Probability evaluation of the impact of landscape pattern on ecosystem service value in the Yangtze River Economic Belt

The rapid development of the economy has changed the regional landscape pattern. It is a high demand to quantitatively evaluate the impact of landscape pattern changes on the value of ecosystem services for ecological civilization construction and high-quality development. In this study, the research object was taken as the Yangtze River Economic Belt. Fishing net analysis was also made using land use data from eight periods from 1980 to 2020. The linear regression and correlation tests were carried out to clarify the spatiotemporal evolution and linear responses of four landscape pattern indexes and ecosystem service total value. Finally, a nonlinear probability evaluation framework was constructed to quantitatively evaluate the sensitivity of ecosystem service total value to changes in landscape pattern indexes. The results indicated that: 1) cropland, forestland, and grassland were the main types of land use in the study area. The area of cropland and forestland decreased each year, whereas, there was an increase in the area of other types of land use. Rapid economic development and urbanization were the main reasons for the significant increase in the construction land. 2) There was a relatively high index on the multi-year average landscape separation in southern Sichuan Province, eastern Yunnan Province, western Guizhou Province, and Chongqing City, resulting in severe landscape fragmentation, whereas, the distribution of patches was relatively concentrated in eastern Sichuan Province, southern Yunnan Province, western Hubei Province, western Hunan Province, northern Anhui Province, eastern Jiangsu Province, and southern Zhejiang Province. There was a significant increase in the indexes of landscape division and Shannon’s diversity in 43.97% and 64.28% of the study area, indicating the balanced and diversified landscape development. Urbanization was attributed to reducing the ecosystem service total value. 3) The increasing landscape separation index and Shannon’s diversity index were selected to represent the serious landscape fragmentation, leading to a decrease in the ecosystem service total value. It was very necessary to explore the response relationship between different landscape pattern indexes and ecosystem service total value, rather than the simple causal or linear relationship. 4) Four distribution functions were utilized to better fit the landscape pattern index and variations in the ecosystem service total value of each grid. Furthermore, the higher ecosystem service total value was more sensitive to the landscape division index and Shannon’s diversity index, according to the probability evaluation framework. The forestland and grassland were the dominant landscapes that affected the increase in the ecosystem service total value. The probability evaluation framework can be expected to quantitatively describe the nonlinear response relationship between the various ecosystem service total value and landscape pattern index. Landscape optimization should be carried out to promote protection and high-quality development. The finding can provide a solid scientific basis to grasp the variation trends of the landscape pattern and ecosystem services value, particularly for the ecological protection and high-quality warfare in the Yangtze River Economic Belt.