Uncertainty in consensus predictions of plant species' vulnerability to climate change

Autores
Rose, Miranda Brooke; Velazco, Santiago José Elías; Regan, Helen M.; Flint, Alan L.; Flint, Lorraine E.; Thorne, James H.; Franklin, Janet
Año de publicación
2024
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Aim: Variation in spatial predictions of species' ranges made by various models has been recognized as a significant source of uncertainty for modelling species distributions. Consensus approaches that combine the results of multiple models have been employed to reduce the uncertainty introduced by different algorithms. We evaluate how estimates of habitat suitability, projected using species distribution models (SDMs), varied among different consensus methods relative to the variation introduced by different global climate models (GCMs) and representative concentration pathways (RCPs) used for projection. Location: California Floristic Province (California, US portion). Methods: We modelled the current and future potential distributions of 82 terrestrial plant species, developing model predictions under different combinations of GCMs, RCPs, time periods, dispersal assumptions and SDM consensus methods commonly used to combine different species distribution modelling algorithms. We assessed how each of these factors contributed to the variability in future predictions of species habitat suitability change and aggregate measures of proportional change in species richness. We also related variability in species-level habitat change to species' attributes. Results: Assuming full dispersal capacity, the variability between habitat predictions made by different consensus methods was higher than the variability introduced by different RCPs and GCMs. The relationships between species' attributes and variability in future habitat predictions depended on the source of uncertainty and dispersal assumptions. However, species with small ranges or low prevalence tended to be associated with high variability in range change forecasts. Main Conclusions: Our results support exploring multiple consensus approaches when considering changes in habitat suitability outside of species' current distributions, especially when projecting species with low prevalence and small range sizes, as these species tend to be of the greatest conservation concern yet produce highly variable model outputs. Differences in vulnerability between diverging greenhouse gas concentration scenarios are most readily observed for end-of-century time periods and within species' currently occupied habitats (no dispersal).
Fil: Rose, Miranda Brooke. San Diego State University; Estados Unidos
Fil: Velazco, Santiago José Elías. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; Argentina
Fil: Regan, Helen M.. University of California; Estados Unidos
Fil: Flint, Alan L.. No especifíca;
Fil: Flint, Lorraine E.. No especifíca;
Fil: Thorne, James H.. University of California at Davis; Estados Unidos
Fil: Franklin, Janet. San Diego State University; Estados Unidos
Materia
climate change
ensemble
species distribution modelling
uncertainty
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/262033

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network_name_str CONICET Digital (CONICET)
spelling Uncertainty in consensus predictions of plant species' vulnerability to climate changeRose, Miranda BrookeVelazco, Santiago José ElíasRegan, Helen M.Flint, Alan L.Flint, Lorraine E.Thorne, James H.Franklin, Janetclimate changeensemblespecies distribution modellinguncertaintyhttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1Aim: Variation in spatial predictions of species' ranges made by various models has been recognized as a significant source of uncertainty for modelling species distributions. Consensus approaches that combine the results of multiple models have been employed to reduce the uncertainty introduced by different algorithms. We evaluate how estimates of habitat suitability, projected using species distribution models (SDMs), varied among different consensus methods relative to the variation introduced by different global climate models (GCMs) and representative concentration pathways (RCPs) used for projection. Location: California Floristic Province (California, US portion). Methods: We modelled the current and future potential distributions of 82 terrestrial plant species, developing model predictions under different combinations of GCMs, RCPs, time periods, dispersal assumptions and SDM consensus methods commonly used to combine different species distribution modelling algorithms. We assessed how each of these factors contributed to the variability in future predictions of species habitat suitability change and aggregate measures of proportional change in species richness. We also related variability in species-level habitat change to species' attributes. Results: Assuming full dispersal capacity, the variability between habitat predictions made by different consensus methods was higher than the variability introduced by different RCPs and GCMs. The relationships between species' attributes and variability in future habitat predictions depended on the source of uncertainty and dispersal assumptions. However, species with small ranges or low prevalence tended to be associated with high variability in range change forecasts. Main Conclusions: Our results support exploring multiple consensus approaches when considering changes in habitat suitability outside of species' current distributions, especially when projecting species with low prevalence and small range sizes, as these species tend to be of the greatest conservation concern yet produce highly variable model outputs. Differences in vulnerability between diverging greenhouse gas concentration scenarios are most readily observed for end-of-century time periods and within species' currently occupied habitats (no dispersal).Fil: Rose, Miranda Brooke. San Diego State University; Estados UnidosFil: Velazco, Santiago José Elías. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; ArgentinaFil: Regan, Helen M.. University of California; Estados UnidosFil: Flint, Alan L.. No especifíca;Fil: Flint, Lorraine E.. No especifíca;Fil: Thorne, James H.. University of California at Davis; Estados UnidosFil: Franklin, Janet. San Diego State University; Estados UnidosWiley Blackwell Publishing, Inc2024-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/262033Rose, Miranda Brooke; Velazco, Santiago José Elías; Regan, Helen M.; Flint, Alan L.; Flint, Lorraine E.; et al.; Uncertainty in consensus predictions of plant species' vulnerability to climate change; Wiley Blackwell Publishing, Inc; Diversity and Distributions; 30; 8; 6-2024; 1-161366-9516CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://onlinelibrary.wiley.com/doi/10.1111/ddi.13898info:eu-repo/semantics/altIdentifier/doi/10.1111/ddi.13898info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:55:09Zoai:ri.conicet.gov.ar:11336/262033instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 09:55:10.246CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Uncertainty in consensus predictions of plant species' vulnerability to climate change
title Uncertainty in consensus predictions of plant species' vulnerability to climate change
spellingShingle Uncertainty in consensus predictions of plant species' vulnerability to climate change
Rose, Miranda Brooke
climate change
ensemble
species distribution modelling
uncertainty
title_short Uncertainty in consensus predictions of plant species' vulnerability to climate change
title_full Uncertainty in consensus predictions of plant species' vulnerability to climate change
title_fullStr Uncertainty in consensus predictions of plant species' vulnerability to climate change
title_full_unstemmed Uncertainty in consensus predictions of plant species' vulnerability to climate change
title_sort Uncertainty in consensus predictions of plant species' vulnerability to climate change
dc.creator.none.fl_str_mv Rose, Miranda Brooke
Velazco, Santiago José Elías
Regan, Helen M.
Flint, Alan L.
Flint, Lorraine E.
Thorne, James H.
Franklin, Janet
author Rose, Miranda Brooke
author_facet Rose, Miranda Brooke
Velazco, Santiago José Elías
Regan, Helen M.
Flint, Alan L.
Flint, Lorraine E.
Thorne, James H.
Franklin, Janet
author_role author
author2 Velazco, Santiago José Elías
Regan, Helen M.
Flint, Alan L.
Flint, Lorraine E.
Thorne, James H.
Franklin, Janet
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv climate change
ensemble
species distribution modelling
uncertainty
topic climate change
ensemble
species distribution modelling
uncertainty
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Aim: Variation in spatial predictions of species' ranges made by various models has been recognized as a significant source of uncertainty for modelling species distributions. Consensus approaches that combine the results of multiple models have been employed to reduce the uncertainty introduced by different algorithms. We evaluate how estimates of habitat suitability, projected using species distribution models (SDMs), varied among different consensus methods relative to the variation introduced by different global climate models (GCMs) and representative concentration pathways (RCPs) used for projection. Location: California Floristic Province (California, US portion). Methods: We modelled the current and future potential distributions of 82 terrestrial plant species, developing model predictions under different combinations of GCMs, RCPs, time periods, dispersal assumptions and SDM consensus methods commonly used to combine different species distribution modelling algorithms. We assessed how each of these factors contributed to the variability in future predictions of species habitat suitability change and aggregate measures of proportional change in species richness. We also related variability in species-level habitat change to species' attributes. Results: Assuming full dispersal capacity, the variability between habitat predictions made by different consensus methods was higher than the variability introduced by different RCPs and GCMs. The relationships between species' attributes and variability in future habitat predictions depended on the source of uncertainty and dispersal assumptions. However, species with small ranges or low prevalence tended to be associated with high variability in range change forecasts. Main Conclusions: Our results support exploring multiple consensus approaches when considering changes in habitat suitability outside of species' current distributions, especially when projecting species with low prevalence and small range sizes, as these species tend to be of the greatest conservation concern yet produce highly variable model outputs. Differences in vulnerability between diverging greenhouse gas concentration scenarios are most readily observed for end-of-century time periods and within species' currently occupied habitats (no dispersal).
Fil: Rose, Miranda Brooke. San Diego State University; Estados Unidos
Fil: Velazco, Santiago José Elías. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; Argentina
Fil: Regan, Helen M.. University of California; Estados Unidos
Fil: Flint, Alan L.. No especifíca;
Fil: Flint, Lorraine E.. No especifíca;
Fil: Thorne, James H.. University of California at Davis; Estados Unidos
Fil: Franklin, Janet. San Diego State University; Estados Unidos
description Aim: Variation in spatial predictions of species' ranges made by various models has been recognized as a significant source of uncertainty for modelling species distributions. Consensus approaches that combine the results of multiple models have been employed to reduce the uncertainty introduced by different algorithms. We evaluate how estimates of habitat suitability, projected using species distribution models (SDMs), varied among different consensus methods relative to the variation introduced by different global climate models (GCMs) and representative concentration pathways (RCPs) used for projection. Location: California Floristic Province (California, US portion). Methods: We modelled the current and future potential distributions of 82 terrestrial plant species, developing model predictions under different combinations of GCMs, RCPs, time periods, dispersal assumptions and SDM consensus methods commonly used to combine different species distribution modelling algorithms. We assessed how each of these factors contributed to the variability in future predictions of species habitat suitability change and aggregate measures of proportional change in species richness. We also related variability in species-level habitat change to species' attributes. Results: Assuming full dispersal capacity, the variability between habitat predictions made by different consensus methods was higher than the variability introduced by different RCPs and GCMs. The relationships between species' attributes and variability in future habitat predictions depended on the source of uncertainty and dispersal assumptions. However, species with small ranges or low prevalence tended to be associated with high variability in range change forecasts. Main Conclusions: Our results support exploring multiple consensus approaches when considering changes in habitat suitability outside of species' current distributions, especially when projecting species with low prevalence and small range sizes, as these species tend to be of the greatest conservation concern yet produce highly variable model outputs. Differences in vulnerability between diverging greenhouse gas concentration scenarios are most readily observed for end-of-century time periods and within species' currently occupied habitats (no dispersal).
publishDate 2024
dc.date.none.fl_str_mv 2024-06
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/262033
Rose, Miranda Brooke; Velazco, Santiago José Elías; Regan, Helen M.; Flint, Alan L.; Flint, Lorraine E.; et al.; Uncertainty in consensus predictions of plant species' vulnerability to climate change; Wiley Blackwell Publishing, Inc; Diversity and Distributions; 30; 8; 6-2024; 1-16
1366-9516
CONICET Digital
CONICET
url http://hdl.handle.net/11336/262033
identifier_str_mv Rose, Miranda Brooke; Velazco, Santiago José Elías; Regan, Helen M.; Flint, Alan L.; Flint, Lorraine E.; et al.; Uncertainty in consensus predictions of plant species' vulnerability to climate change; Wiley Blackwell Publishing, Inc; Diversity and Distributions; 30; 8; 6-2024; 1-16
1366-9516
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://onlinelibrary.wiley.com/doi/10.1111/ddi.13898
info:eu-repo/semantics/altIdentifier/doi/10.1111/ddi.13898
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Wiley Blackwell Publishing, Inc
publisher.none.fl_str_mv Wiley Blackwell Publishing, Inc
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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