Development of new metrics to assess and quantify climatic drivers of Extreme event driven Arctic browning
Rapid climate change in Arctic regions is resulting in more frequent extreme climatic events. These can cause large-scale vegetation damage, and are therefore among key drivers of declines in biomass and productivity (or “browning”) observed across Arctic regions in recent years. Extreme events whic...
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ftninstnf:oai:brage.nina.no:11250/2654637 2024-06-23T07:49:08+00:00 Development of new metrics to assess and quantify climatic drivers of Extreme event driven Arctic browning Treharne, Rachael Bjerke, Jarle W. Tømmervik, Hans Phoenix, Gareth H. 2020 application/pdf https://hdl.handle.net/11250/2654637 https://doi.org/10.1016/j.rse.2020.111749 eng eng urn:issn:0034-4257 https://hdl.handle.net/11250/2654637 https://doi.org/10.1016/j.rse.2020.111749 cristin:1807909 Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal http://creativecommons.org/licenses/by-nc-nd/4.0/deed.no 243 Remote Sensing of Environment Arctic Climate change Extreme events Climate metrics Browning Winter NDVI Heathland Sub-Arctic Ericoid shrubs VDP::Matematikk og Naturvitenskap: 400::Zoologiske og botaniske fag: 480 Journal article 2020 ftninstnf https://doi.org/10.1016/j.rse.2020.111749 2024-06-07T04:11:00Z Rapid climate change in Arctic regions is resulting in more frequent extreme climatic events. These can cause large-scale vegetation damage, and are therefore among key drivers of declines in biomass and productivity (or “browning”) observed across Arctic regions in recent years. Extreme events which cause browning are driven by multiple interacting climatic variables, and are defined by their ecological impact – most commonly plant mortality. Quantifying the climatic causes of these multivariate, ecologically defined events is challenging, and so existing work has typically determined the climatic causes of browning events on a case-by-case basis in a descriptive, unsystematic manner. While this has allowed development of important qualitative understanding of the mechanisms underlying extreme event driven browning, it cannot definitively link browning to specific climatic variables, or predict how changes in these variables will influence browning severity. It is therefore not yet possible to determine how extreme events will influence ecosystem responses to climate change across Arctic regions. To address this, novel, process-based climate metrics that can be used to quantify the conditions and interactions that drive the ecological responses defining common extreme events were developed using publicly available snow depth and air temperature data (two of the main climate variables implicated in browning). These process-based metrics explained up to 63% of variation in plot-level Normalised Difference Vegetation Index (NDVI) at sites within areas affected by extreme events across boreal and sub-Arctic Norway. This demonstrates potential to use simple metrics to assess the contribution of extreme events to changes in Arctic biomass and productivity at regional scales. In addition, scaling up these metrics across the Norwegian Arctic region resulted in significant correlations with remotely-sensed NDVI, and provided much-needed insights into how climatic variables interact to determine the severity of browning across ... Article in Journal/Newspaper Arctic Climate change Norwegian Institute for Nature Research: Brage NINA Arctic Norway Browning ENVELOPE(164.050,164.050,-74.617,-74.617) Remote Sensing of Environment 243 111749 |
institution |
Open Polar |
collection |
Norwegian Institute for Nature Research: Brage NINA |
op_collection_id |
ftninstnf |
language |
English |
topic |
Arctic Climate change Extreme events Climate metrics Browning Winter NDVI Heathland Sub-Arctic Ericoid shrubs VDP::Matematikk og Naturvitenskap: 400::Zoologiske og botaniske fag: 480 |
spellingShingle |
Arctic Climate change Extreme events Climate metrics Browning Winter NDVI Heathland Sub-Arctic Ericoid shrubs VDP::Matematikk og Naturvitenskap: 400::Zoologiske og botaniske fag: 480 Treharne, Rachael Bjerke, Jarle W. Tømmervik, Hans Phoenix, Gareth H. Development of new metrics to assess and quantify climatic drivers of Extreme event driven Arctic browning |
topic_facet |
Arctic Climate change Extreme events Climate metrics Browning Winter NDVI Heathland Sub-Arctic Ericoid shrubs VDP::Matematikk og Naturvitenskap: 400::Zoologiske og botaniske fag: 480 |
description |
Rapid climate change in Arctic regions is resulting in more frequent extreme climatic events. These can cause large-scale vegetation damage, and are therefore among key drivers of declines in biomass and productivity (or “browning”) observed across Arctic regions in recent years. Extreme events which cause browning are driven by multiple interacting climatic variables, and are defined by their ecological impact – most commonly plant mortality. Quantifying the climatic causes of these multivariate, ecologically defined events is challenging, and so existing work has typically determined the climatic causes of browning events on a case-by-case basis in a descriptive, unsystematic manner. While this has allowed development of important qualitative understanding of the mechanisms underlying extreme event driven browning, it cannot definitively link browning to specific climatic variables, or predict how changes in these variables will influence browning severity. It is therefore not yet possible to determine how extreme events will influence ecosystem responses to climate change across Arctic regions. To address this, novel, process-based climate metrics that can be used to quantify the conditions and interactions that drive the ecological responses defining common extreme events were developed using publicly available snow depth and air temperature data (two of the main climate variables implicated in browning). These process-based metrics explained up to 63% of variation in plot-level Normalised Difference Vegetation Index (NDVI) at sites within areas affected by extreme events across boreal and sub-Arctic Norway. This demonstrates potential to use simple metrics to assess the contribution of extreme events to changes in Arctic biomass and productivity at regional scales. In addition, scaling up these metrics across the Norwegian Arctic region resulted in significant correlations with remotely-sensed NDVI, and provided much-needed insights into how climatic variables interact to determine the severity of browning across ... |
format |
Article in Journal/Newspaper |
author |
Treharne, Rachael Bjerke, Jarle W. Tømmervik, Hans Phoenix, Gareth H. |
author_facet |
Treharne, Rachael Bjerke, Jarle W. Tømmervik, Hans Phoenix, Gareth H. |
author_sort |
Treharne, Rachael |
title |
Development of new metrics to assess and quantify climatic drivers of Extreme event driven Arctic browning |
title_short |
Development of new metrics to assess and quantify climatic drivers of Extreme event driven Arctic browning |
title_full |
Development of new metrics to assess and quantify climatic drivers of Extreme event driven Arctic browning |
title_fullStr |
Development of new metrics to assess and quantify climatic drivers of Extreme event driven Arctic browning |
title_full_unstemmed |
Development of new metrics to assess and quantify climatic drivers of Extreme event driven Arctic browning |
title_sort |
development of new metrics to assess and quantify climatic drivers of extreme event driven arctic browning |
publishDate |
2020 |
url |
https://hdl.handle.net/11250/2654637 https://doi.org/10.1016/j.rse.2020.111749 |
long_lat |
ENVELOPE(164.050,164.050,-74.617,-74.617) |
geographic |
Arctic Norway Browning |
geographic_facet |
Arctic Norway Browning |
genre |
Arctic Climate change |
genre_facet |
Arctic Climate change |
op_source |
243 Remote Sensing of Environment |
op_relation |
urn:issn:0034-4257 https://hdl.handle.net/11250/2654637 https://doi.org/10.1016/j.rse.2020.111749 cristin:1807909 |
op_rights |
Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal http://creativecommons.org/licenses/by-nc-nd/4.0/deed.no |
op_doi |
https://doi.org/10.1016/j.rse.2020.111749 |
container_title |
Remote Sensing of Environment |
container_volume |
243 |
container_start_page |
111749 |
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1802639399892025344 |