Floristic and Vegetation Data Analysis in the Age of Artificial Intelligence

Abstract

The structuring of ecological data has long been central to biodiversity research. In Italy, Sandro Pignatti’s promotion of the first national database of Italian flora represented a landmark achievement in organizing ecological knowledge. Building on this legacy, the present paper explores how Artificial Intelligence (AI) can be employed to obtain and analyze data, thereby complementing traditional approaches to vegetation analysis. Rather than offering a technical account of AI, the paper demonstrates its practical value through two case studies conducted with Microsoft Copilot, a free AI tool available in recent Windows systems. The first case study classifies Italian regions based on the chorological types of their flora. The second examines oak woodlands in Central-Southern Italy, considering structural data such as NDVI, biomass, and percentage of leaf cover. Both examples align with Pignatti’s research lines in phytogeography and plant ecology, and are intended to be critically assessed by researchers with expertise in these fields. The aim is not to present definitive findings, but to provide an opportunity to discuss AI-generated data and results. In doing so, the paper supports Pignatti’s vision of structured floristic and vegetation databases as essential for advancing biodiversity knowledge.