Outstanding Challenges in the Transferability of Ecological Models

Katherine L. Yates, Phil J. Bouchet, M. Julian Caley, Kerrie Mengersen, Christophe F. Randin, Stephen Parnell, Alan H. Fielding, Andrew J. Bamford, Stephen Ban, A. Márcia Barbosa, Carsten F. Dormann, Jane Elith, Clare B. Embling, Gary N. Ervin, Rebecca Fisher, Susan Gould, Roland F. Graf, Edward J. Gregr, Patrick N. Halpin, Risto K. Heikkinen & 30 others Stefan Heinänen, Alice R. Jones, Periyadan K. Krishnakumar, Valentina Lauria, Hector Lozano-Montes, Laura Mannocci, Camille Mellin, Mohsen B. Mesgaran, Elena Moreno-Amat, Sophie Mormede, Emilie Novaczek, Steffen Oppel, Guillermo Ortuño Crespo, A. Townsend Peterson, Giovanni Rapacciuolo, Jason J. Roberts, Rebecca E. Ross, Kylie L. Scales, David Schoeman, Paul Snelgrove, Göran Sundblad, Wilfried Thuiller, Leigh G. Torres, Heroen Verbruggen, Lifei Wang, Seth Wenger, Mark J. Whittingham, Yuri Zharikov, Damaris Zurell, Ana M.M. Sequeira

Research output: Contribution to journalReview article

30 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)790-802
Number of pages13
JournalTrends in Ecology and Evolution
Volume33
Issue number10
DOIs
Publication statusPublished - 1 Oct 2018

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Yates, K. L., Bouchet, P. J., Caley, M. J., Mengersen, K., Randin, C. F., Parnell, S., ... Sequeira, A. M. M. (2018). Outstanding Challenges in the Transferability of Ecological Models. Trends in Ecology and Evolution, 33(10), 790-802. https://doi.org/10.1016/j.tree.2018.08.001
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 ; Sundblad, Göran ; Thuiller, Wilfried ; Torres, Leigh G. ; Verbruggen, Heroen ; Wang, Lifei ; Wenger, Seth ; Whittingham, Mark J. ; Zharikov, Yuri ; Zurell, Damaris ; Sequeira, Ana M.M. / Outstanding Challenges in the Transferability of Ecological Models. In: Trends in Ecology and Evolution. 2018 ; Vol. 33, No. 10. pp. 790-802.
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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.",
keywords = "extrapolation, generality, habitat models, model transfers, Predictive modeling, species distribution models, uncertainty",
author = "Yates, {Katherine L.} and Bouchet, {Phil J.} and Caley, {M. Julian} and Kerrie Mengersen and Randin, {Christophe F.} and Stephen Parnell and Fielding, {Alan H.} and Bamford, {Andrew J.} and Stephen Ban and Barbosa, {A. M{\'a}rcia} and Dormann, {Carsten F.} and Jane Elith and Embling, {Clare B.} and Ervin, {Gary N.} and Rebecca Fisher and Susan Gould and Graf, {Roland F.} and Gregr, {Edward J.} and Halpin, {Patrick N.} and Heikkinen, {Risto K.} and Stefan Hein{\"a}nen and Jones, {Alice R.} and Krishnakumar, {Periyadan K.} and Valentina Lauria and Hector Lozano-Montes and Laura Mannocci and Camille Mellin and Mesgaran, {Mohsen B.} and Elena Moreno-Amat and Sophie Mormede and Emilie Novaczek and Steffen Oppel and {Ortu{\~n}o Crespo}, Guillermo and Peterson, {A. Townsend} and Giovanni Rapacciuolo and Roberts, {Jason J.} and Ross, {Rebecca E.} and Scales, {Kylie L.} and David Schoeman and Paul Snelgrove and G{\"o}ran Sundblad and Wilfried Thuiller and Torres, {Leigh G.} and Heroen Verbruggen and Lifei Wang and Seth Wenger and Whittingham, {Mark J.} and Yuri Zharikov and Damaris Zurell and Sequeira, {Ana M.M.}",
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Yates, KL, Bouchet, PJ, Caley, MJ, Mengersen, K, Randin, CF, Parnell, S, Fielding, AH, Bamford, AJ, Ban, S, Barbosa, AM, Dormann, CF, Elith, J, Embling, CB, Ervin, GN, Fisher, R, Gould, S, Graf, RF, Gregr, EJ, Halpin, PN, Heikkinen, RK, Heinänen, S, Jones, AR, Krishnakumar, PK, Lauria, V, Lozano-Montes, H, Mannocci, L, Mellin, C, Mesgaran, MB, Moreno-Amat, E, Mormede, S, Novaczek, E, Oppel, S, Ortuño Crespo, G, Peterson, AT, Rapacciuolo, G, Roberts, JJ, Ross, RE, Scales, KL, Schoeman, D, Snelgrove, P, Sundblad, G, Thuiller, W, Torres, LG, Verbruggen, H, Wang, L, Wenger, S, Whittingham, MJ, Zharikov, Y, Zurell, D & Sequeira, AMM 2018, 'Outstanding Challenges in the Transferability of Ecological Models' Trends in Ecology and Evolution, vol. 33, no. 10, pp. 790-802. https://doi.org/10.1016/j.tree.2018.08.001

Outstanding Challenges in the Transferability of Ecological Models. / 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; Sundblad, Göran; Thuiller, Wilfried; Torres, Leigh G.; Verbruggen, Heroen; Wang, Lifei; Wenger, Seth; Whittingham, Mark J.; Zharikov, Yuri; Zurell, Damaris; Sequeira, Ana M.M.

In: Trends in Ecology and Evolution, Vol. 33, No. 10, 01.10.2018, p. 790-802.

Research output: Contribution to journalReview article

TY - JOUR

T1 - Outstanding Challenges in the Transferability of Ecological Models

AU - Yates, Katherine L.

AU - Bouchet, Phil J.

AU - Caley, M. Julian

AU - Mengersen, Kerrie

AU - Randin, Christophe F.

AU - Parnell, Stephen

AU - Fielding, Alan H.

AU - Bamford, Andrew J.

AU - Ban, Stephen

AU - Barbosa, A. Márcia

AU - Dormann, Carsten F.

AU - Elith, Jane

AU - Embling, Clare B.

AU - Ervin, Gary N.

AU - Fisher, Rebecca

AU - Gould, Susan

AU - Graf, Roland F.

AU - Gregr, Edward J.

AU - Halpin, Patrick N.

AU - Heikkinen, Risto K.

AU - Heinänen, Stefan

AU - Jones, Alice R.

AU - Krishnakumar, Periyadan K.

AU - Lauria, Valentina

AU - Lozano-Montes, Hector

AU - Mannocci, Laura

AU - Mellin, Camille

AU - Mesgaran, Mohsen B.

AU - Moreno-Amat, Elena

AU - Mormede, Sophie

AU - Novaczek, Emilie

AU - Oppel, Steffen

AU - Ortuño Crespo, Guillermo

AU - Peterson, A. Townsend

AU - Rapacciuolo, Giovanni

AU - Roberts, Jason J.

AU - Ross, Rebecca E.

AU - Scales, Kylie L.

AU - Schoeman, David

AU - Snelgrove, Paul

AU - Sundblad, Göran

AU - Thuiller, Wilfried

AU - Torres, Leigh G.

AU - Verbruggen, Heroen

AU - Wang, Lifei

AU - Wenger, Seth

AU - Whittingham, Mark J.

AU - Zharikov, Yuri

AU - Zurell, Damaris

AU - Sequeira, Ana M.M.

PY - 2018/10/1

Y1 - 2018/10/1

N2 - 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.

AB - 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.

KW - extrapolation

KW - generality

KW - habitat models

KW - model transfers

KW - Predictive modeling

KW - species distribution models

KW - uncertainty

UR - http://www.scopus.com/inward/record.url?scp=85052314540&partnerID=8YFLogxK

U2 - 10.1016/j.tree.2018.08.001

DO - 10.1016/j.tree.2018.08.001

M3 - Review article

VL - 33

SP - 790

EP - 802

JO - Trends in Ecology and Evolution

JF - Trends in Ecology and Evolution

SN - 0169-5347

IS - 10

ER -

Yates KL, Bouchet PJ, Caley MJ, Mengersen K, Randin CF, Parnell S et al. Outstanding Challenges in the Transferability of Ecological Models. Trends in Ecology and Evolution. 2018 Oct 1;33(10):790-802. https://doi.org/10.1016/j.tree.2018.08.001