Global biodiversity monitoring: From data sources to Essential Biodiversity Variables

Essential Biodiversity Variables (EBVs) consolidate information from varied biodiversity observation sources. Here we demonstrate the links between data sources, EBVs and indicators and discuss how different sources of biodiversity observations can be harnessed to inform EBVs. We classify sources of...

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Published in:Biological conservation Vol. 213; no. 6; pp. 256 - 263
Main Authors: Proença, Vânia, Martin, Laura Jane, Pereira, Henrique Miguel, Fernandez, Miguel, McRae, Louise, Belnap, Jayne, Böhm, Monika, Brummitt, Neil, García-Moreno, Jaime, Gregory, Richard D., Honrado, João Pradinho, Jürgens, Norbert, Opige, Michael, Schmeller, Dirk S., Tiago, Patrícia, van Swaay, Chris A.M.
Format: Journal Article
Language:English
Published: Elsevier Ltd 01.09.2017
Elsevier
Subjects:
biodiversity
Biodiversity monitoring schemes
data collection
ecosystems
Environmental Sciences
Essential Biodiversity Variables
Europe
field experimentation
GEO BON
Global biodiversity monitoring
Living Planet Index
monitoring
natural resources conservation
North America
Primary biodiversity observations
remote sensing
satellites
North America
Europe
Essential Biodiversity Variables
GEO BON
Global biodiversity monitoring
Primary biodiversity observations
Biodiversity monitoring schemes
Living Planet Index
ISSN:0006-3207, 1873-2917
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Summary:Essential Biodiversity Variables (EBVs) consolidate information from varied biodiversity observation sources. Here we demonstrate the links between data sources, EBVs and indicators and discuss how different sources of biodiversity observations can be harnessed to inform EBVs. We classify sources of primary observations into four types: extensive and intensive monitoring schemes, ecological field studies and satellite remote sensing. We characterize their geographic, taxonomic and temporal coverage. Ecological field studies and intensive monitoring schemes inform a wide range of EBVs, but the former tend to deliver short-term data, while the geographic coverage of the latter is limited. In contrast, extensive monitoring schemes mostly inform the population abundance EBV, but deliver long-term data across an extensive network of sites. Satellite remote sensing is particularly suited to providing information on ecosystem function and structure EBVs. Biases behind data sources may affect the representativeness of global biodiversity datasets. To improve them, researchers must assess data sources and then develop strategies to compensate for identified gaps. We draw on the population abundance dataset informing the Living Planet Index (LPI) to illustrate the effects of data sources on EBV representativeness. We find that long-term monitoring schemes informing the LPI are still scarce outside of Europe and North America and that ecological field studies play a key role in covering that gap. Achieving representative EBV datasets will depend both on the ability to integrate available data, through data harmonization and modeling efforts, and on the establishment of new monitoring programs to address critical data gaps. •Terrestrial biodiversity observations can be organized into four types.•These types differ in taxonomic, geographic, and temporal coverage.•The representativeness of EBV datasets is affected by the underlying types of data.•Global datasets of population abundance are affected by the lack of long-term data.•New monitoring programs must address critical data gaps.
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ISSN:0006-3207
1873-2917
DOI:10.1016/j.biocon.2016.07.014