Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/135717
Campo DC Valoridioma
dc.contributor.authorPatiño, J.en_US
dc.contributor.authorCollart, F.en_US
dc.contributor.authorNaranjo Cigala, Agustínen_US
dc.contributor.authorVanderpoorten, A.en_US
dc.contributor.authorMartín Esquivel, J.L.en_US
dc.contributor.authorMirolo, S.en_US
dc.contributor.authorKarger, D.N.en_US
dc.date.accessioned2025-01-29T12:36:55Z-
dc.date.available2025-01-29T12:36:55Z-
dc.date.issued2023en_US
dc.identifier.urihttp://hdl.handle.net/10553/135717-
dc.description.abstractUnderstanding how grain size affects our ability to characterize species responses to ongoing climate change is of crucial importance in the context of an increasing awareness for the substantial difference that exists between macroclimates and the actual microclimate experienced by a given species. Climate change impacts on biodiversity are expected to peak in mountain areas and montane oceanic islands, wherein the differences between macro and microclimates are precisely the largest. Here, we generated fine-scale climatic data for the Canary Islands, a mountainous oceanic archipelago and a hotspot of endemism, and compared predictions of climate change impacts on species distributions using the newly generated data at 100 m resolution versus available data at 1 km resolution. In particular, we compared the accuracy and spatial predictions of ensemble of small models for 14 Macaronesian endemic bryophyte species using these two climate models: CHELSA (~1 km) and the newly generated CanaryClim (100 m). We also generated future climate data from five individual model intercomparison projects for three warming shared socio-economic pathways. Based on species distribution models generated from CanaryClim and CHELSA, we found that models exhibited a similar accuracy, but CanaryClim-based models predicted buffered warming trends in mid-elevation ridges. Although both climate datasets predicted similar, high future range loss, these were lower for a number of species with CanaryClim. Predicted mean range gains were substantially higher with CanaryClim than with CHELSA. Overall, predicted species extinctions were higher with CHELSA than with CanaryClim. Our results highlight the important role that fine resolution climate datasets can play in predicting the potential distribution of both microrefugia and new suitable range under warming climate across topographically complex oceanic archipelagosen_US
dc.languageengen_US
dc.source4th Society of Island Biology Conference: Ecological and evolutionary processes on real and habitat islands, p. 37 (2023)en_US
dc.subject5404 Geografía regionalen_US
dc.titleBeyond the concept of oceanic islands as climatic refugia: A high resolution climate dataset for the Canary Islands, CanaryClimen_US
dc.typeinfo:eu-repo/semantics/conferenceObjecten_US
dc.typeConferenceObjecten_US
dc.relation.conference4th Society of Island Biology Conferenceen_US
dc.investigacionArtes y Humanidadesen_US
dc.type2Actas de congresosen_US
dc.utils.revisionen_US
dc.identifier.ulpgcen_US
dc.contributor.buulpgcBU-HUMen_US
dc.contributor.buulpgcBU-HUMen_US
dc.contributor.buulpgcBU-HUMen_US
dc.contributor.buulpgcBU-HUMen_US
item.grantfulltextopen-
item.fulltextCon texto completo-
crisitem.author.deptGIR IUNAT: Biología Integrativa y Recursos Biológicos-
crisitem.author.deptIU de Estudios Ambientales y Recursos Naturales-
crisitem.author.deptDepartamento de Geografía-
crisitem.author.orcid0000-0001-8191-7344-
crisitem.author.parentorgIU de Estudios Ambientales y Recursos Naturales-
crisitem.author.fullNameNaranjo Cigala, Agustín-
crisitem.event.eventsstartdate03-07-2023-
crisitem.event.eventsenddate07-07-2023-
Colección:Póster de congreso
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