# Reserve Design to Maximize Species Persistence

- 104 Downloads
- 16 Citations

## Abstract

We develop a reserve design strategy to maximize the probability of species persistence predicted by a stochastic, individual-based, metapopulation model. Because the population model does not fit exact optimization procedures, our strategy involves deriving promising solutions from theory, obtaining promising solutions from a simulation optimization heuristic, and determining the best of the promising solutions using a multiple-comparison statistical test. We use the strategy to address a problem of allocating limited resources to new and existing reserves. The best reserve design depends on emigration, dispersal mortality, and probabilities of movement between reserves. When movement probabilities are symmetric, the best design is to expand a subset of reserves to equal size to exhaust the habitat budget. When movement probabilities are not symmetric, the best design does not expand reserves to equal size and is strongly affected by movement probabilities and emigration rates. We use commercial simulation software to obtain our results.

## Keywords

Optimization Population viability Reserve site selection Resource allocation Search heuristic Simulation optimization Stochastic population model## References

- 1.Boesel, J., Nelson, B. L., & Kim, S.-H. (2003). Using ranking and selection to “clean up” after simulation optimization.
*Operations Research, 51*, 814–825.CrossRefGoogle Scholar - 2.Burgman, M. A., Lindenmayer, D. B., & Elith, J. (2005). Managing landscapes for conservation under uncertainty.
*Ecology, 86*, 2007–2017.CrossRefGoogle Scholar - 3.Cabeza, M., & Moilanen, A. (2001). Design of reserve networks and the persistence of biodiversity.
*Trends in Ecology and Evolution, 16*, 242–248.CrossRefGoogle Scholar - 4.Cabeza, M., & Moilanen, A. (2003). Site-selection algorithms and habitat loss.
*Conservation Biology, 17*, 1402–1413.CrossRefGoogle Scholar - 5.Costello, C., & Polasky, S. (2004). Dynamic reserve site selection.
*Resource and Energy Economics, 26*, 157–174.CrossRefGoogle Scholar - 6.Fahrig, L. (2001). How much habitat is enough?
*Biological Conservation, 100*, 65–74.CrossRefGoogle Scholar - 7.Flather, C. H., & Bevers, M. (2002). Patchy reaction–diffusion and population abundance: the relative importance of habitat amount and arrangement.
*The American Naturalist, 159*, 40–56.CrossRefGoogle Scholar - 8.Gese, E. M., & Mech, L. D. (1991). Dispersal of wolves (
*Canis lupus*) in northeastern Minnesota, 1969–1989.*Canadian Journal of Zoology, 69*, 2946–2955.CrossRefGoogle Scholar - 9.Glover, F., & Laguna, M. (1997). Tabu Search (408 p). Kluwer Academic Publishers.Google Scholar
- 10.Goldsman, D., & Nelson, B. L. (1998). Statistical screening, selection, and multiple comparison procedures in computer simulation. In: D. J. Medeiros, E. F. Watson, J. S. Carson, & M. S. Manivannon (eds.),
*Proceedings of the 1998 Winter Simulation Conference*(pp. 159-166). Piscataway, New Jersey: Institute of Electrical and Electronics Engineers.Google Scholar - 11.Haight, R. G., Cypher, B., Kelly, P. A., Phillips, S., Possingham, H. P., Ralls, K., et al. (2002). Optimizing habitat protection using demographic models of population viability.
*Conservation Biology, 16*, 1386–1397.CrossRefGoogle Scholar - 12.Haight, R. G., Cypher, B., Kelly, P. A., Phillips, S., Ralls, K., & Possingham, H. P. (2004). Optimizing reserve expansion for disjunct populations of San Joaquin kit fox.
*Biological Conservation, 117*, 61–72.CrossRefGoogle Scholar - 13.Haight, R. G., Mladenoff, D. J., & Wydeven, A. P. (1998). Modeling disjunct gray wolf populations in semi-wild landscapes.
*Conservation Biology, 12*, 879–888.CrossRefGoogle Scholar - 14.Hanski, I. (1994). A practical model of metapopulation dynamics.
*Journal of Animal Ecology, 63*, 151–162.CrossRefGoogle Scholar - 15.Lamberson, R. H., Noon, B. R.,Voss, C., & McKelvey, K. S. (1994). Reserve design for territorial species: the effects of patch size and spacing on the viability of the Northern Spotted Owl.
*Conservation Biology, 8*, 185–195.CrossRefGoogle Scholar - 16.McCarthy, M. A., Thompson, C. J., & Possingham, H. P. (2005). Theory for designing nature reserves for single species.
*The American Naturalist, 165*, 250–257.CrossRefGoogle Scholar - 17.Moilanen, A. (2004). SPOMSIM: software for stochastic patch occupancy models of metapopulation dynamics.
*Ecological Modelling, 179*, 533–550.CrossRefGoogle Scholar - 18.Moilanen, A., & Cabeza, M. (2002). Single-species dynamic site selection.
*Ecological Applications, 12*, 913–926.CrossRefGoogle Scholar - 19.Possingham, H. P., & Davies, I. (1995). ALEX: a model for the viability analysis of spatially structured populations.
*Biological Conservation, 73,*143–150.CrossRefGoogle Scholar - 20.ReVelle, C. S., Williams, J. C., & Boland, J. J. (2002). Counterpart models in facility location science and reserve selection science.
*Environmental Modeling and Assessment, 7*, 71–80.CrossRefGoogle Scholar - 21.Rodrigues, A. S. L., & Gaston, K. J. (2002). Optimisation in reserve selection procedures—why not?
*Biological Conservation, 107*, 123–129.CrossRefGoogle Scholar - 22.Schwartz, M. K., Ralls, K., Williams, D. F., Cypher, B. L., Pilgrim, K. L., & Fleischer, R. C. (2005). Gene flow among San Joaquin kit fox populations in a severely changed ecosystem.
*Conservation Genetics, 6*, 25–37.CrossRefGoogle Scholar - 23.Westphal, M. I., Pickett, M., Getz, W. M., & Possingham, H. P. (2003). The use of stochastic dynamic programming in optimal landscape reconstruction for metapopulations.
*Ecological Applications, 13*, 543–555.CrossRefGoogle Scholar - 24.Wiegand, T., Revilla, E., & Moloney, K. A. (2005). Effects of habitat loss and fragmentation on population dynamics.
*Conservation Biology, 19*, 108–121.CrossRefGoogle Scholar - 25.Williams, J. C., ReVelle, C. S., & Levin, S. A. (2005). Spatial attributes and reserve design models: a review.
*Environmental Modeling and Assessment, 10*, 163–181.CrossRefGoogle Scholar