The Temporal and spatial evolution and prediction of ecosystem service value in Yuxi City based on the FLUS-Markov model

doi:10.14088/j.cnki.issn0439-8114.2024.02.029

Abstract

Abstract: Based on the ecological landscape type data of Yuxi City in 2010 and 2020, and the economic value correction ecosystem service value coefficient of grain production,analyzed the ecological landscape types and distribution characteristics of ecosystem service value in Yuxi City were analyzed, and the FLUS-Markov model was used to predict the ecosystem service value and its distribution in Yuxi City by 2030.The results showed that the Kappa coefficient of the predicted results of the model had been increased to 0.896 9, with an overall accuracy of 0.939 3, indicating high accuracy;from 2010 to 2020, the area of forest and grassland in Yuxi City showed a decreasing trend, and the ecosystem mainly composed of forest, grassland, and water still faced threats; the ecosystem service value of Yuxi City was 53.504 71 billion yuan, with a change rate of -0.129 7% in 2030. Yuxi City should strengthen the protection of forest and grassland, strengthen the implementation of policies for returning farmland to forest and grassland, and reasonably control the conversion of grassland and forest land to arable land;the ecosystem service value of Yuxi City showed still as follows： west>center>east in 2030;the contribution rates of ecosystem service value from high to low were Xinping County, Yuanjiang County, Eshan County, Yimen County, Huaning County, Hongta District, Jiangchuan District, Chengjiang City, and Tonghai County in various counties and districts of Yuxi City in 2030.

Key words: FLUS-Markov model, GIS spatial analysis, ecosystem service value, temporal and spatial evolution, prediction, Yuxi City, Yunnan Province

CLC Number:

X196
F062.2

LIU Shi-xin, LI Jian-hua, SUN Yong-qi, DU Yuan-yuan, XIANG Dong-lei, CHEN Yun-chun. The Temporal and spatial evolution and prediction of ecosystem service value in Yuxi City based on the FLUS-Markov model[J]. HUBEI AGRICULTURAL SCIENCES, 2024, 63(2): 189-198.

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