Chinese Geographical Science

In this study, an inventory analysis approach was used to investigate the intensity of agricultural non-point source pollution (ANSP) and its spatial convergence at national and provincial levels in China from 1999 to 2017. On this basis, spatial factors affecting ANSP were explored by constructing a spatial econometric model. The results indicate that: 1) The intensity of China’s ANSP emission showed an overall upward trend and an obvious spatial difference, with the values being high in the eastern and central regions and relatively low in the western region. 2) Significant spatial agglomeration was shown in China’s ANSP intensity, and the agglomeration effect was increasing gradually. 3) In the convergence analysis, a spatial lag model was found applicable for interpretation of the ANSP intensity, with the convergence rate being accelerated after considering the spatial factors but slower than that of regional economic growth. 4) The spatial factors affecting the ANSP intensity are shown to be reduced by improving agricultural infrastructure investment, labor-force quality, and crop production ratio, while the expansion of agricultural economy scale and precipitation and runoff have positive impact on ANSP in the study region. However, agricultural research and development (R&D) investment showed no direct significant effect on the ANSP intensity. Meanwhile, improving the quality of the labor force would significantly reduce the ANSP intensity in the surrounding areas, while the precipitation and runoff would significantly increase the pollution of neighboring regions. This research has laid a theoretical basis for formulation and optimization of ANSP prevention strategies in China and related regions.

Mire is the product of the Quaternary. It mostly formed, developed and declined after the postglacial age. Therefore the chemical element analysis, spore-pollen analysis,14C dating, mire plant determination for mire sediment, and the study on hierarchy relation of mire sediment, can provide a lot of information for restoring paleogeography, paleoclimate and environmental change. So some people called mire sediment—peat as “database of environment”.

Currently the deteriorated water quality for Huaihe River Basin (HRB) in China was still serious because of the negative influence multiple pollution sources including animal manure. However, little attention was paid to the potential risk of animal manure for farmland and water quality of HRB. This study was quantified and forecasted animal manure risk and its spatiotemporal variations in HRB from 2008 to 2018, through pollution discharge coefficient method and pollution load calculation, combined with kriging interpolation method of ArcGIS technology, based on statistics principle. All the data were originated from livestock and poultry breeding in HRB from 2008 to 2018. The future risk of farmland and water environment in HRB was further forecasted. The results indicated that the livestock and poultry manure has become a key pollution source causing a negative influence on farmland and water quality owing to a large amount of animal manure production without efficient recycle utilization. The chemical oxygen demand (COD) and total nitrogen (TN) discharge of animal manure in HRB almost accounted for 17.00% and 39.00% of the whole COD and TN discharge in China. The diffusion concentration of TN and TP in those regions of Shangqiu, Zhoukou, Heze, Zhumadian, Luohe, Jining, Xuchang, Kaifeng, Taian and Zhengzhou of HRB has exceeded the threshold value 10.00 mg/L of TN and 0.08 mg/L of TP, causing water eutrophication and cancer villages. The assessment of farmland and water quality risk revealed that Zhumadian, Zhoukou, Shangqiu, Taian, Jining, Heze, Linyi and Rizhao belonged to high risk areas in HRB, which were still obtained high farmland and water quality risk index in 2030. The results provided insight into an important significance of sustainable balance of livestock and poultry development and ecosystem in HRB.

The structure and dynamics of land resources system in the shelter forest region in the Northeast Plain is discussed according to the remote sensing and statistical information from the typical profiles and spots. For agricultural utilization, the land resources system is made up of five components, i.e. man, land resources, water resources, climatic resources and barren land. The local economy depends heavily upon its land resources, especially farm land. Having been exploited for 50–60 years from the 1930s to 1980s, it has already changed from the reclaiming period into the declining period. There is no waste land to be reclaimed. Facing the increase of population and requirements and the decrease of farmland fertility, proper management of land resources is indispensable if local economic and living level is maintained. It is imperative to make artificial regeneration (highest input) for the land resources and to keep fine circle of the system. If only natural regeneration if relied, the system will be changed to vicious circle.

Since China announced its goal of becoming carbon-neutral by 2060, carbon neutrality has become a major target in the development of China’s urban agglomerations. This study applied the Future Land Use Simulation (FLUS) model to predict the land use pattern of the ecological space of the Beibu Gulf urban agglomeration, in 2060 under ecological priority, agricultural priority and urbanized priority scenarios. The Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model was employed to analyse the spatial changes in ecological space carbon storage in each scenario from 2020 to 2060. Then, this study used a Geographically Weighted Regression (GWR) model to determine the main driving factors that influence the changes in land carbon sinking capacity. The results of the study can be summarised as follows: firstly, the agricultural and ecological priority scenarios will achieve balanced urban expansion and environmental protection of resources in an ecological space. The urbanized priority scenario will reduce the carbon sinking capacity. Among the simulation scenarios for 2060, carbon storage in the urbanized priority scenario will decrease by 112.26 × 106 t compared with that for 2020 and the average carbon density will decrease by 0.96 kg/m2 compared with that for 2020. Carbon storage in the agricultural priority scenario will increase by 84.11 × 106 t, and the average carbon density will decrease by 0.72 kg/m2. Carbon storage in the ecological priority scenario will increase by 3.03 × 106 t, and the average carbon density will increase by 0.03 kg/m2. Under the premise that the population of the town will increases continuously, the ecological priority development approach may be a wise choice. Secondly, slope, distance to river and elevation are the most important factors that influence the carbon sink pattern of the ecological space in the Beibu Gulf urban agglomeration, followed by GDP, population density, slope direction and distance to traffic infrastructure. At the same time, urban space expansion is the main cause of the changes of this natural factors. Thirdly, the decreasing trend of ecological space is difficult to reverse, so reasonable land use policy to curb the spatial expansion of cities need to be made.

Vegetation maps are fundamental for regional-scale ecological research. However, information is often not sufficiently up to date for such research. The Loess Plateau is a key area for vegetation restoration projects and a suitable area for regional ecological research. To carry out regional vegetation mapping based on the principles of hierarchical classification, object-oriented methods, visual interpretation, and accuracy assessment, this study integrated land cover, high-resolution remote sensing images, background environmental data, bioclimate zoning data, and field survey data from the Loess Plateau. To further clarify the implications of vegetation mapping, we compared the deviation of the 2015 vegetation map of the Loess Plateau (VMLP) and the widely used vegetation map of China (VMC) (1 : 1 000 000) for the expressed vegetation information and the evaluation of ecosystem services. The results indicated that 1) the vegetation of the Loess Plateau could be divided into 9 vegetation type groups and 18 vegetation types with classification accuracies of 87.76% and 83.97%, respectively; 2) the distribution of vegetation had obvious zonal regularity; 3) a deviation of 29.56 × 104 km2 occurred when the vegetation coverage area was quantified with the VMC; 4) the vegetation classification accuracy affected the ecosystem service assessment, the total water yield of the Loess Plateau calculated by the VMC and other required parameters was overestimated by 2.2 × 106 mm in 2015. Because vegetation mapping is a basic and important activity, that requires greater attention, this study provides supporting data for subsequent multivariate vegetation mapping and vegetation management for conservation and restoration.