Sixty years of habitat decline: impact of land-cover changes in northern Italy on the decreasing ortolan bunting <Emphasis Type="Italic">Emberiza hortulana</Emphasis>

Habitat loss and degradation are main global threats to biodiversity, and land-use changes in agriculture-dominated landscapes are crucial for an important portion of biodiversity, especially in Europe. We evaluated the effects of land-use changes (1954–2012) on a threatened species, the ortolan bunting, in an agricultural area crucial for its conservation in Italy. We built a distribution model for ortolan bunting in current landscapes and then re-projected it to past scenarios (1954 and 1999–2000). We evaluated the most important land-use changes occurred and estimated their effects on habitat suitability. Bunting occurrence was mostly affected by the extent of grassland (positively; used as foraging/breeding ground), shrubland (quadratic effect; perches/shelter), forest and urbanized land (negatively), and by solar radiation (positively) and slope (quadratic), consistent with other studies carried out especially in southern Europe. The potential distribution of the species was much larger in the past: the estimated decline in suitable habitat is 44–72 % (since 1999–2000/1954), coherent with historical data suggesting strong decline and contraction. Changes in suitability (1954–2012) were mostly associated with changes in the cover of forest, vineyards and abandoned areas (negatively), and shrubland (positively). Land-use/land-cover changes are the main drivers of species occurrence and of habitat decline. The heterogeneous landscape of hilly/low-mountain sites in this area, characterized by a mix of habitats offering complementary resources to ortolan buntings and other species of conservation concern, is currently threatened by abandonment and intensification, but its maintenance may be promoted by a correct definition of Rural Development Programme measures.     

Blood markers among residents from a coal mining area

Environmental Science and Pollution Research - Coal extraction and processing generate environmental contamination, which has several negative impacts on human health. Hematological and biochemical...     

Ecotoxicity of imidacloprid to soil invertebrates in two tropical soils with contrasting texture

Environmental Science and Pollution Research - Imidacloprid is one of the most commercialized insecticides in agriculture in the world, with a broad spectrum of action. However, little is known...     

Chemometric tools applied to optimize a fast solid-phase microextraction method for analysis of polycyclic aromatic hydrocarbons in produced water

Environmental Science and Pollution Research - Chemometric tools are powerful strategies to efficiently optimize many processes. These tools were employed to optimize a fast-solid phase...     

Regression models for exceedance data via the full likelihood

Many situations in practice require appropriate specification of operating characteristics under extreme conditions. Typical examples include environmental sciences where studies include extreme temperature, rainfall and river flow to name a few. In these cases, the effect of geographic and climatological inputs are likely to play a relevant role. This paper is concerned with the study of extreme data in the presence of relevant auxiliary information. The underlying model involves a mixture distribution: a generalized Pareto distribution is assumed for the exceedances beyond a high threshold and a non-parametric approach is assumed for the data below the threshold. Thus, the full likelihood including data below and above the threshold is considered in the estimation. The main novelty is the introduction of a regression structure to explain the variation of the exceedances through all tail parameters. Estimation is performed under the Bayesian paradigm and includes model choice. This allows for determination of higher quantiles under each covariate configuration and upper bounds for the data, where appropriate. Simulation results show that the models are appropriate and identifiable. The models are applied to the study of two temperature datasets: maxima in the U.S.A. and minima in Brazil, and compared to other related models.     

Environmental management policy in a coastal tourism municipality: the case study of Cervia (Italy)

The sustainability concept applied to human activities implies the need to harmonise the protection of environment with a satisfactory economic and social development. This is particularly true for tourism development: a misuse of the natural resources can cause a degradation of the tourist appeal of the destination, bringing it finally to its economic decline. This problem is particularly important in coastal tourism destinations. The implementation of an environmental management system is a powerful way for progressing towards better environmental performances. In this paper, the main results obtained in applying the Eco-Management and Audit Scheme procedure to the municipality of Cervia, a well-known tourist destination located on the Adriatic coast of Italy are described. This research puts into evidence that the main environmental pressures in the summer season are related to the supply of potable water, the production of solid wastes and wastewater air pollution and noise, etc. However, if correctly planned and managed, tourism can also contribute to environmental protection, to the conservation of biodiversity and to a sustainable use of natural resources.     

Assessment of nitrogen leaching from arable land in large river basins: Part II: regionalisation using fuzzy rule based modelling

This study deals with fuzzy rule based modelling of nitrogen (N)-leaching from arable land. Main purpose is the elaboration of a method, which allows dynamical regionalisation of results from process-based models for large regions and can be efficiently included in metamodels or decision support systems for rapid integrated assessment of water resources. The paper is the second part of a two-part paper. In the first paper the distributed ecohydrological model SWIM had been applied to calculate and analyse nitrogen dynamics in arable soils for a set of representative natural and management conditions in the Saale River basin (Ecol. Model. (in press)). Here, in the second paper the results from those simulation experiments are used to define, train and validate fuzzy rule systems for the estimation of N-leaching. Nine fuzzy rule systems, specific for nine soil classes, were created from the simulation experiments, representing the conditions for the whole Saale River basin. The fuzzy rule systems operate on monthly time steps and consist of 15 rules and seven input variables each, which are compiled from time series of precipitation, percolation and evapotranspiration as well as from information about fertilizer and crop specific nitrogen uptake. Simulated annealing as a non-linear discrete optimisation method is used for automatic rule assessment. Validation of the fuzzy rule systems, carried out by split sampling of 30-year simulation period, shows satisfactory performance on an annual basis and good performance on the long-term basis with average correlation between SWIM-simulated and fuzzy rule-estimated N-leaching values of 0.78 and 0.94, respectively.