Intestinal parasites affect the health of birds and pose a risk of transmitting diseases. This study utilized fecal examination to assess the occurrence of intestinal parasites in two captive waterbird species, revealing a high infection rate and a diverse range of parasite groups. Nematodes were found to be the most common intestinal parasite species in two duck species, Common teal (Anas. crecca) and Bailkal teal (Sibirionetta formosa). A total of 96 fecal samples were collected and analyzed using the modified floating and sedimentary McMaster technique, revealing an overall infection rate of 78.13% (75/96), with 42.67% (35/72) being single infections and 57.33% (43/75) mixed infections. Nematodes were the most prevalent with an infection rate of 66.67% (64/96), followed by protozoa (34.48%), trematode (14.42%), and cestode (5.21%). Three nematode species were identified in both ducks, including Cappillaria spp., Strongyloides spp., and Ascaris spp. The mean egg per gram (EPG) of Strongyloides spp. was highest in Common teal while Baikal teal had a higher mean EPG of Cappillaria spp. Duck species, genders and seasons were observed as factors, result showed a significant difference in occurrence rate and mean OPG/EPG between males and females in both duck species, and a higher occurrence during the summer than in the autumn and winter seasons. The high occurrence of intestinal parasites in these two dabbling ducks, particularly nematode species, may reflect the health status of waterbirds in captive. The results are important for understanding the status of intestinal parasites and assessing the risk of epidemics.

Species distribution patterns are essential for the conservation of biodiversity. The aim of this study was to evaluate the influence of multiple ecological hypotheses on the spatial patterns of rodent species richness in China. First, we divided the geographic region of China into 80 × 80 km2 grid cells and mapped the distribution ranges of the 237 rodent species. Rodent taxa were separated into three response variables based on their distribution: (a) all species, (b) non-endemic species, and (c) endemic species. The predictors were divided into four factor sets: (a) energy-water, (b) climatic seasonality, (c) habitat heterogeneity, and (d) human factors, which were used to represent four different ecological hypotheses. We then performed multiple regression analysis (OLS), spatial autoregressive models (SAR), and variation partitioning analyses to determine the effects of predictors on the spatial patterns of rodent species. The Hengduan Mountains and surrounding mountains in southwest China showed the highest species richness and endemism. Habitat heterogeneity is the most important factor explaining the species richness distribution patterns across all species and non-endemic species. Endemic species richness patterns are most susceptible to seasonal changes in climate and least affected by human factors. The effects of energy and water on the three response variables showed consistent levels of importance.