AnalysisPoverty and biodiversity: Measuring the overlap of human poverty and the biodiversity hotspots
Introduction
The need for an interdisciplinary approach to science has become obvious in recent years and is perhaps most pertinent in the fields of conservation and sustainable development. Due to the linkages between socio-economic systems and ecological systems, issues such as development, poverty eradication, and biodiversity conservation need to be addressed not as individual phenomena but rather as complex dynamic systems. Addressing these systems will require input from social and natural scientists, as well as policy makers and practitioners (Sanderson, 2005). In this paper we address the interconnectivity of global biodiversity conservation priorities with human poverty issues. These issues represent key areas of focus for major global initiatives such as the United Nation's Millennium Development Goals, the Convention on Biological Diversity and Make Poverty History campaign.
The starting point for this analysis is the 2000 Nature article by Myers et al. entitled “Biodiversity hotspots for conservation priorities”. In this landmark paper, Myers et al. developed a strategy for prioritizing areas of biodiversity by providing a ranking of hotspots in order to assist planners in the face of insufficient funding. The authors focused their analysis on and defined ‘hotspots’ as areas having “exceptional concentrations of endemic species and experiencing exceptional loss of habitat”. They defined 25 original hotspots, but this list was recently expanded to 34 hotspots and has become the major focus of Conservation International's (CI) work. By focusing on these hotspots, the authors estimate it may be possible to protect 44% of all vascular plant species and 35% of 4 major vertebrate group in only 1.4% of the earth's surface (Myers et al., 2000). This was, and continues to be, an important and timely effort due to the growing evidence of human driven ecosystem degradation and species loss (Vitousek, 1997). While an excellent endeavor to help prioritize funding for conservation, their paper does not address the fact that the success of conservation initiatives is largely dependent on the socio-economic conditions of the areas where these hotspots occur.
Adams et al. (2004) recently reviewed the controversy surrounding the link between biodiversity conservation and poverty alleviation. In their article they developed a typology for this relationship, which spanned the range of opinions. The four categories they developed are:
- 1.
Poverty and conservation are separate policy realms.
- 2.
Poverty is a constraint on conservation.
- 3.
Conservation should not compromise poverty reduction.
- 4.
Poverty reduction depends on living resource conservation.
These categories do not preclude the necessity of both poverty alleviation and conservation, but rather express different viewpoints (or prioritizations) of these complex systems. The Myers et al. (2000) endeavor was excellent for identifying hotspots, but it is a category 1 strategy of maintaining the separation between conservation priorities and poverty alleviation. While conservation and poverty data have seldom been fully integrated (Snel, 2004), Cincotta et al. (2000) have expanded the analysis of hotspots by including the interactions with population densities and growth rates. Smith et al. (2003) have examined governance corruption with respect to hotspots. There have also been several attempts at integrating socio-economic data into conservation prioritization in an effort to move away from this category 1 framework (Sisk et al., 1994, Balmford et al., 2003, Veech, 2003, O'connor et al., 2003). These papers all base their priority setting on conservation costs and threats, and their analysis would generally fall in Adams et al.'s categories 2–3.
While the socio-economic indicators we use could support viewpoints in categories 2–4, the function of this paper is to provide analysis for practitioners to show the geographic overlap of key areas for both poverty alleviation and biodiversity conservation. This analysis could be useful to any of the typology viewpoints, but the discussion that follows the analysis focuses primarily on the category four viewpoint, which is becoming increasingly common in the literature.
Previous attempts are laudable calls to the conservation community to prioritize initiatives based on possible success in light of socio-economic conditions. Our work on the other hand uses vital poverty statistics, such as access to clean water, food scarcity and national debt service, in acknowledgment of the fact that organizations working on poverty issues face critical constraints but continue to work on literally life and death issues. In doing this, we move beyond conservation prioritization, and point to the large scale at which poverty alleviation and biodiversity conservation concerns overlap. We highlight the innate linkages between conservation and poverty by assessing socio-economic poverty indicators that have an impact on, and feedback into, conservation. We also provide a ranking of the critical hotspots and countries based on these indicators. This work recognizes the fact that conservation in general does not automatically translate to protection of high levels of biodiversity, but the linkage between these two is in recognition of the strong and well documented link that ecosystem destruction leads to species loss (Ehrlich and Ehrlich, 1981, Tilman et al., 1994, Czech et al., 2000).
Section snippets
Methods
We disaggregated CI's 34 hotspots into their constituent countries within a Geographic Information System. Hotspots (obtained from Conservation International's website at: http://www.biodiversityhotspots.org/xp/Hotspots/resources/maps.xml) were clipped to a map of the world's countries (obtained from USGS VMap, Level 0 Project). These files were combined in order to determine which hotspots overlapped with which country and to select all countries with at least 100,000 ha of overlapping
Undernourishment
According to the 2003 State of Food Insecurity (SOFI) report of the Food and Agriculture Organization (FAO) there are 842 million people considered ‘food insecure’ in our world. Three-fourths of these people live in rural areas, the overwhelming majority in the developing world. The rural poor rely heavily on local ecosystems for primary goods and services and therefore the importance of biodiversity to food security in the developing world cannot be overstated (Snel, 2004). In the other
Poverty line
Currently 40% of the global population lives in low-income countries; roughly 3 billion people live on less than $2 a day; and 1.2 billion live below The World Bank's (2003) “extreme” poverty line of less than $1 per day. The often-studied relationship between poverty and environmental degradation cuts both ways, where conservation affects local livelihoods and local livelihoods affect conservation efforts. This “bi-directional” relationship can have positive feedback effects, often described
Re-ranking the hotspots
Table 1 shows the 25 poorest performers in each category. We also added some countries to this list when these countries had missing data but were obviously in bad shape with respect to a criteria, as commented on in the above text. From this we ranked the poorest performers for both countries and hotspots. For the country list, we ranked countries based on the number of times (0 to 5) each of them appeared in the top 25 of the socio-economic categories. For the hotspots we analyzed the data
Results
For undernourishment, the top five countries all have greater than 60% of their populations without adequate caloric intake. Four of the five are African countries, with Somalia as the country with the highest percentage of its population undernourished at 75%. There are 15 countries where greater than 50% of their population do not have access to clean water. Twelve of these countries are on the African continent.
For potential population pressure, Hong Kong is clearly in a league of its own.
Limitations
Our examination of the socio-economic landscape in the countries where CI's hotspots lie has a number of limitations:
- 1)
The biodiversity hotspots are aggregated based on similar ecological characteristics, ignoring political boundaries, while most socio-economic data, including all used in this analysis, are available only for national boundaries. As global datasets improve and become more closely linked with geographical information systems, this analysis could focus directly on hotspots rather
Discussion
Much work has been done on prioritization of global conservation efforts based on ecosystem characteristics such as endemism (Myers et al., 2000), habitat type (Olson and Dinerstein, 1998), adaptive variation (Smith et al., 2001), and/or threats to success like governance (Smith et al., 2003), cost (Balmford et al., 2000) and population (Cincotta et al., 2000). Our approach includes key social and economic poverty indicators that have been shown to drive land use change in the ecologically
Conclusion
Adam et al.'s typology demonstrates the range of viewpoints surrounding the conservation–poverty alleviation issue. The analysis here suggests that regardless of which viewpoint you hold, the overlap between severe, multifaceted poverty and key areas of global biodiversity is great, and needs to be acknowledged. The goals of any project will dictate the approach, but as pointed out here, biodiversity hotspot conservation (or poverty alleviation in and surrounding the hotspots) must consider the
Acknowledgements
We thank Myers et al. for their seminal Hotspots paper; CI for the GIS data layers; Kenneth Mulder and Daniel Lopez Dias for their comments on earlier drafts and two anonymous reviewers for their valuable comments. Any errors should be attributed solely to the authors.
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