%0 Journal Article %1 yates2018outstanding %A Yates, Katherine L. %A Bouchet, Phil J. %A Caley, M. Julian %A Mengersen, Kerrie %A Randin, Christophe F. %A Parnell, Stephen %A Fielding, Alan H. %A Bamford, Andrew J. %A Ban, Stephen %A Barbosa, A. Márcia %A Dormann, Carsten F. %A Elith, Jane %A Embling, Clare B. %A Ervin, Gary N. %A Fisher, Rebecca %A Gould, Susan %A Graf, Roland F. %A Gregr, Edward J. %A Halpin, Patrick N. %A Heikkinen, Risto K. %A Heinänen, Stefan %A Jones, Alice R. %A Krishnakumar, Periyadan K. %A Lauria, Valentina %A Lozano-Montes, Hector %A Mannocci, Laura %A Mellin, Camille %A Mesgaran, Mohsen B. %A Moreno-Amat, Elena %A Mormede, Sophie %A Novaczek, Emilie %A Oppel, Steffen %A Ortuño Crespo, Guillermo %A Peterson, A. Townsend %A Rapacciuolo, Giovanni %A Roberts, Jason J. %A Ross, Rebecca E. %A Scales, Kylie L. %A Schoeman, David %A Snelgrove, Paul %A Sundblad, Göran %A Thuiller, Wilfried %A Torres, Leigh G. %A Verbruggen, Heroen %A Wang, Lifei %A Wenger, Seth %A Whittingham, Mark J. %A Zharikov, Yuri %A Zurell, Damaris %A Sequeira, Ana M.M %D 2018 %I Elsevier %J Trends in Ecology & Evolution %K hindcasting niche_modeling review %N 10 %P 790--802 %R 10.1016/j.tree.2018.08.001 %T Outstanding Challenges in the Transferability of Ecological Models %U https://doi.org/10.1016/j.tree.2018.08.001 %V 33 %X 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 ?transferability?) 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 practices 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.

@article{yates2018outstanding, 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 ?transferability?) 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 practices 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.}, added-at = {2024-01-12T00:55:18.000+0100}, author = {Yates, Katherine L. and Bouchet, Phil J. and Caley, M. Julian and Mengersen, Kerrie and Randin, Christophe F. and Parnell, Stephen and Fielding, Alan H. and Bamford, Andrew J. and Ban, Stephen and Barbosa, A. Márcia and Dormann, Carsten F. and Elith, Jane and Embling, Clare B. and Ervin, Gary N. and Fisher, Rebecca and Gould, Susan and Graf, Roland F. and Gregr, Edward J. and Halpin, Patrick N. and Heikkinen, Risto K. and Heinänen, Stefan and Jones, Alice R. and Krishnakumar, Periyadan K. and Lauria, Valentina and Lozano-Montes, Hector and Mannocci, Laura and Mellin, Camille and Mesgaran, Mohsen B. and Moreno-Amat, Elena and Mormede, Sophie and Novaczek, Emilie and Oppel, Steffen and Ortuño Crespo, Guillermo and Peterson, A. Townsend and Rapacciuolo, Giovanni and Roberts, Jason J. and Ross, Rebecca E. and Scales, Kylie L. and Schoeman, David and Snelgrove, Paul and Sundblad, Göran and Thuiller, Wilfried and Torres, Leigh G. and Verbruggen, Heroen and Wang, Lifei and Wenger, Seth and Whittingham, Mark J. and Zharikov, Yuri and Zurell, Damaris and Sequeira, Ana M.M}, biburl = {https://www.bibsonomy.org/bibtex/219a34f52282892f93b69fb58d0e86035/peter.ralph}, comment = {doi: 10.1016/j.tree.2018.08.001}, doi = {10.1016/j.tree.2018.08.001}, interhash = {f87f66caa07564512328b5a45869e5bb}, intrahash = {19a34f52282892f93b69fb58d0e86035}, issn = {01695347}, journal = {Trends in Ecology & Evolution}, keywords = {hindcasting niche_modeling review}, month = oct, number = 10, pages = {790--802}, publisher = {Elsevier}, timestamp = {2024-01-12T00:55:18.000+0100}, title = {Outstanding Challenges in the Transferability of Ecological Models}, url = {https://doi.org/10.1016/j.tree.2018.08.001}, volume = 33, year = 2018 }