Standardizing Ecosystem Morphological Traits from 3D Information Sources

R Valbuena; B O'Connor; F Zellweger; W Simonson; P Vihervaara; M Maltamo; C A Silva; D R A Almeida; F Danks; F Morsdorf; G Chirici; R Lucas; D A Coomes; N C Coops

doi:10.1016/j.tree.2020.03.006

Standardizing Ecosystem Morphological Traits from 3D Information Sources

Trends Ecol Evol. 2020 Aug;35(8):656-667. doi: 10.1016/j.tree.2020.03.006. Epub 2020 May 15.

Authors

R Valbuena¹, B O'Connor², F Zellweger³, W Simonson², P Vihervaara⁴, M Maltamo⁵, C A Silva⁶, D R A Almeida⁷, F Danks², F Morsdorf⁸, G Chirici⁹, R Lucas¹⁰, D A Coomes¹¹, N C Coops¹²

Affiliations

¹ United Nations Environment Programme World Conservation Monitoring Centre (UNEP-WCMC), 219 Huntington Road, CB3 0DL Cambridge, UK; Department of Plant Sciences in the Conservation Research Institute, University of Cambridge, Downing Street, CB2 3EA Cambridge, UK; School of Natural Sciences, Bangor University, Thoday Building, Bangor LL57 2UW, UK. Electronic address: r.valbuena@bangor.ac.uk.
² United Nations Environment Programme World Conservation Monitoring Centre (UNEP-WCMC), 219 Huntington Road, CB3 0DL Cambridge, UK.
³ Department of Plant Sciences in the Conservation Research Institute, University of Cambridge, Downing Street, CB2 3EA Cambridge, UK; Swiss Federal Research Institute WSL, Zürcherstrasse 111, 8903 Birmensdorf, Switzerland.
⁴ Biodiversity Centre, Finnish Environment Institute (SYKE), Latokartanonkaari 11, 00790 Helsinki, Finland.
⁵ Faculty of Forest Sciences, University of Eastern Finland, PO Box 111, Joensuu, Finland.
⁶ Department of Geographical Sciences, University of Maryland, College Park, MD, USA; School of Forest Resources and Conservation, University of Florida, Gainesville, FL, USA.
⁷ Department of Forest Sciences, 'Luiz de Queiroz' College of Agriculture (USP/ESALQ), University of São Paulo, Piracicaba, SP, Brazil.
⁸ Remote Sensing Laboratories, University of Zurich, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland.
⁹ Dipartimento di Scienze e Tecnologie Agrarie, Alimentari, Ambientali e Forestali, Università degli Studi di Firenze, via San Bonaventura 13, 50145 Florence, Italy.
¹⁰ Earth Observation and Ecosystem Dynamics Research Group, Aberystwyth University, Aberystwyth SY23 3DB, UK.
¹¹ Department of Plant Sciences in the Conservation Research Institute, University of Cambridge, Downing Street, CB2 3EA Cambridge, UK.
¹² Department of Forest Resource Management, University of British Columbia, 2424 Main Mall, Vancouver V6T 1Z4, Canada.

PMID: 32423635
DOI: 10.1016/j.tree.2020.03.006

Abstract

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.

Keywords: Essential biodiversity variables (EBVs); Sustainable Development Goals (SDG); digital photogrammetry; light detection and ranging (LIDAR); synthetic aperture radar (SAR).

Publication types

Research Support, Non-U.S. Gov't
Review

MeSH terms

Biodiversity*
Ecosystem*
Imaging, Three-Dimensional
Phenotype