The challenges that IAS decision-making represents are considerable. There is a need to decide on a wide range of actions, maximising the benefits of available resources while using the most up-to-date evidence. This requires knowledge of species presence, pathways of introduction, impacts and available management options. Proactively, we must also anticipate emerging and future threats. To meet the growing needs of policy, the TrIAS project has built a seamless data-driven workflow in support of IAS policy. It has created an open checklist publication framework for drafting GRIIS-Belgium, open software pipelines for feeding indicators on the state of invasions, analysis of trends and for creating risk maps f alien species. TrIAS uses GBIF as a central data hub, which ensures openness and sustainability. The establishment of a unified alien species checklist for the country and the publication of associated occurrences allows for prioritizing emerging species for risk assessment and risk management, the identification of areas at risk, potential problem species in protected areas and the prioritisation of pathways. Data are further used to build species distribution models and risk maps to inform risk assessments. The results are disseminated in a variety of formats, ready to use by stakeholders including citizen scientists, researchers, invasion managers, and IAS decision-makers. All of these workflows have been built on the principles of Open Science, which means that anyone can rerun or adapt this workflow, including running them for any other country or region. The TrIAS workflow and results definitely constitute a significant improvement towards evidence-based decision making that is transparent, repeatable, adaptable, and supported and endorsed by stakeholders.
|Titel||The Human Role in Biological Invasions : a case of Dr Jekyll and Mr Hyde?|
|Editors||Sven D. Jelaska|
|Plaats productie||Zagreb, Croatia |
|ISBN van elektronische versie||978-953-6202-15-7|
|Publicatiestatus||Gepubliceerd - 15-sep-2020|
- Invasieve soorten
- Data & Infrastructuur