A new index to assess the state of dune vegetation derived from true colour images

Vegetation on coastal dunes is a key element, as it promotes the growth and stabilization of these landforms while contributing significantly to biodiversity. Physical (e.g. impact of storms), ecological (e.g. animal grazing) and human-related (e.g. farming and recreation) factors may disturb coastal dune vegetation, changing dune dynamics and eventually inducing ecogeomorphic state shifts. Therefore, understanding vegetation dynamics and state turns crucial to predict dune evolution paths. The latter must be supported by observations combined with the development of tools (e.g. indexes) able to detect eventual changes and to automatically categorize the state of the vegetation. Here, a multi-step index to characterise the dune vegetation state (DUVES) was developed and tested in Barreta Island (South Portugal), where grey dune vegetation has declined in recent years. The index was computed using classified true colour orthophotos and orthomosaics derived from UAS (Unmanned Aerial Systems) surveys. Google Earth images were used as complementary data to analyse the evolution trends. The possible sources of disturbance (i.e. human-related activities and gull occupation) were also investigated by comparing their distribution with the vegetation changes. DUVES successfully identified different states of vegetation cover that expressed its stability, perturbation or growth based on temporal changes and allowed the analysis of their evolutionary trends. The distribution of perturbation was mostly associated with gull nesting areas, increasing over time, and to a less extent to human-related activities. The observed grey dune habitat loss was due to replacement of plants typical from this habitat by ruderal species promoted by the positive feedback established between gulls and vegetation. The developed index proved to be of great utility to define dune habitat evolution and understand the associated drivers, being a tool with a wide range of applications, namely for improving future coastal management actions aimed at conserving dune habitats. Moreover, DUVES is potentially transferable due to its easy adaptability depending on the particularities of each study site or goal.