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Synthetic datasets and community tools for the rapid testing of ecological hypotheses

Authors :
Royal Canadian Geographical Society
Canadian Institute for Advanced Research
Université de Montréal
Natural Sciences and Engineering Research Council of Canada
Royal Marsden NHS Foundation Trust
Royal Society of New Zealand
Poisot, Timothée
Gravel, Dominique
Leroux, Shawn
Wood, Spencer A.
Fortin, Marie-Josée
Baiser, Benjamin
Cirtwill, Alyssa
Araújo, Miguel B.
Stouffer, Daniel B.
Royal Canadian Geographical Society
Canadian Institute for Advanced Research
Université de Montréal
Natural Sciences and Engineering Research Council of Canada
Royal Marsden NHS Foundation Trust
Royal Society of New Zealand
Poisot, Timothée
Gravel, Dominique
Leroux, Shawn
Wood, Spencer A.
Fortin, Marie-Josée
Baiser, Benjamin
Cirtwill, Alyssa
Araújo, Miguel B.
Stouffer, Daniel B.
Publication Year :
2016

Abstract

The increased availability of both open ecological data, and software to interact with it, allows the fast collection and integration of information at all spatial and taxonomic scales. This offers the opportunity to address macroecological questions in a cost‐effective way. In this contribution, we illustrate this approach by forecasting the structure of a stream food web at the global scale. In so doing, we highlight the most salient issues needing to be addressed before this approach can be used with a high degree of confidence.

Details

Database :
OAIster
Notes :
English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1257729437
Document Type :
Electronic Resource