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The landscape has always been a fundamental factor in defining tourist flow attraction for local development. In this paper, landscape related to tourism have been analysed using three different measurements through appropriate performance indicators and rationalised with the aim of identifying a scheme of mutual relations. Applying advanced statistical methods of ranking and data synthesis, the area investigated (Molise, Italy) has been divided into different zones. Each area described has a specific relation between tourism and landscape useful in the implementation of optimal promotion strategies and valorisation of the area. In marginal areas, tourism can have an excellent growth potential, since they are characterized by the high quality of the landscape. However, the analysis highlights some gap areas, which means the existence of areas with high quality of the natural and agricultural landscape is not associated with an appropriate tourism development, or areas where the high tourism development is not associated with an appreciable quality of the landscape.

Italy is one of the European countries most affected by biological invasions. In this study, we focused on the impact of Acacia saligna, an Australian invasive plant species, on the coastal ecosystem’s ecology and biodiversity along the sandy coasts of Molise (southern Italy). We analyzed data from 61 vegetation plots recorded in coastal pine forest and Mediterranean scrub habitats of Molise throughout the preparatory actions of the “LIFE Maestrale” project (NAT/IT/000262). In order to study the ecological impact of Acacia saligna comparing invaded and non-invaded areas, we first assigned the Ellenberg’s indicator values to each plant species, which were then used to relate the presence of Acacia saligna with ecological characteristics of sites through a generalized linear model (GLM). Our results showed a significant positive relationship between the presence of Acacia saligna and high levels of soil nutrients and, on the contrary, a negative relationship with the presence of mesophilic species, which are typical of the community interest habitats of pine forest (2270*). The use of ecological indicators is effective to pinpoint the ecological effects of biological invasions, as well as to evaluate habitat conservation state and to identify vulnerable native species.

Abstract Due to the increasing importance of exposome in environmental epidemiology, feasibility and usefulness of an Environmental Data Management System (EDMS) using Open Data was evaluated. The EDMS includes data from 10 European cities (Celje (Slovenia), Łódź (Poland), Manchester (UK), Palermo (Italy), Paris (France), Porto (Portugal), Regensburg (Germany), Reus (Spain), Rijeka (Croatia), Thessaloniki (Greece)) about external non-specific and specific exposome factors at the city or country level (2017–2020). Findings showed that the highest values of life expectancy were in Reus females (86 years) and Palermo males (81 years). UK had the highest obesity rate (28%), Croatia the highest prescribed drug consumption (62%), Greece and Portugal the highest smoking rates (37%, 42%) and daily alcohol consumption (21%), respectively. The most polluted cities were Thessaloniki for PM10 (38 µg/m3), Łódź for PM2.5 (25 µg/m3), Porto for NO2 (62 µg/m3) and Rijeka for O3 (92 µg/m3). Thessaloniki had the highest grey space (98%) and Łódź the highest cumulative amount of pollen (39,041 p/m3). The highest daily noise levels ≥ 55 dB was in Reus (81% to traffic) and Regensburg (21% to railway). In drinking water, arsenic had the highest value in Thessaloniki (6.4 µg/L), boron in Celje (24 mg/L) and lead in Paris (46.7 µg/L). Portugal and Greece showed the highest pesticide residues in food (7%). In conclusion, utilizing open-access databases enables the translation of research findings into actionable strategies for public health interventions.

Introduction Traffic-related air and noise pollution are important public health issues. The aim of this study was to estimate their effects on allergic/respiratory outcomes in adult and elderly subjects.Materials and methods Six hundred and forty-five subjects living in Pisa (Tuscany, Italy) were investigated through a questionnaire on allergic/respiratory symptoms and diseases. Traffic-related air pollution and noise exposures were assessed at residential address by questionnaire, modelled annual mean NO2 concentrations (1 km and 200 m resolution), and noise level over a 24-h period (Lden). Exposure effects were assessed through logistic regression models stratified by age group (18–64 years, ≥65 years), and adjusted for sex, educational level, occupational exposure, and smoking habits.Results 63.6% of the subjects reported traffic exposure near home. Mean exposure levels were: 28.24 (±3.26 SD) and 27.23 (±3.16 SD) µg/m3 for NO2 at 200 m and 1 km of resolution, respectively; 57.79 dB(A) (±6.12 SD) for Lden. Exposure to vehicular traffic (by questionnaire) and to high noise levels [Lden ≥ 60 dB(A)] were significantly associated with higher odds of allergic rhinitis (OR 2.01, 95%CI 1.09–3.70, and OR 1.99, 95%CI 1.18–3.36, respectively) and borderline with rhino-conjunctivitis (OR 2.20, 95%CI 0.95–5.10, and OR 1.76, 95%CI 0.91–3.42, respectively) only in the elderly. No significant result emerged for NO2.Conclusions Our findings highlighted the need to better assess the effect of traffic-related exposure in the elderly, considering the increasing trend in the future global population’s ageing.

Climatic variables are useful but often weak predictors of plant functional trait variation across ecosystems. Here the authors investigate how assigning plant communities to a habitat hierarchy improves the explanatory power of climate-trait relationships at the continental scale.

Current analyses and predictions of spatially explicit patterns and processes in ecology most often rely on climate data interpolated from standardized weather stations. This interpolated climate data represents long-term average thermal conditions at coarse spatial resolutions only. Hence, many climate-forcing factors that operate at fine spatiotemporal resolutions are overlooked. This is particularly important in relation to effects of observation height (e.g. vegetation, snow and soil characteristics) and in habitats varying in their exposure to radiation, moisture and wind (e.g. topography, radiative forcing or cold-air pooling). Since organisms living close to the ground relate more strongly to these microclimatic conditions than to free-air temperatures, microclimatic ground and near-surface data are needed to provide realistic forecasts of the fate of such organisms under anthropogenic climate change, as well as of the functioning of the ecosystems they live in. To fill this critical gap, we highlight a call for temperature time series submissions to SoilTemp, a geospatial database initiative compiling soil and near-surface temperature data from all over the world. Currently, this database contains time series from 7,538 temperature sensors from 51 countries across all key biomes. The database will pave the way toward an improved global understanding of microclimate and bridge the gap between the available climate data and the climate at fine spatiotemporal resolutions relevant to most organisms and ecosystem processes.

Coastal ecosystems, encompassing land and marine environments and hosting substantial biodiversity, are among the most threatened worldwide. The European Habitats Directive prioritises coastal habitats and species, requiring legislative, direct protection, monitoring, and informational measures. Accurate habitat and species monitoring is crucial to conservation efforts, yet biodiversity research in complex, ever-changing environments like coastal areas is difficult. Citizen Science may bridge biodiversity assessment and eco-friendly monitoring by incorporating non-scientists into the data collection for scientists and stakeholders. A Citizen Science approach supported by a dedicated iNaturalist project (called Wild Coast CASCADE) was implemented to obtain a complete monitoring framework that includes observations of many taxa in terrestrial, aquatic, and transitional dynamic coastal environments in the Central Italian Adriatic coast. We explored data gathered focusing on the IUCN Red List species, the species and habitats of European conservation concern, and the non-native species. Between 2020 and 2023, we collected 3784 records covering 742 species, with 81% meeting the “research grade criteria”, and these were retained for subsequent research. Citizen Science volunteers have collected 291 georeferenced animal records from the global IUCN Red List, 51 plant species from 14 species that are indicators of the presence of habitats of European Conservation Concern, and 44 non-native plants and animals. Our results provide evidence that citizen research projects can effectively assist in monitoring coastal–marine habitats and species. They also underline the potential of Citizen Science for biodiversity conservation and emphasize the importance of public engagement in conservation efforts.

New Italian data on the distribution of the Annex I Habitats 1510*, 2130*, 2250*, 3180*, 3260, 5230*, 6410, 7140, 7220*, 9320 are reported in this contribution. Specifically, 14 new occurrences in Natura 2000 sites are presented and 20 new cells are added in the EEA 10 km × 10 km reference grid. The new data refer to the Italian administrative regions of Abruzzo, Apulia, Friuli Venezia Giulia, Liguria, Marche, Molise, Sardinia, Sicily, Tuscany and Umbria.

High mountain ecosystems are hotspots of biodiversity that are highly vulnerable to climate warming and land use change. In Europe, high mountain habitats are included in the EC Directive 92/43/EEC (Habitats Directive) and the identification of practices facilitating effective monitoring is crucial for meeting HD goals. We analyzed the temporal changes in species composition and diversity on high mountain EU habitats and explored if the subgroup of diagnostic species was able to summarize the comprehensive information on plant community variations. We performed a re-visitation study, using a set of 30 georeferenced historical plots newly collected after 20 years on two EU habitats (Galium magellense community growing on screes (8120 EU) and Trifolium thalii community of snowbeds (6170 EU)) in the Maiella National Park (MNP), which is one of the most threatened Mediterranean mountains in Europe. The presence of several endangered species and the availability of a botanical garden, a seed bank, and a nursery, make the MNP an excellent training ground to explore in situ and ex situ conservation strategies. We compared overall and diagnostic species richness patterns over time by rarefaction curves and described the singular aspects of species diversity (e.g., richness, Shannon index, Simpson index, and Berger–Parker index), by Rènyi’s diversity profiles. Diversity values consistently varied over time and across EU habitat types, with increasing values on scree communities and decreasing values on snowbeds. These changes could be associated with both land use change, through the increase of grazing pressure of Apennine chamois (Rupicapra pyrenaica ornata), which determined a rise of nitrophilous species in the scree community, and an increase of grasses at the expense of forbs in snowbeds, and to climate change, which promoted a general expansion of thermophilous species. Despite the two opposite, ongoing processes on the two plant communities studied, our results evidenced that diagnostic species and overall species followed the same trend of variation, demonstrating the potential of diagnostics for EU habitat monitoring. Our observations suggested that the re-visitation of historical plots and the implementation of frequent monitoring campaigns on diagnostic species can provide important data on species abundance and distribution patterns in these vulnerable ecosystems, supporting optimized in situ and ex situ conservation actions.

In this paper we present a low-cost approach to mapping vegetation cover by means of high-resolution close-range terrestrial photogrammetry. A total of 249 clusters of nine 1 m2 plots each, arranged in a 3 × 3 grid, were set up on 18 summits in Mediterranean mountain regions and in the Alps to capture images for photogrammetric processing and in-situ vegetation cover estimates. This was done with a hand-held pole-mounted digital single-lens reflex (DSLR) camera. Low-growing vegetation was automatically segmented using high-resolution point clouds. For classifying vegetation we used a two-step semi-supervised Random Forest approach. First, we applied an expert-based rule set using the Excess Green index (ExG) to predefine non-vegetation and vegetation points. Second, we applied a Random Forest classifier to further enhance the classification of vegetation points using selected topographic parameters (elevation, slope, aspect, roughness, potential solar irradiation) and additional vegetation indices (Excess Green Minus Excess Red (ExGR) and the vegetation index VEG). For ground cover estimation the photogrammetric point clouds were meshed using Screened Poisson Reconstruction. The relative influence of the topographic parameters on the vegetation cover was determined with linear mixed-effects models (LMMs). Analysis of the LMMs revealed a high impact of elevation, aspect, solar irradiation, and standard deviation of slope. The presented approach goes beyond vegetation cover values based on conventional orthoimages and in-situ vegetation cover estimates from field surveys in that it is able to differentiate complete 3D surface areas, including overhangs, and can distinguish between vegetation-covered and other surfaces in an automated manner. The results of the Random Forest classification confirmed it as suitable for vegetation classification, but the relative feature importance values indicate that the classifier did not leverage the potential of the included topographic parameters. In contrast, our application of LMMs utilized the topographic parameters and was able to reveal dependencies in the two biomes, such as elevation and aspect, which were able to explain between 87% and 92.5% of variance.

This study provides a first step toward the knowledge of the alien-dominated and co-dominated plant communities present in Italy. The first ever checklist of the alien phytocoenoses described or reported in literature for the Italian territory has been compiled, produced by data-mining in national and local thematic literature. The resulting vegetation-type draft-list has been checked in the light of the most recent syntaxonomic documentation and updated with regards to syntaxonomy and nomenclature, with special reference to the frame proposed in the Italian Vegetation Prodrome. The list includes 27 vascular and one bryophyte vegetation classes, hosting 194 low rank alien-dominated syntaxa. The different vegetation types detected for each syntaxonomic class and macro-vegetation group, defined by physiognomical and ecological attributes, are discussed.

Invasive alien plants (IAP) pose a major threat to biodiversity and have a negative impact on the integrity and conservation status of plant communities. Mediterranean dunes are widely exposed to IAP, due to their environmental heterogeneity and the anthropogenic pressures to which they are subjected. The current study explored the possible existence of critical thresholds of IAP cover/abundance and dune path impacts that may cause the decline in diagnostic species cover in shifting and transition dunes. A random sampling of 126 plots in areas invaded and not invaded by IAP across the Italian Adriatic dunes has been used and the recorded species have been classified in ecological guilds. In order to explore the effect of plant community composition and distances from dune paths on the diagnostic species cover, a Random Forest regression model has been fitted. The results revealed that three main critical thresholds can be detected concerning IAP total cover, IAP Oenothera stucchii Soldano abundance and the distance from dune paths and they work differently in shifting and transition dunes. The identification of such cut-off points provides useful insights for an array of actions to preserve the biodiversity of the Mediterranean coastal dunes.

Litter decomposition is a key process for carbon and nutrient cycling in terrestrial ecosystems and is mainly controlled by environmental conditions, substrate quantity and quality as well as microbial community abundance and composition. In particular, the effects of climate and atmospheric nitrogen (N) deposition on litter decomposition and its temporal dynamics are of significant importance, since their effects might change over the course of the decomposition process. Within the TeaComposition initiative, we incubated Green and Rooibos teas at 524 sites across nine biomes. We assessed how macroclimate and atmospheric inorganic N deposition under current and predicted scenarios (RCP 2.6, RCP 8.5) might affect litter mass loss measured after 3 and 12 months. Our study shows that the early to mid-term mass loss at the global scale was affected predominantly by litter quality (explaining 73% and 62% of the total variance after 3 and 12 months, respectively) followed by climate and N deposition. The effects of climate were not litter-specific and became increasingly significant as decomposition progressed, with MAP explaining 2% and MAT 4% of the variation after 12 months of incubation. The effect of N deposition was litter-specific, and significant only for 12-month decomposition of Rooibos tea at the global scale. However, in the temperate biome where atmospheric N deposition rates are relatively high, the 12-month mass loss of Green and Rooibos teas decreased significantly with increasing N deposition, explaining 9.5% and 1.1% of the variance, respectively. The expected changes in macroclimate and N deposition at the global scale by the end of this century are estimated to increase the 12-month mass loss of easily decomposable litter by 1.1–3.5% and of the more stable substrates by 3.8–10.6%, relative to current mass loss. In contrast, expected changes in atmospheric N deposition will decrease the mid-term mass loss of high-quality litter by 1.4–2.2% and that of low-quality litter by 0.9–1.5% in the temperate biome. Our results suggest that projected increases in N deposition may have the capacity to dampen the climate-driven increases in litter decomposition depending on the biome and decomposition stage of substrate.

Global change threatens alpine biodiversity and its effects vary across habitat types and biogeographic regions. We explored vegetation changes over the last 20 years on two Mediterranean alpine calcareous grasslands in central Apennines (Italy): stripped grasslands (EUNIS code E4.436) with Sesleria juncifolia growing on steep slopes, and wind edge swards (EUNIS code E4.42) with Carex myosuroides. Based on a re-visitation of 25 vegetation plots of 4 × 4 m, we assessed changes in overall and endemic plant species cover and richness by nonparametric Kruskal–Wallis test. We explored changes in structure and ecology using growth forms and Landolt indicators for temperatures. We identified species’ contribution to temporal changes using the similarity percentage procedure (SIMPER). The results evidenced a significant decline in all species cover and richness on both plant communities with a significant decline in alpine and endemic species and in hemicryptophytes with rosette and scapose ones on stripped grasslands, as well as a decline in subalpine and suffruticose chamaephytes species on wind edge swards. Such biodiversity loss, so far observed only in the warmest and Southern Mediterranean summits of Europe, is likely attributable to the combined effect of higher temperatures; the increase in the vegetative period; and the decrease in water availability, which is particularly severe in calcareous regions. Our study suggested the vulnerability of the analyzed alpine ecosystems to global change and the importance of monitoring activities to better understand vegetation trends and adaptation strategies in subalpine, alpine, and nival ecosystems.

Coastal ecosystems, encompassing land and marine environments and hosting substantial biodiversity, are among the most threatened worldwide. The European Habitats Directive prioritises coastal habitats and species, requiring legislative, direct protection, monitoring, and informational measures. Accurate habitat and species monitoring is crucial to conservation efforts, yet biodiversity research in complex, ever-changing environments like coastal areas is difficult. Citizen Science may bridge biodiversity assessment and eco-friendly monitoring by incorporating non-scientists into the data collection for scientists and stakeholders. A Citizen Science approach supported by a dedicated iNaturalist project (called Wild Coast CASCADE) was implemented to obtain a complete monitoring framework that includes observations of many taxa in terrestrial, aquatic, and transitional dynamic coastal environments in the Central Italian Adriatic coast. We explored data gathered focusing on the IUCN Red List species, the species and habitats of European conservation concern, and the non-native species. Between 2020 and 2023, we collected 3784 records covering 742 species, with 81% meeting the "research grade criteria", and these were retained for subsequent research. Citizen Science volunteers have collected 291 georeferenced animal records from the global IUCN Red List, 51 plant species from 14 species that are indicators of the presence of habitats of European Conservation Concern, and 44 non-native plants and animals. Our results provide evidence that citizen research projects can effectively assist in monitoring coastal–marine habitats and species. They also underline the potential of Citizen Science for biodiversity conservation and emphasize the importance of public engagement in conservation efforts. [ABSTRACT FROM AUTHOR]