Result description
Unlocking ecological insights with “guardgraph” repository: Mapping Species Interactions for Decision Support
How do species interact across landscapes and how can we harness that knowledge for conservation, compliance? “guardgraph”, a core output of the GUARDEN project, delivers a scalable, queryable infrastructure for modeling species interactions using graph-based logic. Built for integration with field data, regulatory workflows, and predictive analytics, “guardgraph” transforms ecological complexity into actionable intelligence. Whether you’re tracing biodiversity loss, or designing restoration strategies, “guardgraph” empowers users to explore, visualize, and interrogate species networks.
Species interactions API, providing summary and API access to the GloBI database of species interactions. Species interactions data is scarce and hard to retrieve. The service is designed with an infrastructure as code framework having the advantage that it can be easily taken offline to save on costs and be brought live again. Reactivating the service also implies that the latest version of the GloBI database is retrieved and processed.
Addressing target audiences and expressing needs
- To raise awareness and possibly influence policy
- Scientific peers
- Policy makers or regulators
- Technical collaborators (e.g., developers, data scientists, infrastructure partners)
- Funding bodies or stakeholders
- EU and Member State Policy-makers
- Research and Technology Organisations
- Academia/ Universities
R&D, Technology and Innovation aspects
Significant potential exists for further development, such as creating prediction models for interacting species and integrating the API into species distribution modelling The API will also be integrated into the B-Cubed project and made available to colleagues in the “one stop project” for analysis, providing valuable feedback for improvements.
It is easy to install on any Python-compatible system.
Result submitted to Horizon Results Platform by AGENTSCHAP PLANTENTUIN MEISE
