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Two different approaches are applied for the investigation of possible changes within the climate regime – as an important component of vulnerability – on a regional scale for Saxony, Germany. Therefore data were applied from the output of the statistical climate models WETTREG2010 and WEREX-V for a projected period until 2100. In the first step, rain gauge-based precipitation regions with similar statistics have been classified. The results show that stable regions are mainly located in the Ore Mountains, while regions of higher uncertainty in terms of a climate signal exist particularly between the lowlands and mountains. In the second step, station-based data on precipitation, temperature and climatic water balance were interpolated by the regionalisation service RaKliDa. Model runs which lay closest to the observed data for the period 1968 to 2007 were identified. Therefore, regions of similar climates were classified and compared by means of a Taylor diagram. The derived patterns of the observed data are in good agreement with formerly defined climate regions. In the final step, anomalies of 10 yearlong averages from 2021 until 2090 were calculated and then spatially classified. The classification revealed four complex regions of changing climate conditions. The derived patterns show large differences in the spatial distribution of future precipitation and climatic water balance changes. In contrast, temperature anomalies are almost independent of these patterns and nearly equally distributed.
The investigation of Ambrosia pollen counts in the air of Sosnowiec was carried out from 1998 to 2010 by means of the volumetric method. The pollen season which was determined by means of the 98% method started at the end of July and the beginning of August and lasted until the end of October. The highest Ambrosia pollen count was recorded in 1999 (222 grains x m-3) and the lowest in 2001 (18 grains x m-3). It was stated that the daily count of pollen grains depended on the wind direction and maximum air temperature. The strongest correlations were found with maximum temperature and with a wind direction from the south east. A high negative correlation coefficient was found between the frequency of inflows of air masses from the west and the annual total of pollen grains and the value of the maximum daily count. The closest sites of Ambrosia L. are at a distance of 25–40 kilometres from the sampling point. Significant correlations with the frequency of inflow of air masses can support the conclusion that Ambrosia pollen grains recorded in Sosnowiec were most probably carried not only from local sources but also, at least in part, from distant places.
The aim of our study was to evaluate the content of organochlorine pesticides (DDTs and HCHs) in the upper layer of arable soils in Poland. 214 soil samples were analyzed for the content of three HCH congeners (α-HCH, β-HCH, and γ-HCH) and three DDT compounds (pp’DDT, pp’DDE, and pp’DDD). The median soil concentration of Σ3DDT was 24.39 μg·kg⁻¹, while for Σ3HCH it was 2.85 μg·kg⁻¹ with the highest contribution of γ-HCH isomer. Polish criteria for agricultural soils not polluted with DDTs are met by half of the samples. In the case of γ-HCH the Polish limit value of 0.5 μg·kg⁻¹ was met in 6.5% of the samples. However, according to the less restrictive systems applied in other countries (Canada, Romania) none of the soil samples create a hazard due to contamination with DDTs, and only 6-11% exhibit too high concentrations of γ- HCH (residues of Lindane). The mean contents of DDTs and γ-HCH in soils from different provinces varied widely with the reverse interdependence of both groups of pesticides. The districts with the highest concentrations of DDT (Podlaskie, Wielkopolskie, and Mazowieckie) were characterized by the lowest mean residues of Lindane. This suggests the long-term effects of the prescriptive state system of distribution of pesticides used in Poland more than 40 years ago.
Species – area (SAR) and species time (STR) relationships describe the increase of species richness with study area and study time and have received much attention among ecologists and are used in different branches of biodiversity research. Unknown sample size effects often hinder a direct comparison of SAR and STR shapes of different taxa and regions. Further, space and time interact during the accumulation of species due to the common sample universe. Here we develop a simple power function scaling model of species richness that integrates space, time, sample size and their interactions. We show that this model is able to precisely describe average species densities and the increase of species richness in a regional metacommunity of a large sample of spiders on Mazurian lake islands (Northern Poland). The model predicts strong area – sample size and time – sample size interactions. Judged from the SAR (z = 0.08) and STR (y = 0.64) slopes it points to only moderate spatial β-diversities but high local temporal species turnover. We suspect that the parameters of many published SARs are strongly influenced by unknown sampling time and sample size effects that make direct comparison difficult.
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