The Role of Threatened Species in Food Web Structure Across Europe

Dataset for the manuscript entitled "The Role of Threatened Species in Food Web Structure Across Europe".<br><b>Aim</b>Assess the relevance of threatened and non-threatened species to local food web network structures across Europe.<b>Location</b>Europe (extending eastward to include Turkey, Georgia, Armenia, Azerbaijan and Russia west of the Urals).<b>Time-period</b>We derived our interactions from a metaweb of potential tetrapod interactions across Europe, using data spanning the past 50 years.<b>Major taxa studied</b>Terrestrial tetrapods (birds, mammals, amphibians and reptiles).<b>Methods</b>We used a dataset of local European potential food webs, obtained from Galiana et al. (2021). The local food webs were inferred to Europe by combining a species-level metaweb of trophic interactions of European tetrapods, the Tetra-EU 1.0 (Maiorano et al. 2020), with the distribution of these species (Maiorano et al. 2013).Next, we added information about the threat statuses across Europe and measured the importance of species through node-level network structural metrics, including in-degree (number of prey species), out-degree (number of predator species), trophic level, betweenness centrality (how often a species lies on the shortest paths between all other species), closeness centrality (how close to all other species is the focal species), and the integrated Value of Influence (a species' overall impact on a food web, combining both direct and indirect effects).<b>Results</b>While threatened species occasionally hold key roles in specific regions (e.g. the Iberian Peninsula), non-threatened species often demonstrate a higher Integrated Value of Influence and betweenness centrality, underscoring their significant contributions to network integrity.<b>Main conclusions</b>We highlight the importance of integrating threatened and non-threatened species into conservation strategies, recognising their complementary roles in maintaining food web stability at multiple spatial scales.