Accepted Poster
Poster Short Abstract
We analysed iNaturalist data within the LTER-Italy network to explore their potential contribution to long-term ecological monitoring. These observations may help enhance spatial and temporal coverage and could complement existing datasets across terrestrial, freshwater, and marine sites.
Poster Abstract
The increasing availability of smartphones and sensors has significantly expanded the potential for biodiversity monitoring, allowing the collection of scientifically valuable data by a broad community of contributors. Among the digital tools enabling this process, iNaturalist plays a central role as a global platform for documenting and sharing biodiversity observations. Currently, iNaturalist represents the fourth largest data provider to the Global Biodiversity Information Facility (GBIF), highlighting its relevance in supporting large-scale ecological research.
In this study, we analysed data collected through the iNaturalist platform within the framework of the LTER-Italy umbrella project. The Long-Term Ecological Research (LTER) network is an international initiative devoted to the long-term monitoring of ecosystems, aiming to detect environmental changes, understand ecological processes, and support sustainable management of natural resources. The Italian branch (LTER-Italy) includes a wide range of terrestrial, freshwater, transitional, and marine sites distributed across the country, each contributing long-term datasets to national and global research infrastructures.
The LTER-Italy iNaturalist umbrella project automatically aggregates all biodiversity observations recorded within LTER site boundaries. Our analysis evaluated the scientific contribution of these data to ongoing research activities, their spatial and taxonomic coverage, and their potential for integration with established long-term datasets. The results demonstrate that iNaturalist observations could enhance the temporal and spatial resolution of ecological monitoring within LTER sites, fostering synergies between citizen-generated data and institutional research frameworks.
Poster Session