In the long run, swine wastewater can provide benefits to the soil-plant relationship, when its use is planned and the potential environmental impacts are monitored. The objective of this study was to investigate the effects of continuous application of swine wastewater, associated with mineral fertilization, after six years of management in no-tillage and crop rotation (14 production cycles), on the chemical conditions of the soil and the corn crop. The doses of wastewater were 0, 100, 200, 300 m³ ha^-1 during the cycle. The effects of the association between mineral fertilization at sowing and swine wastewater were evaluated simultaneously. Swine wastewater at the dose of 100 m³ ha^-1 promoted availability and absorption of P, K⁺, Mg²⁺ and Zn²⁺ without causing toxicity to plants or damage to the soil, constituting a viable, low-cost alternative of water reuse and fertilization for farmers. The nutrients N, P, K⁺ and B must be complemented with mineral fertilization. Special attention should be directed to the accumulation of Zn²⁺ in the soil along the time of swine wastewater application.

Aquatic ecosystems of urban rivers are contaminated through waste disposal, which poses a public health problem. The objective of this research was to evaluate the quality of water used for recreation and public supply of six rivers in the city of Cascavel - Paraná, including Cascavel, Quati, Bezerra, Antas, Clarito and Amambay. Samples were collected every 4 months in 2017, and their physicochemical and microbiological parameters, as well as resistance profiles of strains of Escherichia coli to antimicrobials distributed by pharmacies of the primary healthcare network, were evaluated. Parameters such as water temperature, turbidity, total nitrogen, total phosphorus, total coliforms and thermotolerant coliforms showed significant differences. The allowed limit for thermotolerant coliforms, which was set by National Environment Council, Resolution 357/2005, was exceeded in all of the six analyzed rivers. It was determined that 48.1% of E. coli strains showed resistance to nine antimicrobial tested. The highest levels of resistance were found for ampicillin (27.7%), tetracycline (27.7%) and amoxicillin (24.0%). The results of this study contribute to the understanding of the hazards associated with the contamination of springs in urban centers with wastewater containing resistant bacteria. Therefore, recovery work is necessary in these areas because of the importance of these water sources for the entire western region of Paraná state.

Associating anthropogenic effects with variations in biodiversity is key to understanding how anthropogenic impacts are extrapolated in public supply micro-watersheds. The structure and dynamics of metacommunities in aquatic environments depend not only on the river network itself, but on a multitude of factors. Therefore, we associate the density and species richness of diatoms, assessed in a micro-watershed, with the following driver factors: local environmental variables, spatial variables, landscape characteristics, and the historical community, comparing their possible dispersal routes. Variance partitioning was performed using partial RDA models, with prior selection of predictor variables, to estimate the relative role of each predictor in the diatom community. The small scale of the micro-watershed resulted in a small spatial gradient, reflecting in the low variation in community richness across sampling stations. However, temporal heterogeneity associated with fluctuating precipitation throughout the year may cause temporal variation in the relative abundance of species. This pattern is a result of the supply of resources that increases biodiversity over time, as it allows the coexistence of species that alternate between dominance and persistence. Thus, even on a small scale and during one year of sampling, we demonstrated that predictors of different natures act together to explain diatom communities in micro-watersheds.

This study evaluates the long-term effects of swine wastewater (SWW) on relevant parameters for soil fertility, including calcium (Ca), magnesium (Mg), potassium (K) cations, cation exchange capacity (CEC), and organic matter (OM) in an agricultural area with 9 years of crop cultivation. Three types of SWW (raw, after leaving the biodigester, and after the manure plant) were analyzed with four application rates of SWW (0, 100, 200, and 300 m³.ha⁻¹), associated or not with mineral fertilization, resulting in eight treatments. The study found that the long-term use of SWW had significant effects on soil parameters. Principal component analysis (PCA) was used to summarize the data. The soil’s calcium (Ca), magnesium (Mg), and cation exchange capacity (CEC) levels were higher in soybean compared to other crops and natural soil. Similarly, the treatment with 0 m³.ha⁻¹ of pig manure and without mineral fertilization showed higher levels of these nutrients. In contrast, potassium (K) was found in greater quantities in oats, SWW from the biodigester, higher doses of manure, and with mineral fertilization. The crops had a higher organic matter (OM) content compared to the natural soil, with corn and raw SWW showing the most significant increase.

Quantitative structure–property relationship (QSPR) modelling has been used in many scientific fields. This approach has been extensively applied in environmental research to predict physicochemical properties of compounds with potential environmental impact. The soil sorption coefficient is an important parameter for the evaluation of environmental risks, and it helps to determine the final fate of substances in the environment. In the last few years, different QSPR models have been developed for the determination of the sorption coefficient. In this study, several QSPR models were generated and evaluated for the prediction of log K_oc from the relationship with log P. These models were obtained from an extensive and diverse training set (n = 639) and from subsets of this initial set (i.e. halves, fourths and eighths). The aim of this study was to investigate whether the size of the training set affects the statistical quality of the obtained models. Furthermore, statistical equivalence was verified between the models obtained from smaller sets and the model obtained from the total training set. The results confirmed the equivalence between the models, thus indicating the possibility of using smaller training sets without compromising the statistical quality and predictive capability, as long as most chemical classes in the test set are represented in the training set.