High spatial resolution remote sensing models for landscape-scale CO₂ exchange in the Canadian Arctic
Climate warming is affecting terrestrial ecosystems in the Canadian Arctic, potentially altering the carbon balance of the landscape and contributing additional CO2 to the atmosphere. High spatial resolution remote sensing data can enhance models of net ecosystem exchange (NEE) and its component flu...
Published in: | Arctic, Antarctic, and Alpine Research |
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Format: | Article in Journal/Newspaper |
Language: | English |
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Taylor & Francis Group
2020
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Online Access: | https://doi.org/10.1080/15230430.2020.1750805 https://doaj.org/article/76def195467044999434b0ad3f1e76ba |
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fttriple:oai:gotriple.eu:oai:doaj.org/article:76def195467044999434b0ad3f1e76ba 2023-05-15T14:14:24+02:00 High spatial resolution remote sensing models for landscape-scale CO₂ exchange in the Canadian Arctic David M. Atkinson Jacqueline K. Y. Hung Fiona M. Gregory Neal A. Scott Paul M. Treitz 2020-01-01 https://doi.org/10.1080/15230430.2020.1750805 https://doaj.org/article/76def195467044999434b0ad3f1e76ba en eng Taylor & Francis Group 1523-0430 1938-4246 doi:10.1080/15230430.2020.1750805 https://doaj.org/article/76def195467044999434b0ad3f1e76ba undefined Arctic, Antarctic, and Alpine Research, Vol 52, Iss 1, Pp 248-263 (2020) carbon dioxide exchange net ecosystem exchange (nee) normalized difference vegetation index (ndvi) arctic envir geo Journal Article https://vocabularies.coar-repositories.org/resource_types/c_6501/ 2020 fttriple https://doi.org/10.1080/15230430.2020.1750805 2023-01-22T17:49:39Z Climate warming is affecting terrestrial ecosystems in the Canadian Arctic, potentially altering the carbon balance of the landscape and contributing additional CO2 to the atmosphere. High spatial resolution remote sensing data can enhance models of net ecosystem exchange (NEE) and its component fluxes, gross ecosystem exchange (GEE), and ecosystem respiration (ER) by quantifying vegetation structure and function over time. In this study, we explored the variability of daytime CO2 exchange rates for three vegetation types along a natural moisture gradient at ecologically distinct mid- and high Arctic sites. We demonstrated that for the two sites studied, there was no statistically significant variation in CO2 exchange rates for the vegetation types through the peak growing season. Hence, the capacity to model these rates with a limited number of satellite data acquisitions is feasible. Simple bivariate models relating the Normalized Difference Vegetation Index (NDVI) to CO2 exchange processes (GEE, ER, and NEE) were developed independent of vegetation type and geographic location and validated using independent data. The spectral models explain between 33 and 94 percent of the variation in CO2 exchange rates at each site, indicating a high level of functional convergence in ecosystem-level structure and function within Arctic landscapes. Article in Journal/Newspaper Antarctic and Alpine Research Arctic Arctic Unknown Arctic Arctic, Antarctic, and Alpine Research 52 1 248 263 |
institution |
Open Polar |
collection |
Unknown |
op_collection_id |
fttriple |
language |
English |
topic |
carbon dioxide exchange net ecosystem exchange (nee) normalized difference vegetation index (ndvi) arctic envir geo |
spellingShingle |
carbon dioxide exchange net ecosystem exchange (nee) normalized difference vegetation index (ndvi) arctic envir geo David M. Atkinson Jacqueline K. Y. Hung Fiona M. Gregory Neal A. Scott Paul M. Treitz High spatial resolution remote sensing models for landscape-scale CO₂ exchange in the Canadian Arctic |
topic_facet |
carbon dioxide exchange net ecosystem exchange (nee) normalized difference vegetation index (ndvi) arctic envir geo |
description |
Climate warming is affecting terrestrial ecosystems in the Canadian Arctic, potentially altering the carbon balance of the landscape and contributing additional CO2 to the atmosphere. High spatial resolution remote sensing data can enhance models of net ecosystem exchange (NEE) and its component fluxes, gross ecosystem exchange (GEE), and ecosystem respiration (ER) by quantifying vegetation structure and function over time. In this study, we explored the variability of daytime CO2 exchange rates for three vegetation types along a natural moisture gradient at ecologically distinct mid- and high Arctic sites. We demonstrated that for the two sites studied, there was no statistically significant variation in CO2 exchange rates for the vegetation types through the peak growing season. Hence, the capacity to model these rates with a limited number of satellite data acquisitions is feasible. Simple bivariate models relating the Normalized Difference Vegetation Index (NDVI) to CO2 exchange processes (GEE, ER, and NEE) were developed independent of vegetation type and geographic location and validated using independent data. The spectral models explain between 33 and 94 percent of the variation in CO2 exchange rates at each site, indicating a high level of functional convergence in ecosystem-level structure and function within Arctic landscapes. |
format |
Article in Journal/Newspaper |
author |
David M. Atkinson Jacqueline K. Y. Hung Fiona M. Gregory Neal A. Scott Paul M. Treitz |
author_facet |
David M. Atkinson Jacqueline K. Y. Hung Fiona M. Gregory Neal A. Scott Paul M. Treitz |
author_sort |
David M. Atkinson |
title |
High spatial resolution remote sensing models for landscape-scale CO₂ exchange in the Canadian Arctic |
title_short |
High spatial resolution remote sensing models for landscape-scale CO₂ exchange in the Canadian Arctic |
title_full |
High spatial resolution remote sensing models for landscape-scale CO₂ exchange in the Canadian Arctic |
title_fullStr |
High spatial resolution remote sensing models for landscape-scale CO₂ exchange in the Canadian Arctic |
title_full_unstemmed |
High spatial resolution remote sensing models for landscape-scale CO₂ exchange in the Canadian Arctic |
title_sort |
high spatial resolution remote sensing models for landscape-scale co₂ exchange in the canadian arctic |
publisher |
Taylor & Francis Group |
publishDate |
2020 |
url |
https://doi.org/10.1080/15230430.2020.1750805 https://doaj.org/article/76def195467044999434b0ad3f1e76ba |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Antarctic and Alpine Research Arctic Arctic |
genre_facet |
Antarctic and Alpine Research Arctic Arctic |
op_source |
Arctic, Antarctic, and Alpine Research, Vol 52, Iss 1, Pp 248-263 (2020) |
op_relation |
1523-0430 1938-4246 doi:10.1080/15230430.2020.1750805 https://doaj.org/article/76def195467044999434b0ad3f1e76ba |
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undefined |
op_doi |
https://doi.org/10.1080/15230430.2020.1750805 |
container_title |
Arctic, Antarctic, and Alpine Research |
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52 |
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1 |
container_start_page |
248 |
op_container_end_page |
263 |
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1766286881926938624 |