Prioritizing Investments for Improved Biodiversity Conservation Outcomes

Every year, large investments are made in biodiversity conservation by governments, nongovernmental organizations, businesses, and individual citizens. Federal expenditures in the United States under the Endangered Species Act (ESA)—the primary federal statute governing the protection and management of biodiversity in the United States—alone sum to more than $1 billion annually. Moreover, this figure excludes state and local efforts to protect biodiversity as well as any private costs associated with mandatory conservation of biodiversity, such as compliance costs associated with the ESA.

Nevertheless, biodiversity has been slow to recover and generally continues to decline. For example, according to the U.S. Fish and Wildlife Service, of more than 1,300 species listed under the ESA, only about 7 percent have achieved greater than 50 percent recovery, and a large majority (77 percent) has reached less than 25 percent recovery. One way to improve these and other conservation  performance measures is to search for options that use the resources committed to biodiversity protection more cost-effectively—by targeting conservation investments toward projects and locations with the highest biological returns per dollar. The need to improve the prioritization of conservation expenditures is heightened by continually increasing pressures from land-use changes, invasive species, climate change, and other growing risks to biodiversity.

Could targeting conservation investments really make a difference? Because of unavoidable budgetary and other resource constraints, only a fraction of all possible conservation interventions can be undertaken. A conservation agency protecting endangered species must inevitably face tradeoffs among choices to protect and restoring current habitats, establish new habitats, and invest in other recovery programs. Complicating these choices, the number of target species may be large, requiring that conservation alternatives be evaluated from the perspective of how to best promote multiple endangered species.

Such choices can have remarkable impacts on conservation outcomes, a notion supported by evidence from a large body of research in systematic conservation design, an emerging sub-field at the interface of ecology, economics, and operations research. Findings generally suggest that better targeting of conservation interventions could enable conservation agencies to more effectively achieve their goals.

Our own recent research indicates that enhanced prioritization of conservation investments toward the protection of endangered species can greatly improve conservation outcomes. While endangered species protections seek to recover listed species and prevent them from going extinct, present conservation efforts generally are not systematically evaluated based on explicit and quantified measures of this goal. 

Several factors force conservation organizations to currently rely heavily on professional judgment when prioritizing funding. For example, sufficient biological data, such as observations on species abundances over time, often do not exist to help conduct reliable population analyses to support systematic prioritization of conservation interventions. The lack of methods to systematically incorporate species viability goals into the evaluations of conservation program designs is another constraint. One indication of this scientific gap can be seen in the National Oceanic and Atmospheric Administration’s (NOAA) recent critical habitat designations, which the federal government is required to perform for any listed species under the ESA. NOAA described currently feasible approaches to prioritizing critical habitats as follows: "Given the state of the science, it is difficult to quantify the benefits of critical habitat designation reliably. It is possible, however, to differentiate among habitat areas based on their relative contribution to conservation. For example, habitat areas can be rated as having a high, medium, or low conservation value. Such a rating is based on best professional judgment."

To address this gap through a supplementary approach, we developed an integrated framework for prioritizing habitat conservation activities on the basis of their cost-effectiveness in enhancing the long-run persistence of threatened species populations. The framework combines population viability analysis for endangered species with a reserve site selection analysis to target alternative habitat improvement activities. We illustrated the framework with a case study of Pacific salmon, but the general approach could be applied to a variety of species and biodiversity protection problems. Selection of Pacific salmon for an application was natural because protecting endangered salmon populations in the Pacific Northwest is one of the highest-profile biodiversity conservation issues in this country and an extensive body of ecological literature on Pacific salmon exists.

What are the benefits from improved prioritization? Our results suggest that integrated benefit-cost prioritization of alternative conservation investments can help create much greater biological benefits than those achieved by less systematic but commonly used approaches such as professional judgment or targeting based on only biological criteria. Generally, we find that identifying the subset of watersheds where the biological returns per dollar of conservation expenditure are highest is critical, particularly because the large majority of biological benefits from a specific conservation program may be associated with the protection of only a fraction of all potential target areas.

For example, if targeting is done optimally, spending 10 percent of the cost of restoring all upstream watersheds for salmon protection yields nearly 80 percent of the maximum possible increase in the predicted 100-year stock persistence achievable by protecting all watersheds. In this context, ad hoc prioritization methods also generate disproportional biological benefits at low budgets, but they are less cost-effective and generate only about 25 percent to 75 percent of the benefits achieved by more systematic cost-benefit prioritization.

 
Juha Siikamäki is a fellow at Resources for the Future. His research focuses on valuing the environment and evaluating the benefits, costs, and cost-effectiveness of different environmental policy options. He is especially interested in understanding the preferences of consumers, households, and landowners for different policy programs and using this information for evaluating and designing environmental policy.

Stephen Newbold is a policy analyst at the U.S. Environmental Protection Agency’s National Center for Environmental Economics. He provides support for regulatory impact analyses at EPA, and maintains a research agenda focused on ecological modeling, ecosystem valuation, systematic conservation design, and estimation of benefits from for climate change policies.

How specific are these findings to the case of Pacific salmon? Though relative benefits from improved targeting will undoubtedly vary by application, there is reason to believe that they may be large in many cases. A recent review of conservation design studies suggests that better incorporation of cost-benefit considerations can generally improve conservation outcomes. Findings in a similar vein also have emerged in cases related to watershed protections and targeting of conservation activities in agricultural and forest landscapes.

Of course, no analytical model can capture all of the relevant ecological and economic dimensions of a complex conservation problem. Systematic prioritization methods are not as a stand-alone recipe for targeting conservation investments, but can be potentially useful supplements to current methods including professional judgment. Nevertheless, given the amounts of resources and species at stake, as well as the increasing pressures on biodiversity, developing more systematic approaches to designing and evaluating conservation programs seems well justified. 

Further Reading:

Ferraro, P.J. 2003. Assigning priority to environmental policy interventions in a heterogeneous world. Journal of Policy Analysis and Management 22(1):27–43.

Margules CR, Pressey RL. 2000. Systematic conservation planning. Nature 405:243-253.

Naidoo, R., A. Balmford, P.J. Ferraro, S. Polasky, T.H. Ricketts, and M. Rouget. 2006. Integrating economic costs into conservation planning. Trends in Ecology and Evolution 21(12):681–687.

Newbold, Stephen C. 2002. Integrated modeling for watershed management: multiple objectives and spatial effects. Journal of the American Water Resources Association 38(2):341-353.