Journal
TRENDS IN ECOLOGY & EVOLUTION
Volume 35, Issue 8, Pages 656-667Publisher
CELL PRESS
DOI: 10.1016/j.tree.2020.03.006
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Funding
- EU Horizon 2020 Marie Sklodowska-Curie Action entitled 'Classification of forest structural types with lidar remote sensing applied to study tree size-density scaling theories' at the University of Cambridge, UK [LORENZLIDAR-658180]
- GlobDiversity, a European Space Agency
- Swiss National Science Foundation [172198]
- Isaac Newton Trust
- Strategic Research Council (SRC) at the Academy of Finland [312559]
- Sao Paulo Research Foundation [2018/21338-3, 2019/14697-0]
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3D-imaging technologies provide measurements of terrestrial and aquatic ecosystems' structure, key for biodiversity studies. However, the practical use of these observations globally faces practical challenges. First, available 3D data are geographically biased, with significant gaps in the tropics. Second, no data source provides, by itself, global coverage at a suitable temporal recurrence. Thus, global monitoring initiatives, such as assessment of essential biodiversity variables (EBVs), will necessarily have to involve the combination of disparate data sets. We propose a standardized framework of ecosystem morphological traits - height, cover, and structural complexity - that could enable monitoring of globally consistent EBVs at regional scales, by flexibly integrating different information sources - satellites, aircrafts, drones, or ground data - allowing global biodiversity targets relating to ecosystem structure to be monitored and regularly reported.
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