Trade-offs and efficiencies in optimal budget-constrained multispecies corridor networks.
Conservation biologists recognize that a system of isolated protected areas will be necessary but insufficient to meet biodiversity objectives. Current approaches to connecting core conservation areas through corridors consider optimal corridor placement based on a single optimization goal: commonly, maximizing the movement for a target species across a network of protected areas. We show that designing corridors for single species based on purely ecological criteria leads to extremely expensive linkages that are suboptimal for multispecies connectivity objectives. Similarly, acquiring the least-expensive linkages leads to ecologically poor solutions. We developed algorithms for optimizing corridors for multispecies use given a specific budget. We applied our approach in western Montana to demonstrate how the solutions may be used to evaluate trade-offs in connectivity for 2 species with different habitat requirements, different core areas, and different conservation values under different budgets. We evaluated corridors that were optimal for each species individually and for both species jointly. Incorporating a budget constraint and jointly optimizing for both species resulted in corridors that were close to the individual species movement-potential optima but with substantial cost savings. Our approach produced corridors that were within 14% and 11% of the best possible corridor connectivity for grizzly bears (Ursus arctos) and wolverines (Gulo gulo), respectively, and saved 75% of the cost. Similarly, joint optimization under a combined budget resulted in improved connectivity for both species relative to splitting the budget in 2 to optimize for each species individually. Our results demonstrate economies of scale and complementarities conservation planners can achieve by optimizing corridor designs for financial costs and for multiple species connectivity jointly. We believe that our approach will facilitate corridor conservation by reducing acquisition costs and by allowing derived corridors to more closely reflect conservation priorities.
Georgia Institute of Technology, School of Computational Science and Engineering, College of Computing, 266 Ferst Drive, Atlanta, GA, 30332, U.S.A.
Bistra
B
Dilkina
Oregon State University, Department of Forest Engineering, Resources, and Management, 280 Peavy Hall, Corvallis, OR, 97331, U.S.A.
Rachel
R
Houtman
Cornell University, Institute for Computational Sustainability, Department of Computer Science, 353 Gates Hall, Ithaca, NY, 14853, U.S.A.
Carla P
CP
Gomes
Oregon State University, Department of Forest Engineering, Resources, and Management, 280 Peavy Hall, Corvallis, OR, 97331, U.S.A.
Claire A
CA
Montgomery
U.S. Forest Service Rocky Mountain Research Station, National Genomics Center for Wildlife and Fish Conservation, Missoula, MT, U.S.A.
Kevin S
KS
McKelvey
U.S. Geological Survey, Glacier Field Station, Northern Rocky Mountain Science Center, 38 Mather Drive, West Glacier, MT, 59936, U.S.A.
Katherine
K
Kendall
U.S. Geological Survey, Glacier Field Station, Northern Rocky Mountain Science Center, 38 Mather Drive, West Glacier, MT, 59936, U.S.A.
Tabitha A
TA
Graves
Cornell University, Institute for Computational Sustainability, Department of Computer Science, 353 Gates Hall, Ithaca, NY, 14853, U.S.A.
Richard
R
Bernstein
U.S. Forest Service Rocky Mountain Research Station, National Genomics Center for Wildlife and Fish Conservation, Missoula, MT, U.S.A.
Michael K
MK
Schwartz
D000818:Animals; D044822:Biodiversity; D003247:Conservation of Natural Resources; D004463:Ecology; D017753:Ecosystem; D009009:Montana
Connectivity; conectividad; conservacián rentable; conservation planning; corredor de vida silvestre; cost-effective conservation; economics; economía; especies amenazadas; optimización; optimization; planificación de la conservación; protected areas; threatened species; wildlife corridor; áreas protegidas