From local spectral species to global spectral communities: A benchmark for ecosystem diversity estimate by remote sensing

Rocchini Duccio, Salvatori Nicole, Beierkuhnlein Carl, Chiarucci Alessandro, De Boissieu Florian, Förster Michael, Garzon-Lopez Carol X., Gillespie Thomas, Hauffe Heidi C., He Kate S., Kleinschmit Birgit, Lenoir Jonathan, Malavasi Marco, Moudrý Vítĕzslav, Nagendra Harini, Payne Davnah, Símová Petra, Torresani Michele, Wegmann Martin, Feret Jean Baptiste. 2021. From local spectral species to global spectral communities: A benchmark for ecosystem diversity estimate by remote sensing. Ecological Informatics, 61:101195, 10 p.

Quartile : Q2, Sujet : ECOLOGY

Résumé : In the light of unprecedented change in global biodiversity, real-time and accurate ecosystem and biodiversity assessments are becoming increasingly essential. Nevertheless, estimation of biodiversity using ecological field data can be difficult for several reasons. For instance, for very large areas, it is challenging to collect data that provide reliable information. Some of these restrictions in Earth observation can be avoided through the use of remote sensing approaches. Various studies have estimated biodiversity on the basis of the Spectral Variation Hypothesis (SVH). According to this hypothesis, spectral heterogeneity over the different pixel units of a spatial grid reflects a higher niche heterogeneity, allowing more organisms to coexist. Recently, the spectral species concept has been derived, following the consideration that spectral heterogeneity at a landscape scale corresponds to a combination of subspaces sharing a similar spectral signature. With the use of high resolution remote sensing data, on a local scale, these subspaces can be identified as separate spectral entities, the so called “spectral species”. Our approach extends this concept over wide spatial extents and to a higher level of biological organization. We applied this method to MODIS imagery data across Europe. Obviously, in this case, a spectral species identified by MODIS is not associated to a single plant species in the field but rather to a species assemblage, habitat, or ecosystem. Based on such spectral information, we propose a straightforward method to derive α- (local relative abundance and richness of spectral species) and β-diversity (turnover of spectral species) maps over wide geographical areas.

Mots-clés Agrovoc : télédétection, biodiversité, écosystème, imagerie, communauté locale, cartographie, écologie, paysage

Mots-clés libres : Biodiversity, Ecological informatics, Modelling, Remote Sensing, Satellite imagery

Agences de financement européennes : European Commission

Agences de financement hors UE : Agence Nationale de la Recherche

Programme de financement européen : H2020

Projets sur financement : (FRA) Suivi de la biodiversité tropicale avec les satellites Sentinel-2 du programme Copernicus, (EU) Optical synergies for spatiotemporal sensing of scalable ecophysiological traits, (EU) Sing synergies between agriculture, biodiversity and Ecosystem services to help farmers capitalising on native biodiversity

Auteurs et affiliations

• Rocchini Duccio, University of Bologna (ITA) - auteur correspondant
• Salvatori Nicole, Università Di Udine (ITA)
• Beierkuhnlein Carl, Universität Bayreuth (DEU)
• Chiarucci Alessandro, University of Bologna (ITA)
• De Boissieu Florian, CIRAD-PERSYST-UMR Eco&Sols (FRA)
• Förster Michael, Technical University of Berlin (DEU)
• Garzon-Lopez Carol X., Rijksuniversiteit Groningen (NLD)
• Gillespie Thomas, UC (USA)
• Hauffe Heidi C., FMACH (ITA)
• He Kate S., Murray State University (USA)
• Kleinschmit Birgit, Technical University of Berlin (DEU)
• Lenoir Jonathan, UPJV (FRA)
• Malavasi Marco, CZU (CZE)
• Moudrý Vítĕzslav, CZU (CZE)
• Nagendra Harini, Azim Premji University (IND)
• Payne Davnah, University of Bern (CHE)
• Símová Petra, CZU (CZE)
• Torresani Michele, Free University of Bolzano-Bozen (ITA)
• Wegmann Martin, University of Wuerzburg (DEU)
• Feret Jean Baptiste, IRSTEA (FRA)

Source : Cirad-Agritrop (https://agritrop.cirad.fr/605799/)

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