Pattern and Trend of Ecosystem Service Value in the Loess Plateau of Northern Shaanxi

• Published in: Land
• Main Authors: Yonghua Zhao, Lei Zhang, Xia Jia, Qi Mu, Lei Han, Zhao Liu, Peng Zhang, Ming Zhao
• Format: Article
• Language: English
• Published: MDPI AG 2023-03-01
• Subjects: Loess Plateau of Northern Shaanxi; ecosystem service value; spatial autocorrelation; entropy weight method; CA–Markov model
• Online Access: https://www.mdpi.com/2073-445X/12/3/607

The ecosystem service value (ESV) is a critical metric for assessing the construction and protection of the environment. The research into the ESV pattern and the future development trend in the Loess Plateau of Northern Shaanxi is important for the conservation of water and soil and the enhancement of the natural environment in the region. In this study, the variations and distribution patterns of the ESV in the study area from 2000 to 2020 were analyzed, the influence of various natural and social factors on the ESV was quantified, the weight of each factor was analyzed and evaluated using the entropy weighting method, and, finally, a prediction was made regarding how the ESV will develop going forward in this area. The results show that (1) the ESV showed a decreasing trend from 2000 to 2020, with the highest value for soil conservation and the lowest value for food production. Among the 25 districts and counties, Suide County had the lowest ESV per unit area, whereas Huanglong County had the highest. (2) The global positive correlation was clearly visible in the ESV. According to local spatial autocorrelation analysis, the area had a “high-high” agglomeration area in the south and a “low-low” agglomeration area in the middle and north. (3) Among the various influencing factors, population density had the highest weight and the distance from roads had the lowest weight. The impact status of the area generally showed a lighter impact in the southern region and a heavier impact in the northern region. (4) In 2030, the total ESV is predicted to be CNY 4343.6 million in the study area, CNY 39 million lower than that in 2020.