Habitat quality (HQ) is of great significance to regional sustainable development, which is a key link for regional ecological security and human welfare. Assessing the temporal and spatial evolution of HQ caused by land-use change could provide a scientific basis for regional ecological protection and land management. Here, based on the ArcGIS platform and the InVEST model, this study quantified the spatial and temporal evolutions of land use, landscape patterns, and HQ from 1985 to 2015, in Taihu Lake Basin (TLB). Hotspot analysis tools were used to identify the spatial agglomeration and evolution characteristics of HQ in TLB. The results showed that, (1) the land use and landscape pattern in TLB experienced dramatic change process during 1985–2015, with the dominating conversion being from farmland to construction land, which led to an increase in landscape heterogeneity and fragmentation. (2) The HQ was generally reduced in the past 30 years. In particular, the decline of HQ was extremely severe in the peripheral area of cities and roads, due to urban sprawl. (3) Regarding the spatial distribution of HQ, the northern and eastern areas were generally higher, while the western and southern areas were generally lower. The hotspots areas were mainly located in the southwestern mountain area and west-central lake area, while the cold spots areas were mainly located in urban areas in the north and the east. (4) The area and degree of habitat degradation were both increased significantly due to land-use change, and the degradation of the Taihu Lake was highlighted. Strengthening the ecological environment management and reducing the threat of urban expansion to the HQ is urgently required. This study could help understand HQ of the TLB and provide a scientific basis for decision-makers.

Due to the indivisibility of agricultural machinery in production, limited farm sizes have reduced mechanization efficiency and increased the cost of grain production in China. As a result, the development of a moderate-scale farming system has been proposed by academic communities and policy makers. However, it is still hotly debated how to determine a moderate farm scale. We offer a new perspective on the costs of machinery services. This manuscript employs the threshold model and uses the nationally representative data from the 2015 China Rural Household Panel Survey (CRHPS) to investigate the role of farm size expansion relative to per area machinery services expenditures (PAMSE). The empirical results reveal that there is a nonlinear relation between the farm size and PAMSE. Specifically, farm size expansion can reduce the PAMSE by improving mechanization efficiency in all cases, while the magnitude of cost-saving is progressively reduced in the process of farm scale expansion. In particular, a 1 mu (1 mu = 1/15 ha) increase in the farm scale could only lead to a 0.3% decrease in the PAMSE when the farm size exceeded 50 mu, which indicates that 50 mu is a minimum efficient farm scale to achieve most economies of scale. Therefore, we suggest that persistent efforts should be devoted to improving farmland circulation efficiency and developing scale farms. More importantly, governmental supporting policies, such as agricultural subsidies, need to attach more importance to these large farms.