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Species distribution models need adequate sets of data, particularly in the case of range‐restricted species. The problem faced in the modeling of rare species is twofold: a small sample size and the occurrence of sampling biases. The present analysis combines spatial‐ and habitat‐thinning approaches to improve maximum entropy models based on geographically incomplete data of relict and subendemic Festuca amethystinaL. grass on Polish territory. The results show that models based on strongly incomplete historic data did not predict the occurrence of all important areas where the species was found in the following decades. However, the introduction of species‐specific thinning allows for more precise prediction of the species range, i.e., the detection of suitable areas on a more local scale. The introduction of habitat thinning caused the diversity of important predictors in model to increase, but spatial thinning decreased the number of significant predictors and made interpretation easier. Additionally, a combination of thinning techniques allowed significant improvements to be made to the model predictions after the experimental addition of a lower number of localities to regions which had previously been poorly recognized. It can be concluded that in the case of incomplete data, the above corrections allow the true range of the species to be predicted after the discovery of a lower number and relatively dispersed new localities. Habitat and spatial thinning were applied to the modeling of the environmental niche of the species and the distribution of suitable areas from incomplete dataMore precise prediction has been achieved; however, models based on very incomplete data did not predict the occurrence of all important areas of the speciesCorrections allow to more realistic predictions after the addition of a lower number and relatively dispersed new localities

Persistent organic pollutants such as polychlorinated dibenzo‐p‐dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs) are environmental contaminants that have widespread distribution and pose a serious threat to aquatic ecosystems. We conducted a study to quantify the distribution, patterns, and transport of PCDDs and PCDFs along the Pilica River in central Poland under different hydrological conditions to estimate the loads of these compounds and understand their fate in aquatic systems. Water samples were collected at five sampling points along the river that represent a range of hydrological conditions including flooding and stable and low water flows. Reduced river water flow was associated with lower average total and toxic equivalent (TEQ) concentrations of PCDDs plus PCDFs: 33.6 pg L−1and 4.21 pg TEQ L−1for flooding; 28.3 pg L−1and 3.6 pg TEQ L−1for stable flow; 18.4 pg L−1and 1.0 pg TEQ L−1for low‐water flow. Similar results were observed for daily loadings of total and TEQ concentrations: the highest values were observed during flooding (331.1–839.4 mg d−1and 27.8–110.7 mg TEQ d−1), medium under stable hydrological conditions (55.8–121.0 mg d−1and 7.7–15.3 mg TEQ d−1), and the lowest values during low water flow (30.9 and 40.3 mg d−1and 1.4–2.4 mg TEQ d−1). The results demonstrate that diffuse sources of pollution play a key role during periods of high water flow (i.e., flooding season), whereas point sources of pollution, including municipal and industrial wastewater treatment plant discharges, mainly determine the PCDD and PCDF concentrations seen during low water periods.

In this paper, the Pilica River catchment (central Poland) is analyzed with a focus on understanding the total phosphorous transfer along the river system which also contains the large artificial Sulejów Reservoir. The paper presents a GIS method for estimating the total phosphorous (TP) load from proxy data representing sub-catchment land use and census data. The modelled load of TP is compared to the actual transfer of TP in the Pilica River system. The results shows that the metrics of connectivity between river system and dwelling areas as well as settlement density in the sub-catchments are useful predictors of the total phosphorous load. The presence of a large reservoir in the middle course of the river can disrupt nutrient transport along a river continuum by trapping and retaining suspended sediment and its associated TP load. Analysis of the indirect estimation of TP loads with the GIS analysis can be useful for identifying beneficial reservoir locations in a catchment. The study has shown that the Sulejów Reservoir has been located in a subcatchment with a largest load of the TP, and this feature helps determine the problem of reservoir eutrphication