环境•农林最新文献

Energy production may lead to soil contamination. This study uses a combined approach to understand the environmental effect of fly ashes resulting from the activity of two thermal power stations (Siekierki and Żerań TPSs). Therefore, the metal(loid)s content and mobility of these elements in soils were evaluated. Furthermore, the effect of root exudates on two types of fly ashes (KKSL-fly ash from conventional coal combustion and KFZL-fly ash from fluidal coal combustion) was studied based on experiments of fly ashes with Artificial Root Exudates (AREs). The study shows that the studied soils are not contaminated according to Polish law. For example, the Cd, Cu, Pb, and Zn content in soils around the Siekierki TPS was up to 0.53, 30.3, 58.8, 138 mg kg^-1, respectively. The Cd, Cu, Pb, and Zn content in soils around the Żerań TPS was up to 1.24, 28.4, 131, and 374 mg kg^-1, respectively. Among investigated elements, the Cu, Cd, and Mn revealed the highest mobility in studied soils (up to 87.4% of Cu in soils around the Żerań TPS), which is controlled by many factors, i.e., Fe,Mn,Al-oxides and pH. The experiment simulating fly ashes weathering demonstrated that ashes are more prone to dissolution when exposed to root exudates relative to H₂O of the corresponding pH. The significant finding is that the KKSL is more susceptible to dissolution with AREs compared to the KFZL, probably due to the glass dissolution in the former one. Therefore, this study may contribute to developing remediation strategies for ash dumps.

Four main classes of introns (group I, group II, spliceosomal, and archaeal) have been reported for all major types of RNA from nuclei and organelles of a wide range of taxa. When and how introns inserted within the genic regions of genomes, however, is often unclear. Introns were examined from Archaea, Bacteria, and Eukarya. Up to 80 bp surrounding each of the 5' and 3' intron/exon borders were compared to search for direct repeats (DRs). For each of the 213 introns examined, DNA sequence analysis revealed DRs at or near the intron/exon borders, ranging from 4 to 30 bp in length, with a mean of 11.4 bp. More than 80% of the repeats were within 10 bp of the intron/exon borders. The numbers of DRs 6–30 bp in length were greater than expected by chance. When a DNA segment moves into a new genomic location, the insertion involves a double-strand DNA break that must be repaired to maintain genome stability and often results in a pair of DRs that now flank the insert. This insertion process applies to both mobile genetic elements (MGEs), such as transposons, and to introns as reported here. The DNA break at the insertion site may be caused by transposon-like events or recombination. Thus, introns and transposons appear to be members of a group of parasitic MGEs that secondarily may benefit their host cell and have expanded greatly in eukaryotes from their prokaryotic ancestors.

Many butterfly species are conspicuous flower visitors. However, understanding their flower visitation patterns in natural habitats remains challenging due to the difficulty of tracking individual butterflies. Therefore, we aimed at establishing a protocol to solve the problem using the Common five-ring butterfly, Ypthima argus (Nymphalidae: Satyrinae). Focusing on the pollen grains attached the butterfly’s body surface, we examined validities of two pollen analyses based on pollen morphology and DNA markers (ITS1 and ITS2), in addition to the classical route census method. We captured thirty-nine butterflies from mid-April to early July and collected pollen grains from each individual. Morphological and DNA analyses of collected pollens identified eighteen and thirty-four taxa of insect pollinated plants respectively, including woody plants such as Castanopsis. The DNA analysis detected as many as thirteen plant taxa from a single butterfly, indicating its high sensitivity for detecting flower visitation. We detected more plant taxa in May when many individuals were flying. This is assumingly related to the post emergence days of the butterflies with more foraging experience. We also found that fluctuations of pollen grain numbers of Leucanthemum vulgare and Erigeron philadelphicus on individual butterflies depend on their flowering periods overlapping partly. Consequently, we conclude that pollen morphology and DNA barcoding analysis, and field observations are mutually complementary techniques, providing an integrated pollen analysis method to study the pollination ecology of butterflies.

Monitoring and predicting the environmental quality of watersheds is essential for understanding and managing water pollution. Current prediction models often suffer from limitations, including the need for excessive information, complex architectures, and extensive computational resources. To address these challenges, this paper proposes a water pollution prediction system using artificial neural network trained by the back-propagation algorithm with a 2–6-2 structure. The model was developed using chemical oxygen demand and NH₄⁺ concentration data collected from the catchment areas of Kaihua and Anji counties in Zhejiang Province between November 2020 and October 2021. The average relative errors of the neural network training for chemical oxygen demand and NH₄⁺ were -4.59% and -2.65%, the correlation coefficients were 100% and 98%, and the root-mean-square errors were 7.83% and 0.14%, which confirmed the effectiveness of the back-propagation neural network training. The average relative errors between the predicted and observed values of chemical oxygen demand and NH₄⁺ by the neural network were -4.46% and 2.34%, respectively, with correlation coefficients of 100% and 88%, coefficient of determination of 0.94, and root-mean-square errors of 7.72% and 0.11%, which indicated that the predicted values of the back-propagation neural network on the quality of the water were highly significant correlated with the measured values. This study highlights the potential of artificial neural network models to offer efficient, accurate, and computationally streamlined solutions for water pollution monitoring.