33,092 research outputs found

    Contrasting multi-taxa diversity patterns between abandoned and non-intensively managed forests in the southern Dolomites

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    The abandonment of silvicultural activities can lead to changes in species richness and composition of biological communities, when compared to those found in managed forests. The aim of this study was to compare the multi-taxonomical diversity of two mature silver fir-beech-spruce forests in the southern Dolomites (Italy), corresponding to the European Union habitat type 9130. The two sites share similar ecological and structural characteristics, but differ in their recent management histories. In the last 50 years, one site underwent non-intensive management, while the other was left unmanaged and was included in a forest reserve. The species richness and composition of eight taxa were surveyed in the two sites between 2009 and 2011. The difference in mean species richness between the two forest management types was tested through permutation tests, while differences in species composition were tested by principal coordinates analysis and the permutational multivariate analysis of variance. Mean species richness of soil macrofungi, deadwood lichens, bark beetles, and longhorn beetles were significantly higher in the abandoned than in the non-intensively managed forests. Deadwood fungi and epiphytic lichens did not differ in mean species richness between the two study sites, while mean species richness of ground beetles and birds were higher in the non-intensively managed than in the abandoned forest. Significant differences in species composition between the two sites were found for all the taxa, except for longhorn beetles. These results indicate that improving forest landscape heterogeneity through the creation of a mosaic of abandoned and extensively managed forests should better fulfill the requirements of ecologically different taxa

    Patterns of co-occurrence of rare and threatened species in winter arable plant communities of Italy

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    Detecting patterns of species co-occurrence is among the main tasks of plant community ecology. Arable plant communities are important elements of agroecosystems, because they support plant and animal biodiversity and provide ecosystem services. These plant communities are shaped by both agricultural and environmental drivers. The pressure of intensive agriculture worldwide has caused the decline of many characteristic arable species and communities. Italy is the European country where arable plant biodiversity is the best preserved. In this study, we assessed the patterns of co-occurrence of rare and threatened arable plants in 106 plots of winter arable vegetation located from Piedmont to Calabria, in the mainland part of the country. For this purpose, we based our investigation on the analysis of a recently acquired dataset and on the European list of rare and threatened arable plants. We highlight how dierent species of conservation interest tend to occur in the same community. On the other hand, generalist and more competitive taxa show similar patterns of co-occurrence. We suggest that single species of conservation value could be suitable indicators of a well-preserved community. On the other hand, to be eective, conservation strategies should target the whole community, rather than single species

    Assembling the Tree of Life in Europe (AToLE)

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    A network of scientists under the umbrella of 'Assembling the Tree of Life in Europe (AToLE)' seeks funding under the FP7-Theme: Cooperation - Environment (including Climate Change and Biodiversity Conservation) programme of the European Commission.
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    Optimized R functions for analysis of ecological community data using the R virtual laboratory (RvLab)

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    Background: Parallel data manipulation using R has previously been addressed by members of the R community, however most of these studies produce ad hoc solutions that are not readily available to the average R user. Our targeted users, ranging from the expert ecologist/microbiologists to computational biologists, often experience difficulties in finding optimal ways to exploit the full capacity of their computational resources. In addition, improving performance of commonly used R scripts becomes increasingly difficult especially with large datasets. Furthermore, the implementations described here can be of significant interest to expert bioinformaticians or R developers. Therefore, our goals can be summarized as: (i) description of a complete methodology for the analysis of large datasets by combining capabilities of diverse R packages, (ii) presentation of their application through a virtual R laboratory (RvLab) that makes execution of complex functions and visualization of results easy and readily available to the end-user. New information: In this paper, the novelty stems from implementations of parallel methodologies which rely on the processing of data on different levels of abstraction and the availability of these processes through an integrated portal. Parallel implementation R packages, such as the pbdMPI (Programming with Big Data – Interface to MPI) package, are used to implement Single Program Multiple Data (SPMD) parallelization on primitive mathematical operations, allowing for interplay with functions of the vegan package. The dplyr and RPostgreSQL R packages are further integrated offering connections to dataframe like objects (databases) as secondary storage solutions whenever memory demands exceed available RAM resources. The RvLab is running on a PC cluster, using version 3.1.2 (2014-10-31) on a x86_64-pc-linux-gnu (64-bit) platform, and offers an intuitive virtual environmet interface enabling users to perform analysis of ecological and microbial communities based on optimized vegan functions. A beta version of the RvLab is available after registration at: https://portal.lifewatchgreece.eu

    Are neonicotinoid insecticides driving declines of widespread butterflies?

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    There has been widespread concern that neonicotinoid pesticides may be adversely impacting wild and managed bees for some years, but recently attention has shifted to examining broader effects they may be having on biodiversity. For example in the Netherlands, declines in insectivorous birds are positively associated with levels of neonicotinoid pollution in surface water. In England, the total abundance of widespread butterfly species declined by 58% on farmed land between 2000 and 2009 despite both a doubling in conservation spending in the UK, and predictions that climate change should benefit most species. Here we build models of the UK population indices from 1985 to 2012 for 17 widespread butterfly species that commonly occur at farmland sites. Of the factors we tested, three correlated significantly with butterfly populations. Summer temperature and the index for a species the previous year are both positively associated with butterfly indices. By contrast, the number of hectares of farmland where neonicotinoid pesticides are used is negatively associated with butterfly indices. Indices for 15 of the 17 species show negative associations with neonicotinoid usage. The declines in butterflies have largely occurred in England, where neonicotinoid usage is at its highest. In Scotland, where neonicotinoid usage is comparatively low, butterfly numbers are stable. Further research is needed urgently to show whether there is a causal link between neonicotinoid usage and the decline of widespread butterflies or whether it simply represents a proxy for other environmental factors associated with intensive agriculture

    Species richness-environment relationships of European arthropods at two spatial grains : habitats and countries

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    We study how species richness of arthropods relates to theories concerning net primary productivity, ambient energy, water-energy dynamics and spatial environmental heterogeneity. We use two datasets of arthropod richness with similar spatial extents (Scandinavia to Mediterranean), but contrasting spatial grain (local habitat and country). Samples of ground-dwelling spiders, beetles, bugs and ants were collected from 32 paired habitats at 16 locations across Europe. Species richness of these taxonomic groups was also determined for 25 European countries based on the Fauna Europaea database. We tested effects of net primary productivity (NPP), annual mean temperature (T), annual rainfall (R) and potential evapotranspiration of the coldest month (PETmin) on species richness and turnover. Spatial environmental heterogeneity within countries was considered by including the ranges of NPP, T, R and PETmin. At the local habitat grain, relationships between species richness and environmental variables differed strongly between taxa and trophic groups. However, species turnover across locations was strongly correlated with differences in T. At the country grain, species richness was significantly correlated with environmental variables from all four theories. In particular, species richness within countries increased strongly with spatial heterogeneity in T. The importance of spatial heterogeneity in T for both species turnover across locations and for species richness within countries suggests that the temperature niche is an important determinant of arthropod diversity. We suggest that, unless climatic heterogeneity is constant across sampling units, coarse-grained studies should always account for environmental heterogeneity as a predictor of arthropod species richness, just as studies with variable area of sampling units routinely consider area
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