We describe large-scale patterns of terrestrial mammal distribution in China by using geographical information system (GIS) spatial analysis. Mammal taxa, examined by species, family, and order, were binned into 10 km × 10 km grids to explore the relationship between their spatial distribution and geographical factors potentially affecting the same. The spatial pattern of species richness revealed four agglomerations: high richness in the south, low in north, and two low richness areas in eastern and western China. Species richness patterns in Carnivora was the most similar to overall terrestrial mammals’ richness; however, species richness in different orders exhibited distributions distinct from the overall pattern. We found a negative relationship between richness and latitude gradient. Species richness was most strongly correlated with forested ecosystems, and was found to be higher at an elevation of 2000~2200 m, with greater altitudinal variation indicative of higher species richness.

To address the development of rural basic public services (RBPS) among contiguous destitute areas of China, we develop a comprehensive RBPS evaluation methodology to examine RBPS development level of 728 poverty-stricken counties, using geographical information system (GIS) to describe their multiscale and multidimensional spatiotemporal change during 2010–2012; besides, we also try to reveal how RBPS interacts with county economy (CE) by integrating Tapio model and weighted Voronoi circle-layer structure. Our results show that (1) at a multiscale of area–province–county, in spite of the overall low level, RBPS is steadily growing during 2010–2012, along with a positive spatial autocorrelation and an obvious nonequilibrium that is high in east China but low in west; however, the RBPS gaps among the whole counties are gradually narrowing, shifting their development grades from a mostly relative shortage or relatively severe shortage in 2010 to a main state of relatively richness or relatively equilibrium in 2012, (2) from a multidimensional view, the RBPS gaps among most dimensions of different areas are gradually narrowing, except for the dimension of social public safety service that shows a significant regional differentiation among different areas. RBPS in Tibetan areas is the most unequalled and falls into the most obvious heterogeneity, and (3) there exist weak correlations between county-level original RBPS and original CE for each year and each circle layer, while significantly positive correlation is found only between mean RBPS and mean CE for four circle-layer subsets of counties, respectively; overall, RBPS development level lags behind that of CE as a main result of the weak decoupling between them. This study may provide a good understanding of the status, regional differences, and evolution of RBPS in poverty-stricken rural China, and serves as a scientific reference regarding decision-making in both promoting intrarural antipoverty harmonious development and constructing the new countryside of China.

The survival and distribution of animals cannot be separated from a certain environment. How patterns in mammalian species depend on the environment remain unclear. This study incorporating spatial data on climate, precipitation, topography, and vegetation quantitatively analyzed the influence of specific geographical factors on the spatial distribution of terrestrial mammalian richness using the Geodetector model. We used the spatial analysis method of geographical information systems (GIS), separating the mammalian distribution of 621 species into 10 by 10 km grids to measure spatial richness. Our results showed that there were significant spatial differences in terrestrial mammalian richness in China. There was a low richness in the east and west, but high richness in the south. Individual factor detection results showed that annual precipitation (AP) and the minimum temperature of the coldest month (MTCM) were the dominant factors affecting the spatial pattern of mammal richness in China. Patterns in the distribution of species richness had distinct characteristics for different mammalian orders and were influenced by different environmental factors. The richness distribution of most orders was mainly affected by MTCM and AP. Interactive detection results showed that interacting factors in pairs play much bigger roles in the spatial distribution of species richness than individual factors. The synergistic effect of elevation with AP and MTCM best explained the distribution differences of species richness. We found that the Geodetector model is a valuable tool, hoping to be more widely used in biogeography.

The rapid pace of development in western China has brought about inevitable concerns for environmental conditions and their management. The Sanjiangyuan National Park strives to address concerns for sustainable water resources management and biodiversity management, especially for the protection of endangered flora and fauna. In this study, a machine learning model (MaxEnt) was used to predict the human activity intensity and its effects on species in Sanjiangyuan protected by the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES). The model used human settlements as input and datasets such as terrain factors, climate, and artificial structures as environmental factors. The results showed that human activity intensity was significantly different between the East and the West. The area with the highest human activity intensity was Yushu County in the south area, and Xinghai-Zeku County in the east. By comparing the mammal richness with human activity intensity, we found human–wildlife coexistence in Sanjiangyuan. A detailed analysis on the CITES protected species showed that many important species, such as snow leopards, red pandas, and small Indian civets, occupied areas with high human activity intensity. The national park protects 3/4 CITES species with 1/3 in the area of the Sanjiangyuan region, owing to the relatively low human activity intensity.