Satellite-derived Ecosystem Functional Types capture ecosystem functional heterogeneity at regional scale

Abstract. Assessing ecosystem functioning is crucial for managing and conserving ecosystems and their services. Numerous ways to evaluate ecosystem functioning have been developed, using species traits, such as Plant Functional Types (PFTs), flux measurements with the Eddy Covariance (EC) technique, and remote sensing techniques. We propose that the spatial heterogeneity in ecosystem functioning at a regional scale can be assessed and monitored using satellite-derived Ecosystem Functional Types (EFTs): groups of ecosystems or patches of the land surface that share similar dynamics of matter and energy exchanges. We hypothesize that, as observed for PFTs, different EFTs should have distinct patterns and magnitudes of Net Ecosystem Exchange (NEE) of carbon dioxide measured using the EC technique. We derived EFTs from 2001–2014 time-series of satellite images of the Enhanced Vegetation Index (EVI) and compared them with NEE measurements (derived from in situ field observations using the EC technique) across 50 European sites. Our results show that distinct EFTs classes display significantly different dynamics and magnitudes of NEE and that EFTs perform marginally better than PFTs in explaining NEE regional patterns. Land-cover maps based on PFTs are difficult to update on an annual basis and are not sensitive to changes in ecosystem performance (e.g., droughts or pests) that do involve short-term changes in PFT composition. In contrast, satellite-derived EFTs are sensitive to short-term changes in ecosystem performance. Satellite-derived EFTs are an ecosystem functional classification built from satellite observations that allow the identification of homogeneous land patches based on ecosystem functions, e.g., ecosystem net productivity measured on the ground as NEE. Satellite-derived EFTs can be recalculated annually, providing a straightforward way to assess and monitor interannual changes in ecosystem functioning and functional diversity.

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Publication Details

Journal
Biogeosciences
Published
2026-02-12
DOI
https://doi.org/10.5194/bg-23-1223-2026
Primary Topic
Plant Water Relations and Carbon Dynamics
Type
article
Field-Weighted Citation Impact
0.00

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article

Satellite-derived Ecosystem Functional Types capture ecosystem functional heterogeneity at regional scale

Marian Pavelka, Ladislav Šigut, Kim Pilegaard, Eugénie Paul‐Limoges et al.
Biogeosciences
Plant Water Relations and Carbon Dynamics
article

Satellite-derived Ecosystem Functional Types capture ecosystem functional heterogeneity at regional scale

Marian Pavelka, Ladislav Šigut, Kim Pilegaard, Eugénie Paul‐Limoges, Ana Meijide, Domingo Alcaraz‐Segura, Andreas Ibrom, Lukas Siebicke, Kathrin Fuchs, Jiří Dušek, Pierpaolo Duce, Antonio Manco, Beatriz P. Cazorla, Ignacio Goded, JULIO PEÑAS, Javier Cabello, Rodrigo Vargas, Georg Wohlfahrt, Benimiano Gioli, Javier Martínez-López, Leonardo Montagnani, Alexander Knohl, Lutz Merbold
article en

Abstract

Abstract. Assessing ecosystem functioning is crucial for managing and conserving ecosystems and their services. Numerous ways to evaluate ecosystem functioning have been developed, using species traits, such as Plant Functional Types (PFTs), flux measurements with the Eddy Covariance (EC) technique, and remote sensing techniques. We propose that the spatial heterogeneity in ecosystem functioning at a regional scale can be assessed and monitored using satellite-derived Ecosystem Functional Types (EFTs): groups of ecosystems or patches of the land surface that share similar dynamics of matter and energy exchanges. We hypothesize that, as observed for PFTs, different EFTs should have distinct patterns and magnitudes of Net Ecosystem Exchange (NEE) of carbon dioxide measured using the EC technique. We derived EFTs from 2001–2014 time-series of satellite images of the Enhanced Vegetation Index (EVI) and compared them with NEE measurements (derived from in situ field observations using the EC technique) across 50 European sites. Our results show that distinct EFTs classes display significantly different dynamics and magnitudes of NEE and that EFTs perform marginally better than PFTs in explaining NEE regional patterns. Land-cover maps based on PFTs are difficult to update on an annual basis and are not sensitive to changes in ecosystem performance (e.g., droughts or pests) that do involve short-term changes in PFT composition. In contrast, satellite-derived EFTs are sensitive to short-term changes in ecosystem performance. Satellite-derived EFTs are an ecosystem functional classification built from satellite observations that allow the identification of homogeneous land patches based on ecosystem functions, e.g., ecosystem net productivity measured on the ground as NEE. Satellite-derived EFTs can be recalculated annually, providing a straightforward way to assess and monitor interannual changes in ecosystem functioning and functional diversity.

BiogeosciencesVol. 23(3)
Karlsruhe Institute of Technology (DE), University of Bonn (DE), Free University of Bozen-Bolzano (IT), Universidad de Granada (ES), Universität Innsbruck (AT), Swiss Federal Institute for Forest, Snow and Landscape Research (CH), Instituto Andaluz de Ciencias de la Tierra (ES), Istituto per il Sistema Produzione Animale in Ambiente Mediterraneo (IT), Instituto de Ciencias Agrarias (ES), Czech Academy of Sciences, Global Change Research Institute (CZ), Joint Research Centre (IT), Federal Office for Agriculture (CH), Istituto di Biometeorologia (IT), National Research Council (IT), University of Almería (ES), Arizona State University (US), University of Göttingen (DE), Technical University of Denmark (DK)
National Aeronautics and Space Administration, European Commission, Deutsche Forschungsgemeinschaft, Nuclear Safety and Security Commission, Ministerio de Ciencia e Innovación, Universidad de Granada, LifeWatch – Niclas Öberg Foundation, Provincia autonoma di Bolzano - Alto Adige, Universidad de Almería, European Regional Development Fund, Agencia Estatal de Investigación
Openalex Percentile: Top 69%
Plant Water Relations and Carbon Dynamics
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