Please use this identifier to cite or link to this item: http://hdl.handle.net/10174/23525

Title: Outstanding Challenges in the Transferability of Ecological Models
Authors: Yates, Katherine L.
Bouchet, Phil J.
Caley, M. Julian
Mengersen, Kerrie
Randin, Christophe F.
Parnell, Stephen
Fielding, Alan H.
Bamford, Andrew J.
Ban, Stephen
Barbosa, A. Márcia
Dormann, Carsten F.
Elith, Jane
Embling, Clare B.
Ervin, Gary N.
Fisher, Rebecca
Gould, Susan
Graf, Roland F.
Gregr, Edward J.
Halpin, Patrick N.
Heikkinen, Risto K.
Heinänen, Stefan
Jones, Alice R.
Krishnakumar, Periyadan K.
Lauria, Valentina
Lozano-Montes, Hector
Mannocci, Laura
Mellin, Camille
Mesgaran, Mohsen B.
Moreno-Amat, Elena
Mormede, Sophie
Novaczek, Emilie
Oppel, Steffen
Ortuño Crespo, Guillermo
Peterson, A. Townsend
Rapacciuolo, Giovanni
Roberts, Jason J.
Ross, Rebecca E.
Scales, Kylie L.
Schoeman, David
Snelgrove, Paul
et al.
Issue Date: 2018
Citation: Yates, Katherine L.; Bouchet, Phil J.; Caley, M. Julian; Mengersen, Kerrie; Randin, Christophe F.; Parnell, Stephen; Fielding, Alan H.; Bamford, Andrew J.; Ban, Stephen; Barbosa, A. Márcia; Dormann, Carsten F.; Elith, Jane; Embling, Clare B.; Ervin, Gary N.; Fisher, Rebecca; Gould, Susan; Graf, Roland F.; Gregr, Edward J.; Halpin, Patrick N.; Heikkinen, Risto K.; Heinänen, Stefan; Jones, Alice R.; Krishnakumar, Periyadan K.; Lauria, Valentina; Lozano-Montes, Hector; Mannocci, Laura; Mellin, Camille; Mesgaran, Mohsen B.; Moreno-Amat, Elena; Mormede, Sophie; Novaczek, Emilie; Oppel, Steffen; Ortuño Crespo, Guillermo; Peterson, A. Townsend; Rapacciuolo, Giovanni; Roberts, Jason J.; Ross, Rebecca E.; Scales, Kylie L.; Schoeman, David; Snelgrove, Paul; et al.Outstanding Challenges in the Transferability of Ecological Models, Trends in Ecology & Evolution, 33, 10, 790-802, 2018.
Abstract: Predictive models are central to many scientific disciplines and vital for informing management in a rapidly changing world. However, limited understanding of the accuracy and precision of models transferred to novel conditions (their ‘trans- ferability’) undermines confidence in their predictions. Here, 50 experts identified priority knowledge gaps which, if filled, will most improve model transfers. These are summarized into six technical and six fundamental challenges, which underlie the combined need to intensify research on the determinants of ecological predictability, including species traits and data quality, and develop best prac- tices for transferring models. Of high importance is the identification of a widely applicable set of transferability metrics, with appropriate tools to quantify the sources and impacts of prediction uncertainty under novel conditions.
URI: http://hdl.handle.net/10174/23525
Other Identifiers: 01695347
Type: article
Appears in Collections:CIBIO-UE - Publicações - Artigos em Revistas Internacionais Com Arbitragem Científica

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