Rapid mobilization of evidence to improve decision-making on invasive species

Invasive alien species (IAS) represent a major environmental and economic problem. Prevention, risk analysis, management planning and policy evaluation all require open, rapidly mobilized data from fragmented sources. These include essential biodiversity variables for invasions needed to inform decision-making, maximise the benefits of available resources, anticipate future threats, use the
most up-to-date evidence and to do this all in a rapidly changing environment.
The TrIAS project has built a semi-automated data-driven workflow in support of IAS policy that covers a full suite of instruments. Checklist and occurrence data-publication pipelines provide the raw data. Aggregation workflows generate both a unified, annotated, alien species inventory. Using the Global Biodiversity Information Facility as a central data hub, we ensure openness and sustainability, and from this is built an occurrence cube of species, location and year, based upon the checklist. These data products are then used to feed indicators of species invasion, including occupancy trends within and outside protected areas and pathways of introduction. The occurrence cube is also the basis of risk models and maps, used to forecast the establishment risk of IAS in response to climate change. The unified checklist is published as the Belgian contribution to the Global Register of Introduced and Invasive Species (GRIIS) and all products are communicated to a wide range of stakeholders, including citizen scientists, researchers, invasion managers and IAS decision-makers. These results
also support risk assessments performed by taxon experts, which will integrate expert opinion into policy advice. 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.