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dc.contributor.authorTrew, BT
dc.contributor.authorEarly, R
dc.contributor.authorDuffy, JP
dc.contributor.authorChown, SL
dc.contributor.authorMaclean, I
dc.date.accessioned2022-09-02T12:08:34Z
dc.date.issued2022-04-28
dc.date.updated2022-09-02T10:48:58Z
dc.description.abstractAim: Species distribution models (SDMs) have been used widely to predict the responses of species to climate change. However, the climate data used to drive these models typically represents ambient air temperatures, derived from measurements taken 1–2 m above the ground. Most plant species live near the ground where temperatures can differ significantly, owing to the effects of solar radiation and reduced wind speed. Here, we investigate differences in spatio-temporal patterns in near-ground leaf and ambient air temperatures and the implications this has on projected changes in species richness of a suite of Fynbos plant species. Location: Fynbos Biome, South Africa. Methods: For each individual plant species (n = 83), we constructed two types of SDMs: one using ambient air temperatures and one using near-ground leaf temperatures. Each of these models was fitted to species occurrence data for a recent time period and projected backwards into the past. Species richness projections for both time periods were then constructed using binarized projections. Results: We found that the impact of climate change on species richness – both the degree of suitable climate lost from the historical range and gained outside of the historical range – was greater using SDMs built with near-ground leaf temperatures. Independent validation of the hindcast projections revealed near-ground SDMs to be more accurate. Main Conclusions: Our study suggests that SDMs constructed using ambient air temperatures are likely overestimating the breadth of the species’ occupied thermal niche, thus underestimating the climate change-driven risk to species where near-ground leaf and ambient air temperatures are particularly decoupled from one another. Additionally, ambient air SDMs may be underestimating the ex-situ refugial potential of inland mountains. Ambient air temperatures should not be considered an effective surrogate for investigating climate change impacts on species living near the ground.en_GB
dc.format.extent1282-1297
dc.identifier.citationVol. 28, No. 6, pp. 1282-1297en_GB
dc.identifier.doihttps://doi.org/10.1111/ddi.13540
dc.identifier.urihttp://hdl.handle.net/10871/130653
dc.identifierORCID: 0000-0002-0649-828X (Trew, Brittany T)
dc.identifierORCID: 0000-0003-4108-5904 (Early, Regan)
dc.language.isoenen_GB
dc.publisherWileyen_GB
dc.relation.urlhttp://www.gbif.orgen_GB
dc.relation.urlhttps://doi.org/10.5281/zenodo.6374097en_GB
dc.relation.urlhttps://cds. climate.copernicus.eu/cdsapp#!/homeen_GB
dc.relation.urlhttps://mrke.github.ioen_GB
dc.relation.urlhttps://soiltemp.weebly.com/en_GB
dc.relation.urlhttps://figshare.com/s/d40f9cb44441b252318cen_GB
dc.rights© 2022 The Authors. Diversity and Distributions published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.en_GB
dc.subjectbiodiversity hotspotsen_GB
dc.subjectclimate changeen_GB
dc.subjectconservationen_GB
dc.subjectmediterranean-type biomeen_GB
dc.subjectmicroclimateen_GB
dc.subjectmountainsen_GB
dc.subjectrefugiaen_GB
dc.subjectspecies distribution modelsen_GB
dc.titleUsing near‐ground leaf temperatures alters the projected climate change impacts on the historical range of a floristic biodiversity hotspoten_GB
dc.typeArticleen_GB
dc.date.available2022-09-02T12:08:34Z
dc.identifier.issn1366-9516
dc.descriptionThis is the final version. Available from Wiley via the DOI in this record. en_GB
dc.descriptionDATA AVAILABILITY STATEMENT: All datasets used are third-party datasets available freely on public repositories. The occurrence data for plant species in the Cape floristic Region are freely available from the Global Biodiversity Information Facility (www.gbif.org), and the occurrence data used in this study is available at: https://doi.org/10.5281/zenodo.6374097; the hourly climate data are available from the ERA5 fifth-generation ECMWF atmospheric reanalysis of the global climate (https://cds. climate.copernicus.eu/cdsapp#!/home); hourly near-ground temperatures are fully reproducible using the microclimf package for R 4.0 (https://mrke.github.io); temperature data from the Cederberg used for verification were sourced via the SOILTEMP global database of soil temperatures (https://soiltemp.weebly.com/). All figures created for this study are also available on Figshare (private link: https:// figshare.com/s/d40f9cb44441b252318c).en_GB
dc.identifier.eissn1472-4642
dc.identifier.journalDiversity and Distributionsen_GB
dc.relation.ispartofDiversity and Distributions, 28(6)
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_GB
dcterms.dateAccepted2022-04-06
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2022-04-28
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2022-09-02T12:04:53Z
refterms.versionFCDVoR
refterms.dateFOA2022-09-02T12:08:47Z
refterms.panelAen_GB
refterms.dateFirstOnline2022-04-28


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© 2022 The Authors. Diversity and Distributions published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Except where otherwise noted, this item's licence is described as © 2022 The Authors. Diversity and Distributions published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.