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Title

Where are the wild things? Why we need better data on species distribution

Publication Year

2014

Author(s)
  • Duputie, Anne
  • Zimmermann, Niklaus E.
  • Chuine, Isabelle
Source
GLOBAL ECOLOGY AND BIOGEOGRAPHY Volume: 23 Issue: 4 Pages: 457-467 Published: 2014
ISSN
1466-822X eISSN: 1466-8238
Abstract

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.

Author Keyword(s)
  • species occurrence data
  • uncertainty
  • species distribution models
  • European forest trees
  • Climate change
  • model robustness
KeyWord(s) Plus
  • DISTRIBUTION MODELS
  • CLIMATE-CHANGE
  • CITIZEN SCIENCE
  • GLOBAL BIODIVERSITY
  • ECOLOGICAL RESEARCH
  • VEGETATION MODEL
  • TREE
  • RANGE
  • UNCERTAINTY
  • PREDICTIONS
ESI Discipline(s)
  • Environment/Ecology
  • Geosciences
Web of Science Category(ies)
  • Ecology
  • Geography, Physical
Adress(es)

[Duputie, Anne; Chuine, Isabelle] CEFE UMR 5175, F-34293 Montpellier 5, France; [Zimmermann, Niklaus E.] WSL, Swiss Fed Res Inst, Landscape Dynam Unit, CH-8903 Birmensdorf, Switzerland

Reprint Adress

Duputie, A (reprint author), Univ Lille 1, CNRS, Lab Genet & Evolut Populat Vegetales, UMR 8198, F-59650 Villeneuve Dascq, France.

Country(ies)
  • France
  • Switzerland
CNRS - Adress(es)
  • Centre d'Ecologie Fonctionnelle et Evolutive (CEFE), UMR5175
  • Evolution, Ecologie et Paléontologie (Evo-Eco-Paleo), UMR8198
Accession Number
WOS:000332061800008
uid:/MBD6FVW0
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