Abstract
Essential Biodiversity Variables (EBVs) allow observation and reporting of global biodiversity change, but a detailed framework
for the empirical derivation of specific EBVs has yet to be developed. Here, we re-examine and refine the previous candidate
set of species traits EBVs and show how traits related to phenology, morphology, reproduction, physiology and movement
can contribute to EBV operationalization. The selected EBVs express intra-specific trait variation and allow monitoring of how
organisms respond to global change. We evaluate the societal relevance of species traits EBVs for policy targets and demonstrate
how open, interoperable and machine-readable trait data enable the building of EBV data products. We outline collection methods, meta(data) standardization, reproducible workflows, semantic tools and licence requirements for producing species traits EBVs. An operationalization is critical for assessing progress towards biodiversity conservation and sustainable development goals and has wide implications for data-intensive science in ecology, biogeography, conservation and Earth observation.
for the empirical derivation of specific EBVs has yet to be developed. Here, we re-examine and refine the previous candidate
set of species traits EBVs and show how traits related to phenology, morphology, reproduction, physiology and movement
can contribute to EBV operationalization. The selected EBVs express intra-specific trait variation and allow monitoring of how
organisms respond to global change. We evaluate the societal relevance of species traits EBVs for policy targets and demonstrate
how open, interoperable and machine-readable trait data enable the building of EBV data products. We outline collection methods, meta(data) standardization, reproducible workflows, semantic tools and licence requirements for producing species traits EBVs. An operationalization is critical for assessing progress towards biodiversity conservation and sustainable development goals and has wide implications for data-intensive science in ecology, biogeography, conservation and Earth observation.
Original language | English |
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Pages (from-to) | 1531-1540 |
Number of pages | 10 |
Journal | Nature Ecology & Evolution |
Volume | 2 |
Early online date | 17 Sept 2018 |
DOIs | |
Publication status | Published - 1 Oct 2018 |
Keywords
- ITC-ISI-JOURNAL-ARTICLE
- ITC-HYBRID