Coexisting with large carnivores in human-dominated European landscapes is a highly relevant and current challenge. Over the last two centuries, the wolf (Canis lupus) population in Europe has experienced a significant decline, primarily due to direct human persecution. However, recent conservation policies, combined with the species’ remarkable ecological flexibility, have enabled a rapid recovery. This process, which now also extends to densely populated areas, is exemplified by the ongoing expansion across the Po Plain, one of Europe’s most heavily human-dominated landscapes. Our study aims to provide the first assessment of habitat suitability for wolf presence in the Po Plain. Using a ten-year dataset of wolf occurrences (2015–2024), we evaluated the influence of several environmental and human-related factors by applying habitat suitability models with the Maximum Entropy algorithm (MaxEnt). The goal was to quantify potentially suitable habitats within the plain and to identify the factors that could either facilitate or constrain wolf presence. The results showed that approximately half of the Po Plain is suitable for wolf presence. Among anthropogenic variables, “urban areas” was the only factor that significantly and negatively affected habitat suitability, while other variables had negligible impacts. This underscores the species’ remarkable ecological and behavioural adaptability. By investigating wolf distribution in one of Europe’s most anthropised regions, this study aims to shed light on the species’ ability to thrive in human-altered landscapes, contributing to ongoing conservation efforts and informing future strategies for coexistence in highly populated lowland ecosystems.

Green infrastructure (GI) networks comprising multiple natural and artificial habitats are important tools for the management of ecosystem services. However, even though ecosystem services are deeply linked with the state of biodiversity, many approaches to GI network planning do not explicitly consider the ecological needs of biotic communities, which are often threatened by anthropic activities even in presence of protected areas. Here, to contribute in fill this gap, we describe an easy-to-apply, biodiversity-centric approach to model an ecological network as a backbone for a GI network, based on the ecological needs of a range of representative species. For each species, ideal habitats (nodes) were identified, and crossing costs were assigned to other habitat types depending on their compatibility with the species ecology. Corridors linking the nodes were then mapped, minimizing overall habitat crossing costs. We applied the method to the Isonzo–Vipacco river area in Northern Italy, highlighting a potential ecological network where nodes and corridors occupied 27% and 11.8% of the study area, respectively. The prospective of its conflicts with anthropic activities and possible solutions for its implementation was also discussed. Our method could be applied to a variety of situations and geographic contexts, being equally useful for supporting the protection of entire biocenoses or of specific sensitive species, as well as enhancing the ecosystem services they provide.