Synthetic datasets and community tools for the rapid testing of ecological hypotheses |
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| Authors: | Timothée Poisot Dominique Gravel Shawn Leroux Spencer A. Wood Marie‐Josée Fortin Benjamin Baiser Alyssa R. Cirtwill Miguel B. Araújo Daniel B. Stouffer |
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| Affiliation: | 1. Univ. de Montréal, Dépt de Sciences Biologiques, Montréal, Canada;2. Québec Centre for Biodiversity Sciences, Montréal, Canada;3. Univ. du Québec à Rimouski, Dépt de Biologie, Rimouski, Canada;4. Memorial Univ. of Newfoundland, Dept of Biology, St. John's, Canada;5. Woods Inst. for the Environment, Stanford Univ., Stanford, CA, USA;6. School for Environmental and Forest Science, Univ. of Washington, Seattle, WA, USA;7. Univ. of Toronto, Dept of Ecology and Evolutionary Biology, Toronto, Canada;8. Univ. of Florida, Dept of Wildlife, Ecology and Conservation, Gainseville, FL, USA;9. Centre for Integrative Ecology, School of Biological Sciences, Univ. of Canterbury, Christchurch, New Zealand;10. Museo Nacional de Ciencias Naturales, CSIC, C/José Gutiérrez Abascal 2, Madrid, Espa?a |
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| 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. |
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