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Partitioning tree diversity patterns to prioritize conservation investments

Published online by Cambridge University Press:  11 March 2021

Patrick F McKenzie
Affiliation:
Department of Ecology and Evolutionary Biology, University of Tennessee, TN, USA Department of Ecology, Evolution, and Environmental Biology, Columbia University, NY, USA
Gwenllian D Iacona
Affiliation:
Department of Ecology and Evolutionary Biology, University of Tennessee, TN, USA Resources for the Future, Washington, DC, USA
Eric R Larson
Affiliation:
Department of Ecology and Evolutionary Biology, University of Tennessee, TN, USA Department of Natural Resources and Environmental Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA
Paul R Armsworth
Affiliation:
Department of Ecology and Evolutionary Biology, University of Tennessee, TN, USA
Corresponding
E-mail address:

Summary

The available tools and approaches to inform conservation decisions commonly assume detailed distribution data. We examine how well-established ecological concepts about patterns in local richness and community turnover can help overcome data limitations when planning future protected areas. To inform our analyses, we surveyed tree species in protected areas in the southern Appalachian Mountains in the eastern USA. We used the survey data to construct predictive models for alpha and beta diversity based on readily observed biophysical variables and combined them to create a heuristic that could predict among-site richness in trees (gamma diversity). The predictive models suggest that site elevation and latitude in this montane system explain much of the variation in alpha and beta diversity in tree species. We tested how well resulting protected areas would represent species if a conservation planner lacking detailed species inventories for candidate sites were to rely only on our alpha, beta and gamma diversity predictions. Our approach selected sites that, when aggregated, covered a large proportion of the overall species pool. The combined gamma diversity models performed even better when we also accounted for the cost of protecting sites. Our results demonstrate that classic community biogeography concepts remain highly relevant to conservation practice today.

Type
Research Paper
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of Foundation for Environmental Conservation

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