000153634 001__ 153634
000153634 005__ 20251017144554.0
000153634 0247_ $$2doi$$a10.1111/ecog.04627
000153634 0248_ $$2sideral$$a116852
000153634 037__ $$aART-2020-116852
000153634 041__ $$aeng
000153634 100__ $$aFeng, X.
000153634 245__ $$aPhysiology in ecological niche modeling: using zebra mussel's upper thermal tolerance to refine model predictions through Bayesian analysis
000153634 260__ $$c2020
000153634 5060_ $$aAccess copy available to the general public$$fUnrestricted
000153634 5203_ $$aClimate change and human-mediated dispersal are increasingly influencing species’ geographic distributions. Ecological niche models (ENMs) are widely used in forecasting species’ distributions, but are weak in extrapolation to novel environments because they rely on available distributional data and do not incorporate mechanistic information, such as species’ physiological response to abiotic conditions. To improve accuracy of ENMs, we incorporated physiological knowledge through Bayesian analysis. In a case study of the zebra mussel Dreissena polymorpha, we used native and global occurrences to obtain native and global models representing narrower and broader understanding of zebra mussel’ response to temperature. We also obtained thermal limit and survival information for zebra mussel from peer-reviewed literature and used the two types of information separately and jointly to calibrate native models. We showed that, compared to global models, native models predicted lower relative probability of presence along zebra mussel''s upper thermal limit, suggesting the shortcoming of native models in predicting zebra mussel''s response to warm temperature. We also found that native models showed improved prediction of relative probability of presence when thermal limit was used alone, and best approximated global models when both thermal limit and survival data were used. Our result suggests that integration of physiological knowledge enhances extrapolation of ENM in novel environments. Our modeling framework can be generalized for other species or other physiological limits and may incorporate evolutionary information (e.g. evolved thermal tolerance), thus has the potential to improve predictions of species’ invasive potential and distributional response to climate change. © 2019 The Authors. Ecography published by John Wiley & Sons on behalf of Nordic Society Oikos
000153634 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttps://creativecommons.org/licenses/by/4.0/deed.es
000153634 590__ $$a5.992$$b2020
000153634 591__ $$aBIODIVERSITY CONSERVATION$$b5 / 60 = 0.083$$c2020$$dQ1$$eT1
000153634 591__ $$aECOLOGY$$b18 / 166 = 0.108$$c2020$$dQ1$$eT1
000153634 592__ $$a2.972$$b2020
000153634 593__ $$aEcology, Evolution, Behavior and Systematics$$c2020$$dQ1
000153634 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000153634 700__ $$aLiang, Y.
000153634 700__ $$0(orcid)0000-0002-1552-8233$$aGallardo, B.
000153634 700__ $$aPapes, M.
000153634 773__ $$g43, 2 (2020), 270-282$$pEcography$$tEcography$$x0906-7590
000153634 85641 $$uhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85074773633&doi=10.1111%2fecog.04627&partnerID=40&md5=3a1427dcca4a70f68f0dd3500f30e7cd$$zTexto completo de la revista
000153634 8564_ $$s1478845$$uhttps://zaguan.unizar.es/record/153634/files/texto_completo.pdf$$yVersión publicada
000153634 8564_ $$s2334348$$uhttps://zaguan.unizar.es/record/153634/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000153634 909CO $$ooai:zaguan.unizar.es:153634$$particulos$$pdriver
000153634 951__ $$a2025-10-17-14:12:37
000153634 980__ $$aARTICLE