TY - JOUR
T1 - Standardizing Ecosystem Morphological Traits from 3D Information Sources
AU - Valbuena, R.
AU - O'Connor, B.
AU - Zellweger, F.
AU - Simonson, W.
AU - Vihervaara, P.
AU - Maltamo, M.
AU - Silva, C. A.
AU - Almeida, D. R.A.
AU - Danks, F.
AU - Morsdorf, F.
AU - Chirici, G.
AU - Lucas, R.
AU - Coomes, D. A.
AU - Coops, N. C.
N1 - Funding Information:
This project resulted from a collaboration with the United Nations Environment Programme World Conservation Monitoring Centre (UNEP-WCMC) which is the biodiversity assessment and policy implementation arm of United Nations Environment Programme, the world’s foremost intergovernmental environmental organization. R.V. and D.A.C. acknowledge the support of an 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’ ( LORENZLIDAR-658180 ) at the University of Cambridge, UK. Within the framework of LORENZLIDAR, R.V. completed a 6-month secondment at UNEP-WCMC for assessing the feasibility of LIDAR to retrieve EBVs on ecosystem structure. This secondment was carried out in the context of GlobDiversity, a European Space Agency-funded project to assess the feasibility of satellite observations to support the development of EBVs on terrestrial ecosystem structure and function. F.Z. was funded by the Swiss National Science Foundation (project number 172198 ) and the Isaac Newton Trust. P.V. acknowledges IBC-CARBON Project funded by The Strategic Research Council (SRC) at the Academy of Finland (Grant no. 312559). D.R.A.A. was supported by the São Paulo Research Foundation ( #2018/21338-3 and #2019/14697-0 ). A first version of this manuscript was greatly improved after very constructive comments and encouragement from the editor and three anonymous reviewers.
Funding Information:
This project resulted from a collaboration with the United Nations Environment Programme World Conservation Monitoring Centre (UNEP-WCMC) which is the biodiversity assessment and policy implementation arm of United Nations Environment Programme, the world's foremost intergovernmental environmental organization. R.V. and D.A.C. acknowledge the support of an 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’ (LORENZLIDAR-658180) at the University of Cambridge, UK. Within the framework of LORENZLIDAR, R.V. completed a 6-month secondment at UNEP-WCMC for assessing the feasibility of LIDAR to retrieve EBVs on ecosystem structure. This secondment was carried out in the context of GlobDiversity, a European Space Agency-funded project to assess the feasibility of satellite observations to support the development of EBVs on terrestrial ecosystem structure and function. F.Z. was funded by the Swiss National Science Foundation (project number 172198) and the Isaac Newton Trust. P.V. acknowledges IBC-CARBON Project funded by The Strategic Research Council (SRC) at the Academy of Finland (Grant no. 312559). D.R.A.A. was supported by the São Paulo Research Foundation (#2018/21338-3 and #2019/14697-0). A first version of this manuscript was greatly improved after very constructive comments and encouragement from the editor and three anonymous reviewers.
Publisher Copyright:
© 2020 Elsevier Ltd
PY - 2020/8/1
Y1 - 2020/8/1
N2 - 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.
AB - 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.
KW - digital photogrammetry
KW - Essential biodiversity variables (EBVs)
KW - light detection and ranging (LIDAR)
KW - Sustainable Development Goals (SDG)
KW - synthetic aperture radar (SAR)
KW - Phenotype
KW - Ecosystem
KW - Biodiversity
KW - Imaging, Three-Dimensional
UR - http://www.scopus.com/inward/record.url?scp=85084584874&partnerID=8YFLogxK
U2 - 10.1016/j.tree.2020.03.006
DO - 10.1016/j.tree.2020.03.006
M3 - Review article
C2 - 32423635
AN - SCOPUS:85084584874
SN - 0169-5347
VL - 35
SP - 656
EP - 667
JO - Trends in Ecology and Evolution
JF - Trends in Ecology and Evolution
IS - 8
ER -
