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Assemblage time series reveal biodiversity change but not systematic loss

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posted on 20.04.2016 by Maria Dornelas, Nicholas J. Gotelli, Brian McGill, Hideyasu Shimadzu, Faye Moyes, Caya Sievers, Anne E. Magurran
The extent to which biodiversity change in local assemblages contributes to global biodiversity loss is poorly understood. We analyzed 100 time series from biomes across Earth to ask how diversity within assemblages is changing through time. We quantified patterns of temporal α diversity, measured as change in local diversity, and temporal β diversity, measured as change in community composition. Contrary to our expectations, we did not detect systematic loss of α diversity. However, community composition changed systematically through time, in excess of predictions from null models. Heterogeneous rates of environmental change, species range shifts associated with climate change, and biotic homogenization may explain the different patterns of temporal α and β diversity. Monitoring and understanding change in species composition should be a conservation priority.

Funding

Supported by the European Research Council (BioTIME 250189), the Scottish Funding Council (MASTS, grant reference HR09011) (M.D.), and the Royal Society (A.E.M.).

History

School

  • Science

Department

  • Mathematical Sciences

Published in

Science

Volume

344

Issue

6181

Pages

296 - 299

Citation

DORNELAS, M., ... et al, 2014. Assemblage time series reveal biodiversity change but not systematic loss. Science, 344 (6181), pp. 296 - 299.

Publisher

American Association for the Advancement of Science / © The Authors

Version

AM (Accepted Manuscript)

Publication date

2014

Notes

This is the author's version of the work. It is posted here by permission of the AAAS for personal use, not for redistribution. The definitive version was published in Science, 344 (6181), pp. 296 - 299 on 18th April 2014, doi: 10.1126/science.1248484. The definitive version is available at: http://dx.doi.org/10.1126/science.1248484.

ISSN

0036-8075

eISSN

1095-9203

Language

en

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