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In this paper, integrating field surveys and literature data, an analysis of Ophioglossum lusitanicum plant communities and related 92/43/EEC habitats are reported for Italy. Two new syntaxa, Euphorbio exiguae-Ophioglossetum lusitanici ass. nova hoc loco and trifolietosum scabri subass. nova hoc loco of the Rumici bucephalophori-Ophioglossetum lusitanici were described in the Apulia and Campania regions.Both types of vegetation identified in Apulia, Campania, and Sicily regions represent two different aspects of the same priority habitat: "pseudo-steppe with grasses and annuals of the Thero-Brachypodietea" (habitat code 6220*). A phytosociological and ecological dataset of the literature and new field surveys highlighting the soil type as parameters affecting the vegetation cover of this small fernlike plant, with the Trachynion distachyae Rivas–Martínez, 1978 alliance on calcareous soils and Helianthemion guttati Br.-Bl. in Br.-Bl. et al., 1940 alliance on volcanic soils. Many species of other types of annual meadows have been identified within Ophioglossum communities due to the very small patches of land, where they have been found, and ecological conditions that facilitate this phenomenon of the transgression of other therophytes species. [ABSTRACT FROM AUTHOR]

Anoxia (Protanoxia) orientalis is a beetle of the family Melolonthidae for which Italy represents the western limit of its distribution. The ecology of this species is little known from the quantitative point of view. The ecological correlates of A. orientalis presence in the whole European range and, more specifically, at its western border in Sicily, are analyzed in this paper to develop a potential distribution map for Sicily and to define the habitat selection of this species. There was a clear non-random habitat selection by A. orientalis at both the European and the Sicilian scales and a clear difference in the factors affecting the presence of this species in the larger spatial scale compared to Sicily. At the European scale, the bioclimatic factors were more important than landscape factors, whereas the same was not true at the Sicilian scale. In Sicily, the populations were statistically influenced by a combination of predictors that make their potential optimal distribution very narrow and mostly limited to a few coastal areas, suggesting a region-specific ecological diversification. Since A. orientalis is in strong decline in Italy due to the degradation of coastal environments, it is necessary to minimize the degradation of the dune and back dune environments in Sicily to achieve better management for the populations of this beetle species. [ABSTRACT FROM AUTHOR]

In the light of the "Biological Diversity" concept, habitats are cardinal pieces for biodiversity quantitative estimation at a local and global scale. In Europe EUNIS (European Nature Information System) is a system tool for habitat identification and assessment. Earth Observation (EO) data, which are acquired by satellite sensors, offer new opportunities for environmental sciences and they are revolutionizing the methodologies applied. These are providing unprecedented insights for habitat monitoring and for evaluating the Sustainable Development Goals (SDGs) indicators. This paper shows the results of a novel approach for a spatially explicit habitat mapping in Italy at a national scale, using a supervised machine learning model (SMLM), through the combination of vegetation plot database (as response variable), and both spectral and environmental predictors. The procedure integrates forest habitat data in Italy from the European Vegetation Archive (EVA), with Sentinel-2 imagery processing (vegetation indices time series, spectral indices, and single bands spectral signals) and environmental data variables (i.e., climatic and topographic), to parameterize a Random Forests (RF) classifier. The obtained results classify 24 forest habitats according to the EUNIS III level: 12 broadleaved deciduous (T1), 4 broadleaved evergreen (T2) and eight needleleaved forest habitats (T3), and achieved an overall accuracy of 87% at the EUNIS II level classes (T1, T2, T3), and an overall accuracy of 76.14% at the EUNIS III level. The highest overall accuracy value was obtained for the broadleaved evergreen forest equal to 91%, followed by 76% and 68% for needleleaved and broadleaved deciduous habitat forests, respectively. The results of the proposed methodology open the way to increase the EUNIS habitat categories to be mapped together with their geographical extent, and to test different semi-supervised machine learning algorithms and ensemble modelling methods. [ABSTRACT FROM AUTHOR]

The high altitude mountain slopes of the Dolomites (Italian Alps) are characterized by great habitat and landform heterogeneities. In this paper, we investigated the effect of Nature 2000 habitat and landform types in driving the high altitude ground beetle (Carabidae) distribution in the Western Dolomites (Brenta group, Italy). We studied the carabid assemblages collected in 55 sampling points distributed in four Nature 2000 habitat types and four landform types located between 1860 and 2890 m above sea level (a.s.l.). Twenty-two species, half of them Alpine endemics, were sampled. Species richness and taxonomic distinctness did not show any significant difference among habitat types; conversely, these differences became significant when the landform type was considered. Total activity density and the frequency of brachypterous, endemic and predatory species showed significant differences between both habitat and landform types. Indicator species analysis identified twelve species linked to a specific habitat type and thirteen species linked to a specific landform type. Canonical correspondence analysis showed that altitude and vegetation cover drove the species distribution in each habitat and landform type while the aspect had a weak effect. Our results highlight the need for a geomorphological characterization of the sampling points when high altitude ground-dwelling arthropods are investigated. [ABSTRACT FROM AUTHOR]