The high-quality development in the Yunnan–Guizhou region (YGR) is a significant support for the high-quality development of China. It will help shape a new pattern of regional coordinated development. Referring to a Beautiful China and the United Nations Sustainable Development Goals (SDGs) evaluation indexes, we built an evaluation index system that puts the high-quality development at its heart. This system includes the resource load, economic development, ecological environment protection, and social progress. Taking 25 prefecture-level cities of the YGR as study subjects, the authors used the entropy weight–TOPSIS model to evaluate high-quality development and evolution. Then, the authors used the Geographical Detector (GD) method and a Geographic-Weighted Regression (GWR) model to analyze factors and mechanisms of the evolution of high-quality development. The results suggest that the changes of urban built-up area, per capita GDP, total foreign trade value, tourism revenue, and total investment of fixed assets investment are the primary factors of spatial differentiation of this evolution. The influence and direction of each factor are different in different periods, with apparent spatio-temporal heterogeneity. From 2005 to 2018, the synergistic effect of changes in total foreign trade value and tourism revenue is the leading force in shaping the evolution pattern. The high-quality development of the YGR generally presents the spatial pattern of “central Yunnan–central Guizhou core dual drive”, ”high in east and low in west”, and the evolution speed presents a development characteristic of “low speed–relatively high speed–high speed”. The research can provide a reference for high-quality and precise development and decision-making in the YGR.
The water quality of a basin is pronouncedly affected by the surrounding types of land use. Analyzing the impact of LULC and landscape patterns on water quality is critical for identifying potential drivers. To further study how LUCC affects the water quality in a typical plateau lake basin, this study investigated the impacts of land-use types on water quality in the Dianchi Lake Basin in Southwest China. We analyzed changes in land-use types and the landscape pattern of the Dianchi basin, calculated the CWQI (Canadian Water Quality Index) value based on the water quality indexes (PH, total phosphorus (TP), total nitrogen (TN), chemical oxygen demand (COD), dissolved oxygen (DO), permanganate index (CODMn), five-day biochemical ox-ygen demand (BOD5), ammonia nitrogen (NH3-N), turbitidy, and chlorophyll-a (Chla)), used the RDA (Redundancy Analysis) and SMLR (Stepwise multiple linear regression) methods, the coupling degree, coupling coordination degree, and the geographical detector model to explore the relationship between water quality and changes in the land-use type. The results show that (1) changes in the land-use types were obvious: the majority of the land, which was originally forest land, became built land in 2020 and farmland in 1990 (except for the Dianchi water). Landscape pattern indexes indicated that almost all land-use types were first scattered, then gathered from 1990 to 2020. (2) Changes in the water quality of Dianchi Lake lagged behind the changes in land-use types, and the variation trends were similar to the landscape pattern variation trends. The CWQI value decreased in a nearly linear fashion from 1990 to 1998, exhibited a slight change from 1999 to 2013, and quickly increased from 2013. (3) Land-use types demonstrated a tight correlation with the Dianchi water quality, and LPI was the most dominant factor in both Caohai Lake and Waihai Lake. (4) There were different indexes affecting the coupling coordination degrees of Caohai Lake and Waihai Lake.
Fewer studies on ecological security (ES) in border areas limit the synergistic development of border areas in the context of rapid globalization. The study of ES in border areas of southwest China can enrich the evaluation methods, summarize the knowledge related to ES in border areas, and provide references for similar areas in the world. Therefore, twenty-five international border counties in Yunnan Province were selected to establish a system to evaluate ES; an entropy weight TOPSIS model was used to evaluate the changes in ES from 2004 to 2019. Then, an obstacle degree model was used to diagnose the factors affecting ES. The state of ES was predicted by a gray prediction model (GM) (1,1) in 2025 and 2030. The results show that an improving ES situation presented a spatial distribution pattern of high to low from the southwest to the west and east. Various factors, including fixed assets investment, per-capita fiscal revenue, per-capita GDP, food production, and water regulation, created obstacles to a desirable ES in the study area. Although the ES of border areas will maintain an upward trend under the existing development model, the number of counties that will reach a secure state of ES in 2025 and 2030 is predicted to only be 1 and 2, respectively.
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