Subpopulation Triage: How to Allocate Conservation Effort among Populations
Threatened species often exist in a small number of isolated subpopulations. Given limitations on conservation spending, managers must choose from strategies that range from managing just one subpopulation and risking all other subpopulations to managing all subpopulations equally and poorly, thereby risking the loss of all subpopulations. We took an economic approach to this problem in an effort to discover a simple rule of thumb for optimally allocating conservation effort among subpopulations. This rule was derived by maximizing the expected number of extant subpopulations remaining given n subpopulations are actually managed. We also derived a spatiotemporally optimized strategy through stochastic dynamic programming. The rule of thumb suggested that more subpopulations should be managed if the budget increases or if the cost of reducing local extinction probabilities decreases. The rule performed well against the exact optimal strategy that was the result of the stochastic dynamic program and much better than other simple strategies (e.g., always manage one extant subpopulation or half of the remaining subpopulation). We applied our approach to the allocation of funds in 2 contrasting case studies: reduction of poaching of Sumatran tigers (Panthera tigris sumatrae) and habitat acquisition for San Joaquin kit foxes (Vulpes macrotis mutica). For our estimated annual budget for Sumatran tiger management, the mean time to extinction was about 32 years. For our estimated annual management budget for kit foxes in the San Joaquin Valley, the mean time to extinction was approximately 24 years. Our framework allows managers to deal with the important question of how to allocate scarce conservation resources among subpopulations of any threatened species.
Keywords: San Joaquin kit fox; Sumatran tiger; Tigre de Sumatra; Vulpes macrotis mutica; asignación de recursos financieros; decision theory; especies amenazadas; financial resource allocation; manejo óptimo; optimal management; principio general; programación estocástica dinámica; rule of thumb; stochastic dynamic programming; teoría de decisiones; threatened species
Document Type: Research Article
Affiliations: The Ecology Centre, The Applied Environmental Decision Analysis Centre, School of Integrative Biology, The University of Queensland, St. Lucia, QLD 4072, Australia
Publication date: June 1, 2008