E-Letter responses to:

p-forum: Stuart L. Pimm, Márcio Ayres, Andrew Balmford, George Branch, Katrina Brandon, Thomas Brooks, Rodrigo Bustamante, Robert Costanza, Richard Cowling, Lisa M. Curran, Andrew Dobson, Stephen Farber, Gustavo A. B. da Fonseca, Claude Gascon, Roger Kitching, Jeffrey McNeely, Thomas Lovejoy, Russell A. Mittermeier, Norman Myers, Jonathan A. Patz, Bradley Raffle, David Rapport, Peter Raven, Callum Roberts, Jon Paul Rodríguez, Anthony B. Rylands, Compton Tucker, Carl Safina, Cristián Samper, Melanie L. J. Stiassny, Jatna Supriatna, Diana H. Wall, and David Wilcove ENVIRONMENT: Can We Defy Nature's End? Science 2001; 293: 2207-2208 [Summary] [Full text] [PDF]

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Cost-effective Biodiversity Planning

Daniel P. Faith   (2 November 2001)

Cost-effective Biodiversity Planning 2 November 2001
Daniel P. Faith, Research Scientist Australian Museum Respond to this E-Letter: Re: Cost-effective Biodiversity Planning	Pimm et al. argue for the cost-effectiveness of biodiversity protection focussed on 25 global hotspots and 3 major tropical wilderness areas. Given this global perspective, their Policy Forum inevitably is less informative about conservation priorities and cost-effectiveness within these 28 broad priority regions. On the one hand, Pimm et al. say that "surely all remaining habitats across the species-rich tropics must be priorities," presumably implying protection of all remaining intact areas of habitat within the hotspots and major wilderness areas. In this context, resolving "complex issues of reserve selection" is not seen as a primary consideration. On the other hand, Pimm et al. do suggest, without elaboration, that "knowing which areas within hotspots are especially important could reduce costs considerably." This may refer to a proposed "hotspots within hotspots" approach (1). However, the hotspots approach may have limited value at these finer scales, relative to reserve selection methods (2). Selection methods now directly address cost-effectiveness by finding sets of priority protected areas that satisfy biodiversity targets and minimize conflict with other needs of society (3). Putting the "costs on the table" at the outset contrasts with the hotspots perspective, which rejects consideration of economic factors in "the first step" of setting priorities (1). In cost-effective planning, an area’s biodiversity value reflects not just endemicity but, more generally, complementarity (the context-dependent marginal gain in biodiversity protection offered by the area). These complementarity values are compared to (weighted) costs to achieve trade-offs (3). Further, when "threats" reflect other land-use opportunities, they now imply a priority for decision-making, not necessarily biodiversity conservation (4). Advantages of cost-effective conservation planning within regions are highlighted by what may be the only trade-offs-based biodiversity planning completed within any of the 28 global priority regions. A recent Biodiversity Rapid Appraisal Project ("BioRap") for Papua New Guinea (PNG), which falls within the New Guinea tropical wilderness area (1), identified a set of conservation priority areas achieving a high target level of biodiversity representation with minimum opportunity cost (5). Opportunity costs of conservation, reflecting forgone forestry or agricultural production, varied markedly among areas. The basis for BioRap’s high cost-effectiveness was not so much low-cost land, but rather the capacity to meet biodiversity targets with minimal use of the high-cost areas (5, 6). Such a capacity for cost-effectiveness puts a premium on trade-offs-based planning within hotspots or other regions having many high-cost areas. Further, such planning may be needed urgently in regions where that capacity itself is under threat. BioRap’s least-cost priority areas covered 16.8% of the country, but this same level of biodiversity conservation could have been achieved with only 10% coverage, in the absence of land degradation and other factors (5). A challenge is to explore scenarios to anticipate the capacity-reducing implications of land-use and climate change (6). To illustrate this, I calculated trade-off curves under two scenarios for PNG (see figure below). The lower curve assumes no land-use constraints, whereas the upper curve represents a scenario in which areas presently having high land-use intensity (5) in 1% or more of their area are assumed now to be lost to biodiversity conservation, through intensive land-use. Without constraints, 85% of the biodiversity target is achievable in PNG at a very low cost (about 1/10 the cost of achieving the full target), reflecting a general property of biodiversity trade-offs curves (3). Under the second scenario, the capacity for cost-effective conservation is reduced; the cost for that same achievement level has more than doubled. Similarly, the full target level of conservation would cost about 80,000 units without constraints, but under the second scenario that same cost achieves only about 88% of the biodiversity target. Although PNG itself is not one of the 25 global biodiversity hotspots, it may be a "cost-effectiveness hotspot" in presenting a narrow window of opportunity to achieve cost-effective biodiversity conservation (7). Identifying such windows of opportunity globally requires similar rapid assessments and scenarios analysis. Given the low cost of rapid biodiversity planning (PNG BioRap cost less than $0.5 million), such assessments can be a cost-effective part of any country’s response to the Convention on Biological Diversity. BioRap trade-off curves. Alternative sets of biodiversity priority areas imply a percentage-degree to which a biodiversity target is not met ("forgone biodiversity conservation") and a corresponding minimum opportunity cost of conservation, "forgone forestry opportunity". Each curve, defining best-possible trade-offs, was approximated by calculating priority-area sets for 5 different weightings on costs. References and Notes R. Mittermeier, N. Myers, C. G. Mittermeier, Hotspots: Earth’s Biologically Richest and Most Threatened Ecoregions (CEMEX, Mexico City and Washington DC, 1999). W. V. Reid, Trends Ecol. Evol. 13, 275 (1998). D. P. Faith, Biodiversity and regional sustainability analysis. (CSIRO, Canberra, 1995) and D. P. Faith, P. A. Walker, Biodiv. Conserv. 5, 417 (1996). D. P. Faith, P. A. Walker, Biodiv. Conserv 5, 431 (1996). See special section of Pac. Conserv. Biol. 6, 277 (2001); available at http://www.amonline.net.au/systematics/index.htm D. P. Faith, Science online (2001); URL: http://www.sciencemag.org/cgi/eletters/293/5535/1591 D. P. Faith, in C. A. Brebbia, Y. Villacampa, J. Uso, Eds. Ecosystems and Sustainable Development III (WIT Press, Southampton, 2001).