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Combining probabilities of occurrence with spatial reserve design

  1. Mar Cabeza1,*,
  2. Miguel B. Araújo2,
  3. Robert J. Wilson3,
  4. Chris D. Thomas3,
  5. Matthew J. R. Cowley4,
  6. Atte Moilanen1

Article first published online: 7 APR 2004

DOI: 10.1111/j.0021-8901.2004.00905.x

Issue

Journal of Applied Ecology

Journal of Applied Ecology

Volume 41, Issue 2, pages 252–262, April 2004

Additional Information

How to Cite

Cabeza, M., Araújo, M. B., Wilson, R. J., Thomas, C. D., Cowley, M. J. R. and Moilanen, A. (2004), Combining probabilities of occurrence with spatial reserve design. Journal of Applied Ecology, 41: 252–262. doi: 10.1111/j.0021-8901.2004.00905.x

Author Information

  1. 1

    Metapopulation Research Group, Department of Ecology and Systematics, University of Helsinki, FIN-00014 Helsinki, Finland;

  2. 2

    Macroecology and Conservation Unit, University of Évora, Portugal;

  3. 3

    Centre for Biodiversity and Conservation, School of Biology, University of Leeds, UK; and

  4. 4

    EMEC Ecology, The Old Ragged School, Nottingham, UK

* Mar Cabeza, Metapopulation Research Group, Department of Ecology and Systematics, University of Helsinki, FIN-00014 Helsinki, Finland (fax + 358 9 19157694; e-mail mar.cabeza-jaimejuan@helsinki.fi).

Publication History

  1. Issue published online: 7 APR 2004
  2. Article first published online: 7 APR 2004
  3. Received 18 October 2002; final copy received 25 January 2004

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Keywords:

  • butterflies;
  • fragmentation;
  • habitat models;
  • reserve selection

Summary

  • 1
    There is a great concern about the loss of biodiversity that calls for more nature protection. Unfortunately, the funding available for conservation is limited, and often a compromise is needed between nature protection and economic interests. Reserve selection algorithms are optimization techniques that concentrate on identifying a set of reserves that represents biodiversity efficiently. Simple approaches to reserve selection use presence–absence data assuming that if a species occurs in a selected reserve, it will persist there indefinitely.
  • 2
    A refinement of this technique is the selection of reserves according to the local probabilities of occurrence of the given species. These can be estimated from habitat models fitted by empirical modelling techniques. However, local probabilities of occurrence are not static, and are influenced by the changing threats to biodiversity in and around the reserves.
  • 3
    The effects of landscape change can be minimized when compact reserves are favoured. Compact reserves that represent all species with a given target probability of occurrence can be achieved by combining the probability approach with spatial reserve design.
  • 4
    In this study we brought together two reserve selection approaches that implicitly deal with biodiversity persistence, by combining habitat models and spatial reserve design in a single algorithm. We applied the combined algorithm to a data set of 26 species of butterflies from north Wales.
  • 5
    For the particular case study addressed in this paper, clustered reserve networks could be identified at no or a small increase in cost.
  • 6
    A new, backwards, heuristic algorithm performed better and more consistently than the regular forwards heuristic approach.
  • 7
    Synthesis and applications. The reserve selection approach presented considers habitat quality (via probabilities of occurrence) and the spatial configuration of the reserves during the selection process. Emphasis on reserve networks that include high-quality sites in an aggregated manner increases the potential for long-term persistence of species in the reserve network.
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