Analyses of the Italian coastal dune plant communities within the Nature 2000 Network

Abstract

By occupying a transition zone between terrestrial and marine ecosystems, coastal dunes are one of the most ecologically relevant ecosystems on earth. One of the main characteristics of coastal dunes is the spatial variability of the plant communities due to a strong environmental heterogeneity. This allows the coexistence of different plant communities in relatively small spaces and determines the typical sea-inland vegetation zonation. At present, dune environments are considered to be threatened worldwide. Coastal dune management and conservation have become critical issues, representing a priority for many European countries. In Italy coastal sand dunes and inland dunes are considered in a bad or unsuitable conservation state with relation to urbanization and other human pressures. Thus, dune habitats (as defined by the European Habitats Directive 92/43/EEC) require special attention and conservation actions, especially in the light of predicted global changes. In this thesis I analysed the current knowledge of Italian dunes vegetation by setting up a national coastal database; I focused on dune habitats diversity and geographical distribution at the national level; I used this large amount of data to forecast future distribution of dune habitats under climate change scenarios and to evaluate the current and projected effectiveness of the protected areas network. I conducted a detailed research on the Italian phytosociological information putting together different accessible sources regarding Italian coastal dunes vegetation. I also conducted a field campaign adding original phytosociological plots in areas with scarce vegetation information, in order to complete the national coastal database as far as possible. Phytosociological plots (relevés) were georeferenced and assigned to a habitat type following the guide-lines of the Interpretation Manuals of the Habitats Directive. I collected 2.806 relevés (both published and unpublished) distributed in 13 coastal habitats, and stored them using the database software Turboveg. The oldest plot in the database is dated 1967, whereas the newest is dated 2011, although most of the data comes from the 1980’s till present. The most part of the relevés has a medium-high geographical accuracy and, to avoid small position errors, I transferred the relevés on a coastal UTM grid (10 km x 10 km) for further analysis. Embryo dune, mobile dune and transition dune habitats had the highest number of records in the database, followed by beach and fixed dune habitats. The Crucianellion maritimae fixed beach dunes and the Malcomietalia dune grasslands habitats were characterised by the highest number of species and phytosociological associations, most of them endemic of few regions (in particular Sardinia, Sicily, Calabria, Basilicata and Tuscany). Regarding dune habitats’ geographical distribution, those close to the sea were widespread along the Italian sandy coasts, while fixed and inland dune habitats showed a more restricted spatial distribution. There is a wide variety of psammophilous plant communities along the Italian coasts linked to the variability of bioclimatic and phytogeographic features. A particularly high number of relevés and habitat types were found in central Italy and also the insular areas were characterised by high species richness and by endemic and rare associations. In addition, on the northern Adriatic coast there was a rare, priority habitat (Fixed coastal dunes with herbaceous vegetation – Grey dunes) with a high species richness and a restricted geographic distribution. For the most representative dune habitats at national level I developed habitat distribution models to forecast the response of sandy dunes to climate change over the next 50 years. I took a community-level strategy by adopting two complementary modelling approaches: indirect (speciesbased) and direct (habitat-based). In the indirect approach I modelled individual plant species distributions as a function of the environmental predictors. Then, for each habitat, I used the predicted occurrences of its diagnostic species as explanatory variables in the models to predict habitat distribution both in the current projections and in the future scenarios. I compared this indirect approach with a straightforward direct one, using the current distribution of the habitat itself to model its present and future distribution based on the environmental predictors. Using the R-based package BIOMOD, I performed all the projections combining in an ensemble forecast eight different and widely used nichebased modelling techniques. As explanatory variables I selected six noncorrelated bioclimatic variables and three land use and morphosedimentological variables. I focused on two IPCC emission scenarios (A2 - high emissions- and B2 -intermediate emissions-) for the year 2050 in order to explore possible changes in an intermediate time range. Predictive performance, as assessed by TSS (True Skill Statistic), was particularly good in the indirect models, while the evaluation of direct models revealed that this is a less reliable approach for coastal dune habitats. There were no significant differences between the two future scenarios (A2 and B2) that showed pretty much the same percentage of increase/decrease of coastal habitats for the year 2050. The results showed that habitats closer to the sea (beach and embryo dune) could increase their geographical distribution in the near future even by more than 40%. On the contrary, mobile dune and fixed dunes habitats were projected to lose most of their current geographical distribution (more than 75%), while the transition dune habitat was projected to remain stable. Finally, I performed a comprehensive gap analysis based on the modelled habitat distributions (current and future predictions of the indirect models) and the Italian conservation areas network, in order to evaluate its present and future efficacy. The current protected areas network was fairly effective in preserving coastal dune habitats as most of them were well represented in the protected areas. Only the priority fixed dune habitat with Juniperus spp. failed to reach the conservation target (minimum number of grid cells where each habitat occurred overlapping with protected areas), thus being, at present, less protected than other habitats. However, in the two future scenarios the distribution range reduction of mobile and fixed dune habitats due to climate change could lead to a decrease in the future efficacy of protected areas. In conclusion, the information derived from the database gives an excellent account of the diversity of Italian coastal dune habitat types, and thereby it constitutes an important tool for nature conservation. As it is highly probable that human development and recreational activities along coasts will continue to be intense, an appropriate management of wellpreserved dune systems, paired with the restoration of the more damaged ones, is urgently needed to guarantee their conservation for the future generations. Furthermore our results call for adaptive and flexible management of protected areas in face of habitat distribution shifts linked to predicted climate change.