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Spatial patterns in species distributions reveal biodiversity change

Author

Listed:
  • Robert J. Wilson

    (University of Leeds
    Universidad Rey Juan Carlos)

  • Chris D. Thomas

    (University of Leeds
    University of York)

  • Richard Fox

    (Butterfly Conservation)

  • David B. Roy

    (NERC Centre for Ecology and Hydrology, Monks Wood)

  • William E. Kunin

    (University of Leeds)

Abstract

Interpretation of global biodiversity change is hampered by a lack of information on the historical status of most species in most parts of the world1,2,3,4,5. Here we show that declines and increases can be deduced from current species distributions alone, using spatial patterns of occupancy combined with distribution size. Declining species show sparse, fragmented distributions for their distribution size, reflecting the extinction process; expanding species show denser, more aggregated distributions, reflecting colonization. Past distribution size changes for British butterflies were deduced successfully from current distributions, and former distributions had some power to predict future change. What is more, the relationship between distribution pattern and change in British butterflies independently predicted distribution change for butterfly species in Flanders, Belgium, and distribution change in British rare plant species is similarly related to spatial distribution pattern. This link between current distribution patterns and processes of distribution change could be used to assess relative levels of threat facing different species, even for regions and taxa lacking detailed historical and ecological information.

Suggested Citation

  • Robert J. Wilson & Chris D. Thomas & Richard Fox & David B. Roy & William E. Kunin, 2004. "Spatial patterns in species distributions reveal biodiversity change," Nature, Nature, vol. 432(7015), pages 393-396, November.
    • Handle: RePEc:nat:nature:v:432:y:2004:i:7015:d:10.1038_nature03031
    DOI: 10.1038/nature03031
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    Cited by:

    1. Louis Iverson & Anantha Prasad & Stephen Matthews, 2008. "Modeling potential climate change impacts on the trees of the northeastern United States," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 13(5), pages 487-516, June.
    2. Emilie Reuchlin-Hugenholtz & Nancy L Shackell & Jeffrey A Hutchings, 2015. "The Potential for Spatial Distribution Indices to Signal Thresholds in Marine Fish Biomass," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-22, March.
    3. Erhan Mutlu & Ilaria de Meo & Claudia Miglietta & Mehmet Cengiz Deval, 2023. "Ecological Indicative Stressors of Native vs. Non-Native Fish in an Ultra-Oligotrophic Region of the Mediterranean Sea," Sustainability, MDPI, vol. 15(3), pages 1-28, February.
    4. Nwaichi, E. O. & Colin, S. E., 2017. "Sequestration of PAHs in a Phytoremediation Using Indian Mustard and Bambara Plants," Journal of Biotechnology Research, Academic Research Publishing Group, vol. 3(5), pages 31-41, 05-2017.
    5. Boyd, Robin J. & Bowler, Diana E. & Isaac, Nick J.B. & Pescott, Oliver L., 2024. "On the trade-off between accuracy and spatial resolution when estimating species occupancy from geographically biased samples," Ecological Modelling, Elsevier, vol. 493(C).
    6. Hui, Cang, 2011. "Forecasting population trend from the scaling pattern of occupancy," Ecological Modelling, Elsevier, vol. 222(3), pages 442-446.

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