Biodiversity Building Blocks for policy

Food, Bioeconomy & Natural ResourcesHORIZON-IAID: 101059592
EC Contribution
€47,785
Consortium Size
13 orgs
Start Year
2023
Summary

The world is changing rapidly; climate change, land use change, pollution and natural resource exploitation are creating a global crisis for biodiversity whose magnitude and dynamics are hard to quantify. Decision makers at all levels need uptodate information from which to evaluate policy options. For this reason rapid, reliable, repeatable monitoring of biodiversity data is needed at all scales from local to global. Only by leveraging large volumes of data, advanced modelling techniques and powerful computing tools can we hope to synthesize these data within timescales that are relevant to policy.Data on biodiversity come from a diverse range of sources, citizen scientists, museums, herbaria and researchers are all major contributors, but increasingly new technologies are being deployed, such as automatic sensors, camera traps, eDNA and satellite tracking. Integrating these data is a major challenge, but is necessary if we are to create dependable information on biodiversity change. B3 will use the concept of data cubes to simplify and standardize access to biodiversity data using the Essential Biodiversity Variables framework. These cubes will be used, in conjunction with other environmental data and scenarios, as the basis for models and indicators of past, current and future biodiversity. The overarching goal of the project is to provide easy access to tools in a cloud computing environment, in real-time and on-demand, with state of the art prediction models of biodiversity, that will output models and indicators of biodiversity status and change. The project envisages a future where primary biodiversity data are seamlessly integrated into monitoring and forecasting such that policy and management can proactively respond to problems while at the same time reduce the costs of monitoring and management, and the negative impacts of biodiversity change.

Consortium (13)

Project Results (24)

Source: CORDIS, the EU research results database.

Publications (22)
Mapping potential environmental impacts of alien species in the face of climate change
Biological Invasions· 2025DOI
Sabrina Kumschick, Lysandre Journiac, Océane Boulesnane-Genguant, Christophe Botella, Robin Pouteau, Mathieu Rouget
One-hectare fine-scale dataset of a fynbos plant community in the Cape Floristic Region
Data in Brief· 2025DOI
Jan-Hendrik Keet, Cang Hui
Policy Brief: Unlocking The Full Potential Of The Green Deal Data Space
· 2025DOI
Schleidt K., Serral I., de la Vega D., Maso J., Jetschny S., Groom Q., Beber R., Bastin L., Estupinan-Suarez L. M.
Why countries need the Global Biodiversity Information Facility: Lessons from Belgium [policy brief]
· 2025DOI
Groom Q., Adriaens T., Desmet P., Vanderhoeven S., Yovcheva N.
An analysis of sex ratios using a biodiversity data cube
BioHackrXiv Preprints· 2024DOI
Groom, Q. J., & Trekels, M.
Applying the maximum entropy principle to neural networks enhances multi-species distribution models
· 2024DOI
Ryckewaert, M., Marcos, D., Botella, C., Servajean, M., Bonnet, P., Joly, A.
Considerations for developing and implementing a safe list for alien taxa
Bioscience· 2024DOI
Kumschick S, Fernandez Winzer L, McCulloch-Jones EJ, Chetty D, Fried J, Govender T, Potgieter LJ, Rapetsoa MC, Richardson DM, van Velden J, van der Colff D, Miza S, Wilson JRU
Editorial: Biodiversity informatics: building a lifeboat for high functionality data to decision pipeline
Frontiers in Ecology & Evolution· 2024DOI
Hui, C., MacFadyen, S., Visser, V., Groom, Q., & Isaac, N.J.B.
Effective biodiversity monitoring requires FAIR data and FAIR models for FAIR indicators (Findable, Accessible, Interoperable, and Reusable) [Policy Brief]
· 2024DOI
Sica, Y., Seebens, H., Fernandez, M., Hughes, A. C., Cang, H., Kumschick, S., Estupinan-Suarez, L. M., Groom, Q., Niamir, A., Gudde, R., Krug, R. M., Hendrickx, L., Yovcheva, N., Gill, M. J., Rodrigues, A., Gonzalez, A.
Extinction potential from invasive alien species
bioRxiv· 2024
Martin, P.-L., Arbieu, U., Bang, A., Camacho, M., Cuthbert, R. N., Genovesi, P., Kumschick, S., Pili, A., Seebens, H., Wang, S., Latombe, G.
Extinction potential from invasive alien species
· 2024DOI
Martin Philippe-Lesaffre, Ugo Arbieu, Alok Bang, Morelia Camacho, Ross N. Cuthbert, Piero Genovesi, Sabrina Kumschick, Arman Pili, Hanno Seebens, Shengyu Wang, Guillaume Latombe
Mapping impacts of alien species on biodiversity in the face of climate change
Research Square· 2024DOI
Kumschick, S., Journiac, L., Boulesnane-Genguant, O., Botella, C., Pouteau, R., Rouget, M.
Methods in Ecology and Evolution
Methods in Ecology & Evolution· 2024DOI
Latombe, G., Boittiaux, P., Hui, C., & McGeoch, M.
On the mathematical properties of spatial Rao’s Q to compute ecosystem heterogeneity
Theoretical Ecology· 2024DOI
Duccio Rocchini, Michele Torresani, Carlo Ricotta
Phenological Diversity Trends with Remote Sensing Datacubes
· 2024DOI
Elliot Samuel Shayle, Matteo Marcantonio, Rocco Labadessa, Chiara Richiardi, Saverio Vicario
Under the mantra: ‘Make use of colorblind friendly graphs’
Environmetrics· 2024DOI
Rocchini, D.; Chieffallo, L; Thouverai, E;
Unveiling ecological dynamics through simulation and visualization of biodiversity data cubes
· 2024DOI
Ward Langeraert, Wissam Barhdadi, Dimitri Brosens, Rocìo Cortès, Peter Desmet, Michele Di Musciano, Chandra Earl, Sanne Govaert, Pieter Huybrechts, Matilde Martini, Arthur Vinícius Rodrigues, Annegreet Veeken, Mukhtar Muhammed Yahaya, Toon Van Daele
A kernel integral method to remove biases in estimating trait turnover
· 2023DOI
Guillaume Latombe, Paul Boittiaux, Cang Hui, Melodie McGeoch
A quixotic view of spatial bias in modelling the distribution of species and their diversity
npj biodiversity· 2023DOI
Rocchini, D., Tordoni, E., Marchetto, E. et al.
B-Cubed: Leveraging Analysis-Ready Biodiversity Datasets and Cloud Computing for Timely and Actionable Biodiversity Monitoring
Biodiversity Information Science and Standards· 2023DOI
Groom Q, Abraham L, Adriaens T, Breugelmans L, Clarke DA, Fernández MA, Hendrickx L, Hui C, Kumschick S, Martini M, McGeoch M, Metodiev T, Miller J, Oldoni D, Pereira HM, Preda C, Robertson T, Rocchini D, Seebens H, Teixeira H, Trekels M, Wilson JR, Yovch
Disentangling the relationships among abundance, invasiveness and invasibility in trait space
npj Biodiversity· 2023DOI
Hui, C., Pyšek, P. & Richardson, D.M.
USE it: Uniformly sampling pseudo-absences within the environmental space for applications in habitat suitability models
Methods in Ecology and Evolution· 2023DOI
Da Re, D., Tordoni, E., Lenoir, J.,Lembrechts, J. J., Vanwambeke, S. O., Rocchini, D., &Bazzichetto, M.
Other Results (1)
Periodic Reporting for period 1 - B3 (Biodiversity Building Blocks for policy)
Deliverables (1)
Documents, reports