Essential Biodiversity Variables
Essential Biodiversity Variables
Understanding biodiversity change is in the heart of the global GEO BON initiative. The concept of Essential Biodiversity Variables (EBV) has been coined to document this, and is actively being defined by the GLOBIS-B project. The EU BON project has had a task force for EBVs since 2013, and working with other initiatives, has contributed to many papers about the subject (see below). EBVs are still in the drawing board and need to be piloted. How to derive EBVs from openly available data through standardised workflows is the question to solve. The EBVs for species populations are probably the ones where we are closest in achieving this.
The EBV for species populations has tentatively been defined as the relative abundance of a taxon in space and time, measured repeatedly using a consistent methodology. This can be illustrated in a multidimensional data cube as can be seen below. How the data cube can be filled from observation data has been explored by the EU BON project in several pilot applications. Another challenge is how to derived unbiased measures of abundance from patchy and heterogeneous data.
EU BON tools to explore parts of the EBV data flows
Spatial dataset browser http://biodiversity.eubon.eu/web/guest/spatial-dataset-browser
- Allows user to choose an area and see what datasets available. Filtering by EBV class still needed.
Species richness application http://biodiversity.eubon.eu/web/guest/species-richness
- Demonstrates a freely scalable data cube with umbers of records and numbers of species.
Relative observation trends http://biodiversity.eubon.eu/web/guest/species-trend-visualization
- Visualises trends in relative abundance of species in arbitrarily definable areas using a simple reporting rate algorithm.
GBIF Integrated Publishing Toolkit for sample-based data
- Enables data providers to share quantitative observation data.
Papers on EBVs with EU BON contributions
Schmeller DS, et al (2017) A suite of essential biodiversity variables for detecting critical biodiversity change. Biological Reviews. http://onlinelibrary.wiley.com/wol1/doi/10.1111/brv.12332/abstract
Proença V , et al (2016) Global biodiversity monitoring: from data sources to Essential Biodiversity Variables. Biological Conservation. http://www.sciencedirect.com/science/article/pii/S0006320716302786
Brummitt N, et al (2016) Taking Stock of Nature: Essential Biodiversity Variables Explained. Biological Conservation. http://www.sciencedirect.com/science/article/pii/S0006320716303652
Pettorelli N, et al (2016) Framing the concept of satellite remote sensing essential biodiversity variables: challenges and future directions. Remote Sensing in Ecology and Conservation. http://onlinelibrary.wiley.com/doi/10.1002/rse2.15/abstract
Turak E, et al (2016) Using the essential biodiversity variables framework to measure biodiversity change at national scale. Biological Conservation. http://www.sciencedirect.com/science/article/pii/S0006320716303226
Geijzendorffer IR, et al (2015) Bridging the gap between biodiversity data and policy reporting needs: An Essential Biodiversity Variables perspective, Journal of Applied Ecology. http://onlinelibrary.wiley.com/doi/10.1111/1365-2664.12417/abstract
Hoffmann A, et al (2014) Improved access to integrated biodiversity data for science, practice, and policy - the European Biodiversity Observation Network (EU BON). Nature Conservation. http://www.pensoft.net/journals/natureconservation/article/6498/the-need-for-an-integrated-biodiversity-policy-support-process-%E2%80%93-building-the-european-contribution-to-a-global-biodiv