Suchergebnisse

AbstractAgricultural management has a great influence on biodiversity and its services in agroecosystems. In Europe, a relevant proportion of biodiversity is dependent on low-input agriculture. To assess the effects of agricultural management on biodiversity, in this study we surveyed the communities of arable plants, diurnal flying insects, and pollinators in three conventional and in two organic fields of a traditional Elephant garlic (Allium ampeloprasum L.) crop of the Valdichiana area, in Tuscany (central Italy). The sampling was carried out twice during the season: in spring, during crop growing, and in summer, after crop harvesting. We assessed the effects of the different agricultural management on the richness and composition (species occurrence and abundance) of the three communities using univariate and multivariate analyses. Concerning our specific case study, only plant species richness was significantly higher in organic fields (15.7 ± 2.7 species per plot), compared to conventional ones (5.4 ± 2.3 species per plot). Regarding community composition, only pollinators showed a marginally significant difference between conventional and organic fields. Conversely, the effect of specific fields significantly explained differences in composition of all the investigated groups (plants, total insects, and pollinators). The results suggest that, in our case study, the emerged differences in diversity of the investigated communities were mainly attributable to environmental and management factors related to single fields, more than to organic or conventional farming. Such evidence could be partly due to the very local scale of the study, to the heterogeneity of the surveyed fields, and to the reduced number of surveyed fields. Further investigation is therefore needed.

AbstractThe variation of species diversity over space and time has been widely recognised as a key challenge in ecology. However, measuring species diversity over large areas might be difficult for logistic reasons related to both time and cost savings for sampling, as well as accessibility of remote ecosystems. In this paper, we present a new package - - to calculate diversity indices based on remotely sensed data, by discussing the theory behind the developed algorithms. Obviously, measures of diversity from space should not be viewed as a replacement of in situ data on biological diversity, but they are rather complementary to existing data and approaches. In practice, they integrate available information of Earth surface properties, including aspects of functional (structural, biophysical and biochemical), taxonomic, phylogenetic and genetic diversity. Making use of the package can result useful in making multiple calculations based on reproducible open source algorithms, robustly rooted in Information Theory.