Probabilistic network analysis of social-ecological relationships emerging from EU LIFE projects for nature and biodiversity: An application of ERGM models in the case study of the Veneto region (Italy)

Considering social-ecological relationships in managing protected areas is fundamental to ensuring effective biodiversity conservation and restoration governance. Network analysis offers valuable methods to disentangle intangible relations between and within the social and ecological systems. In this way, it could be possible to identify and integrate multiple social and ecological variables that inevitably affect collaborative environmental governance's effectiveness. Nevertheless, this research area is still nascent, with few methodologies and concrete applications reported in the scientific literature. With this study, we aim to propose a robust novel application of a network methodology to enrich the evaluation of the effectiveness of collaborative environmental governance for nature and biodiversity, which has been applied through the analysis of social-ecological relationships that emerged from EU-cofounded LIFE-NAT projects. Specifically, we focus on LIFE-NAT projects implemented in the Veneto Region (Italy) financed in the last programming period (2014–2020). Through formulating four research hypotheses to be tested through Exponential Random Graph Models, we analyze 13 LIFE-NAT projects involving 83 social actors and 29 Natura 2000 (N2000) sites composed of 57 protected habitats. Results show that LIFE-NAT projects in Veneto Region stimulate polycentric governance. Nevertheless, they still need to concretize a multi-actor and multilevel governance. Furthermore, the analysis highlights that selected LIFE-NAT projects implement activities in N2000 sites able to support ecological connectivity and synergies across marine, freshwater, and land habitats through the bridging role of forests, especially in estuarine and coastal areas.