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Monitoring Winter Stress Vulnerability of High-Latitude Understory Vegetation Using Intraspecific Trait Variability and Remote Sensing Approaches

Ritz, E.; Bjerke, J. W.; Tømmervik, H.

Abstract:
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. ... mehr

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Verlagsausgabe §
DOI: 10.5445/IR/1000118966
Veröffentlicht am 18.05.2020
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Wasser und Gewässerentwicklung (IWG)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2020
Sprache Englisch
Identifikator ISSN: 1424-8220
KITopen-ID: 1000118966
Erschienen in Sensors
Band 20
Heft 7
Seiten Article: 2102
Vorab online veröffentlicht am 08.04.2020
Schlagwörter climate change; evergreen plants; extreme events; flavonol and chlorophyll sensor (Dualex); greenness indices; mosses; near-remote sensing active and passive NDVI sensors; Sentinel-2; subarctic vegetation damage
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