ΔTraitSDMs: species distribution models that account for local adaptation and phenotypic plasticity
Improving our understanding of species ranges under rapid climate change requires application of our knowledge of the tolerance and adaptive capacity of populations to changing environmental conditions. Here, we describe an emerging modelling approach, ΔTraitSDM, which attempts to achieve this by ex...
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Veröffentlicht in: | The New phytologist 2019-06, Vol.222 (4), p.1757-1765 |
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creator | Garzón, Marta Benito Robson, T. Matthew Hampe, Arndt |
description | Improving our understanding of species ranges under rapid climate change requires application of our knowledge of the tolerance and adaptive capacity of populations to changing environmental conditions. Here, we describe an emerging modelling approach, ΔTraitSDM, which attempts to achieve this by explaining species distribution ranges based on phenotypic plasticity and local adaptation of fitness-related traits measured across large geographical gradients. The collection of intraspecific trait data measured in common gardens spanning broad environmental clines has promoted the development of these new models – first in trees but now rapidly expanding to other organisms. We review, explain and harmonize the main findings from this new generation of models that, by including trait variation over geographical scales, are able to provide new insights into future species ranges. Overall, ΔTraitSDM predictions generally deliver a less alarming message than previous models of species distribution under new climates, indicating that phenotypic plasticity should help, to a considerable degree, some plant populations to persist under climate change. The development of ΔTraitSDMs offers a new perspective to analyse intraspecific variation in single and multiple traits, with the rationale that trait (co)variation and consequently fitness can significantly change across geographical gradients and new climates. |
doi_str_mv | 10.1111/nph.15716 |
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We review, explain and harmonize the main findings from this new generation of models that, by including trait variation over geographical scales, are able to provide new insights into future species ranges. Overall, ΔTraitSDM predictions generally deliver a less alarming message than previous models of species distribution under new climates, indicating that phenotypic plasticity should help, to a considerable degree, some plant populations to persist under climate change. The development of ΔTraitSDMs offers a new perspective to analyse intraspecific variation in single and multiple traits, with the rationale that trait (co)variation and consequently fitness can significantly change across geographical gradients and new climates.</description><identifier>ISSN: 0028-646X</identifier><identifier>EISSN: 1469-8137</identifier><identifier>DOI: 10.1111/nph.15716</identifier><identifier>PMID: 30697749</identifier><language>eng</language><publisher>England: Wiley</publisher><subject>Adaptation ; Adaptation, Physiological ; Climate ; Climate change ; Clines ; common gardens ; Distribution ; Ecosystem ; Environmental changes ; Environmental conditions ; Fitness ; Gradients ; intraspecific variation ; Life Sciences ; local adaptation ; Models, Biological ; Phenotype ; Phenotypic plasticity ; Plant population ; Plant populations ; Plastic properties ; Plasticity ; Populations ; Quantitative Trait, Heritable ; Research review ; Species ; species ranges ; Species Specificity ; traits ; trees ; Variation</subject><ispartof>The New phytologist, 2019-06, Vol.222 (4), p.1757-1765</ispartof><rights>2019 The Authors © 2019 New Phytologist Trust</rights><rights>2019 The Authors. 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New Phytologist © 2019 New Phytologist Trust.</rights><rights>Copyright © 2019 New Phytologist Trust</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><orcidid>0000-0002-3436-123X ; 0000-0002-8631-796X ; 0000-0003-2551-9784</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/26675930$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/26675930$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>230,314,780,784,803,885,1416,1432,27922,27923,45572,45573,46407,46831,58015,58248</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30697749$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://hal.inrae.fr/hal-02627579$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Garzón, Marta Benito</creatorcontrib><creatorcontrib>Robson, T. 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The collection of intraspecific trait data measured in common gardens spanning broad environmental clines has promoted the development of these new models – first in trees but now rapidly expanding to other organisms. We review, explain and harmonize the main findings from this new generation of models that, by including trait variation over geographical scales, are able to provide new insights into future species ranges. Overall, ΔTraitSDM predictions generally deliver a less alarming message than previous models of species distribution under new climates, indicating that phenotypic plasticity should help, to a considerable degree, some plant populations to persist under climate change. 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subjects | Adaptation Adaptation, Physiological Climate Climate change Clines common gardens Distribution Ecosystem Environmental changes Environmental conditions Fitness Gradients intraspecific variation Life Sciences local adaptation Models, Biological Phenotype Phenotypic plasticity Plant population Plant populations Plastic properties Plasticity Populations Quantitative Trait, Heritable Research review Species species ranges Species Specificity traits trees Variation |
title | ΔTraitSDMs: species distribution models that account for local adaptation and phenotypic plasticity |
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