Figure - available from: Biodiversity Information Science and Standards
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EBV netCDF Structure of the Global habitat availability for mammals dataset by Daniele Baisero (License CC BY 4.0). Blue elements are variables, green elements represent groups, attributes are displayed in black and dimension are red.
Source publication
The concept of Essential Biodiversity Variables (EBVs) was conceived to study, report, and manage biodiversity change. The EBV netCDF structure was developed in order to support publication and interoperability of biodiversity data. This standard is based on the Network Common Data Format (netCDF). Additionally, it follows the Climate and Forecast...
Citations
... The interoperability itself is supported by the adoption of common standards that allows the integration of data collected or produced by different sources (e.g., and facilitates the traceability and scalability of those products. The EBV data standard has been specifically developed to allow the proper documentation and integration of EBV data products (Quoß et al., 2022). ...
... as a global repository for spatial-temporal data on biodiversity, ecosystems and ecosystem services across multiple dimensions, realms and scale. Data developers can publish their Essential Variables data products and derived indicators and document their metadata and workflow following the EBV data standard (Quoß et al., 2022), as well as the produced EBV data cubes in NetCDF format . Developing open-cloud processing capabilities would go a long way in mainstreaming the use of data and models to users without limited access to local and expensive computing infrastructures, whether it be for research or national reporting purposes. ...
Fragmented systems for monitoring and assessing biodiversity and ecosystem services limit countries’ ability to track progress across multilateral environmental agreements, coordinate actions, and thus meet agreed upon global commitment. This paper initiates to address this gap through integrated data-to-decision workflows for more synergistic implementation of global goals. We propose Essential Biodiversity Variables (EBVs) and Essential Ecosystem Service Variables (EESVs) as integrative tools to harmonize monitoring, indicator development, and reporting across frameworks such as the Kunming-Montreal Global Biodiversity Framework and the System of Environmental-Economic Accounts Ecosystem Accounting, while providing the foundational data for knowledge synthesis in the assessments of the Intergovernmental Platform on Biodiversity and Ecosystem Services. Through three case studies, we demonstrate the use of EBVs and EESVs in national assessments, modelling, and scenario analyses for strategic policy and spatial planning, using scalable and repeatable workflows from primary data to indicators. The paper highlights the value of an integrated use of science, policy, and data frameworks in implementing biodiversity conservation and sustainable development goals. We call for the global community to identify and agree upon minimum facets of biodiversity to monitor with national observation agencies to improve the rigour of data, models, and indicators.
... services to support biodiversity assessments based on EBV datasets, which are time series of spatial biodiversity datasets in raster format produced from the integration of remote sensing and in situ data, via the EBV Data Portal -REST API developed for machine-readable access to the datasets new data and metadata standard EBV-Cube (Quoß et al., 2022) -R package ebvcube 301 ...
This study presents a methodology for the prioritization of use cases to evaluate and demonstrate the potential of an ecosystem that the European Commission (EC) is outlining through the European Regional Group on Earth Observations (EuroGEO). This ecosystem will interconnect European technologies, digital infrastructures and data, enable the implementation of use cases and strengthen Europe's contribution to the Group on Earth Observations (GEO).
This methodology can also be used to identify noteworthy research projects in the Earth observation (EO) domain that possess policy relevance and have the potential to be transformed into sustained and operational services beyond the funding period. The methodology has been applied to a Horizon 2020 project named "EuroGEO Showcases: Applications Powered by Europe (e-shape)", composed of 37 pilots.
The analysis results reflect the current landscape within the e-shape project and to some extent in the European EO research activities more broadly, with respect to the methodology defined. The most prominent identified weak aspects are the lack of a) continuity potential of input data, (b) geographic scalability and (c) adherence to an open science approach. In addition, the analysis led to the prioritization of several pilots that can be used to develop sustained and operational services for public policy.
... All created data has been made openly available on a data repository in cloud-optimized geoTIFF 296 format for the most-likely transition and current PNV (10.5281/zenodo.13686776) as well as on the 297 EBV data portal in a standardized netCDF format (Quoß et al., 2022) T., Marcenò, C., Landucci, F., Danihelka, J., Hájek, M., Dengler, J., Novák, P., Zukal, 349 D., Jiménez-Alfaro, B., Mucina, L., Abdulhak, S., Aćić, S., Agrillo, E., Attorre, F., 350 ...
The extent and intactness of natural ecosystems is a key factor enabling species populations to thrive. However, the distribution of ecosystems is changing owing to both climatic and anthropogenic factors. Recently negotiated European policy directives, such as the Nature Restoration Law, argue for the restoration of natural ecosystems. Yet to determine what is to be restored the range of possible outcomes should be first explored, also with regards to future climatic conditions. Here the concept of potential natural vegetation (PNV) is applied and mapped in a data-driven manner at European extent, exploring where PNV transitions are most likely to happen under contemporary and future conditions. Specifically, I predict the distribution of current and future potential coverage of six natural vegetation types at 1 km² grain using Bayesian machine learning approaches. I find that most current land cover and land use could develop to no single, but multiple PNV states, although options for some types, such as areas suitable for wetlands might become rarer under future climatic conditions. Furthermore, the challenge of transitioning to PNV was found to be particularly high for current intensively cultivated landscapes. Overall data-driven PNV mapping holds considerable promise for assessing land potentials and supporting restoration assessments. Future work should expand the thematic grain of vegetation maps and consider feedback with biotic factors.
