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Articles

Combining European Earth Observation products with Dynamic Global Vegetation Models for estimating Essential Biodiversity Variables

ORCID Icon, ORCID Icon, ORCID Icon, & ORCID Icon
Pages 262-277 | Received 14 Jul 2018, Accepted 12 Mar 2019, Published online: 26 Mar 2019
 

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.

Acknowledgements

The authors would like to acknowledge the European Commission ‘Horizon 2020 Program’ that funded ERA-PLANET/GEOEssential (Grant Agreement no. 689443) project.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The authors would like to acknowledge the European Commission ‘Horizon 2020 Program’ that funded ERA-PLANET/GEOEssential (Grant Agreement no. 689443) project. H2020 Societal Challenges.

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