Where are the wild things? Why we need better data on species distribution
AIM: The effects of ongoing global change are causing increasing concern about the ability of species or biomes to shift or adapt. Tremendous efforts have been made to develop ever more sophisticated species distribution models to provide forecasts for the future of biodiversity. All these models re...
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Published in: | Global ecology and biogeography Vol. 23; no. 4; pp. 457 - 467 |
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Main Authors: | , , |
Format: | Journal Article |
Language: | English |
Published: |
Oxford
Blackwell Publishing Ltd
01-04-2014
John Wiley & Sons Ltd Blackwell Wiley Subscription Services, Inc Wiley |
Subjects: | |
Online Access: | Get full text |
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Summary: | AIM: The effects of ongoing global change are causing increasing concern about the ability of species or biomes to shift or adapt. Tremendous efforts have been made to develop ever more sophisticated species distribution models to provide forecasts for the future of biodiversity. All these models rely on species occurrence data, either for calibration or validation. Here we evaluate (i) whether distribution data diverge among widely used sources, for supposedly well‐known taxa, and (ii) to what extent these divergences affect species distribution models. LOCATION: Europe (as an example). METHODS: We compared the distribution maps of 21 of the most common European trees, according to four large‐scale, putatively reliable sources of distribution data. For each species, we compared the outputs of correlative species distribution models built using occurrence data from each of these sources of data. We also investigated how discrepancies in large‐scale occurrence data affected the validation scores of two process‐based tree distribution models. RESULTS: Maps of tree occurrence diverged in 8–74% of the forested area, depending on species. These discrepancies affected projections of niche models: for example, 22–75% of the area projected as suitable by at least one model generated using one source of data was not projected as such by all other models. For most species, this proportion increased under scenarios of climate change, whatever the model used. To a lesser extent, uncertainties on current species distributions also affect the validation score of process‐based distribution models. MAIN CONCLUSIONS: Reliable, widely used sources of occurrence data strongly diverge even for well‐known taxa – the most common European trees. Scientists and stakeholders should acknowledge this gap in knowledge, since accurate data are a prerequisite to providing stakeholders with robust forecasts on biodiversity. Participatory science programmes and remote sensing techniques are promising tools for rapidly gathering such data. |
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Bibliography: | http://dx.doi.org/10.1111/geb.12118 ArticleID:GEB12118 Appendix S1 Rates of false positives and false negatives, and overall matches of atlas-derived occurrences, as compared to forest inventory data (ICP dataset). Appendix S2 Upscaling and downscaling procedure for each of the five sources of distribution data. Appendix S3 Areas of occurrence of the 21 species according to the available sources of data, and modelled areas for the current period and under scenarios, for models built using occurrence data from each data source. Appendix S4 Maps showing the number of databases indicating each of the 21 species' occurrences across Europe. Appendix S5 Maps showing discrepancies between the three atlases. Appendix S6 Maps showing observed occurrences, modelled current and forecast probabilities of occurrence for the 21 species. Appendix S7 Proportion of area where models disagree, within the area predicted as suitable by at least one model. Appendix S8 Post-hoc validation score of two process-based models, using different sources of occurrence as reference. Appendix S9 'Suitable' area of three European species, as projected by two process-based models as a function of the data source used to define a presence/absence threshold. istex:459A962B954EA17FDE07E6EAB321DFA53E4BA770 ANR EVORANGE - No. ANR-09-PEXT-01102 SCION - No. ANR-09-PEXT-01105 ark:/67375/WNG-38MZCHNX-C ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 1466-822X 1466-8238 1466-822X |
DOI: | 10.1111/geb.12118 |