[Influence of Land Use Structure and Spatial Pattern on Water Quality of Small and Medium-sized Rivers in Poyang Lake Basin].

To reveal the influence mechanism of land use structure and spatial pattern on water quality of small and medium-sized rivers, water samples were collected from 25 sampling points in three small and medium-sized rivers of the Poyang Lake Basin in January 2022 and July 2022. Bioenv analysis, the Mantel test, and variance partitioning analysis were used to quantify the effects of land use structure and spatial patterns on water quality at different spatial scales; generalized additive models were used to fit the relationship between water quality and different land use structures and spatial patterns; and a generalized linear model was used to construct segmented regression models and calculate the thresholds based on the stepwise recursive method. The results showed that:① the average interpretation rate of land use structure and spatial pattern on river water quality was 59.72% during the wet period and 48.95% during the dry period. The sub-basin and riparian 100 m scales were the key scales of land use structure and spatial pattern affecting water quality in small and medium-sized rivers, with an average explanation rate of 54.70% and 64.88%, respectively. The joint explanation of land use structure and spatial pattern was an important factor driving the change in river water quality, accounting for 66.90% of the total explanation. ② The impact of land use structure on the water quality of small and medium-sized rivers had a significant threshold effect. When the proportion of construction land was less than 2%, farmland was less than 8%, or forest land was more than 82% at the sub-basin scale and the proportion of construction land was less than 12%, farmland was less than 41%, or forest land was more than 49% at the riparian buffer scale, all could significantly improve water quality. ③ The effect of spatial pattern on water quality in small and medium-sized rivers also had a threshold effect but was weaker than that of land use structure. A patch shape value more than 28.77 or patch diversity more than 0.69 at the sub-basin scale and a patch shape value more than 2.99 or patch diversity more than 1.02 at the riparian buffer scale could improve water quality. The above results showed that strengthening the management of land use at the sub-basin and riparian 100 m scales and setting a reasonable threshold of land use structure and spatial pattern can effectively prevent water quality from deteriorating.

Spatial-temporal heterogeneity and driving factors of PM2.5 in China: A natural and socioeconomic perspective.

Background: Fine particulate matter (PM2.5), one of the major atmospheric pollutants, has a significant impact on human health. However, the determinant power of natural and socioeconomic factors on the spatial-temporal variation of PM2.5 pollution is controversial in China. Methods: In this study, we explored spatial-temporal characteristics and driving factors of PM2.5 through 252 prefecture-level cities in China from 2015 to 2019, based on the spatial autocorrelation and geographically and temporally weighted regression model (GTWR). Results: PM2.5 concentrations showed a significant downward trend, with a decline rate of 3.58 µg m-3 a-1, and a 26.49% decrease in 2019 compared to 2015, Eastern and Central China were the two regions with the highest PM2.5 concentrations. The driving force of socioeconomic factors on PM2.5 concentrations was slightly higher than that of natural factors. Population density had a positive significant driving effect on PM2.5 concentrations, and precipitation was the negative main driving factor. The two main driving factors (population density and precipitation) showed that the driving capability in northern region was stronger than that in southern China. North China and Central China were the regions of largest decline, and the reason for the PM2.5 decline might be the transition from a high environmental pollution-based industrial economy to a resource-clean high-tech economy since the implementation the Air Pollution Prevention and Control Action Plan in 2013. Conclusion: We need to fully consider the coordinated development of population size and local environmental carrying capacity in terms of control of PM2.5 concentrations in the future. This research is helpful for policy-makers to understand the distribution characteristics of PM2.5 emission and put forward effective policy to alleviate haze pollution.

Anthropogenic Intensity-Determined Assembly and Network Stability of Bacterioplankton Communities in the Le'an River.

Bacterioplankton are essential components of riverine ecosystems. However, the mechanisms (deterministic or stochastic processes) and co-occurrence networks by which these communities respond to anthropogenic disturbances are not well understood. Here, we integrated niche-neutrality dynamic balancing and co-occurrence network analysis to investigate the dispersal dynamics of bacterioplankton communities along human activity intensity gradients. Results showed that the lower reaches (where intensity of human activity is high) had an increased composition of bacterioplankton communities which induced strong increases in bacterioplankton diversity. Human activity intensity changes influenced bacterioplankton community assembly via regulation of the deterministic-stochastic balance, with deterministic processes more important as human activity increases. Bacterioplankton molecular ecological network stability and robustness were higher on average in the upper reaches (where there is lower intensity of human activity), but a human activity intensity increase of about 10%/10% can reduce co-occurrence network stability of bacterioplankton communities by an average of 0.62%/0.42% in the dry and wet season, respectively. In addition, water chemistry (especially NO3 --N and Cl-) contributed more to explaining community assembly (especially the composition) than geographic distance and land use in the dry season, while the bacterioplankton community (especially the bacterioplankton network) was more influenced by distance (especially the length of rivers and dendritic streams) and land use (especially forest regions) in the wet season. Our research provides a new perspective of community assembly in rivers and important insights into future research on environmental monitoring and classified management of aquatic ecosystems under the influence of human activity.