Most studies on habitat selection among animals are conducted at local scales, whereas reliable determination of species requirements at larger spatial scales can be problematic. We used data available for NATURA 2000 sites to determine the habitat requirements of two relatively widespread and common species-pine marten Martes martes and stone marten Martes foina-in Southern Europe. Using presence-absence data, we applied statistical models at two spatial scales. At the local scale (within the dispersal distances of the species), sites occupied by martens were compared with unoccupied sites using buffers of different sizes, whereas at the regional scale, unoccupied sites were selected randomly. To adjust for spatial autocorrelation of data, penalised quasi-likelihood approximations were used. Both species of martens demonstrated preferences for areas with higher proportions of forest cover and steeper terrain. At the local, but not at the regional, scale, pine martens occurred at lower elevations, whilst stone martens occurred at higher elevations. We found that climatic variables (mean temperature, precipitation) had no significant effect on the presence of the martens. The results of our analyses generally confirmed findings of previous studies on habitat selection of both marten species in Southern Europe. This demonstrates the utility of data collected for NATURA 2000 sites for use in various analyses such as conservation planning and evaluating the impact of climate change on the distribution of animal species.
We present the results of research concerning the temporal and spatial variability of the dates of the onset of the growing season (OGS) in Poland using satellite data. The data from the years 2001-2010 were obtained from the MODIS Global Land Cover Dynamics Product (MCD12Q2). The study examined the relationship between the OGS dates and types of land cover, meteorological elements (air temperature and snow depth), and atmospheric circulation conditions. In the study period, the average OGS dates for the entire country showed the strongest correlation with minimum air temperature from January to March (R 2 =0.95). The photosynthetic activity of vegetation in early spring was also considerably influenced by the strength of zonal flow and the type of land cover. The latest OGS dates in Poland were observed in areas with a higher share of wetlands and inland waters, and the earliest ones in urban areas and agricultural land.
Road maintenance in winter using de-icing agents, which is widely used in Eastern Europe, is the cause of water salinization in neighbouring environments, which might lead to biodiversity loss in aquatic ecosystems. In this study, we investigated NaCl toxicity to test young organisms: Daphnia magna and Poecilla reticulata (standard tests organisms). The salinity of NaCl was measured by electrolytic conductivity (EC). It was statistically demonstrated that the test solutions should be prepared using natural water. For D. magna the NOEC was 7.17 mS/cm and the LC50 9.76 mS/cm. Poecilla reticulata showed resistance to salinity up to a conductivity of 25.2 mS/cm, and no lethal effects were recorded for any individual in the test population. The study showed that winter salinities recorded in inland waters (without emergencies such as sudden influx of pollutants due to industrial accidents) are unlikely to affect fish but may be hazardous to small plankton. However, the high dare of D. magna may result in a reduction of planktivorous fish.
Abstract-The article presents methodological considerations on the spatial interpolation of Ewert's index of continentality for Poland. The primary objective was to perform spatial interpolation and generate maps of the index combined with selection of an optimal interpolation method and validation of the use of the decision tree proposed by Szymanowski et al. (Meteorol Z 22:577-585, 2013). The analysis involved four selected years and a multi-year average of the period 1981-2010 and was based on data from 111 meteorological stations. Three regression models: multiple linear regression (MLR), geographically weighted regression (GWR), and mixed geographically weighted regression were used in the analysis as well as extensions of two of them to the residual kriging form. The regression models were compared demonstrating a better fit of the local model and, hence, the non-stationarity of the spatial process. However, the decisive role in the selection of the interpolator was assigned to the possibility of extension of the regression model to residual kriging. A key element here is the autocorrelation of the regression residuals, which proved to be significant for MLR and irrelevant for GWR. This resulted in exclusion of geographically weighted regression kriging from further analysis. The multiple linear regression kriging was found as the optimal interpolator. This was confirmed by cross validation combined with an analysis of improvement of the model in accordance with the criterion of the mean absolute error (MAE). The results obtained facilitate modification of the scheme of selection of an optimal interpolator and development of guidelines for automation of interpolation of Ewert's index of continentality for Poland.
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