Monitoring Winter Stress Vulnerability of High-Latitude Understory Vegetation Using Intraspecific Trait Variability and Remote Sensing Approaches
In this study, we focused on three species that have proven to be vulnerable to winter stress: Empetrum nigrum, Vaccinium vitis-idaea and Hylocomium splendens. Our objective was to determine plant traits suitable for monitoring plant stress as well as trait shifts during spring. To this end, we used...
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Online Access: | https://doi.org/10.3390/s20072102 https://doaj.org/article/401312e1db5e47e5b9eda7cd7546709b |
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ftdoajarticles:oai:doaj.org/article:401312e1db5e47e5b9eda7cd7546709b 2023-05-15T16:06:06+02:00 Monitoring Winter Stress Vulnerability of High-Latitude Understory Vegetation Using Intraspecific Trait Variability and Remote Sensing Approaches Elmar Ritz Jarle W. Bjerke Hans Tømmervik 2020-04-01T00:00:00Z https://doi.org/10.3390/s20072102 https://doaj.org/article/401312e1db5e47e5b9eda7cd7546709b EN eng MDPI AG https://www.mdpi.com/1424-8220/20/7/2102 https://doaj.org/toc/1424-8220 doi:10.3390/s20072102 1424-8220 https://doaj.org/article/401312e1db5e47e5b9eda7cd7546709b Sensors, Vol 20, Iss 2102, p 2102 (2020) climate change evergreen plants extreme events flavonol and chlorophyll sensor (Dualex) greenness indices mosses Chemical technology TP1-1185 article 2020 ftdoajarticles https://doi.org/10.3390/s20072102 2022-12-30T20:04:48Z In this study, we focused on three species that have proven to be vulnerable to winter stress: Empetrum nigrum, Vaccinium vitis-idaea and Hylocomium splendens. Our objective was to determine plant traits suitable for monitoring plant stress as well as trait shifts during spring. To this end, we used a combination of active and passive handheld normalized difference vegetation index (NDVI) sensors, RGB indices derived from ordinary cameras, an optical chlorophyll and flavonol sensor (Dualex), and common plant traits that are sensitive to winter stress, i.e. height, specific leaf area (SLA). Our results indicate that NDVI is a good predictor for plant stress, as it correlates well with height ( r = 0.70, p < 0.001) and chlorophyll content ( r = 0.63, p < 0.001). NDVI is also related to soil depth ( r = 0.45, p < 0.001) as well as to plant stress levels based on observations in the field ( r = −0.60, p < 0.001). Flavonol content and SLA remained relatively stable during spring. Our results confirm a multi-method approach using NDVI data from the Sentinel-2 satellite and active near-remote sensing devices to determine the contribution of understory vegetation to the total ecosystem greenness. We identified low soil depth to be the major stressor for understory vegetation in the studied plots. The RGB indices were good proxies to detect plant stress (e.g. Channel G%: r = −0.77, p < 0.001) and showed high correlation with NDVI ( r = 0.75, p < 0.001). Ordinary cameras and modified cameras with the infrared filter removed were found to perform equally well. Article in Journal/Newspaper Empetrum nigrum Directory of Open Access Journals: DOAJ Articles The Sentinel ENVELOPE(73.317,73.317,-52.983,-52.983) Sensors 20 7 2102 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
climate change evergreen plants extreme events flavonol and chlorophyll sensor (Dualex) greenness indices mosses Chemical technology TP1-1185 |
spellingShingle |
climate change evergreen plants extreme events flavonol and chlorophyll sensor (Dualex) greenness indices mosses Chemical technology TP1-1185 Elmar Ritz Jarle W. Bjerke Hans Tømmervik Monitoring Winter Stress Vulnerability of High-Latitude Understory Vegetation Using Intraspecific Trait Variability and Remote Sensing Approaches |
topic_facet |
climate change evergreen plants extreme events flavonol and chlorophyll sensor (Dualex) greenness indices mosses Chemical technology TP1-1185 |
description |
In this study, we focused on three species that have proven to be vulnerable to winter stress: Empetrum nigrum, Vaccinium vitis-idaea and Hylocomium splendens. Our objective was to determine plant traits suitable for monitoring plant stress as well as trait shifts during spring. To this end, we used a combination of active and passive handheld normalized difference vegetation index (NDVI) sensors, RGB indices derived from ordinary cameras, an optical chlorophyll and flavonol sensor (Dualex), and common plant traits that are sensitive to winter stress, i.e. height, specific leaf area (SLA). Our results indicate that NDVI is a good predictor for plant stress, as it correlates well with height ( r = 0.70, p < 0.001) and chlorophyll content ( r = 0.63, p < 0.001). NDVI is also related to soil depth ( r = 0.45, p < 0.001) as well as to plant stress levels based on observations in the field ( r = −0.60, p < 0.001). Flavonol content and SLA remained relatively stable during spring. Our results confirm a multi-method approach using NDVI data from the Sentinel-2 satellite and active near-remote sensing devices to determine the contribution of understory vegetation to the total ecosystem greenness. We identified low soil depth to be the major stressor for understory vegetation in the studied plots. The RGB indices were good proxies to detect plant stress (e.g. Channel G%: r = −0.77, p < 0.001) and showed high correlation with NDVI ( r = 0.75, p < 0.001). Ordinary cameras and modified cameras with the infrared filter removed were found to perform equally well. |
format |
Article in Journal/Newspaper |
author |
Elmar Ritz Jarle W. Bjerke Hans Tømmervik |
author_facet |
Elmar Ritz Jarle W. Bjerke Hans Tømmervik |
author_sort |
Elmar Ritz |
title |
Monitoring Winter Stress Vulnerability of High-Latitude Understory Vegetation Using Intraspecific Trait Variability and Remote Sensing Approaches |
title_short |
Monitoring Winter Stress Vulnerability of High-Latitude Understory Vegetation Using Intraspecific Trait Variability and Remote Sensing Approaches |
title_full |
Monitoring Winter Stress Vulnerability of High-Latitude Understory Vegetation Using Intraspecific Trait Variability and Remote Sensing Approaches |
title_fullStr |
Monitoring Winter Stress Vulnerability of High-Latitude Understory Vegetation Using Intraspecific Trait Variability and Remote Sensing Approaches |
title_full_unstemmed |
Monitoring Winter Stress Vulnerability of High-Latitude Understory Vegetation Using Intraspecific Trait Variability and Remote Sensing Approaches |
title_sort |
monitoring winter stress vulnerability of high-latitude understory vegetation using intraspecific trait variability and remote sensing approaches |
publisher |
MDPI AG |
publishDate |
2020 |
url |
https://doi.org/10.3390/s20072102 https://doaj.org/article/401312e1db5e47e5b9eda7cd7546709b |
long_lat |
ENVELOPE(73.317,73.317,-52.983,-52.983) |
geographic |
The Sentinel |
geographic_facet |
The Sentinel |
genre |
Empetrum nigrum |
genre_facet |
Empetrum nigrum |
op_source |
Sensors, Vol 20, Iss 2102, p 2102 (2020) |
op_relation |
https://www.mdpi.com/1424-8220/20/7/2102 https://doaj.org/toc/1424-8220 doi:10.3390/s20072102 1424-8220 https://doaj.org/article/401312e1db5e47e5b9eda7cd7546709b |
op_doi |
https://doi.org/10.3390/s20072102 |
container_title |
Sensors |
container_volume |
20 |
container_issue |
7 |
container_start_page |
2102 |
_version_ |
1766402014620680192 |