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Reserve design to optimize functional connectivity and animal density |
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| Authors: | Amrita Gupta Bistra Dilkina Dana J Morin Angela K Fuller J Andrew Royle Christopher Sutherland Carla P Gomes |
| Institution: | 1. School of Computational Science and Engineering, College of Computing, Georgia Institute of Technology, 266 Ferst Drive, Atlanta, GA, 30332 U.S.A.;2. New York Cooperative Fish and Wildlife Research Unit, Department of Natural Resources, Cornell University, 211 Fernow Hall, 226 Mann Drive, Ithaca, NY, 14853 U.S.A.
Current address: Cooperative Wildlife Research Laboratory, Southern Illinois University, 251 Life Science II, Carbondale, IL 62901, U.S.A.;3. U.S. Geological Survey, New York Cooperative Fish and Wildlife Research Unit, Department of Natural Resources, Cornell University, 211 Fernow Hall, 226 Mann Drive, Ithaca, NY, 14853 U.S.A.;4. U.S. Geological Survey, Patuxent Wildlife Research Center, 12100 Beech Forest Road, Laurel, MD, 20708 U.S.A.;5. New York Cooperative Fish and Wildlife Research Unit, Department of Natural Resources, Cornell University, 211 Fernow Hall, 226 Mann Drive, Ithaca, NY, 14853 U.S.A. Current address: Department of Environmental Conservation, University of Massachusetts—Amherst, 118 Holdsworth Hall, Amherst, MA 01003, U.S.A.;6. Department of Computer Science, Institute for Computational Sustainability, Cornell University, 353 Gates Hall, Ithaca, NY, 14853 U.S.A. |
| Abstract: | Ecological distance-based spatial capture–recapture models (SCR) are a promising approach for simultaneously estimating animal density and connectivity, both of which affect spatial population processes and ultimately species persistence. We explored how SCR models can be integrated into reserve-design frameworks that explicitly acknowledge both the spatial distribution of individuals and their space use resulting from landscape structure. We formulated the design of wildlife reserves as a budget-constrained optimization problem and conducted a simulation to explore 3 different SCR-informed optimization objectives that prioritized different conservation goals by maximizing the number of protected individuals, reserve connectivity, and density-weighted connectivity. We also studied the effect on our 3 objectives of enforcing that the space-use requirements of individuals be met by the reserve for individuals to be considered conserved (referred to as home-range constraints). Maximizing local population density resulted in fragmented reserves that would likely not aid long-term population persistence, and maximizing the connectivity objective yielded reserves that protected the fewest individuals. However, maximizing density-weighted connectivity or preemptively imposing home-range constraints on reserve design yielded reserves of largely spatially compact sets of parcels covering high-density areas in the landscape with high functional connectivity between them. Our results quantify the extent to which reserve design is constrained by individual home-range requirements and highlight that accounting for individual space use in the objective and constraints can help in the design of reserves that balance abundance and connectivity in a biologically relevant manner. |
| Keywords: | connectivity conservation conservation planning functional connectivity integer linear programing mathematical optimization reserve design spatial capture–recapture captura-recaptura espacial conectividad funcional conservación de la conectividad diseño de reservas optimización matemática planeación de la conservación programación entera lineal 功能连接度 保护区设计 保护规划 连接度保护 空间捕获–重捕模型 整数线性规划 数学最优化 |