Purpose of the work package:
Work package 3 aims to identify, document, mobilize and curate the baseline biological, environmental, and socio-economic data available for the European continent. The biological data will be used to evaluate spatial completeness and adequacy for deriving relevant indicators and to identify key areas, species, and/or habitats for future biodiversity monitoring in Europe. Work package 3 will also use state-of-the-art modelling approaches to create spatially explicit projections of current and future distributions of species, traits, interaction networks and habitats. As such, work package 3 will be providing essential data products and information on European biodiversity to the other work packages and to be further incorporated in the TEN-N design and case studies, including the identification of winner and loser species and habitats in different configurations of the network.
To achieve our goals, we will:
– Identify and assess existing data sources on Europe’s biological, environmental, and socio-economic aspects
– Develop a comprehensive metadata repository of the available data, incorporating relevant information on biological, temporal and taxonomic scopes of the data as well as the methodology to produce the datasets and their accessibility.
– Perform an analysis of the existing gaps of knowledge in biodiversity data for Europe to provide measures of uncertainty related to the use of data on distributions, traits and interactions.
– Identify the areas, habitats, and bioregions with a greater need for biodiversity monitoring as highlighted in the gap analysis.
– Use advanced modelling techniques to project current and future distributions of species, traits, interaction networks and habitats, based on different scenarios of future changes.
– Use the projections to identify areas, species and/or habitats of high conservation value, and to design the TEN-N to maximize its ecological representativeness, resilience and connectivity.
– Develop case studies that demonstrate the potential of the baseline and scenario data and modelling outputs for informing conservation policy and practice at different spatial and temporal scales.