Modelling plant species distribution in alpine grasslands using airborne imaging spectroscopy
2014
Pottier, Julien | Malenovsky, Zbynek | Psomas, Achilleas | Homolova, Lucie | Schaepman, Michael E. | Choler, Philippe | Thuiller, Wilfried | Guisan, Antoine | Zimmermann, Niklaus E | Unité de recherche sur l'Ecosystème Prairial (UREP) ; Institut National de la Recherche Agronomique (INRA) | School of Biological Sciences | Swiss Federal Institute for Forest, Snow and Landscape Research WSL | Remote Sensing Laboratories ; Universität Zürich [Zürich] = University of Zurich (UZH) | Université Joseph Fourier - Grenoble 1 (UJF) | Centre National de la Recherche Scientifique (CNRS) | Department of Ecology and Evolution [UNIL, Lausanne] = Département d'écologie et évolution (DEE) ; Université de Lausanne = University of Lausanne (UNIL) | European ECOCHANGE project [GOCE-CT-2007-036866]; Swiss National Science Foundation (BIOASSEMBLE) [31003A-125145]; ERC (EC FP7 (TEEMBIO)); UZH URPP 'Global Change and Biodiversity' [281422]; 'Station Alpine Joseph Fourier' in France
International audience
Показать больше [+] Меньше [-]Английский. Remote sensing using airborne imaging spectroscopy(AIS)is known to retrieve fundamental optical properties of ecosystems. However, the value of these properties for predicting plant species distribution remains unclear. Here, we assess whether such data can add value to topographic variables for predicting plant distributions in French and Swiss alpine grasslands. We fitted statistical models with high spectral and spatial resolution reflectance data and tested four optical indices sensitive to leaf chlorophyll content, leaf water content and leaf area index. We found moderate added-value of AIS datafor predicting alpine plant species distribution. Contrary to expectations, differences between species distribution models (SDMs) were not linked to their local abundance or phylogenetic/functional similarity. Moreover, spectral signatures of species were found to be partly site-specific. We discuss current limits of AIS-based SDMs, highlighting issues of scale and informational content of AIS data.
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Эту запись предоставил Institut national de la recherche agronomique