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...

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Published in:Ecosphere
Main Authors: Pedersen, Stine Højlund, Liston, Glen E., Tamstorf, Mikkel P., Abermann, Jakob, Lund, Magnus, Schmidt, Niels Martin
Other Authors: Miljøstyrelsen, Energistyrelsen, National Science Foundation
Format: Article in Journal/Newspaper
Language:English
Published: Wiley 2018
Subjects:
Online Access:http://dx.doi.org/10.1002/ecs2.2309
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spelling 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
institution Open Polar
collection Wiley Online Library
op_collection_id 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
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genre Greenland
Ice Sheet
genre_facet Greenland
Ice Sheet
op_source Ecosphere
volume 9, issue 6
ISSN 2150-8925 2150-8925
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