Abstract
The PREDICTS project—Projecting Responses of Ecological Diversity In Changing Terrestrial Systems (www.predicts.org.uk)—has collated from published studies a large, reasonably representative database of comparable samples of biodiversity from multiple sites that differ in the nature or intensity of human impacts relating to land use. We have used this evidence base to develop global and regional statistical models of how local biodiversity responds to these measures. We describe and make freely available this 2016 release of the database, containing more than 3.2 million records sampled at over 26,000 locations and representing over 47,000 species. We outline how the database can help in answering a range of questions in ecology and conservation biology. To our knowledge, this is the largest and most geographically and taxonomically representative database of spatial comparisons of biodiversity that has been collated to date; it will be useful to researchers and international efforts wishing to model and understand the global status of biodiversity.
Original language | English |
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Pages (from-to) | 145-188 |
Number of pages | 44 |
Journal | Ecology and Evolution |
Volume | 7 |
Issue number | 1 |
Early online date | 16 Dec 2016 |
DOIs | |
Publication status | Published - Jan 2017 |
Externally published | Yes |
Bibliographical note
We thank the many researchers who generously contributed their data to the PREDICTS project; including The Nature Conservation Foundation, Ros Blanche, Zhi Ping Cao, Kristina Cockle, Emily Davis, Moisés Barbosa de Souza, Carsten F Dormann, Christo Fabricius, Colin Ferguson, Heleen Fermon, Toby Gardner, Eva Gaublomme, Marco S Gottschalk, Peter Hietz, Juan Carlos Iturrondobeitia, Daniel L Kelly, Lee Hsiang Liow, Takashi Matsumoto, William McShea, Elder F Morato, Andreas Müller, Philip Nyeko, Tim O'Connor, Clint Otto, Simon Paradis, Marino Rodrigues, Watana Sakchoowong, Hari Sridhar, Susan Walker, Rachael Winfree, Timothy T Work, Torsten Wronski, Gregory Zimmerman and all the field assistants, parataxonomists and taxonomists who collected and identified the animals, plants and fungi in the database. We thank all the many funding agencies and other organizations that have supported the original research that produced these data; these include Natural Sciences and Engineering Research Council of Canada and Tembec, the University of Miami Beyond the Book Research Scholarship, the NSF Graduate Research Fellowship and the National Science Foundation Research Experience for Undergraduates Supplemental Award. We thank Technical Solutions and Informatics staff at the Natural History Museum, London, especially Srinivas Patlola, Simon Rycroft, Ben Scott and Chris Sleep.Funding
PREDICTS has been supported by U.K. Natural Environment Research Council grants (NE/J011193/2 and NE/L002515/1), the United Nations Environment Program World Conservation Monitoring Centre, Biotechnology and Biological Sciences Research Council grant (BB/F017324/1), a Hans Rausing PhD Scholarship and COLCIENCIAS (Departamento Administrativo de Ciencia, Tecnología e Innovación de Colombia).
Keywords
- data sharing
- global biodiversity modeling
- global change
- habitat destruction
- land use