworth, R. K. F. (2014). Seagrass meadows globally as a coupled social-

ecological system: Implications for human wellbeing. Marine Pollution Bulletin,

83, 387–397.

Cullen-Unsworth, L. & Unsworth, R. (2013). Seagrass meadows, ecosystem services,

and sustainability. Environment: Science and Policy for Sustainable Development,

55, 14–28.

De Boer, W.F., van Schie, A.M.P., Jocene, D.F., Mabote, A.B.P. & Guissamulo, A.

(2001). The impact of the artisanal fishery on a tropical intertidal benthic fish

community. Environmental Biology of Fishes 61: 213-229.

De la Torre-Castro, M. & Ronnback, P. (2004). Links between humans and seagrasses—

an example from tropical East Africa. Ocean and Coastal Management, 47, 361–

387.

De la Torre-Castro, M., Di Carlo, G. & Jiddawi, N. S. (2014). Seagrass importance for a

small-scale fishery in the tropics: The need for seascape management. Marine

Pollution Bulletin, 83, 398–407.

De la Torre-Castro. M., S. Frocklin, S. Borjesson, J. Okupnik, & N. S. Jiddawi. (2017).

Gender analysis for better coastal management: increasing our understanding of

social-ecological seascapes. Marine Policy 83:62-74.

52

De Troch, Marleen, Mees, J., Papadopoulos, I. & Wakwabi, E. O. (1996). Fish

communities in a tropical bay (Gazi Bay, Kenya): seagrass beds vs unvegetated

areas. Netherlands Journal of Zoology, 46(3-4), 236–252.

Dorenbosch, M., Grol, M.G.G., Nagelkerken, I. & van der Velde, G. (2006). Seagrass

beds and mangroves as potential nurseries for the threatened Indo-Pacific

humphead wrasse, Cheilinus undulatus and Caribbean rainbow parrotfish, Scarus

guacamaia. Biological Conservation. 129:277-282.

Duarte, C. M. (2002). The future of seagrass meadows. Environmental Conservation,

29, 192–206.

Duarte, C. M., Marba, N., Gacia, E., Fourqurean, J. W., Beggins, J. & Barron, C. (2010).

Seagrass community metabolism: Assessing the carbon sink capacity of seagrass

meadows. Global Biogeochemical Cycles, 24, GB4032.

Duarte, C., Losada, I., Hendriks, I. Mazarrasa, I. & Marba, N. (2013). The role of coastal

plant communities for climate change mitigation and adaptation. Nature Climate

Change 3, 961–968.

Duarte, C.M. & Chiscano, C.L. (1999). Seagrass biomass and production: a

reassessment. Aquatic. Botany. 5, 159-174.

Duarte, C.M. (1996). Growth and population dynamics of Thalassodendron ciliatum in a

Kenyan back-reef lagoon. Aquatic Botany 55:1–11.

Dytham, C. (2011). Choosing and using statistics: a biologist’s guide. Wiley-Blackwell

publisher. 3rd Edition. (i- 298).

53

Eklof, J.S, Kautsky, N. & Malinga, R.H (2006). Effects of tropical open-water seaweed

farming on seagrass ecosystem structure and function. Marine Ecology Progress

Series 325:73-84

English, S., Wilkinson, C. & Baker, V. (1997). Survey Manual for Tropical Marine

Resources. ASEAN-Australia Marine Science Project, Australian Institute of

Marine Science, Townsville, Queensland.

Farina, S., Tomas, F., Prado, P., Romero, J., & Alcoverro, T. (2009). Seagrass meadow

structure alters interactions between the sea urchin Paracentrotus lividus and its

predators. Marine Ecology Progress Series, 377, 131–137.

Fourqurean, J.W, Duarte, C.M, Kennedy, H., Marba, N., Holmer, M., Mateo, M. A,

Apostolaki E.T., Kendrick, G.A., Krause-Jensen, D., McGlathery, K.J. & Serrano,

O. (2012). Seagrass ecosystems as a globally significant carbon stock. Nature

Geoscience 5:505–509

Froese, R. & D. Pauly, (Eds). (2000). FishBase 2000: concepts, design and data sources.

ICLARM, Los Banos, Laguna, Philippines. 344 p.

Fulanda, B., Munga, C., Ohtomi, J., Osore, M., Mugo, R., & Hossain, M. Y. (2009). The

structure and evolution of the coastal migrant fishery of Kenya. Ocean Coastal

and Management, 54, 401–414.

Gell, F.R. & Whittington, M.W. (2002). Diversity of fishes in seagrass beds in the

Quirimba Archipelago, northern Mozambique. Marine and Freshwater research

53, 115-121.

Githaiga, M. N., Kairo, J. G., Gilpin, L., & Huxham, M. (2017). Carbon storage in the

seagrass meadows of Gazi Bay, Kenya. PLoS ONE, 12(5), e0177001.

54

Gomes, I., Erzini, K., & McClanahan, T. R. (2014). Trap modification opens new gates

to achieve sustainable coral reef fisheries. Aquatic Conservation: Marine

Freshwater Ecosystems, 24, 680–695.

Graham, N.A., Wilson S.K, Jennings S, Polunin N.V, Robinson J, Bijoux J.P, & Daw

T.M. (2007). Lag effects in the impacts of mass coral bleaching on coral reef

fish, fisheries, and ecosystems. Conservation Biology. 21(5):1291-300.

Green, E.P. & Short, F.T. (Eds.), (2003). World Atlas of Seagrasses. University of

California Press, Berkeley.

Gullstrom, M., Bodin, M., Nilsson, P. G., & Ohman, M. C. (2008). Seagrass structural

complexity and landscape configuration as determinants of tropical fish

assemblage composition. Marine Ecology Progress Series, 363, 241–255.

Gullstrom, M., de la Torre Castro, M., Bandeira, S. O., Bjork, M., Dahlberg, M.,

Kautsky, N., & Ohman, M.C. (2002). Seagrass ecosystems in the Western Indian

Ocean. AMBIO: A Journal of the Human Environment, 31, 588–596.

Harcourt, D., Briers, R. A., & Huxham, M. (2018). The thin(ning) green line?

Investigating changes in Kenya’s seagrass coverage. Biology Letters, 14,

20180227.

Harmelin-Vivien, M.L. & Francour, P. (1992). Trawling or Visual Censuses?

Methodological Bias in the assessment of fish populations in seagrass beds.

Marine Ecology. 13:41-51.

Heck, K. L., Jr., Carruthers, T. J. B., Duarte, C. M., Hughes, A. R., Kendrick, G., &

Orth, R. J. (2008). Trophic transfers from seagrass meadows subsidize diverse

marine and terrestrial consumers. Ecosystems, 11, 1198–1210.

55

Hejnowicz, A. P., Kennedy, H., Rudd, M. A., & Huxham, M. R. (2015). Harnessing the

climate mitigation, conservation and poverty alleviation potential of seagrasses:

Prospects for developing blue carbon initiatives and payment for ecosystem

service programmes. Frontier Marine Science, 2, 32.

Hemminga, M.A & Duarte, C.M (2000). Seagrass Ecology. Cambridge University

Press.

Hemminga, M.A., Slim, F.J., Kazungu, J., Ganssen, G.M., Nieuwenhuize, J., & Kruyt,

N.M. (1994). Carbon outwelling from a mangrove forest with adjacent seagrass

beds and coral-reefs (Gazi Bay, Kenya). Marine Ecology Progress Series 106,

291–301.

Hicks, C. C. & McClanahan, T. R. (2012). Assessing gear modifications needed to

optimize yields in a heavily exploited, multi-species, seagrass and coral reef

fishery. PLoS ONE, 7(5), e36022.

Hoegh-Guldberg O, Mumby P.J, Hooten A.J, Steneck R.S, Greenfield P, Gomez E, et

al., (2007). Coral reefs under rapid climate change and ocean

acidification. Science. 14;318(5857):1737–1742.

Jackson, E. L., Rowden, A. A., & Attrill, M. J. (2001). The importance of seagrass beds

as a habitat for fishery species. Oceanography Marine Biology, 39, 269–303.

Kaunda-Arara, B., Rose, G. A., Muchiri, M. S., & Kaka, R. (2003). Long-term trends in

coral reef fish yields and exploitation rates of commercial species from coastal

Kenya. Western Indian Ocean Journal of Marine Science, 2, 105–116.

Kennedy, Beggins, J., Duarte, C.M., Fourqurean, J.W., Holmer, M. Marba, N., &

Middelburg, J.J (2010). Seagrass sediments as a global carbon sink: Isotopic

constraints. Global Biogeochemical Cycles 24:10

56

Kimani & Mavuti, (2002). Abundance and Population Structure of the black lip pearl

oyster, Pinctada margaritifera L. 1758 (Bivalvia: Pteriidae), in Coastal Kenya

Western Indian Ocean Journal of Marine Science. 1 (2) (2002), pp. 169-179.

Kimani, E. N., Mwatha, G. K., Wakwabi, E. O., Ntiba, J. M. & Okoth, B. K. (1996).

Fishes of a shallow tropical mangrove estuary, Gazi, Kenya. Marine and

Freshwater Research, 47(7), 857–868.

Kitheka, J. U., Ohowa, B. O., Mwashote, B. M., Shimbira, W. S., Mwaluma, J. M., &.

Kazungu, J. (1996). Water circulation dynamics, water column nutrients and

plankton productivity in a well-flushed tropical bay in Kenya. Journal Sea

Research, 35, 257–268.

Ladds, M.A, Sibanda, N., Arnold, R. & Dunn, M. (2018). Creating functional groups of

marine fish from categorical traits. PeerJ. 6: e5795.

Lieske, E. & Myers, R. (2001). Coral reef fishes: Indo-pacific and Caribbean. London:

Harpecollins, 400 pp.

Maina, G. W., Samoilys, M. A., Alidina, H. & Osuka, K. (2013). Targeted fishing of the

shoemaker spinefoot rabbitfish, Siganus sutor, on potential spawning aggregations

in southern Kenya. In J. Robinson & M. A. Samoilys (Eds.), Reef fish spawning

aggregations in the Western Indian Ocean: Research for management.

WIOMSA/SIDA/SFA/CORDIO. WIOMSA Book Series 13

Mangi, S. C. & Roberts, C. M. (2006). Quantifying the environmental impacts of

artisanal fishing gear on Kenya’s coral reef ecosystems. Marine Pollution Bulletin,

52, 1646–1660.

57

Mangi, S.C, Roberts C.M & Rodwell, L.D (2007) Reef fisheries management in Kenya:

Preliminary approach using the driver-pressure-state-impacts-response (DPSIR).

scheme of indicators. Ocean and Coastal Management 50: 463-480.

Marguillier, S., van der Velde, G., Dehairs, F., Hemminga, M.A., Rajagopal, S. (1997).

Trophic relationships in an interlinked mangrove-seagrass ecosystem as traced

by δ13C and δ15N. Marine Ecology Progress Series 151: 115-121.

McClanahan, T. R. (1988). Seasonality in East Africa’s coastal waters. Marine Ecology

Progress Series, 44, 191–199.

McClanahan, T. R. (2008). Malthusian overfishing and efforts to overcome it on Kenyan

coral reefs. Ecological Applications, 18(6), 1516–1529.

McClanahan, T. R. & Abunge, C. A. (2014). Catch rates and income are associated with

fisheries management restrictions and not an environmental disturbance, in a

heavily exploited tropical fishery. Marine Ecology Progress Series, 513, 201–210.

McClanahan, T. R. & Mangi, S. (2001). The effect of closed area and beach seine

exclusion on coral reef fish catches. Fisheries Management and Ecology, 8, 107–

121.

McClanahan, T. R. & Mangi, S. (2004). Gear-based management of a tropical artisanal

fishery based on species selectivity and capture size. Fisheries Management and

Ecology, 11, 51–60.

McClanahan, T., Allison, E. H. & Cinner, J. E. (2013). Managing fisheries for human

and food security. Fish and Fisheries, 16(1), 78–103.

58

McClanahan, T., Maina, J. & Davies, J. (2005a). Perceptions of resource users and

managers towards fisheries management options in Kenyan coral reefs. Fisheries

Management and Ecology, 12, 105–112.

McClanahan, T., Verheji, E. & Maina, J. (2005b). Comparing the management

effectiveness of a marine park and a multiple‐ use collaborative fisheries

management area in East Africa. Aquatic Conservation, Freshwater and Marine

Ecosystems, 16 (2) 147 -165.

Moberg, F. & Ronnback, P. (2003) Ecosystem services of the tropical seascape:

interactions, substitutions and restoration. Ocean and Coastal Management

46:27–46

Munga, C. N., Okemwa, G. M., Kimani, E. N., Wambiji, N. W., Aura, C. M., Maina, G.

W., & Manyala, J. O. (2015). KCDP project. KMFRI research Report No.

OCS/FIS/2014–2015/X. 45 pp.

Munro, J. (1996). The scope of tropical reef fisheries and their management. In: Polunin,

N.C., Roberts, C. (Eds.), Reef Fisheries. Springer, Netherlands, pp. 1-14.

Myers J. A., Heck K. L. (2013). Amphipod control of epiphyte load and its concomitant

effects on shoalgrass Halodule wrightii biomass. Marine Ecological Progress

Series. 483 133–142.

Nordlund, L. M. & Gullstrom, M. (2013). Biodiversity loss in seagrass meadows due to

local invertebrate fisheries and harbour activities. Estuarine, Coastal and Shelf

Science, 135, 231–240.

Nordlund, L. M., Cullen-Unsworth, L. C., Unsworth, R. K. F., & Gullstrom, M. (2018).

Global significance of seagrass fishery activity. Fish and Fisheries, 19, 399–412.

59

Nordlund, L., Erlandsson, J., De la Torre-Castro, M., & Jiddawi, N. S. (2010). Changes

in an East African social-ecological seagrass system: Invertebrate harvesting

affecting species composition and local livelihood. Aquatic Living Resources,

23(4), 399–416.

Nordlund, L.M., Koch, E.W., Barbier, E.B. & Creed, J.C. (2016). Seagrass ecosystem

services and their variability across genera and geographical regions. PLoS One

12(1).

Ochiewo, J. (2004). Changing fisheries practices and their socio-economic implications

in south coast Kenya. Ocean & Coastal Management, 47, 389–408.

Okemwa, G. M., Maina, G. W., Munga, C. N., Mueni, E., Barabara, M. S., Ndegwa, S.

& Ntheketha, N. (2017). Managing coastal pelagic fisheries: A case study of the

small-scale purse seine fishery in Kenya. Ocean & Coastal Management, 144, 31–

39.

Orth, R. J., Carruthers, T. J. B., Dennison, W.C., Duarte, C. M., Fourqurean, J. W.,

Heck, K. L. & Williams, S. L. (2006). A global crisis for seagrass ecosystems.

BioScience, 56, 987–996.

Pandolfi, J.M, Connolly, S.R, Marshall, D.J & Cohen, A.L. (2011). Projecting coral reef

futures under global warming and ocean acidification. Science.

22;333(6041):418–422.

Pauly, D. (1988). Some definitions of overfishing relevant to coastal zone management

in South East Asia. Tropical Coastal Area Management 3(1): 14-15.

Plan Vivo. Mikoko Pamoja, Plan Vivo Foundation, Edinburgh, UK (2015).

http://www.planvivo.org/project-network/mikoko-pamoja-kenya/2015

60

Polidoro, B.A, Carpenter K.E, Collins L, Duke N.C, Ellison A.M, Ellison J.C, et al.,

(2010) The Loss of Species: Mangrove Extinction Risk and Geographic Areas of

Global Concern. PLoS ONE 5(4): e10095.

Potouroglou, M., Bull, J.C., Krauss, K.W., Kennedy, H.A., Fusi, M., Daffonchio, D.

(2017). Measuring the role of seagrass in regulating sediment surface elevation.

Science. Rep. 7:11917.

R Core Team. (2018). R: A language and environment for statistical computing. Vienna:

R Foundation for Statistical Computing. Retrieved from http://www.R-project.org/

Rehren, J., Wolff, M. & Jiddawi, D. (2018). Fisheries assessment of Chwaka Bay

(Zanzibar) – following a holistic approach. Journal of Applied Ichthyology,

34(1), 117–128.

Richmond, M. D. (Ed.). (2011). A field guide to the seashores of Eastern Africa and the

Western Indian Ocean Islands. Dar es salaam: Sida/WIOMSA. 464pp. ISBN

9987-8977-9-7.

Rotherham, & West, R.J. (2002). Do different seagrass species support distinct fish

communities in south‐ eastern Australia? Fisheries Ecology and Management.

9:(4), 235:248.

Ruiz J.M, Pérez M, Romero J (2001) Effects of fish farm loadings on seagrass

(Posidonia oceanica) distribution, growth and photosynthesis. Marine Pollution

Bulletin 42: 749−760.

Samoilys, M.A., Halford, A. & Osuka, K. (2019). Disentangling drivers of the

abundance of coral reef fishes in the Western Indian Ocean. Ecology and

Evolution. 9:4149–4167.

61

Samoilys, M. A., Osuka, K., Maina, G. W. & Obura, D. O. (2017). Artisanal fisheries on

Kenya’s coral reefs: Decadal trends reveal management needs. Fisheries

Research, 186, 177–191.

Samoilys, M., Pabari, M., Andrew, T., Maina, G. W., Church, J., Momanyi, A., &

Mutta, D. (2015). Resilience of coastal systems and their human partners in the

Western Indian Ocean. Nairobi: IUCN ESARO, WIOMSA, CORDIO and UNEP

Nairobi Convention. x + 74pp.

Samoilys, M.A (1997). (Eds). Manual for assessing fish stocks on pacific coral reefs.

The State of Queensland, Department of Primary Industries. pp1-80.

Samoilys, M.A., Maina G.W. and Osuka (2011). Artisanal fishing gears of Kenyan

coast. Mombasa. CORDIO/USAID.

Scott, A.L., York, P.H., Duncan, C., Macreadie, P.I., Connolly, R.M., Ellis, M.T., Jarvis,

J.C., Jinks, K.I., Marsh, H.I. & Rasheed, M.I. (2018). The Role of Herbivory in

Structuring Tropical Seagrass Ecosystem Service Delivery. Frontiers Plant

Science. 9: 127.

Short, F.T., Dennison, W.C., Carruthers, T.J.B. and Waycott, M. (2007). Global seagrass

distribution and diversity: A bioregional model. Journal of Experimental Marine

Biology and Ecology 350: 3-20.

Tuda, P. M. (2018). Assessing the state and impacts of the artisanal reef fisheries and

their management implications in Kenyan south coast (PhD dissertation).

University of Bremen. 135 pp.

Tuda, P. M., & Wolff, M. (2015). Evolving trends in the Kenyan artisanal reef fishery

and its implications for fisheries management. Ocean Coastal Management, 104,

36–44.

62

Tuda, P. M., Wolff, M., & Breckwoldt, A. (2016). Size structure and gear selectivity of

target species in the multispecies, multigear fishery of the Kenyan south coast.

Ocean & Coastal Management, 130, 95–106.

Tuda, P., Nyaga, W., Maina, G. W., Wanyonyi, I., & Obura, D. (2008). Estimating total

fishing effort over tidal to annual periods in the Diani - Chale-Gazi Reef Fishery

in Kenya. In D. O. Obura, J. Tamelander, & O. Linden (Eds.), Ten years after

bleaching - facing the consequences of climate change in the Indian Ocean.

CORDIO Status Report 2008. Mombasa: Coastal Oceans Research and

Development in the Indian Ocean/Sida-SAREC.

Unsworth, R. K. F. & Cullen, L. C. (2010). Recognizing the necessity for Indo-Pacific

seagrass conservation. Conservation Letters, 3, 63–73.

Unsworth R. K. F., Taylor J. D., Powell A., Bell J. J. & Smith D. J. (2007). The

contribution of scarid herbivory to seagrass ecosystem dynamics in the Indo-

Pacific. Estuarine Coastal Shelf Science. 74 53–62.

Unsworth, R. K. F., Nordlund, M. L. & Cullen, U. L. C. (2018). Seagrass meadows

support global fisheries production. Conservation Letters, 2, 12566.

Van der Velde, G., Dehairs, F., Marguillier, S., Mwatha, G.K., Veld, R.L.J.M.,

Rajagopal, S. & Van Avesaath, P.H. (1995). Structural and stable isotope

differences in the fish communities of mangrove creeks, seagrass meadows and

sand flats in Gazi Bay (Kenya). In: Interlinkages between Eastern-African

coastal ecosystems. Netherlands Institute of Ecology, Centre for Estuarine and

Coastal Ecology, Yerseke, The Netherlands, pp. 132-157.

Watson, R.A., Carlos, G., & Samoilys, M. (1995). Bias introduced by the non-random

movement of fish in visual transect surveys. Ecological Modelling 77: 205 – 214.

63

Waycott, M., C. M. Duarte, T. J. B. Carruthers, R. J. Orth, W. C. Dennison, S. Olyarnik,

A. Calladine, J. W. Fourqurean, K. L. Heck, A. R. Hughes, G. A. Kendrick, W. J.

Kenworthy, F. T. Short, and S. L. Williams. (2009). Accelerating loss of

seagrasses across the globe threatens coastal ecosystems. Proceedings of the

National Academy of Sciences of the United States of America 106:12377–12381.

Wylie, L., Sutton-Grier, A.E. & Moore, A. (2016). Keys to successful blue carbon

projects: Lessons learned from global case studies. Marine Policy 65: 76-84.

64

APPENDICES Appendix 1: Relative abundance (%) of finfish and shellfish species observed with Catch Assessment Survey during NEM and SEM

Taxa Families Species NEM SEM

Finfish Scaridae Leptoscarus vaigiensis 48.54 15.64

Scarus ghobban 15.27 5.89

Scarus sordidus - 2.22

Scarus psittatus 1.83 0.47

Scarus rubroviolaceus - 0.058

Lutjanidae Lutjanus fulviflamma 7.47 12.31

Lutjanus sebae 0.00 0.41

Lutjanus kasmira 0.27 0.06

Mullidae Parupeneus barberinus 4.89 1.11

Parupeneus heptacanthus - 0.35

Parupeneus rubescens 0.54 -

Parupeneus indicus 0.07 0.29

Siganidae Siganus sutor 4.01 3.27

Siganus luridus - 0.16

Siganus stellatus 0.20 -

Lethrinidae Lethrinus nebulosus 3.26 8.63

Lethrinus variegatus - 0.12

Lethrinus lentjan 6.45 8.58

Lethrinus mahsena - 0.35

65

Lethrinus elongicutus - 0.06

Lethrinus microdon - 0.06

Lethrinus harak 0.07 2.92

Plotosidae Plotosus lineatus 2.72 5.66

Muraenesocidae Muraenesox cinereus 0.54 3.03

Acanthuridae Acanthurus xanthopterus 0.68 0.41

Ctenochaetus binotatus - 0.06

Labridae Cheilinus chlorourus 0.48 0.06

Cheilio inermis 0.34 0.58

Pteragogus flagellifera - 0.12

Apogonidae Cheilodipterus 0.14 -

quinquelineatus

Chaetondontidae Chaetodon auriga 0.07 -

Chaetodon unimaculatus 0.07 -

Haemulidae Plectorhinchus schotaf 0.07 -

Plectorhinchus vittatus 0.07 -

Plectorhinchus chubbi - 1.23

Plectorhinchus gaterinus 0.48 0.76

Plectorhinchus schotaf - 0.70

Plectorhinchus pictum - 0.29

Pomadasys kaakan - 0.35

Plectorhinchus guttatus 0.14 -

Diagramma pictum - 0.58

66

Nemipteridae Scolopsis ghanam 0.07 0.29

Mugilidae Mugil cephalus - 0.99

Gerreidae Gerres oyena - 0.82

Serranidae Cephalopholis boenak - 0.18

Epinephelus coioides - 0.06

Epinephelus longispinis - 0.06

Epinephelus malabaricus - 0.35

Platycephalidae Thysanophrys chiltonae - 0.64

Platycephalus indicus - 0.58

Chirocentridae Chirocentrus dorab - 0.47

Cynoglissidae Cynoglassis zanzibarensis - 0.12

Muraenidae Gymnothorax undulatus - 0.12

Dasyatidae Himantura gerrardi - 0.12

Neotrygon kuhlii - 0.12

Pastinachus sephen - 0.12

Scombridae Scomberoides lysan - 0.12

Rastrelliger kauagurta - 0.06

Belonidae Ablennes hias - 0.06

Albulidae Albula vulpes - 0.06

Monacanthidae Aluterus scriptus - 0.06

Carangidae Carangoides ferdau - 0.06

Caranx heberi - 0.06

Caranx ignobilis - 0.06

67

Trechinotus blochii - 0.12

Monodactylidae Monodactylus argenteus - 0.06

Pomacathidae Pomacanthus imperator - 0.06

Balistidae Pseudobalistes fuscus - 0.06

Rachycentridae Rachycentron canadum - 0.06

Rhinidae Rhynchobatus djiddensis - 0.06

Total 31 70

Shellfish Muricidae Chicoreus ramosus - 3.97

Portunidae Portunus pelagicus 0.54 1.22

Thalamita crenata - 0.12

Thalamita poisson - 0.06

Sepiidae Sepia pharaonis 0.48 1.28

Sepia latimanus - 2.92

Holothuriidae Actinopyga mauritiana 0.14 -

Holothuria scabra 0.07 0.06

Ostraciidae Lactoria cornuta 0.08 0.06

Loliginidae Loligo duvaucelli 0 2.51

Sepioteuthis lessoniana 0 0.64

Cypraeidae Cypraea tigris 0 1.46

Paliniridae Panulirus ornatus 0 1.28

Fasciolariidae Pleuroploca tapezium 0 1.28

Octopodidae Octopus vulgaris 0 0.41

Total 10 15

68

Appendix 2: Mean density ( ± se) (Individuals/1000m2) of species observed with Underwater Visual Census (UVC)

Taxa Families Species Mean density (±

se)

Finfish Acanthuridae Acanthurus nigricauda 1.2 ± .088

Aplysiidae Dolabella auricularia 1.0 ± 0.70

Carangidae Caranx lugubris 5.0 ± 4.41

Chaetodontidae Chaetodon lineolatus 1.8 ± 1.60

Ephippidae Platax orbicularis 3.4 ± 3.20

Fistularidae Fistularia commersonii 0.40 ± 0.40

Labridae Thalassoma 11.8 ± 4.80

amblycephalum

Lethrinidae Lethrinus harak 7.2 ± 2.93

Lutjanidae Lutjanus fulviflamma 8 ± 3.50

Mullidae Parupeneaus barberinus 4.0 ± 2.80

Parupeneaus indicus 1.0 ± 0.81

Scaridae Leptoscarus vaigiensis 10 ± 3.02

Siganidae Siganus sutor 7.6 ± 3.12

Syngnathidae Syngnathoides biaculeatus 0.80 ± 0.80

Tetraodontidae Arothron hispidus 3.60 ± 2.15

Arothron immaculatus 0.80 ± 0.80

Arothron nigropunctatus 2.0 ± 1.31

Canthigaster solandri 2.6 ± 2.40

Finfish total 14 18

69

Shellfish Callapidae Calappa hepatica 1.2 ± 1.0

Cypraeidae Cypraea tigris 4.20 ± 1.75

Diadematidae Astropyga radiate 0.20 ± 0.20

Diadema savignyi 2.0 ± 1.41

Diadema setosum 14.6 ± 12.04

Echinothrix diadema 0.80 ± 0.80

Echinometridae Echinometra mathaei 2.6 ± 1.93

Hexabranchidae Hexabranchus marginatus 0.40 ± 0.28

Holothuriidae Holothuria atra 0.40 ± 0.40

Oreasteridae Culcita schideliana 0.40 ± 0.40

Protoreaster lincki 3.60 ± 1.66

Pinnidae Pinna muricata 6.8 ± 3.59

Strombidae Lambis lambis 1.2 ± 1.20

Strombus gibberulus 6.8 ± 4.31

Toxopnuestidae Tripneustes gratilla 17.6 ± 8.54

Shellfish total 10 15

Total (finfish 24 33 and shellfish

70

Appendix 3: Five fishing gears recorded in catch assessment survey. A. Basket trap, B. Speargun, C. Hook and line D. Nets and E. Hook and stick

A B

C D

E