Little is known about how changes in the biodiversity and functional traits of macroinvertebrates in rivers respond to the responses of anthropic pressures and their driving factors. Macroinvertebrates were sampled at 17 sites in the Irtysh River Basin and classified macroinvertebrates into 10 traits and 38 categories between May and August 2022. Then, we performed R-mode linked to Q-mode (RLQ) analysis and calculated functional richness, evenness, divergence, and Rao’s quadratic entropy (RaoQ) for each site and community-weighted means for each trait category. Our results indicated that there were pronounced alterations in species variability in the urban region. Functional divergence indicated fierce competition among species and considerable niche overlap in the urban region. Functional evenness indicated that species abundance distribution and interspecific functional distance were not uniform in the urban region. Functional richness indicated that the urban region was the strongest region in terms of niche occupation, resource utilization, and buffering capacity for environmental fluctuations. Rao’s quadratic entropy showed that the trait difference of macroinvertebrates was the largest in all regions, which was caused by the gradient environmental difference. Research has revealed that urbanization significantly influences the evolutionary trajectory of macroinvertebrate fauna, culminating in an upsurge in pollution-tolerant species and a convergence of functional traits. We recommend strengthening the control of urban and industrial pollution and wise planning and management of land and water resources to mitigate the impact of anthropogenic destruction on habitat fragmentation in the Irtysh River Basin.

In this study, we investigated how changes in salinity affect biodiversity and function in 11 typical water bodies in the Altai region. The salinity of the freshwater bodies ranged from 0 to 5, the brackish water salinities ranged from 5 to 20, and the hypersaline environments had salinities > 20. We identified 11 orders, 34 families, and 55 genera in 3061 benthic samples and classified them into 10 traits and 32 categories. Subsequently, we conducted Mantel tests and canonical correlation analysis (CCA) and calculated biodiversity and functional diversity indices for each sampling site. The results indicated that biodiversity and the proportion of functional traits were greater in freshwater environments than in saline environments and decreased gradually with increasing salinity. Noticeable shifts in species distribution were observed in high-salinity environments and were accompanied by specific functional traits such as swimming ability, smaller body sizes, and air-breathing adaptations. The diversity indices revealed that the species were more evenly distributed in high-diversity environments under the influence of salinity. In contrast, in high-salinity environments, only a few species dominated. The results suggested that increasing salinity accelerated the evolution of benthic communities, leading to reduced species diversity and functional homogenization. We recommend enhancing the monitoring of saline water resources and implementing sustainable water resource management to mitigate the impact of salinity stress on aquatic communities in response to climate-induced soil and water salinization.

The Yellow River is the second largest river in China and it supports a rich biodiversity and numerous endemic fish species (Atrilinea macrolepis, Brachymystax lenok tsinlingensis, and Hucho taimen). It is one of China’s most important freshwater aquaculture and mariculture regions, and many non-native species have been introduced into the region. This study provided the Yellow River Basin’s first and current list of non-native aquatic species including a total of 112 species comprised of 59 fishes, 27 aquatic plants, 21 Mollusca, three reptiles, one crustacean and one amphibian. The primary introduction pathway is aquaculture (69 species), followed by the aquarium and ornamental trade (30 species), forage (four species), unintentional introductions (four species), ecological restoration (two species), religious releases (two species), and one species for biocontrol. Asia is the primary geographic origin of non-native species (39 species), followed by North America (33 species), South America (16 species), Europe (10 species), Africa (nine species) and Oceania (five species). Many non-native species have become important species in local aquaculture, the aquarium and ornamental trade or for other human uses. Many non-native species have caused significant negative economic, ecological and societal impacts. More research, field investigations and new guiding policies should be applied for the effective control and management of non-native species in the Yellow River Basin.

Artificial water bodies in Central Asia offer unique environments in which to study plankton diversity influenced by topographic barriers. However, the complexity of these ecosystems and limited comprehensive studies in the region challenge our understanding. In this study, we systematically investigated the water environment parameters and phytoplankton community structure by surveying 14 artificial waters on the southern side of the Altai Mountains and the northern and southern sides of the Tianshan Mountains in the Xinjiang region. The survey covered physical and nutrient indicators, and the results showed noticeable spatial differences between waters in different regions. The temperature, dissolved oxygen, total nitrogen, and total phosphorus of artificial water in the southern Altai Mountains vary greatly. In contrast, the waters in the northern Tianshan Mountains have more consistent physical indicators. The results of phytoplankton identification showed that the phytoplankton communities in different regions are somewhat different, with diatom species being the dominant taxon. The cluster analysis and the non-metric multidimensional scaling (NMDS) results also confirmed the variability of the phytoplankton communities in the areas. The variance partitioning analysis (VPA) results showed that climatic and environmental factors can explain some of the variability of the observed data. Nevertheless, the residual values indicated the presence of other unmeasured factors or the influence of stochasticity. This study provides a scientific basis for regional water resource management and environmental protection.

In this study, the composition and structure of the macrobenthic community in the Ulungu River Basin was investigated and the water quality status of the basin was evaluated. In May and August 2022, and October 2023, the macrobenthic and water environmental factors at 11 sample sites in the basin were investigated, and the water quality of the basin was evaluated by the Shannon–Wiener index, FBI, and BMWP index. A total of 6101 macrobenthic organisms were collected; these organisms belonged to 3 phyla, 7 classes, 14 orders, 57 families, and 117 genera. Arthropod species accounted for the largest number of species (87.9%). A total of nine dominant species were found: Micronecta sp., Eukiefferiella sp., Baetis sp., Polypedilum sp., Saetheria sp., Ephemerella sp., Limnodrilus sp., Ephemera sp., and Hydropsyche sp. At the temporal level, the average density and biomass of macrobenthos were in the order of August > October > May; at the spatial level, the average density was greater in the tributaries than in the main stream, and the average biomass was greater in the main stream than in the tributaries. The mean values of the Shannon—Wiener index and Margalef richness index were as follows: August > October > May at the temporal level; the mean values of the Pielou evenness index were as follows: May > October > August at the temporal level. At the spatial level, the overall mean value of each diversity index indicated that the tributaries had larger diversity indices than the main stream. The water quality evaluation results revealed that the overall water quality level of the Ulungu River Basin ranges from light pollution to poor quality. Human interference activities greatly impact the water quality of the basin. To restore the ecology of the basin, it is necessary to strengthen the management and control of pollution sources.