Accessible near-team
ecological predictions

Demystifying complexity of forecasting biodiversity change for conservation management

Interactive Maps

Explore scenarios with clarity

Species Insights

Track fauna across habitats

Flora Dynamics

Visualize vegetation changing patterns

Background

Europe has made significant progress in open ecological observation and network science through research infrastructures such as GBIF, ICOS, and eLTER. However, while data collection and retrospective analyses are now well established, the ability to anticipate ecological change remains limited. This platform showcases in an accessible way different projects that integrate ecological data from diverse monitoring networks into forecasts of biodiversity change, openly accessible to researchers and decision-makers. The predictions are driven by powerful models that are implemented as interoperable workflows in collaboration with LifeWatch ERIC.

© Jacinto Román

Why forecasts of biodiversity change?

Ecological forecasting can generate important actionable insight for policymakers and also advance ecological theory. The iterative nature of near-term ecological forecasting – evaluating forecasts with new observations, updating models, and then making new forecasts – has the potential to accelerate learning and enable proactive environmental decision-making.

Interactive Biodiversity Predictions

We combine geospatial data and continuous monitoring to develop open-access interoperable workflows that integrate these data into ecological modelling to produce predictions of changes in population abundances and ecosystem processes in complex natural systems. All workflows are developed in collaboration with stakeholder and are hosted by LifeWatch ERIC, a European Research Infrastructure, which ensures that outputs are sustained into the future and widely accessible.

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Meet the Team

Our team brings together ecologists, data scientists, GIS specialists and field biologists dedicated to understanding and predicting biodiversity change. We combine advanced modelling, long-term ecological monitoring and innovative digital tools to create a living digital twin of Doñana.
From designing species models to collecting real-world observations, each member contributes a piece to a shared mission: transforming complex environmental data into accessible insights for conservation and decision-making.

Maria Paniw
EBD-CSIC
Billur Bektas
ETH Zurich
Sanne Evers
EBD-CSIC
Patrícia Singh
University of Potsdam
Cara Gallagher
University of Aarhus

Latest News

The PREDICT project is officially kicking off.

Contact us

Whether you have questions about our digital twin, collaboration opportunities, data access or upcoming features, we’d love to hear from you. Send us a message and our team will get back to you as soon as possible.