Plant communities and their environments are a vital part of synecology research. In this study, we investigated the characteristics of three typical medicinal perennial herbs, Glycyrrhiza uralensis, Rheum altaicum, and Ferula sinkiangensis, and examined their response to local soil properties in Altay Prefecture, China. A total of 29 species belonging to 15 families and 25 genera were recorded. In terms of the target medicinal plants, the importance value was low and community structures were exceedingly simple. Quantitative classification based on WARD cluster analysis suggested that each medicinal plant can be classified into one of three types: annual herbaceous, perennial herbaceous, and subshrub or shrub. Interestingly, the plants gradually transformed from exhibiting nonresistance to xerophytes or halophytes. An investigation of the soil properties beneath the medicinal plants showed that nutrients in black soil were much more abundant than those in sandy and saline soil. Except for leaching phenomenon, the nutrient contents in the soil surface layer (0–10 cm) were higher than those in deep layers (10–20 cm and 20–40 cm), and to some extent, the nutrient contents were inversely proportional to the depth of the soil. The redundancy analysis (RDA) results of the medicinal plants and their relationship with soil properties indicated that the main soil variables impacting the distribution of G. uralensis were available potassium (AK), aspect (ASP), soil moisture (SM), total nitrogen (TN), and total phosphorus (TP); SM, electric conductivity (EC), elevation (ELE), ASP, pH value (pH), available nitrogen (AN), soil organic content (SOC), and the carbon/nitrogen (C/N) ratio had positive effects on the distribution of R. altaicum. F. sinkiangensis grew better in habitats with high contents of SM, EC, TN, AN, available phosphorus (AP), total potassium (TK), and AK. This study aimed at providing effective suggestions for artificial cultivation, conservation, and resilience of Chinese medicinal plants.

Most rivers worldwide are highly regulated by anthropogenic activities through flow regulation and water pollution. Environmental flow regulation is used to reduce the effects of anthropogenic activities on aquatic ecosystems. Formulating flow alteration–ecological response relationships is a key factor in environmental flow assessment. Traditional environmental flow models are characterized by natural relationships between flow regimes and ecosystem factors. However, food webs are often altered from natural states, which disturb environmental flow assessment in such ecosystems. In ecosystems deteriorated by heavy anthropogenic activities, the effects of environmental flow regulation on species are difficult to assess with current modeling approaches. Environmental flow management compels the development of tools that link flow regimes and food webs in an ecosystem. Food web approaches are more suitable for the task because they are more adaptive for disordered multiple species in a food web deteriorated by anthropogenic activities. This paper presents a global method of environmental flow assessment in deteriorated aquatic ecosystems. Linkages between flow regimes and food web dynamics are modeled by incorporating multiple species into an ecosystem to explore ecosystem-based environmental flow management. The approach allows scientists and water resources managers to analyze environmental flows in deteriorated ecosystems in an ecosystem-based way.

Conserving aquatic ecosystems requires efficient tools to accurately assess the biodiversity of aquatic species. However, existing knowledge is insufficient in terms of the reliability and the comparability of methods measuring fish diversity. Environmental DNA (eDNA), as a promising method, was used to detect fish taxa in this study. We optimized the eDNA method in the laboratory, and applied the optimal eDNA method to survey fish diversity in a natural aquatic life reserve. We simulated necessary steps of the eDNA method in the lab to increase the confidence of the field survey. Specifically, we compared different eDNA sampling, extraction, and sequencing strategies for accurately capturing fish species of the target area. We found that 1L water samples were sufficient for sampling eDNA information of the majority taxa. The filtration was more effective than the centrifugal precipitation for the eDNA extraction. The cloning sequencing was better than the high-throughput sequencing. The field survey showed that the Shannon–Wiener diversity index of fish taxa was the highest in Huairou Reservoir. The diversity index also showed seasonal changes. The accuracy rate of detecting fish taxa was positively correlated with the eDNA concentration. This study provides a scientific reference for an application of the eDNA method in terms of surveying and estimating the biodiversity of aquatic species.

Various disturbances like extreme climate events, fires, and insect outbreak severely impact forest ecosystems, and differences are expected between planted and natural forests. However, there is little information on the spatio-temporal dynamics of the disturbances in terms of both forest types. In this study, we used the LandTrendr algorithm to detect disturbances in planted and natural forests in a temperate region of Northern China from 1985 to 2020 using Landsat and Sentinel 2 satellite data. The planted and natural forests suffered severe disturbances in 1994 in the south (park establishment) and in 2012 in the north (severe drought). More than one third of the area of planted (37.5%) or natural (35.8%) forests was highly disturbed. The duration of forest disturbances was mostly 1 to 3 years in terms of planted or natural forests. The NDVI anomaly of the planted forests decreased from 0.24 to −0.08 after drought events, while the reduction was from 0.22 to −0.06 for natural forests. Afterwards, the NDVI anomaly of the planted forests showed a slow upward variation but not for the natural forests. This study allows us to evaluate the response of various forest types to disturbance regimes.