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Combining European Earth Observation products with Dynamic Global Vegetation Models for estimating Essential Biodiversity Variables
Authors:Mateus Dantas de Paula  Marta Gómez Giménez  Aidin Niamir  Martin Thurner  Thomas Hickler
Affiliation:1. Biodiversity and Climate Research Centre (BiK-F), Senckenberg Gesellschaft für Naturforschung, Frankfurt am Main, Germany;2. Department of Ecological Modelling, UFZ—Helmholtz Centre for Environmental Research Leipzig, Germanymateus.dantas@senckenberg.de"ORCIDhttps://orcid.org/0000-0003-4350-2572;4. Biodiversity and Climate Research Centre (BiK-F), Senckenberg Gesellschaft für Naturforschung, Frankfurt am Main, Germany"ORCIDhttps://orcid.org/0000-0002-8161-835X;5. Biodiversity and Climate Research Centre (BiK-F), Senckenberg Gesellschaft für Naturforschung, Frankfurt am Main, Germany"ORCIDhttps://orcid.org/0000-0003-4511-3407;6. Biodiversity and Climate Research Centre (BiK-F), Senckenberg Gesellschaft für Naturforschung, Frankfurt am Main, Germany"ORCIDhttps://orcid.org/0000-0002-4668-7552
Abstract:ABSTRACT

Global, fast and accessible monitoring of biodiversity is one of the main pillars of the efforts undertaken in order to revert it loss. The Group on Earth Observations Biodiversity Observation Network (GEO-BON) provided an expert-based definition of the biological properties that should be monitored, the Essential Biodiversity Variables (EBVs). Initiatives to provide indicators for EBVs rely on global, freely available remote sensing (RS) products in combination with empirical models and field data, and are invaluable for decision making. In this study, we provide alternatives for the expansion and improvement of the EBV indicators, by suggesting current and future data from the European Space Agencýs COPERNICUS and explore the potential of RS-integrated Dynamic Global Vegetation Models (DGVMs) for the estimation of EBVs. Our review found that mainly due to the inclusion of the Sentinel constellation, Copernicus products have similar or superior potential for EBV indicator estimation in relation to their NASA counterparts. DGVMs simulate the ecosystem level EBVs (ecosystem function and structure), and when integrated with remote sensing data have great potential to not only offer improved estimation of current states but to provide projection of ecosystem impacts. We suggest that focus on producing EBV relevant outputs should be a priority within the research community, to support biodiversity preservation efforts.
Keywords:Dynamic Global Vegetation Modelling  remote sensing  ecosystem dynamics  Copernicus Programme  Essential Biodiversity Variables
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