Quantifying snow controls on vegetation greenness
Abstract Snow is a key driver for biotic processes in Arctic ecosystems. Yet, quantifying relationships between snow metrics and biological components is challenging due to lack of temporally and spatially distributed observations at ecologically relevant scales and resolutions. In this study, we qu...
Published in: | Ecosphere |
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Online Access: | http://dx.doi.org/10.1002/ecs2.2309 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fecs2.2309 https://onlinelibrary.wiley.com/doi/pdf/10.1002/ecs2.2309 https://onlinelibrary.wiley.com/doi/full-xml/10.1002/ecs2.2309 http://api.wiley.com/onlinelibrary/chorus/v1/articles/10.1002%2Fecs2.2309 https://esajournals.onlinelibrary.wiley.com/doi/pdf/10.1002/ecs2.2309 |
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crwiley:10.1002/ecs2.2309 2024-09-15T18:09:17+00:00 Quantifying snow controls on vegetation greenness Pedersen, Stine Højlund Liston, Glen E. Tamstorf, Mikkel P. Abermann, Jakob Lund, Magnus Schmidt, Niels Martin Miljøstyrelsen Energistyrelsen National Science Foundation 2018 http://dx.doi.org/10.1002/ecs2.2309 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fecs2.2309 https://onlinelibrary.wiley.com/doi/pdf/10.1002/ecs2.2309 https://onlinelibrary.wiley.com/doi/full-xml/10.1002/ecs2.2309 http://api.wiley.com/onlinelibrary/chorus/v1/articles/10.1002%2Fecs2.2309 https://esajournals.onlinelibrary.wiley.com/doi/pdf/10.1002/ecs2.2309 en eng Wiley http://creativecommons.org/licenses/by/3.0/ http://creativecommons.org/licenses/by/3.0/ Ecosphere volume 9, issue 6 ISSN 2150-8925 2150-8925 journal-article 2018 crwiley https://doi.org/10.1002/ecs2.2309 2024-08-06T04:19:36Z Abstract Snow is a key driver for biotic processes in Arctic ecosystems. Yet, quantifying relationships between snow metrics and biological components is challenging due to lack of temporally and spatially distributed observations at ecologically relevant scales and resolutions. In this study, we quantified relationships between snow, air temperature, and vegetation greenness (using annual maximum normalized difference vegetation index [Max NDVI ] and its timing [Max NDVI _ DOY ]) from ground‐based and remote‐sensing observations, in combination with physically based models, across a heterogeneous landscape in a high‐Arctic, northeast Greenland region. Across the 98‐km distance from the Greenland Ice Sheet (Gr IS ) to the coast, we quantified significant inland–coast gradients of air temperature, winter precipitation (using pre‐melt snow‐water‐equivalent [ SWE ]), and snowmelt timing (using snow‐free day of year [SnowFree_ DOY ]). Near the coast, the mean annual air temperature was 4.5°C lower, the mean SWE was 0.3 m greater, and the mean SnowFree_ DOY was 37 d later, than near the Gr IS . The regional continentality gradient was eight times stronger than the south‐to‐north air–temperature gradient along the Greenland east coast. Across this strong gradient, the mean vegetation greening‐up period (SnowFree_ DOY ‐Max NDVI _ DOY ) varied spatially by 24–57 d. We quantified significant non‐linear relationships between the vegetation characteristics of Max NDVI and Max NDVI _ DOY , and SWE , SnowFree_ DOY , and growing degree‐days‐sums during greening‐up (Greening_ GDD ) across the 16‐yr study period (2000–2015). These demonstrated that the snow metrics, both SWE and SnowFree_ DOY , were more important drivers of Max NDVI and Max NDVI _ DOY than Greening_ GDD within this seasonally snow‐covered region. The methodologies that provided temporally and spatially distributed snow, air temperature, and vegetation greenness data are applicable to any snow‐ and vegetation‐covered area on Earth. Article in Journal/Newspaper Greenland Ice Sheet Wiley Online Library Ecosphere 9 6 |
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Open Polar |
collection |
Wiley Online Library |
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crwiley |
language |
English |
description |
Abstract Snow is a key driver for biotic processes in Arctic ecosystems. Yet, quantifying relationships between snow metrics and biological components is challenging due to lack of temporally and spatially distributed observations at ecologically relevant scales and resolutions. In this study, we quantified relationships between snow, air temperature, and vegetation greenness (using annual maximum normalized difference vegetation index [Max NDVI ] and its timing [Max NDVI _ DOY ]) from ground‐based and remote‐sensing observations, in combination with physically based models, across a heterogeneous landscape in a high‐Arctic, northeast Greenland region. Across the 98‐km distance from the Greenland Ice Sheet (Gr IS ) to the coast, we quantified significant inland–coast gradients of air temperature, winter precipitation (using pre‐melt snow‐water‐equivalent [ SWE ]), and snowmelt timing (using snow‐free day of year [SnowFree_ DOY ]). Near the coast, the mean annual air temperature was 4.5°C lower, the mean SWE was 0.3 m greater, and the mean SnowFree_ DOY was 37 d later, than near the Gr IS . The regional continentality gradient was eight times stronger than the south‐to‐north air–temperature gradient along the Greenland east coast. Across this strong gradient, the mean vegetation greening‐up period (SnowFree_ DOY ‐Max NDVI _ DOY ) varied spatially by 24–57 d. We quantified significant non‐linear relationships between the vegetation characteristics of Max NDVI and Max NDVI _ DOY , and SWE , SnowFree_ DOY , and growing degree‐days‐sums during greening‐up (Greening_ GDD ) across the 16‐yr study period (2000–2015). These demonstrated that the snow metrics, both SWE and SnowFree_ DOY , were more important drivers of Max NDVI and Max NDVI _ DOY than Greening_ GDD within this seasonally snow‐covered region. The methodologies that provided temporally and spatially distributed snow, air temperature, and vegetation greenness data are applicable to any snow‐ and vegetation‐covered area on Earth. |
author2 |
Miljøstyrelsen Energistyrelsen National Science Foundation |
format |
Article in Journal/Newspaper |
author |
Pedersen, Stine Højlund Liston, Glen E. Tamstorf, Mikkel P. Abermann, Jakob Lund, Magnus Schmidt, Niels Martin |
spellingShingle |
Pedersen, Stine Højlund Liston, Glen E. Tamstorf, Mikkel P. Abermann, Jakob Lund, Magnus Schmidt, Niels Martin Quantifying snow controls on vegetation greenness |
author_facet |
Pedersen, Stine Højlund Liston, Glen E. Tamstorf, Mikkel P. Abermann, Jakob Lund, Magnus Schmidt, Niels Martin |
author_sort |
Pedersen, Stine Højlund |
title |
Quantifying snow controls on vegetation greenness |
title_short |
Quantifying snow controls on vegetation greenness |
title_full |
Quantifying snow controls on vegetation greenness |
title_fullStr |
Quantifying snow controls on vegetation greenness |
title_full_unstemmed |
Quantifying snow controls on vegetation greenness |
title_sort |
quantifying snow controls on vegetation greenness |
publisher |
Wiley |
publishDate |
2018 |
url |
http://dx.doi.org/10.1002/ecs2.2309 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fecs2.2309 https://onlinelibrary.wiley.com/doi/pdf/10.1002/ecs2.2309 https://onlinelibrary.wiley.com/doi/full-xml/10.1002/ecs2.2309 http://api.wiley.com/onlinelibrary/chorus/v1/articles/10.1002%2Fecs2.2309 https://esajournals.onlinelibrary.wiley.com/doi/pdf/10.1002/ecs2.2309 |
genre |
Greenland Ice Sheet |
genre_facet |
Greenland Ice Sheet |
op_source |
Ecosphere volume 9, issue 6 ISSN 2150-8925 2150-8925 |
op_rights |
http://creativecommons.org/licenses/by/3.0/ http://creativecommons.org/licenses/by/3.0/ |
op_doi |
https://doi.org/10.1002/ecs2.2309 |
container_title |
Ecosphere |
container_volume |
9 |
container_issue |
6 |
_version_ |
1810446753735901184 |