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Ecosystem Services Economics

Biodiversity Indicators, Ecosystem Services and Local Livelihoods in Small Island Developing States (SIDS): Early Warnings of Biodiversity Change

Sonja Sabita Teelucksingh Department of Economics, University of the West Indies (Trinidad) and Fondazione Eni Enrico Mattei, Italy Charles Perrings ecoSERVICES Group, School of Life Sciences, Arizona State University

July 2010

Papers in this series are not formal publications of UNEP. They are circulated to encourage thought and discussion. The use and citation of

this paper should take this into account. The views expressed are those of the authors and should not be attributed to UNEP. Copies are

available from the EcosystemServices Economics Unit, Division of Environmental Policy Implementation, UNEP, Nairobi, Kenya.

SMALLISLANDDEVELOPINGSTATES 2

DEDICATED TO THE MEMORY OF PROFESSOR DENNIS PANTIN OF THE UNIVERSITY OF THE WEST INDIES, WHO STRIVED ALWAYS TO BE RELEVANT TO THE RESEARCH NEEDS OF HIS COUNTRY AND HIS REGION, WHO ENCOURAGED HIS COLLEAGUES TO FOLLOW IN THIS PATH, AND WHO TAUGHT HIS STUDENTS TO DO THE SAME.


TABLE OF CONTENTS

ABSTRACT

1. INTRODUCTION ............................................................................................................5

2. AFOCUSONMARINE/COASTALBIODIVERSITYINDICATORSINSIDS .............................7

3. POPULATINGTHE SIDSBIODIVERSITY INDICATORS:DATAAVAILABILITY, STATUSAND

TRENDS ...................................................................................................................... 10

4. DRIVERSOFCHANGE .................................................................................................. 19

5. STATEOFBENEFITSDERIVEDFROMBIODIVERSITYINSIDS ......................................... 24

6. CONCLUSIONS ............................................................................................................ 28

APPENDIX1:THEU.N.LISTOFSIDS ............................................................................................ 30

APPENDIX2:THE2010BIODIVERSITYINDICATORSPARTNERSHIP ............................................... 32

REFERENCES................................................................................................................................ 34


ABSTRACT With 2010 upon us, much attention has been focused upon the development and assessment of global indicators by which it is possible to effectively measure the progress toward the stated targets of reduction in biodiversity loss. The ultimate winners or losers of biodiversity changes can only be judged, however, by an analysis that links such indicators of biodiversity change to the ecosystem services they support, and ultimately to the human livelihoods dependent upon these services. This firstly requires a spatial downscaling of existing, aggregate global indicator analyses to more in-depth, micro studies. This paper seeks to bridge this gap with a focus on Small Island Developing States (SIDS). Biodiversity is a crucial component of local livelihoods in SIDS, with marine and coastal biomes in particular contributing significantly to food security and income via their role in the provisioning services of capture fisheries and the tourism /eco-tourism industries. Following the work of Butchart et.al (2010), this paper suggests the subset of individual and aggregate indicators of biodiversity that are particularly relevant to SIDS, discusses the existence of such data, and calculates the current trends of biodiversity at the local and regional levels of SIDS. An adapted DPSIR framework is then used to categorise these indicators, with climate change as a major global driver explicitly incorporated into the analysis. Finally, a framework for the implications for the state of benefits derived from biodiversity in SIDS, and their links to local livelihoods and human wellbeing, is discussed.

KEYWORDS: Small Island Developing States, SIDS, Biodiversity Indicators, Marine, DPSIR, Local Livelihoods


1. INTRODUCTION The Millennium Ecosystem Assessment both recorded the current decline in the world’s biological diversity and assessed its implications in the provision of ecosystem services and human wellbeing. By ensuring proper functioning of functioning of ecosystems that generate a stream of ecosystem goods and services essential to human well being, biodiversity has been identified as fundamental for the sustainability of current and future human livelihoods (Millennium Ecosystem Assessment 2005 [1]). Notwithstanding this, changes in biodiversity continue. Indeed, biodiversity loss has been termed the “central environmental challenge of our time” (Levin 1999). Part of the problem is to identify indicators of change that capture both the physical alteration in ecosystems and their component parts, and the implications this has for human wellbeing. This requires a multi-disciplinary approach (Baumgartner et. al 2006). While ecological research is an essential component of biodiversity studies, economists have begun to play an increasingly important role. Ecology tells us that biodiversity is indispensable for ecosystem functioning and ecosystem services (Kinzig et.al., 2001, Hooper et.al. 2005). Economics tells us that biodiversity’s ultimate value lies in its contribution to ecosystem services that are linked to human livelihoods and wellbeing, the pursuit of which itself places biodiversity at risk (Daily 1997, Polasky et. al 2005). Ecological models can at times over-simplify the economic, political and institutional dimensions of the problem; similarly, economic models can over-simplify ecological effects (Dreschler et. al 2007). One result has been the development of integrated ecological-economic models to overcome such limitations (Perrings et.al 2002, Egoh et. al 2007). Understanding the dimensions of biodiversity loss will come both from better biological models and from a better understanding of the socio-economic causes and consequences of biodiversity change. Underlying these solutions is a need for effective data that can give status indications of the state of biodiversity and integrate into combined models such as these. In this 2010 Year of Biodiversity, much attention has therefore been focused on the development of biodiversity indicators that integrate both ecological and economic concerns1. Along these lines, Butchart et.al (2010) undertake an excellent review of the current status and trends of global biodiversity. While their study (unsurprisingly) concludes that the 2010 targets are far from being met, it also suggests a roadmap for the development of biodiversity indicators. With a variety of available definitions, a broad range of stakeholders with conflicting objectives at varying spatial and geo-political levels, challenges in valuation and a lack of policy measures designed to take into account economic peculiarities, complexity is the hallmark of the biodiversity problem (OECD 1999). Notwithstanding these complications, it is essential to assess the interactions between biodiversity and human wellbeing at both the global scale and in the countries and regions where biodiversity is most rapidly changing. However, given that only a small fraction of existing species have even been named, let alone characterized in terms of their contribution to ecological functioning, ecosystem services and human wellbeing, it is important to adopt a sampling strategy that will help us understand the changes that are taking place without requiring a complete census of species, ecosystems and their services..

1 The Biodiversity Indicators Partnernship (http://www.twentyten.net) presents a thorough framework within which biodiversity indicators can be calculated.


The dominant strategy over the last two decades has been to focus on biodiversity “hotspots” – areas characterized by high levels of endemism, species richness and threat. Most of these are found in the “developing world” (Myers et.al 2000). We consider an alternative biogeographical grouping that has certain advantages as a litmus test of biodiversity change. Specifically, we consider Small Island Developing States (SIDS). These are generally recognized to be the countries that are most vulnerable to biodiversity change (Global Environment Outlook 2003. They are also the countries likely to be the most rapidly affected by at least two of the global drivers of biodiversity change: climate and globalization. In the development literature, ‘small islands’ have never been established as a special case, and were commonly subsumed within the broader category of ‘small countries’ and ‘microstates’, (Bayliss-Smith et. al, 1988). However, from an environmental perspective, small islands have emerged as a particularly interesting category (Brookfield, 1990, Hein 1990). The category of ‘small islands’ now subsumes a wide array of economic, social, political, cultural, climatic and geographic conditions. Both the Millennium Ecosystem Assessment and the Millennium Development Goals explicitly recognize SIDS as a category of analysis in its own right. Geographically, the SIDS are spread across the continents of Africa, Asia, and Latin America and the Caribbean (LAC); a 2008 UN Report classified 51 states into the SIDS category (UN Desa 2007 Development for All) (see Appendix 1). SIDS generally share a number of economic and environmental characteristics that combine to make them good advance indicators both of biodiversity change and the human consequences of that change (Teelucksingh and Nunes 2010, Ghermandi et.al 2010). The underlying characteristic of SIDS is that of vulnerability. Small populations are coupled with high population densities, concentrated in coastal zones that comprise much of the land area. An inevitably high ratio of coastal to total land area means that island ecosystems are characterized by highly coupled terrestrial and marine ecosystems (McElroy et al. 1990). They are also known to be extremely vulnerable to environmental degradation (van Beukering et al. 2007), both in terms of endogenous ecosystem change, as well as exogenous environmental shifts. There is a heavy reliance on natural resource exploitation, with many of the SIDS being “monocrop”, tourism-oriented economies. SIDS are highly vulnerable to natural disasters and climate change impacts. They also exhibit a high degree of economic vulnerability to the world economy due to their dependence on international trade. Indeed, SIDS are amongst the sites where biodiversity is most threatened (Global Environment Outlook 2003). In what follows, we focus on biodiversity indicators in Small Island Developing States.


2. A FOCUS ON MARINE/COASTAL BIODIVERSITY INDICATORS IN SIDS

With 2010 as the headline year for determining progress to halting trends of biodiversity loss, much attention has been given to the ways in which biodiversity changes can be measured. The Convention on Biological Diversity identified 17 headline indicators (CBD 2006); the Biodiversity Indicators Partnership has developed a suite of composite indicators along these lines under 7 key focal areas (see Appendix 2). Many of these indicators have been primarily developed for global calculation and use. Butchart et al (2010) calculated values and trends for many of these indicators at a global level in an effort to assess progress towards the 2010 targets. To downscale the analysis to the level of Small Island Developing States, we focus on marine/coastal indicators. Marineand coastal habitats play a particularly important role in SIDS. For many small islands the marine environment can be the most important economic resource (Bass 1993). Marine resources available to island states can, if properly utilised, significantly contribute to the sustainable development of the country (Dolman 1990). Provisioning services through fisheries resources are particularly important to local livelihoods and the food security of local communities2. Furthermore, a geographic advantage in marine habitat has led to tourism (and, increasingly, eco-tourism) playing significant roles in many island economies. However, if marine resources are ill unmanaged it is the poorer, rural coastal communities of the small island economies who are most heavily impacted. Biodiversity change affects human wellbeing through the effect it has on the flow of ecosystem services. In SIDS this may be measured by the marginal impact of biodiversity change on these industries. Teelucksingh and Nunes (2010) review the existing literature on biodiversity valuation and ecosystem services in SIDS and find studies for only 17 out of the 51 nations that can be identified as Small Island Developing States. In all cases, there are few basic data on biodiversity change. The first step is therefore to measure marine biodiversity change via (1) the development of relevant indicators and (2) the population of these indicators with reliable data. The original list of indicators of the BIP are presented in Appendix 2. Of the 7 focal areas within which the indicators of the BIP are presented, one was deemed to be, in its present state, irrelevant to marine systems - that of “status of traditional knowledge, innovations and practice”.

2 For example, in Seychelles, prepared tuna, fish flours and fresh fish and shrimps accounted for 91% of

total exports of the Seychelles in 2002 (United Nations 2004). However, it is important to note that in many

SIDS, statistics at the aggregate level may not reflect a dominance of the fisheries sector, in particular in the

SIDS that are dominated by monocultural, export-oriented industries. Notwithstanding this, the role of fisheries

in the sustenance and well-being of rural coastal communities of all SIDS is something that cannot be

overlooked.


The indicator for this area is defined as linguistic diversity and indigenous languages. It is feasible that, in the future, other indicators will be developed for this area that may have a bearing on marine and coastal communities; for the present we leave this focal area out of the current analysis. The focal area “Trends in Genetic Diversity” currently refers to two indicators in varying stages of development: ex-situ crop collections, and the genetic diversity of terrestrial domesticated animals. These indicators do not explicitly refer to coastal/marine biodiversity and so for the moment this focal area will not be considered here. However, note that the genetic diversity of marine animals is deemed to be an essential indicator for SIDS and it is to be hoped (and indeed recommended) that future research focuses on this indicator. The focal area “Ecosystem Integrity and Ecosystem Goods and Services” discusses indicators relating to, among others, the category “Connectivity/Fragmentation of Ecosystems”. The fragmentation of many ecosystems and the subsequent loss of connectivity has significant implications for the flow of ecosystem services. In its current state, this focal area is subdivided into two indicators: forest fragmentation, and river fragmentation/flow regulation. Apart from indirect effects, coastal and marine ecosystems are not explicitly recognized. This is a gap that future research can potentially fill. In the case of small islands, there potentially exists high connectivity between terrestrial and marine ecosystems. However, more work needs to be done to evaluate the implications of connectivity between terrestrial and marine ecosystems in small islands for the flow of economically valuable ecosystem services, and to develop indicators to correctly quantify this. As a result, this focal area is not considered for analysis here. Another category to fall under this focal area is “Biodiversity for Food and Medicine”. Two indicators are suggested by the BIN, “nutritional status of biodiversity” and “biodiversity for food and medicine”. Marine biodiversity available to coastal island communities have a nutritional as well as an income importance in small island developing states, with issues of food security becoming of prime relevance. It is envisaged that for this category, future development of sub-indices of this category can reflect a focus on marine biodiversity. Butchart et al develop a sampled red list indicator for this category. A focal area of considerable potential importance to coastal and marine systems in SIDS is “Sustainable Use”. At present, the BIP presents indicators for this area in three main categories: Areas under Sustainable Management, Proportion of Products derived from Sustainable Sources, and Ecological Footprints. All indicators currently defined under the first category of Areas under Sustainable Management relate to forested and agricultural ecosystems only. It is feasible that in the future an indicator can be added here to target coastal/marine systems, but for the present this one was found to be not relevant to marine systems. We therefore now assemble the subset of the BIP indicators that are suggested to be the most relevant to marine/coastal biodiversity analyses in SIDS (Table 1).


Table 1: Marine/Coastal Biodiversity Indicators for SIDS

SIDS 1. Status and trends of the components of biodiversity SIDS 1.1. Trends in extent of selected biomes, ecosystems and habitats

SIDS 1.1.1. extent of assorted habitats (mangroves, seagrass beds and coral reefs) SIDS 1.2. Trends in abundance and distribution of selected species

SIDS 1.2.1. living planet index SIDS 1.2.2. waterbird indicator

SIDS 1.3. Coverage of protected areas SIDS 1.3.1. coverage of protected areas SIDS 1.3.2. overlays with biodiversity SIDS 1.3.3. management effectiveness

SIDS 1.4. Change in status of threatened species SIDS 1.4.1. red list index and sampled red list index

SIDS 2. Sustainable use SIDS 2.1. Proportion of Products derived from Sustainable Sources

SIDS 2.1.1. proportion of fish stocks in safe biological limits SIDS 2.1.2. status of species in trade SIDS 2.1.3. wild commodities index

SIDS 2.2. Ecological Footprint and related concepts SIDS 2.2.1. ecological footprint and related concepts

SIDS 3. Threats to biodiversity SIDS 3.1. Invasive Alien Species

SIDS 3.1.1. trends in invasive alien species SIDS 3.1.2. international trade measures

SIDS 4. Ecosystem integrity and ecosystem goods and services SIDS 4.1. Marine Trophic Index

SIDS 4.1.1. marine trophic index SIDS 4.2. Water Quality

SIDS 4.2.1. water quality index for biodiversity SIDS 4.3. Health and Well Being of Communities

SIDS 4.3.1. health and well being of communities directly dependent on ecosystem goods and services SIDS 4.4. Biodiversity for Food and Medicine

SIDS 4.4.1. nutritional status of biodiversity SIDS 4.4.2. biodiversity for food and medicine

SIDS 5. Status of access and benefits sharing SIDS 5.1.1. status of access and benefit sharing

SIDS 6. Status of resource transfers SIDS 6.1. Official Development Assistance Provided in Support of the Convention

SIDS 6.1.1. official development assistance provided in support of the convention Table 1 describes 20 SIDS-related indicators, disaggregated across 6 focal areas. We now consider the availability of data to estimate these indicators in the context of SIDS, the location of such data, and the status and trends they reveal.


3. POPULATING THE SIDS BIODIVERSITY INDICATORS: DATA AVAILABILITY, STATUS AND TRENDS

Our discussion takes place on three levels. First, we consider the existing indicators in terms of their level of development. Given that the work of the BIP is current and ongoing, some of the indicators presented in Table 1 above are in formative stages only and are not in a position to be universally and quantifiably assessed3. Second, since we wish to downscale from a global a national/regional scale, an additional question is which of these primarily globally-based indicators can be applied at a sub-global level4. Third, the existence of reliable data at the relevant level of spatial scale for the calculation of the highlighted indices needs to be considered. The measurement of biodiversity through indicators is a burgeoning area, and much data are being routinely collected in the developed but not in the developing world. Indeed, many of the global indicators discussed in Butchart et.al (2010) rely on developed country data. This is a somewhat paradoxical state of affairs since it is widely acknowledged that not only are the developing countries characterized by high levels of biodiversity, but also that these areas are where such levels are under increasingly critical threat. In the absence of existing data for some indicators, the question then becomes what proxies can be used to populate the relevant SIDS indices, and what assumptions need to be made to do so. This highlights the information gaps that currently exist, and indicates areas for future research and monitoring. SIDS 1.1.1 Extent of Assorted Habitats (Mangroves, Seagrass Beds and Coral Reefs) refers to the three biomes of Mangroves, Seagrass Beds and Coral Reefs. Information on SIDS was available for mangroves and coral reefs, but not for Seagrass Beds. Butchart et.al (2010) gather information for this indicator from a published paper on global trends, as well as the UNEP-WMCC World Atlas on Seagrasses. However, comprehensive information on SIDS was not available at either of these sources. Global data for mangroves was available in FAO (2005). It was possible to extract information for 49 SIDS, with no data available for Cape Verde, and the Cook Islands. FAO (2005) presents the most recent reliable estimates of mangrove areas and the reference year of this information. With extrapolation processes, linear regressions, local surveys and qualitative information, this publication also presents estimates for the years 1980, 1990, 200 and 2005, and percentage annual change over the periods 1980-1990, 1990-2000, and 2000-2005. Tables 3 and 4 below summarizes this data.

3 In this context, Butchart et.al (2010), following the work of the BIP, themselves amend the list in accordance with level of indicator construction, in some cases supplementing the BIP by suggesting their own methods of quantifying relevant indicators.

4 The BIP is in the process of developing a portal for national indicators, see http://www.bipnational.net/ - however, this is not yet in a position of applicability, and furthermore, there are not many developing

countries listed in these early pilot stages.


Table 2: Mangrove area (ha) in SIDS and percentage of world total, 1980-2005

Total SIDS World Totals % Composition 1980 2066354 18794000 10.99 1990 1897278 16925000 11.21 2000 1778420 15740000 11.30 2005 1727970 15231000 11.35

Table 2 presents the mangrove areas of SIDS across the four time periods, and also calculates the percentages of world totals. The first point to note is that all SIDS continue to account for around 10% of global mangroves. In addition, total mangrove area in SIDS has been declining from 1990 to 2005, though the percentage share registers an increase due to the greater corresponding decline in world totals.

Table 3: Mangrove area (ha) in SIDS regional composition, and percentage of world regional totals, 1980-2005

1980 1990 2000 2005 Africa (6) 278670 251090 223707 212735

Caribbean (23) 1086162 1033252 1019627 1017483 Asia / Pacific (22) 701522 612936 535086 497752

Total SIDS by Year 2066354 1897278 1778420 1727970 World Totals 18794000 16925000 15740000 15231000

% Composition Africa 1.48 1.48 1.42 1.40 % Composition Caribbean 5.78 6.10 6.48 6.68

% Composition Asia / Pacific 3.73 3.62 3.40 3.27 Table 3 presents a decomposition of the mangrove areas of SIDS with respect to their respective regions. Across the time period, the Caribbean islands account for the major share of mangroves in SIDS, contributing around 6% to world totals. In addition, it is the Caribbean’s share of the world totals of mangrove area that is increasing over time, while the other two regions of Africa and Asia/Pacific show declining areas. All regions register declines in mangrove areas over the period. Data on coral reefs as percentage of world totals were obtained from the “Sea Around Us” website (www.seaaroundus.org). Rather than presenting country specific coral reef estimates, this website presents the fraction of the world’s global coral reef area that occurs in the Exclusive Economic Zone of a given country. This is due to the controversy over estimates of surface area covered by corals in different parts of the world due to issues of definition and issues of scale (Sea Around Us). Presenting the material this way, it is then the responsibility of the user to multiply these percentages by their preferred global estimates. We use here the global estimates of Spalding et.al (2001), as presented in Wilkinson (2008).

Table 4 Coral Reef Cover in SIDS by Region, 2000

Total Africa 1.3 Total Caribbean 4.8 Total Asia/Pacific 30.6 Total SIDS 36.7

Based on these calculations, Table 4 above illustrates the percentage share of global coral cover that can be found in the Exclusive Economic Zones of SIDS. In addition, we are able to demonstrate this share by region. All SIDS together account for a remarkable 36.7% of global


coral cover. Most of this is found in the Asia/Pacific region. African SIDS have the smallest share of global coral cover, accounting for only 1.3% of the total. These data are indicative only given the status of coral reef monitoring. In addition, give estimates of cover only. They do not differentiate between types of coral, or give relative indications as to the health of reef systems. Neither are we able to obtain trends over time. Given the importance of reef ecosystems to island biodiversity, and the provisioning services of fisheries and tourism, a possible proxy to yield reef health over time could be the landings of coral reef fisheries. Such data could feasibly be found on the FAO online databases, as well as the Sea Around Us website (though for the moment the latter does not contain such level of detail for coral reefs), and Reefbase (www.reefbase.org). However, the problems inherent in such a proxy are that changes over time may be indicative of many other factors over and above changing coral reef cover and health, such as over-fishing, species dynamics, gear innovations, ongoing legislations such as the establishment of marine parks or the illegalization of the use of certain types of gear such as blast fishing. Such factors, unless they could be adequately corrected for, would distort the potential correlation of reef fisheries data to reef ecosystem health and stability. SIDS 1.2.1. Living Planet Index measures the health of the world’s ecosystems via trends in veterbrate population abundance over time, within the categories of mammal, bird, reptile, amphibian and fish. The latest Living Planet Report of 2008 presents such data. However, very little information was available for individual SIDS. The SIDS 1.2.2. Waterbird Indicator suggested by the BIN and used by Butchart et.al (2010) is the waterbird population status index, which measures changes in the proportion of waterbird populations. The latest version of Waterbird Population Estimates (Version 4) is available online, but contains no information at a country level. As such, it was impossible to calculate this for SIDS. Information for the indicator SIDS 1.3.1. Coverage of Protected Areas came from the World Database of Protected Areas, http://www.wdpa.org/Statistics.aspx. This includes time series data from 1990 to 2009 for (1) the proportion of marine areas protected (percentage of territorial waters up to 12 nautical miles) (2) the proportion of terrestrial areas protected (percentage of terrestrial area) and (3) the proportion of terrestrial and marine areas protected (percentage of terrestrial area and territorial waters up to 12 nautical miles). Data was distilled for 48 SIDS, with no information available on these parameters for Sao Tome and Principe, the Maldives, and Nauru. According to TwentyTen, the indicator SIDS 1.3.2. Overlays with Biodiversity is comprised of three sub-indicators:

• the degree of protection of terrestrial and marine ecoregions of the world; • the degree of protection of Important Bird Areas (IBAs); • the degree of protection of Alliance for Zero Extinction sites (AZEs).

These sub indicators are based on overlay analyses of ecoregions, IBAs or AZEs with designated protected areas included in the World Database on Protected Areas (WDPA). While the Ecoregion Protection Indicator currently provides only a snapshot of the protection of the world’s ecoregions at a given time, the IBA and AZE Protection Indices show trends over time in the protection of areas of particular importance to biodiversity. Detailed IBA data by country can be found at http://www.birdlife.org/datazone/sites/index.html, and country-specific AZEs can be found at http://www.zeroextinction.org/search.cfm. This information is itself summarised in the IBAT database (www.ibat.org), where numbers of IBAs and AZEs per country are presented.


Table 5 KBAs and AZEs in SIDS

KBA AZE AFRICA 65 11 CARIBBEAN 65 47 ASIA / PACIFIC 133 34 TOTAL SIDS 263 92

Rather than just numbers of sites, Butchart et.al (2010) focus on IBAs and AZEs through the use of downloadable maps to identify spatial overlays of these areas with WPA sites. This is an interesting point of further research on protected areas in SIDS. The declaration of a protected area does not necessarily imply that the area is protected. Nor does it imply that the objectives of protection are fulfilled. It is therefore important that the effectiveness of protected area management be assessed. As a result, the indicator SIDS 1.3.3. Management Effectiveness was developed. There exist a number of management effectiveness evaluation methods that are suggested on the WDPA website at http://www.wdpa.org/ME/searchdatabase.aspx. However, not enough information is available here for the SIDS. The SIDS 1.4.1. Red List Index and Sampled Red List Index measure trends over time in the overall extinction risk of species, as measured by their category of extinction list on the IUCN red list. Data and publications at country level are available on the IUCN website at http://www.iucnredlist.org/about/summary-statistics; in addition, the IBAT database (www.ibat.org) also summarises this information. We highlight in particular the following categories, for which SIDS data are largely available:

• Number of threatened species in each major group of organisms in each country (Critically Endangered, Endangered and Vulnerable categories only)

• Number of extinct, threatened and other species of animals in each Red List Category in each country

• Number of extinct, threatened and other species of plants in each Red List Category in each country

• Total endemic and threatened endemic species in each country (totals by taxonomic group)

However, in sub-global assessments, caution needs to be exercised in the use of Red List indicators. The RLI group was developed for the classification of species at risk of global extinction; that is, for assessment at a global level only. Furthermore, if as in the case of a SIDS analysis we are restricting the discussion to marine indicators, then using Red List information at a country level can be misleading. A species at risk in many countries may not be at risk leveling a particular SID. The IUCN presents guidelines for the development of regional/national indicators at http://www.iucnredlist.org/documents/reg_guidelines_en.pdf. In addition, the IUCN presents sub-global (regional and national) information at http://www.regionalredlist.org. However, there exists no information for any of our 51 SIDS here. One strong possibility for the future is the rigorous use of the IUCN Red List methodology to marine-specific RLIs at a national and regional level of the SIDS. The indicator SIDS 2.1.1. Proportion of Fish Stocks in Safe Biological Limits, is promised in the database of the Millennium Development Goals at http://unstats.un.org/unsd/mdg/Data.aspx. However, a search at country level revealed that hardly any data exist in this database for our 51 SIDS. Butchart et.al (2010) develop this indicator as the proportion of fish stocks that are fully


exploited, over exploited or depleted, with underlying data derived from Ewinger et.al (2009). However, the data in this publication is geared towards global-level analyses and no relevant country specific information exists here. There exists a large country-level data set on the FAO website at http://www.fao.org/fishery/statistics/en; much fisheries data at a country level is also available on the Sea Around Us website at http://www.seaaroundus.org/eez/. However, data along the lines of this indicator for the SIDS are not yet available. In recognition of the fact that international demand, and trade to satisfy this demand, is becoming a significant driver of biodiversity change in many countries, the indicator SIDS 2.1.2., Status of Species in Trade, tracks changes in the status of internationally traded species together with the growth of international trade conventions that are developing to tackle this challenge. Newly developed by the BIN Partnership, this indicator is not yet quantifiable. The IUCN Red List Indicators are suggested as possible ways forward for the quantification of this indicator. Given its recent developments, we are not yet able to quantify this for SIDS. Much like a stock market index, the SIDS 2.1.3 Wild Commodities Index tracks how sustainably a species is being used, through the analysis of population, harvest and market price data. Another newly developed indicator by the BIN Partnership, this indicator is also not yet quantifiable. It is however applicable to national and regional scales and the calculation for key marine species of selected SIDS is a route for the future. While the Living Planet index measures the health of the world’s ecosystems, the SIDS 2.2.1. Ecological Footprint and Related Concepts measures disparities in humanity’s demand on these ecosystems, via a measurement of the area of biologically productive land and water required to provide the resources we use and to absorb our waste assuming average productive capacity. The footprint of a country can be disaggregated into different indicators. Cropland, Grazing, Forest and Fishing Ground Footprints refer to all the cropland, grazing, forest and fishing grounds required, on average, for human consumption. The Carbon Footprint refers to the necessary absorption of carbon dioxide that is emitted through the generation of energy consumed. The Built-Up Land refers to the space needed for infrastructure. To see if ecological limits are being exceeded, the Ecological Footprint is then compared with Biocapacity, which measures the area of biologically productive land available to provide resources and absorb waste. A comparison between the two yields a measure of Ecological Deficit or Reserve. Data for 2006 is available in the Ecological Footprint Atlas at http://www.footprintnetwork.org/images/uploads/Ecological_Footprint_Atlas_2009.pdf. However, data were available for only 6 of 51 SIDS. The indicator SIDS 3.1.1. Trends in Invasive Alien Species, is considered to be one area particularly relevant to SIDS biodiversity. The establishment and spread of Invasive alien species (IAS) can threaten ecosystems, habitats and other species. Economic activity, in particular globalization through trade, is the fundamental cause of IAS introductions (Perrings et. al. 2000, Perrings et.al. 2002, Perrings et al., 2010, Mwebaze et.al 2010). The more open economies are, the more vulnerable they can become to IAS. For economies such as SIDS where openness through export and import dependence is the key to economic survival, this is a very significant issue. Furthermore, the economic and environmental vulnerabilities of SIDS can signal the imposition of heavy economic and human welfare costs as a result of IAS. The effects of IAS on island biodiversity and island economies are explicitly recognized by the BIN Partnership. However, much needs to be done to quantify this challenge in SIDS. Butchart et.al (2010) focus only on European data. Further indicators are needed to reflect the challenge of invasive species in small island developing states.


Table 6:Integration of SIDS in the Global Economy Source: Adapted from Teelucksingh and Nunes (2010)

Country Comoros Grenada Maldives Papua New

Guinea Solomon Islands Trinidad and

Tobago Vanuatu

Main Economic Sector

Vanilla, Cloves, Essential Oils

Nutmeg, frozen albacore, tuna, cocoa beans

Tourism

Silver, petroleum, copper and gold

Wood, tuna, cocoa

Petroleum, natural gas and derivatives

Copra, seaweed, wood and meat

% of Total Exports

94% of 2002 exports

52% of 2003 exports

80% of 2002 exports

71% of 2003 exports

77% of 2002 exports

54% of 2000 export

76% of 2002 exports

Imports (as % of GDP)

39% (2007 figures)

67% (2006) 72% (2000)

68% (2007) 44% (2000) 37% (2007 58% (2006)

The BIN Partnership suggests the development of 5 measured indicators to analyse IAS. Firstly, they refer to the status and distribution of alien species invasion, as measured by the number of documented IAS per country. Data for individual SIDS on this can be distilled from http://academic.sun.ac.za/cib/iasi/index.asp. However, numbers of IAS do not adequately reflect the degree of threat to native ecosystems, and so this indicator needs to be complemented by others. The second suggestion of the BIN Partnership is the use of the Red List Index (RLI) for impacts of invasive alien species. Demonstrating the overall impact of IAS on the global extinction risk of species, this indicator can show the overall impact of IAS on the global extinction risk of species. However, this offers limited information on the problem in the SIDS. An additional two indicators suggested by the BIN Partnership are trends in both national and international IAS policy. These refer to the numbers of national and international policies relevant to IAS. We can distill information for some SIDS from McGeoch et.al (2010) with respect to number of signatory SIDS countries to selected national and international legislation relevant to the control of IAS. The final indicator for this category suggested by the BIN Partnership is a composite global indicator of biological invasion. By combining the previous indicators of numbers of IAS, and national and international policy indicators, this composite measure will yield both the magnitude of the IAS problem and the policy response to it. This indicator is newly developed at the global level, and therefore not yet relevant to sub-global analyses such as this one for SIDS. Given the relevance of this category of IAS for SIDS, and the apparent paucity of aggregated data at national levels on this topic, we suggest here one departure from the BIN Partnership indicators – the amalgamation and use of existing international trade data as a proxy for IAS, with an indicator entitled SIDS 3.1.2 International Trade Measures. Given the role of international trade in the introduction of invasive species, and the high degree of openness of small island economies, international trade data can be used as a possible proxy of measurement for this category. The benefit of such a suggestion is that trade data at national and regional levels are easily available from Balance of Payments accounts at the World Bank or IMF databases. The SIDS 4.1.1. Marine Trophic Index (MTI) measures the mean trophic level of fish catches. Predation is a key process that shapes marine ecosystems and their structure (Pauly and Watson


2005). Because body size is correlated with mouth size, predator-prey size ratios are generally predictable, with predators usually being 3-4 times larger than their prey (Pauly and Watson 2005). In this context, the trophic level at which fishing occurs can be an indication of the status of the biodiversity of the ecosystem from which the landed species come. The assumption is that if fisheries catches consist of increasingly smaller fish or species low in the food web5, this is an indication that resources not being sustainably exploited (Pauly 2005). In this context, the MTI is used as a biodiversity indicator, in particular with reference to the richness and abundance of larger fish species at higher trophic levels (Pauly 2005). If the assumption is made that the relative abundance of taxa in the catch data are representative of the relative abundance of the same taxa in the ecosystem, then declining trends can indicate a decline in the abundance of fishes higher up the food web, therefore indicating a current and potential impact on biodiversity, both in terms of intra-species and inter-species. A related and comparable indicator to the MTI is the Mean Maximum Length (ML). Data for the MTI and the ML in all SIDS is available from the Sea Around Us website (www.seaaroundus.org) from 1950 to 2006. There are many criticisms of the use of the MTI as an indicator of ecosystem health (Pauly and Watson, 2005). In particular, the sensitivity of the MTI to the underlying catch data is vulnerable to the fact that the catch data upon which national statistics may be focused may be inaccurate, and unrepresentative of the abundance of species in the ecosystem. To this end, the Sea Around Us project has undertaken the reconstruction of catch statistics at the country level to reflect the full range of the fisheries of a country. Note that for our 51 SIDS, 11 countries are associated with reconstructed catch data on the project database. A related problem is that of the category of “Miscellaneous Fishes”, for which no MTI can be calculated. The Sea Around Us data includes the MTI based on only reported taxa. A related measure suggested to complement the MTI is the Fishing-in-Balance (FiB) index, which measures the “balance” between catches and trophic level (Pauly 2005). The value of the FiB remains constant if changes in trophic level are matched by equal and opposite changes in ecologically correct changes in catch. An increase in FiB signifies that catches have increased by a greater rate than that predicted by the declines in the associated MTI; similarly, a decrease in FiB indicates increasing catches have failed to compensate for the decrease in the MTI. The data gathered uses 1950 as a baseline year (though the online database of the Sea Around Us allows us to change this reference year). In addition, what is defined as a “measure of transfer efficiency” between the trophic level of an ecosystem is necessary; the default setting of the database is a value of 10%, and the database also allows for a change in this factor. Time series data for the FiB for all SIDS is available from 1950 to 2006. A weakness of the FiB is that it will increase if geographic expansion of the fisheries has occurred (Pauly 2005). This suggests that a better measure of the FiB will be one that is normalized for the geographic areas of the fisheries in a given year. In this context, the Sea Around Us project defines an “Expansion Factor”, calculated as the anti-log of the FiB. This is a preliminary and new indicator that begins to address the issue of spatial expansion which can mask ecosystem trends. Time series data for this is also available for all SIDS on the project website.

5 This is a phenomenon known as “fishing down the food web”, Pauly (2005) and Pauly and Watson

(2005).


The indicator SIDS 4.2.1 Water Quality Index for Biodiversity refers to inland water quality, with specific reference to rivers, lakes, groundwaters and wetlands. The measurement for this are samples taking from monitoring stations worldwide, that collect data on parameters such as temperature, dissolved oxygen, pH, salinity, nitrogen and phosphorus. Though the current SIDS focus is on coastal/marine indicators, this indicator is deemed relevant given the high link between terrestrial and marine ecosystems in small land-masses where much of the area can be defined as coastal zone. Global data exist at http://www.gemstat.org/, where searches can be conducted by country or by watershed. However, there is hardly any information on SIDS. SIDS 4.3.1 Health and Well Being of Communities directly dependent on Ecosystem Goods and Services is currently under development by the BIN Partnership. It is suggested that this can be quantified by a calculation of the “number of rural poor people dependent on threatened ecosystems”. In the context of developing countries in general, this is a key indicator for the effects of biodiversity changes on local livelihoods. But how can this be operationalised? Butchart et.al (2010) develop their own measure by calculating the number of “poor” people living in “remote” rural within “threatened” ecoregions areas (with terms in quotes defined quantitatively but subjectively by the authors) using Marine Habitat Mapping. Data paucity constrains us from replicating this for the SIDS. However, it is possible to envisage a re-definition of such an indicator for SIDS in terms of marine ecosystems. If we make the assumption that most of the coral reef fisheries and coastal fisheries are artisanal ones, then a good proxy for this indicator within SIDS could be employment records for the artisanal fishing industries of these islands. The FAO explicitly recognizes the link among poverty, vulnerability and food security. In this context, the indicator SIDS 4.4.1 Nutritional Status of Biodiversity, relates to food composition. This indicator is newly developed and no data are yet available for the SIDS. Given that this category can have particular relevance in the context of fisheries as the source of nutrition in many SIDS (Ewinger et.al 2008), this index can possibly be amended in the future for a marine focus on SIDS. The indicator SIDS 4.4.2 Biodiversity for Food and Medicine provides the change in conservation status over time in animals used for food and medicine, and provides a baseline for the conservation status of medicinal plants (BIN website). The current food and medicine indicator is based on data from the IUCN Red List of Threatened Species. A Red List Index (RLI) for birds, mammals and amphibians used for food and medicine has been produced. No secondary data was available for SIDS. In addition, the use of RLIs at sub-global levels continues to be a contentious affair. Though identified on the BIN Partnership website, the status of the indicator SIDS 5.1.1. Status of Access and Benefit-Sharing records is “to be determined”. It refers specifically to the issues of access to and distribution of benefits from the utilization of genetic resources. Intellectual Property Rights is a major issue of debate in the economic development literature (Trommetter 2005). The sovereignty of each State over its genetic resources, its ability to control access and its responsibility to negotiate for the fair and equitable sharing of benefits resulting from the exploitation of such resources is explicitly recognised by the Convention on Biological Diversity (CBD) (Nunes et.al 2007, Markandya and Nunes 2008). By ruling out open access to genetic resources, the CBD has established that there exists a value to biodiversity that owners of the resources can exploit (Nunes et.al 2007). This has a potentially significant impact on developing countries, as a considerable part of the genetic material of interest is found in the rural and indigenous communities of the developing world (Markandya and Nunes 2008). The conditions, not only of access, but of benefit sharing therefore become of paramount importance. The CBD


recognises the right of indigenous communities and traditional lifestyles in the conservation and management of genetic resources. The State therefore has the responsibility to ensure the fair and equitable sharing of benefits, which some claim will also increase biodiversity conservation (Trommetter 2005, Markandya and Nunes 2008). The indicator SIDS 6.1.1. Official Development Assistance Provided in Support of the Convention measures aid contributions from the OECD development assistance committee that specifically target the defined objectives of the Convention of Biological Diversity. According to the BIN partnership, indicators for this category are currently under construction and so not yet available. Butchart et.al (2010) suggest the use of statistics on the OECD website at http://stats.oecd.org/qwids/, where classification codes for aid contributions that include explicit references to biodiversity exist. This category as suggested by Butchart et.al (2010) is in fact one of the few that explicitly characterize a dataset for the SIDS. This completes our review of the biodiversity indicators considered particularly relevant to SIDS, their level of development, their relevance to sub-global analyses, their ability to be calculated for SIDS given existing data, and, if such data exists, where it can be found. Finally, it is important to note that there exist inter-linkages among many of the indicators here, and any biodiversity analysis cannot ignore this fact. In fact, it can be argued that as the signposts for biodiversity both global and sub-global, biodiversity indicators should not only be placed within a causal link, but should also be embedded within a framework that connects to the drivers of biodiversity change.


4. DRIVERS OF CHANGE The DPSIR methodology seeks to embed environmental challenges within a socio-economic framework (Maxim et.al 2009, Rodriguez-Labajos et.al 2009, Ness 2010). Societal developments or Drivers cause Pressures to be exerted upon environmental resources, which result in changes in the State of resources. Such changes lead to Impacts on human wellbeing through impacts on ecosystems. Depending on the magnitude of these impacts, this can cause policy Responses at different levels of spatial scale. In its application, there have been various adaptations of the DPSIR framework (Niemeijer and de Groot 2008). However, the underlying methodology of the existence of causal links between environmental changes and socio-economic systems remains constant.

Figure 1: The DPSIR Model Source: Maxim et.al (2009)

The DPSIR framework is characterised by five interlinked parameters. These interlinkages do not, however, occur in a linear, deterministic fashion. As Figure 5 indicates, there may be multiple links between these parameters. Maxim et.al (2009) suggest that the main complexity arises from the Responses parameter that in turn has causal links with every other parameter in the system. The exact form and nature of these interplays depend on the environmental resource being considered, the actors on both the policy and welfare sides, and the level of spatial scale at which the analysis is taking place. However, notwithstanding the debates over the exact nature of the causal chain, it is argued that the investigation of environmental challenges within such a framework as this will lead to a better understanding of what causes environmental shifts, who is affected by them, and how best policy-makers at all levels of scale can respond to these (Niemeijer and de Groot 2008). The DPSIR methodology reflects the fact that there exist feedbacks within the coupled social-ecological system, but leaves open the question of whether the indicators used by decision-makers effectively represent those feedbacks. In economic models, relationships treated parametrically in the DPSIR framework are captured by functional forms that reflect both the state of the system and the effect of institutional conditions, property rights and so on. Proponents of the DPSIR framework argue that it can demystify the complex nature of biodiversity, and in this way lead to more effective responses to biodiversity loss (Spangenberg et.al 2009). They also claim that biodiversity indicators themselves should be framed using


DPSIR (Niemeijer and de Groot 2008)6. One of the pilot applications of the BIN Partnership at the national level, conducted in the Philippines for marine resources, group the applied indicators into Pressure, State and Response categories (BIN website). Walpole et.al (2009) also suggest a set of (interlinked) headline indicators along similar lines, with the identification of the four focal areas of Pressures-Threats, Status-Trends, Benefits-Services and Actions-Responses. In arguing the case for the use of a DPSIR framework for biodiversity indicator selection, Niemeijer and de Groot (2008) present three adaptations of this methodology, differing mainly in the number of elements in the causal chain. The construction of indicators for the drivers of biodiversity change is complicated by the fact that little is known about the effect of a number of drivers from climate change (Walpol et.al 2009, Mooney et.al 2009).to the range of direct anthropogenic stressors (Maxim et.al 2009). The Millennium Ecosystem Assessment identified the most important direct and indirect drivers on biodiversity and ecosystem services to be habitat change, climate change, invasive species, over-exploitation, and pollution, with the driving forces behind such pressures categorised into demographic, economic, socio-political, cultural, religious and scientific/technological changes (Millennium Ecosystem Assessment [3] 2005, Omann et.al 2009). This list collapses the Drivers and Pressures parameters of the DPSIR framework (Maxim et.al 2009). It is also important to note that while the macro-level drivers of biodiversity change have been well documented by the Millennium Ecosystem Assessment, the drivers of change at sub-global levels have been inconsistently documented (Spagengberg et.al 2009). It is important to place the drivers of biodiversity change within a framework recognizes the linkages and feedbacks within socio-ecological systems, and that connects the drivers, their impacts on human welfare at all spatial scales, and the policy responses to these impacts to standardised national and global biodiversity indicators. This can only be achieved once there exists adequate data at national and international levels. In this respect, it is useful if existing biodiversity indicators and the ongoing development of such indicators are placed within a framework such as DPSIR. In this context, we attempt to re-categorise the SIDS biodiversity indicators in Table 1 above using an adapted DPSIR framework, following the recommendations of Walpole et.al (2009), the BIP Partnership and the applications of Butchart et.al (2010). These analyses suggest the categorization of the 4 focal areas of Pressures-Threats, Status-Trends, Benefits-Services and Actions-Responses.

6 However this is not without debate. For example, Spagenberg et.al (2009) claim that DPSIR does not on

its own fit biodiversity research but instead should be adapted or combined with other methodological tools.

Ness (2010) also highlight some of the challenges with respect to the use of a pure DPSIR approach.


Table 7: Marine/Coastal Biodiversity Indicators for SIDS within a DPSIR Framework7

Number Indicator DPSIR Category SIDS 1.1.1. extent of assorted habitats (mangroves, seagrass beds and

coral reefs) Status-Trends

SIDS 1.2.1. living planet index Status-Trends SIDS 1.2.2. waterbird indicator Status-Trends SIDS 1.3.1. coverage of protected areas Actions-Responses SIDS 1.3.2. overlays with biodiversity Actions-Responses SIDS 1.3.3. management effectiveness Actions-Responses SIDS 1.4.1. red list index and sampled red list index Pressures-Threats SIDS 2.1.1. proportion of fish stocks in safe biological limits Pressures-Threats SIDS 2.1.2. status of species in trade Status-Trends SIDS 2.1.3. wild commodities index Status-Trends SIDS 2.2.1. ecological footprint and related concepts Pressures-Threats SIDS 3.1.1. trends in invasive alien species Pressures-Threats

Actions-Responses SIDS 3.1.2. international trade measures Status-Trends SIDS 4.1.1. marine trophic index Impact SIDS 4.2.1. water quality index for biodiversity Status-Trends SIDS 4.3.1. health and well being of communities directly dependent

on ecosystem goods and services Benefits-Services

SIDS 4.4.1. nutritional status of biodiversity Benefits-Services SIDS 4.4.2. biodiversity for food and medicine Benefits-Services SIDS 5.1.1. status of access and benefit sharing Actions-Responses SIDS 6.1.1. official development assistance provided in support of the

convention Actions-Responses

SIDS are known to be extremely vulnerable to environmental degradation (van Beukering et.al 2007). Due to the heavy reliance on natural resource exploitation for economic livelihoods at both micro- and macro-levels, environmental shifts such as ecosystem changes, natural disasters and climate change impacts can have extreme economic and welfare effects8. The main direct drivers of change of biodiversity as identified by the MEA are habitat change, climate change, invasive alien species, pollution (MEA 2005); we can place these drivers in the context of SIDS. In addition, we can distinguish between national, regional and international pressures on biodiversity in SIDS; these categorisations then affect the policy and management responses available to a small island economy (see Table 4 below).

7 Maxim et.al (2009) discuss the ways in which the same variables can be categorized into different

aspects of the DPSIR framework depending on the angle of analysis. As such, it can be considered more of a

discursive rather than an analytical framework.

8 For example, hurricanes are well known to cause considerable amount of damage in the Caribbean, with

the small island developing states of this region in particular highly susceptible to these phenomena.


Table 8: Drivers of Marine/Coastal Biodiversity Change in the SIDS Context

Driver of Change The SIDS Context Relevant Biodiversity

Indicator

Level of Spatial Scale

of Driver

Intra-Linkages among Drivers

Habitat Change

Coral Reef Changes SIDS 1.1.1 national regional

Affects fisheries

Invasive Alien Species Invasive Alien Species SIDS 3.1.1 SIDS 3.1.2

national Affects fisheries Affects coral reefs

Overexploitation Overexploitation of Fisheries

SIDS 2.1.1 SIDS 4.1.1

national regional

Affects coral reefs

C

limat

e ch

ange

Pollution Land-Based Sources of Marine Pollution

SIDS 4.2.1 national regional

Affects fisheries Affects coral reefs

C

limate change

“Habitat change” is focused solely on the status and changes of Coral Reefs. It is estimated that 70% of the world’s coral reefs are threatened or have been destroyed (Obura and Grimsditch 2009). There are large ecosystem service consequences, and therefore human livelihood consequences, of coral reef degradation (Mooney et.al 2009, Ghermandi et.al 2010). “Overexploitation” is taken to refer specifically to fisheries resources. “Pollution” is taken to specifically mean land-based sources of marine pollution, which in the context of SIDS has particular relevance at regional scales. Finally, climate change is introduced, not as a separate driver of change, but an all-encompassing one that simultaneously affects all other drivers. Climate change can be identified as a global driver of biodiversity change in SIDS. As small islands, climate change can have significant direct and indirect effects on economic and social systems, from the erosion of coastal zones due to sea-level rise (which in the case of some SIDS such as the Maldives, is currently of paramount and urgent concern) to the effects of warming seas on coral reef ecosystems upon whose services many local livelihoods depend through coral reef fisheries and tourism activities, to the (debatable) effects of increased frequency and severity of tropical storms. Climate change is considered to be one of the greatest threats to coral reef ecosystems, with mass coral bleaching due to increasing sea temperatures and ocean acidification responsible for much of the present loss of coral cover (Brander et al. 2007, Obura and Grimsditch 2009). There is dramatic evidence of this in terms of mass coral bleaching events in the tropics (Mooney et.al 2009). In terms of fisheries resources, climate change directly affects the distribution of species, the seasonality of specific biological processes and the structure of existing food webs (Ewinger et.al 2009). Climate change can also raise the risk level of species invasions (Ewinger et.al 2009). Underlying this is the inability of SIDS to meaningfully affect climate changes – small islands can be considered “environment-takers”, only able to react and mitigate to global levels. From Table 3 above, there exist relevant biodiversity indicators that can quantify these drivers. It is interesting to note that climate change is not explicitly identified in Table 3. Its impacts can be captured indirectly via an analysis of specific indicators that link to climate change9. For example, Butchart et.al (2010) attempt to incorporate climate change impacts into the Wild Bird Index, by linking the IPCC climate change scenarios with the degree to which it is estimated that European bird population trends have responded to climate changes. With respect to the SIDS, we can therefore consider the interrelated indicators that can be directly affected by climate change, such as the Extent of Coral Reefs (SIDS 1.1.1) and the Proportion of Fish Stocks in Safe

9 Of course, to discuss any driver in isolation from the others is to ignore the synergistic effects among them in terms of their effects on existing ecosystems.


Biological Limits (SIDS 2.1.1). In addition, it is possible to gather international data on sea temperatures and precipitation levels that can indicate our global changing climate. Table 3 also attempts to address the spatial location of each driver of change In the marine context, issues such as the national exploitation of common migratory regional fish stocks, and the transboundary effects of land-based coastal pollution, represent particular challenges in terms of policy actions. National decisions as well as regional externalities lead to changes in marine quality and the resultant ecosystem goods and services. While geographic proximity and shared marine space necessitate regional environmental cooperation of regional SIDS that transcends national political boundaries, island nations remain particularly insular in their approaches to environmental policies. However, due to their characteristics, small island economies and their communities are heavily reliant on these ecosystem goods and services for their livelihoods. Small island economies stand to lose a great deal if marine resources and marine biodiversity are not appropriately managed.


5. STATE OF BENEFITS DERIVED FROM BIODIVERSITY IN SIDS

The approach taken by the Millennium Ecosystem Assessment to understanding the link between biodiversity change and human wellbeing is summarized in Figure 6, .

Figure 2: Linking Biodiversity, Ecosystem Services and Human Wellbeing Source: Millennium Ecosystem Assessment 2005 [6].

The notion of “human wellbeing” and local livelihoods is a complex one. The MEA presents a comprehensive overview of the factors that both comprise and affect the state of human wellbeing, see Figure 2 above (MEA 2005[6]). They suggest that there exists five components to human wellbeing: the basic material needs for a good life, health, good social relations, security, and freedom of choice and action (MEA 2005[6]). They attempt to construct a framework in which both the direct and indirect linkages of these factors to biodiversity and ecosystem services are presented. The hypothesis is that drivers of change impact upon ecosystems and the goods and services they provide, thus affecting human wellbeing. If we are able to quantitatively or qualitatively define these linkages, the impacts upon human well being of decisions that affect biodiversity and ecosystems at any level of spatial scale can then be mapped. In addition, we can theorise as to a number of “feedback” loops: that the supply of ecosystem services themselves can impact the drivers of change, that the state of human wellbeing itself can affect ecosystem services via the increases or decreases of demands placed on these services, and that human wellbeing is directly linked to the drivers of change. In a developing country context, the notion


of human wellbeing and the distribution of the benefits of biodiversity resources through their supply of ecosystem services, or the benefit-sharing component of the ecosystem services provided by the biodiversity resources, is a crucial one. There exist many indicators that are commonly used in an attempt to measure the state of “human wellbeing”. The most common of these is, of course, the GDP of a country (MEA 2005). There exist UN-related measures such as the Human Development Index and the Human Poverty Index, and also many alternatives to this have been developed. In this context, the indicator SIDS 4.3.1 Health and Well Being of Communities directly dependent on Ecosystem Goods and Services seems to be a key indicator for the effects of biodiversity changes on local livelihoods in the context of developing countries in general. However, as discussed above, this indicator is currently under development, with the suggestion that a calculation be made of the “number of rural poor people dependent on threatened ecosystems”. In the meantime, we suggest here that this indicator be developed in a number of different ways to better reflect the SIDS reality, and, furthermore, that in the context of extreme biodiversity data paucity in SIDS, we develop this more localized focus of this indicator in the context of available and existing international statistics databases that offer many quantitative rankings of factors related to human wellbeing. Addressing the question of the role of biodiversity in the productive economic sectors cannot be overlooked. The provisioning services – foods, fuels, fibers etc – are critical to employment and incomes in SIDS, as they are in many other developing countries. This requires indicators that link biodiversity change to changes in ecosystem service flows, and hence to the wellbeing of both producers and consumers (Teelucksingh and Nunes 2010). In the context of the focus on marine/coastal resources in SIDS, we focus on the productive sectors of tourism and fisheries. Fisheries, in particular artisanal fisheries, are important economic resources to local coastal livelihoods in many SIDS (Dhoray and Teelucksingh 2007). In addition, fisheries resources play a crucial role in the food security of many rural SIDS communities (Ewinger et.al 2009). While provisioning services through fisheries resources are particularly important to local communities, tourism industry also plays a significant role in island economies (Teelucksingh and Nunes 2010, Ghermandi et.al. 2010). Furthermore, the Convention on Biological Diversity recognizes ecotourism as a vital growing segment of the tourism industry. Ecotourism is increasingly viewed as an important tool for promoting sustainable livelihoods, cultural preservation, and biodiversity conservation (Honey 2006). Both the fisheries and tourism industries in SIDS, and the local livelihoods they support, are largely dependent on island biodiversity (CBD 2010). Inevitably, these industries can also be linked to biodiversity threats at local and regional levels. Coral Reef biodiversity is of particular importance to island ecosystems. Existing within multiple regions and political jurisdictions, coral reefs and their habitats support the highest marine biodiversity in the world (Obura and Grimsditch 2009). Considered the most diverse ecosystems of the ocean (Debenham 2007), coral reefs occupy approximately only 0.1-0.5% of the ocean floor (Moberg and Folke 1999). Nevertheless, coral reef ecosystems are a significant source of welfare to both developing and developed countries. In addition to provisioning services from reef fisheries, there are significant recreational, cultural and aesthetic values to both local and international communities embedded within coral reef ecosystems. Today, it is estimated that more than 500 million people depend on them for a host of ecosystem services (Obura and Grimsditch 2009). At the same time, coral reef ecosystems face significant threats of degradation. It is estimated that 70% of the world’s coral are threatened or have been destroyed (Obura and Grimsditch 2009). Climate change in particular is considered to be one of the


greatest threats, with mass coral bleaching due to increasing sea temperatures responsible for much of the present loss of coral cover (Brander et al. 2007; Obura and Grimsditch 2009). In addition, human activities such as destructive fishing practices, land-based pollution and non-sustainable tourism act in synergy to place the world’s coral reefs under multiple threats. Access rules – and in particular property rights that allow open access – are also an important source of the sub-optimal use of coral reef resources (and hence their degradation) (Brander et al. 2007). The significant levels of services provided by coral reefs to both national and international communities, the non-market based characteristics of some of these services, and the associated multiple threats and challenges, are the subject of an increasing literature on coral reef valuation. Such studies provide a quantitative estimation of the welfare changes associated with coral reef degradation in order to better inform decision-making processes and to enhance financing of conservation activities. The third category in particular has led to a focus on the valuation of recreational services provided by coral reef ecosystems, with an aim to the capture of greater levels of consumer surplus so as to better aid conservation and ultimately serve the economic interests of the local community stakeholders. Ghermandi et.al (2010) undertake a comprehensive overview of valuation studies on coral reef ecosystems, with particular reference to recreational, cultural and aesthetic services. Table 10: Biodiversity, Ecosystem Services and Local Livelihoods in the SIDS Context

Drivers of Change in the SIDS

(Pressures-Threats)

Biodiversity Indicators

Economic Sector Impact

(Benefits-Services)

Economic Impact

Indicators

Level of Spatial Scale

of Policy Response (Actions-Responses)

Policy Response Indicators

Coral Reef Changes SIDS 1.1.1 Fisheries Tourism

Species Population Levels Employment in Fishing

Tourist Arrivals

National Regional

SIDS 1.3.1 SIDS 1.3.2 SIDS 1.3.3

Invasive Alien Species SIDS 3.1.1

Fisheries

Species Population Levels Regional SIDS 3.1.2

Overexploitation of Fisheries

SIDS 2.1.1 SIDS 4.1.1 Types of Fishing

Methods

Fisheries Tourism

Species Population Levels Catch and Effort Levels

Effort Types Coral Reef Fisheries Data

National Regional

Fisheries Legislation

and monitoring at National

and Regional Levels

Clim

ate

chan

ge

Land-Based Sources of Marine Pollution

SIDS 4.2.1 SIDS 4.1.1

Other indicators needed for

marine quality

Fisheries Tourism

Species Population Levels

Regional Marine Pollution

Legislation and

monitoring at Regional

Levels

Clim

ate Change

With respect to the our focus on SIDS and marine biodiversity, we can create a more focused approach of this framework, linking (1) the drivers of change (2) the economic sector impacts of these changes and (3) the policy responses to these impacts. Table 5 identifies the areas for which no indicators currently exist, and in so doing demonstrating where future indicator development can lie. To begin with, we focus on the provisioning services category, with specific reference to the fisheries and tourism industries. We therefore consider only the “material needs” component of the notion of “human wellbeing” discussed above, linking the contributions of these two sectors


to this component. By identifying the drivers of change (pressures-threats) on the biodiversity of marine ecosystems, and linking these to existing (or non-existing) indicators, we are able to trace the flow to these two economic sectors. In this context, we can develop indicators of economic impact (linking to the benefits-services provided by the biodiversity resources under consideration), such as employment levels in these two industries, and fisheries catch and landings data for specific species. Given these impacts, policy responses (actions-responses) are necessary. It is crucial, however, that these policy responses take place at the correct levels of spatial scale. In the context of SIDS and shared marine spaces, it is not always the case that policy enacted and implemented at national levels will be effective. We therefore identify the level of spatial scale at which the policy discussions should be placed, and the necessary indicators that will demonstrate movement along this path. It is interesting to note that many policy responses are best developed at regional levels. In the context of marine issues and shared marine resources, this is not a surprising finding. However, despite this fact, regional cooperation among SIDS in marine matters continues to be lacking. Finally, the notion of climate-change as an all-encompassing driver affecting every level of the discussion is once again suggested. Taking place at a global level, policy response is also necessary at a global level.


6. CONCLUSIONS What are the implications of this discussion of indicators in Small Island Developing States (SIDS)? As one of the biogeographical regions where international stresses on biodiversity are most likely to result in relatively rapid loss of species, and yet where biodiversity is most important for local livelihoods, SIDS have the potential to serve as an early warning system for future biodiversity change. Using a subset of individual and aggregate indicators of biodiversity that are particularly relevant to SIDS, those concerning marine/coastal systems, we have evaluated the data available for the calculation of the identified marine/coastal biodiversity indicators and discussed current status and trends. There are two reasons to believe that SIDS respond more rapidly to the global drivers of environmental change than other systems. First, because SIDS are dominated by coastal and marine ecosystems, many on a smaller scale than elsewhere, they are particularly sensitive to changes in climate, sea temperature, sea acidity, sea level and extreme weather events. Second, because SIDS are extremely open economies and often highly dependent on tourism, they are subject to the frequent introduction of alien species through trade, transport and travel. Because, at the same time, the biodiversity in SIDS includes a high proportion of specialized endemic species that have evolved with few strong competitors or predators, they are especially vulnerable to introduced alien species. Indeed, invasive species are the leading cause of extinctions in island ecosystems. For both reasons there is an advantage in focusing on trends in biodiversity indicators in SIDS as precursors to trends elsewhere. Of course the ecological responses to external stresses in SIDS would be expected to differ from responses in other systems, but the existence of a strong response to some stressor in SIDS is an alert to the potential importance of the same stressor in other systems. At the same time, the observations needed to track biodiversity indicators in SIDS are few and far between. One of the recurrent themes in the discussion of marine/coastal indicators was lack of data. This makes it impossible, at the moment, to use many of the suggested indicators. However, in a developing country context, lack of data is not entirely a surprise. Developing countries in general face challenges of data collection and monitoring; more so in environmental matters such as biodiversity than in many other areas. Biodiversity indicators are only now being standardized for use at global levels. The work of Butchart et.al (2010) represents one of the first comprehensive attempts to assess global trends using such indicators. Furthermore, it is recognized that even at the global or developed country level, data to populate these indicators is a challenge. Walpole et.al (2010) comment on the “patchy” global data that exists for biodiversity monitoring and calculations, and the need for both global and national data monitoring and capacity building in the area of biodiversity measurement. This paper is more of a discussion of ‘what is not’ rather than ‘what is’. However, such a stock-taking exercise is a crucial one, as it can highlight where further investments are needed. Finally, lack of a complete data set does not preclude us from analyzing the linkages between biodiversity indicators, ecosystem services and local livelihoods in SIDS. Nor does it preclude the development of policies enabling local mitigation or adaptation. For the fisheries and tourism sectors, and the marine resources upon which these can be assumed to depend, there are data on mangroves, coral reefs, and protected areas. This makes it possible to evaluate the impact of at least a sub-set of the policy instruments commonly used to secure biodiversity in coastal zones. In this context, this current discussion therefore seeks to contribute to a sub-global focus on Small Island Developing States, where global biodiversity is most in danger from decisions


taken at national, regional and international levels, and where the effects on human livelihoods are and will continue to be most keenly felt.


APPENDIX 1: THE U.N. LISTOF SIDS (source: UN DESA 2007) Africa Cape Verde Comoros Guinea-Bissau Mauritius Sao Tome & Principe Seychelles Caribbean Anguilla Antigua and Barbuda Aruba Bahamas Barbados Belize British Virgin Islands Cuba Dominica Dominican Rep Grenada Guyana Haiti Jamaica Montserrat Netherlands Antilles Puerto Rico St. Kitts and Nevis St. Lucia St. Vincent & Grenadines Suriname Trinidad and Tobago Virgin Islands, U.S. Asia / Pacific American Samoa Commonwealth of Northern Marianas Cook Islands East Timor Fiji French Polynesia Guam Kiribati Maldives Marshall Islands Micronesia (Federated States of) Nauru New Caledonia


Niue Palau Papua New Guinea Samoa Singapore Solomon Islands Tonga Tuvalu Vanuatu


APPENDIX 2: THE 2010 BIODIVERSITY INDICATORS PARTNERSHIP (source: http://www.twentyten.net) The 2010 BIP fits the indicator suite into 7 focal areas as follows: 1. Status and trends of the components of biodiversity

1.1. Trends in extent of selected biomes, ecosystems and habitats 1.1.1. extent of forests and forest types 1.1.2. extent of assorted habitats

1.2. Trends in abundance and distribution of selected species

1.2.1. living planet index 1.2.2. global wild bird index 1.2.3. waterbird indicator

1.3. Coverage of protected areas 1.3.1. coverage of protected areas 1.3.2. overlays with biodiversity 1.3.3. management effectiveness

1.4. Change in status of threatened species 1.4.1. red list index and sampled red list index

1.5. Trends in genetic diversity 1.5.1. ex-situ crop collections 1.5.2. genetic diversity of terrestrial domesticated animals

2. Sustainable use

2.1. Areas under Sustainable Management 2.1.1. area of forest under sustainable management: certification 2.1.2. area of forest under sustainable management: degradation and deforestation 2.1.3. area of agricultural ecosystems under sustainable management

2.2. Proportion of Products derived from Sustainable Sources 2.2.1. proportion of fish stocks in safe biological limits 2.2.2. status of species in trade 2.2.3. wild commodities index

2.3. Ecological Footprint and related concepts 2.3.1. ecological footprint and related concepts

3. Threats to biodiversity

3.1. Nitrogen Deposition 3.1.1. nitrogen deposition

3.2. Invasive Alien Species 3.2.1. trends in invasive alien species

4. Ecosystem integrity and ecosystem goods and services


4.1. Marine Trophic Index 4.1.1. marine trophic index

4.2. Water Quality 4.2.1. water quality index for biodiversity

4.3. Connectivity/Fragmentation of Ecosystems 4.3.1. forest fragmentation 4.3.2. river fragmentation and flow regulation

4.4. Health and Well Being of Communities 4.4.1. health and well being of communities directly dependent on ecosystem goods and

services

4.5. Biodiversity for Food and Medicine 4.5.1. nutritional status of biodiversity 4.5.2. biodiversity for food and medicine

5. Status of traditional knowledge, innovations and practice

5.1. Status and Trends of Linguistic Diversity and Numbers of Speakers of Indigenous Languages

5.1.1. status and trends of linguistic diversity and numbers of speakers of indigenous languages

6. Status of access and benefits sharing

(to be developed) 7. Status of resource transfers

7.1. Official Development Assistance Provided in Support of the Convention 7.1.1. official development assistance provided in support of the convention


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