ORCID
- Clare B. Embling: 0000-0002-8238-433X
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
DOI Link
DOI
10.1016/j.tree.2018.08.001
Publication Date
2018-10-01
Publication Title
Trends in Ecology and Evolution
Volume
33
Issue
10
ISSN
0169-5347
Embargo Period
2021-10-20
First Page
790
Last Page
802
Recommended Citation
Yates, K., Bouchet, P., Caley, M., Mengersen, K., Randin, C., Parnell, S., Fielding, A., Bamford, A., Ban, S., Barbosa, A., Dormann, C., Elith, J., Embling, C., Ervin, G., Fisher, R., Gould, S., Graf, R., Gregr, E., Halpin, P., Heikkinen, R., Heinänen, S., Jones, A., Krishnakumar, P., Lauria, V., Lozano-Montes, H., Mannocci, L., Mellin, C., Mesgaran, M., Moreno-Amat, E., Mormede, S., Novaczek, E., Oppel, S., Ortuño, C., Peterson, A., Rapacciuolo, G., Roberts, J., Ross, R., Scales, K., Schoeman, D., Snelgrove, P., Sundblad, G., Thuiller, W., Torres, L. G., Verbruggen, H., Wang, L., Wenger, S., Whittingham, M. J., Zharikov, Y., Zurell, D., & Sequeira, A. M. (2018) 'Outstanding Challenges in the Transferability of Ecological Models', Trends in Ecology and Evolution, 33(10), pp. 790-802. Available at: 10.1016/j.tree.2018.08.001
