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From local to regional: Functional diversity in differently managed alpine grasslands


Rossi, Christian; Kneubühler, Mathias; Schütz, Martin; Schaepman, Michael E; Haller, Rudolf M; Risch, Anita C (2020). From local to regional: Functional diversity in differently managed alpine grasslands. Remote Sensing of Environment, 236:111415.

Abstract

Increasing evidence suggests that ecosystem functions are strongly linked to morphological plant traits, like specific leaf area (SLA) and its variability, which serve as a proxy of functional diversity (FD). Functional diversity is rarely studied at regional scales, and its scale dependence is poorly understood. Capturing trait variations at distinct spatial scales and in differently managed grasslands remains challenging, mainly because a limited number of trait measurements are available and field campaigns are time-consuming. Here, we derived α- and β-FD indices based on SLA measured in the field and estimated from optical satellite data by using molecular absorption profiles of leaves in canopies. We inverted the 1-D columnar radiative transfer model PROSAIL using Sentinel-2 reflectance data at canopy level. From the inversion we were able to distinguish different alpine management types based on retrieved SLA. Model uncertainties were mainly related to the different local plant communities, here represented by functional diversity indices and community-weighted means of traits. Thus, successful PROSAIL application was affected by management type. Management categories displaying lower α-FD, like mowed and fertilized, delivered the most reliable results. Further, we compared FD (i.e., richness, evenness, divergence) from local to regional scales. Locally, management determines the magnitude of FD, whereas on a regional scale, parcel size and the uniformity of agricultural practices control trait diversity. Our results highlight the importance of quantifying β-FD from space as it delivers additional information on the impact of management types, differing from locally measured α-FD values.

Abstract

Increasing evidence suggests that ecosystem functions are strongly linked to morphological plant traits, like specific leaf area (SLA) and its variability, which serve as a proxy of functional diversity (FD). Functional diversity is rarely studied at regional scales, and its scale dependence is poorly understood. Capturing trait variations at distinct spatial scales and in differently managed grasslands remains challenging, mainly because a limited number of trait measurements are available and field campaigns are time-consuming. Here, we derived α- and β-FD indices based on SLA measured in the field and estimated from optical satellite data by using molecular absorption profiles of leaves in canopies. We inverted the 1-D columnar radiative transfer model PROSAIL using Sentinel-2 reflectance data at canopy level. From the inversion we were able to distinguish different alpine management types based on retrieved SLA. Model uncertainties were mainly related to the different local plant communities, here represented by functional diversity indices and community-weighted means of traits. Thus, successful PROSAIL application was affected by management type. Management categories displaying lower α-FD, like mowed and fertilized, delivered the most reliable results. Further, we compared FD (i.e., richness, evenness, divergence) from local to regional scales. Locally, management determines the magnitude of FD, whereas on a regional scale, parcel size and the uniformity of agricultural practices control trait diversity. Our results highlight the importance of quantifying β-FD from space as it delivers additional information on the impact of management types, differing from locally measured α-FD values.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
Dewey Decimal Classification:910 Geography & travel
Uncontrolled Keywords:Computers in Earth Sciences, Soil Science, Geology
Language:English
Date:1 January 2020
Deposited On:18 Dec 2019 14:27
Last Modified:19 Dec 2019 08:36
Publisher:Elsevier
ISSN:0034-4257
OA Status:Closed
Publisher DOI:https://doi.org/10.1016/j.rse.2019.111415

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