Sound knowledge of the local distribution and diversity of freshwater snail intermediate hosts and the factors driving the occurrence and abundance of them is crucial to understanding snail-borne parasitic disease transmission and to setting up effective interventions in endemic areas. In this study, we investigated the freshwater snails, water quality parameters, physical characteristics of habitats, predators and competitors, and human activity variables at 102 sites during December 2018 and August 2019 in Shenzhen and adjacent areas in China. We used decision tree models and canonical correspondence analysis to identify the main environmental and biotic factors affecting the occurrence and abundance of snail species. A total of nine species of snail were collected throughout the study area, with Biomphalaria straminea, Sinotaia quadrata, and Physella acuta being the most predominant species. Our study showed that the most important variables affecting the abundance and occurrence of snail species were the presence of predators and competitors, macrophyte cover, chlorophyll-a, substrate type, river depth, and water velocity. In terms of human activities, snail species occurred more frequently and in larger numbers in water bodies affected by human disturbances, especially for sewage discharge, which may reduce the occurrence and abundance of snail predators and competitors. These findings suggest that proper management of water bodies to reduce water pollution may increase the abundance of snail predators and competitors, and should be considered in integrated snail control strategies in the study area.

This paper presents a study of the terminal settling velocity and drag coefficient of the Oncomelanias with highly irregular shape in the range of particle Reynolds number (10 < R_ep < 600). The movement characteristics of the Oncomelanias with horizontal and slant postures are revealed using image analysis and wavelet analysis. The shape features of Oncomelanias with different dimensions are quantified and formulated. The authors propose a new model for predicting the drag coefficient of the dormant and active Oncomelanias, which is proven to be better than several widely-used formulas. Further, a simple settling velocity model that can predict the terminal velocity of the Oncomelanias fairly with several easy-to-measure parameters is developed. These findings provide a basis for the further improvement for the hydraulic schistosomiasis control project and supply reference for the settling characteristics and drag coefficient of cone-shaped particles.

The stability of wetlands is threatened by the combined effects of global climate change and human activity. In particular, the vegetation cover status of lake wetlands has changed. Here, the change in vegetation cover at the estuary of Poyang Lake was monitored, and its influencing factors are studied to elucidate the dynamic change characteristics of vegetation at the inlet of this lake. Flood and water level changes are two of the main factors affecting the evolution of wetland vegetation at the estuary of Poyang Lake. Therefore, Landsat data from 2000 to 2019 were used to study the spatial and temporal variation in the Normalized Difference Vegetation Index (NDVI) in the vegetation cover area. Theil–Sen Median trend analysis and Mann–Kendall tests were used to study the long-term trend characteristics of NDVI. The response between NDVI and the explanatory variables at the estuary of Poyang Lake was quantified using regression tree analysis to study the regional climate, water level, and flood inundation duration. Results showed the following: (1) Vegetation in a large area of the study area improved significantly from 2000 to 2010 and only slightly from 2010 to 2019, and few areas with slight degradation of vegetation were found. In most of these areas, the vegetation from 2000 to 2010 exhibited a gradual change, from nothing to something, which started around 2004; (2) The main variable that separated the NDVI values was the mean water level in October. When the mean October water level was greater than 14.467 m, the study area was still flooded in October. Thus, the regional value of BestNDVI was approximately 0.3, indicating poor vegetation growth. When the mean water level in October was less than 14.467 m, the elevation of the study area was higher than the water level value, and after the water receded in October, the wetland vegetation exhibited autumn growth in that year. Thus, the vegetation in the study area grew more abundantly. These results could help manage and protect the degraded wetland ecology.