摘要:土地利用方式改变着区域生态系统服务供给的潜在能力，进而对区域生态环境和经济可持续发展产生重要影响。以我国珠江-西江经济带广西段为例，测算1990年、2005年和2018年3期土地利用变化（LUC）和生态系统服务价值（ESV），进而利用ESV损益流向表和双变量空间自相关模型探讨LUC影响下ESV的时空特征。结果表明：（1）28年间研究区ESV总值变化不大，近年来ESV相比2005年有所降低，建设用地面积增幅最大，耕地和林地面积先减少后增多，以林地与耕地相互转移为主；（2）林地是研究区最重要的生态用地，维持生物多样性、水文调节、保持土壤、气体调节和气候调节构成研究区ESV的主体；生态系统服务价值强度（ESVI）高值区主要分布在桂西北、桂东和桂北，低值区分布在地势较为平坦的桂中丘陵平原区；各区县ESVI呈显著空间正自相关性（P<0.05），空间集聚程度较高，高-高聚集、低-低聚集分别与生态系统服务价值强度高值、低值区域高度重合；（3）研究期间林地与耕地之间的相互转移是ESV增减的主要原因；3个时期土地利用程度与ESVI的双变量空间自相关图具有相似的空间特征，呈现出显著空间负自相关模式（P<0.05）。



Abstract:Land use patterns change the potential supply of regional ecosystem services, which in turn has an important impact on regional ecological environment and sustainable economic development. Taking the Guangxi section of the Pearl River-West River Economic Belt in China as an example, the Land Use Change (LUC) and Ecosystem Services Value (ESV) in 1990, 2005 and 2018 were calculated. Then the spatial and temporal characteristics of ESV under the influence of LUC were discussed by using the ESV profit and loss flow table and the bivariate spatial autocorrelation. The results showed that(1) The total values of ESV in the study area have not changed significantly in 28 years, and the ESV decreased in recent years compared with that in 2005. The area of construction land increased the most, the area of cultivated land and forestland decreased first and then increased, and land use type transfers were mainly based on the mutual transfer of forestland and cultivated land. (2) Forestland was the most important ecological land in the study area. Biodiversity maintenance, hydrologic regulation, soil conservation, gas regulation and climate regulation constituted the main body of the ESV in the study area. The high-value areas of ecosystem services value intensity (ESVI) were mainly distributed in the northwest, east and north of Guangxi, while the low-value areas were located in the hills and plain areas in the middle of Guangxi with relatively flat terrain. The ESVI of each district and county showed significantly positively spatial autocorrelation (P<0.05), with a high degree of spatial aggregation. High-high aggregation and low-low aggregation were highly coincident with high-value and low-value regions of ecosystem services value intensity. (3) The mutual transfers between forestland and cultivated land during the study period were the main reasons for the increase and decrease of ESV. The land use degree and ESVI's bivariate spatial autocorrelation map had similar spatial characteristics in the three periods, showing a significantly spatially negative autocorrelation pattern (P<0.05).





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