As anuran biodiversity quickly declines, it is important to understand local patterns of anuran occurrence. However, the limitations of traditional sampling methods make anuran biodiversity surveys inadequate. Tropical environments are rich in anuran species, which makes biodiversity measurements more difficult. Therefore, it is important to develop a rapid, inexpensive and nondestructive method to measure anuran biodiversity in tropical environments. We used eDNA metabarcoding to measure anuran diversity at 288 sites in 18 regions of Hainan Island. We also used traditional methods and compared the results with those obtained through the eDNA metabarcoding methods. We detected 9 anuran species by traditional sampling methods. We produced 626 million reads by eDNA metabarcoding and assigned them to 15 anuran species. Therefore, eDNA metabarcoding can be used for rapid and large-scale anuran biodiversity surveys.

Environmental DNA (eDNA) metabarcoding is a powerful method for monitoring aquatic biodiversity and evaluating ecosystem health. In this study, we applied eDNA metabarcoding and a multi-species biotic integrity index (Mt-IBI), constructed by selecting and screening core metrics to capture key ecological responses, to assess the Irtysh River Basin in Xinjiang, China, analyzing samples from 52 sites. The community structure showed high sensitivity to environmental stressors, with dissolved oxygen (DO), total nitrogen (TN), and elevation being key factors, while alien fish richness negatively impacted ecosystem health. These findings highlight the importance of maintaining environmental parameters and controlling invasive species, demonstrating the potential of the Mt-IBI for early detection of ecological degradation and guiding freshwater conservation.

This study investigated the spatial and temporal variations of macrobenthos community structure in the Yuqu River Basin during the dry and wet seasons due to environmental factors. This study quantified the independent and interactive contributions of hydrophysical, hydrochemical, and climatic factors to the community structure through a variance decomposition analysis (VPA). The study findings indicate that during May (the dry season), factors such as water depth, flow velocity, dissolved oxygen, and air temperature exhibit relatively minor fluctuations, rendering the aquatic environment more stable than in the rainy season. This stability is particularly conducive to the maintenance of the macrobenthic community structure and species diversity, which is especially evident in aquatic insects with nesting habits, such as those belonging to the Trichoptera order (including genera like Glossosoma, Glossosomatidae, and Georodes). In contrast, during August (the rainy season), substantial precipitation alters the thermal conditions of the river, increases flow velocity, raises water levels, and introduces a significant influx of organic matter through sedimentation. This distinctive ecological environment fosters unique adaptive strategies among macrobenthic organisms. Notwithstanding a notable decline in species diversity during this particular phase, there is a concurrent increase in the abundance of individual organisms, which is indicative of the populations’ remarkable capacity to swiftly adapt to environmental heterogeneity. Research has demonstrated that macrobenthic communities within the Yuqu River Basin adopt pronounced adaptive tactics that vary significantly between seasons. During the dry season, these macrobenthic fauna rely heavily on the stability of their physical habitat. In stark contrast, they are compelled to navigate and cope with the more intricate and dynamic changes in hydrological and chemical conditions that characterize the rainy season. The presented results uncover the sensitive responsiveness of the macrobenthic fauna to seasonal hydrological and environmental fluctuations in high-altitude river systems and their adaptive strategies under diverse ecological stressors. Arthropods, in particular, exhibit a marked sensitivity to seasonal hydrological and environmental changes. This study delves into the biodiversity of high-altitude river ecosystems, analyzing the ecological environment and the distribution patterns and seasonal variation characteristics of macrobenthic communities. This study aims to examine how diverse seasons and hydroclimatic conditions modulate the composition of macrobenthic assemblages within the tributaries and principal channels of high-altitude river systems, thereby establishing a foundational reference for future water ecosystem assessments in such regions.

Marine protected areas (MPAs) across various countries have contributed to safeguarding coastal and marine environments. Despite these efforts, marine non-native species (NNS) continue to threaten biodiversity and ecosystems, even within MPAs. Currently, there is a lack of comprehensive studies on the inventories, distribution patterns, and effect factors of NNS within MPAs. Here we show a database containing over 15,000 occurrence records of 2714 marine NNS across 16,401 national or regional MPAs worldwide. To identify the primary mechanisms driving the occurrence of NNS, we utilize model selection with proxies representing colonization pressure, environmental variables, and MPA characteristics. Among the environmental predictors analyzed, sea surface temperature emerged as the sole factor strongly associated with NNS richness. Higher sea surface temperatures are linked to increased NNS richness, aligning with global marine biodiversity trends. Furthermore, human activities help species overcome geographical barriers and migration constraints. Consequently, this influences the distribution patterns of marine introduced species and associated environmental factors. As global climate change continues to alter sea temperatures, it is crucial to protect marine regions that are increasingly vulnerable to intense human activities and biological invasions. (c) 2024 Published by Elsevier B.V. on behalf of Chinese Society for Environmental Sciences, Harbin Institute of Technology, Chinese Research Academy of Environmental Sciences. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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.

Artificial reservoirs in arid regions provide unique ecological environments for studying the spatial and functional dynamics of plankton communities under the combined stressors of climate change and anthropogenic activities. This study conducted a systematic investigation of the phytoplankton community structure and its environmental drivers in 17 artificial reservoirs in the Ili region of Xinjiang in August and October 2024. The Ili region is located in the temperate continental arid zone of northwestern China. A total of 209 phytoplankton species were identified, with Bacillariophyta, Chlorophyta, and Cyanobacteria comprising over 92% of the community, indicating an oligarchic dominance pattern. The decoupling between numerical dominance (diatoms) and biomass dominance (cyanobacteria) revealed functional differentiation and ecological complementarity among major taxa. Through multivariate analyses, including Mantel tests, principal component analysis (PCA), and redundancy analysis (RDA), we found that phytoplankton community structures at different ecological levels responded distinctly to environmental gradients. Oxidation-reduction potential (ORP), dissolved oxygen (DO), and mineralization parameters (EC, TDS) were key drivers of morphological operational taxonomic unit (MOTU). In contrast, dominant species (SP) were more responsive to salinity and pH. A seasonal analysis demonstrated significant shifts in correlation structures between summer and autumn, reflecting the regulatory influence of the climate on redox conditions and nutrient solubility. Machine learning using the random forest model effectively identified core taxa (e.g., MOTU1 and SP1) with strong discriminatory power, confirming their potential as bioindicators for water quality assessments and the early warning of ecological shifts. These core taxa exhibited wide spatial distribution and stable dominance, while localized dominant species showed high sensitivity to site-specific environmental conditions. Our findings underscore the need to integrate taxonomic resolution with functional and spatial analyses to reveal ecological response mechanisms in arid-zone reservoirs. This study provides a scientific foundation for environmental monitoring, water resource management, and resilience assessments in climate-sensitive freshwater ecosystems.