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High resolution temperature data for ecological research and management on the Southern Ocean Islands

Southern Ocean Islands are globally significant conservation areas. Predicting how their terrestrial ecosystems will respond to current and forecast climate change is essential for their management and requires high-quality temperature data at fine spatial resolutions. Existing datasets are inadequa...

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Autores principales: Leihy, Rachel I., Duffy, Grant A., Nortje, Erika, Chown, Steven L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6122169/
https://www.ncbi.nlm.nih.gov/pubmed/30179229
http://dx.doi.org/10.1038/sdata.2018.177
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author Leihy, Rachel I.
Duffy, Grant A.
Nortje, Erika
Chown, Steven L.
author_facet Leihy, Rachel I.
Duffy, Grant A.
Nortje, Erika
Chown, Steven L.
author_sort Leihy, Rachel I.
collection PubMed
description Southern Ocean Islands are globally significant conservation areas. Predicting how their terrestrial ecosystems will respond to current and forecast climate change is essential for their management and requires high-quality temperature data at fine spatial resolutions. Existing datasets are inadequate for this purpose. Remote-sensed land surface temperature (LST) observations, such as those collected by satellite-mounted spectroradiometers, can provide high-resolution, spatially-continuous data for isolated locations. These methods require a clear sightline to measure surface conditions, however, which can leave large data-gaps in temperature time series. Using a spatio-temporal gap-filling method applied to high-resolution (~1 km) LST observations for 20 Southern Ocean Islands, we compiled a complete monthly temperature dataset for a 15-year period (2001–2015). We validated results using in situ measurements of microclimate temperature. Gap-filled temperature observations described the thermal heterogeneity of the region better than existing climatology datasets, particularly for islands with steep elevational gradients and strong prevailing winds. This dataset will be especially useful for terrestrial ecologists, conservation biologists, and for developing island-specific management and mitigation strategies for environmental change.
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spelling pubmed-61221692018-09-07 High resolution temperature data for ecological research and management on the Southern Ocean Islands Leihy, Rachel I. Duffy, Grant A. Nortje, Erika Chown, Steven L. Sci Data Data Descriptor Southern Ocean Islands are globally significant conservation areas. Predicting how their terrestrial ecosystems will respond to current and forecast climate change is essential for their management and requires high-quality temperature data at fine spatial resolutions. Existing datasets are inadequate for this purpose. Remote-sensed land surface temperature (LST) observations, such as those collected by satellite-mounted spectroradiometers, can provide high-resolution, spatially-continuous data for isolated locations. These methods require a clear sightline to measure surface conditions, however, which can leave large data-gaps in temperature time series. Using a spatio-temporal gap-filling method applied to high-resolution (~1 km) LST observations for 20 Southern Ocean Islands, we compiled a complete monthly temperature dataset for a 15-year period (2001–2015). We validated results using in situ measurements of microclimate temperature. Gap-filled temperature observations described the thermal heterogeneity of the region better than existing climatology datasets, particularly for islands with steep elevational gradients and strong prevailing winds. This dataset will be especially useful for terrestrial ecologists, conservation biologists, and for developing island-specific management and mitigation strategies for environmental change. Nature Publishing Group 2018-09-04 /pmc/articles/PMC6122169/ /pubmed/30179229 http://dx.doi.org/10.1038/sdata.2018.177 Text en Copyright © 2018, The Author(s) http://creativecommons.org/licenses/by/4.0/ Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files made available in this article.
spellingShingle Data Descriptor
Leihy, Rachel I.
Duffy, Grant A.
Nortje, Erika
Chown, Steven L.
High resolution temperature data for ecological research and management on the Southern Ocean Islands
title High resolution temperature data for ecological research and management on the Southern Ocean Islands
title_full High resolution temperature data for ecological research and management on the Southern Ocean Islands
title_fullStr High resolution temperature data for ecological research and management on the Southern Ocean Islands
title_full_unstemmed High resolution temperature data for ecological research and management on the Southern Ocean Islands
title_short High resolution temperature data for ecological research and management on the Southern Ocean Islands
title_sort high resolution temperature data for ecological research and management on the southern ocean islands
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6122169/
https://www.ncbi.nlm.nih.gov/pubmed/30179229
http://dx.doi.org/10.1038/sdata.2018.177
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