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Spatial and Temporal Distribution of the Ecosystem Provisioning Service and Its Correlation with Food Production in the Songhua River Basin, Northeastern China

Yuhan Zhao, Hui Yang (), Chunyu Zhu and Jiansheng Cao ()
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Yuhan Zhao: Key Laboratory of Agricultural Water Resources, Hebei Key Laboratory of Agricultural Water-Saving, Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang 050001, China
Hui Yang: Key Laboratory of Agricultural Water Resources, Hebei Key Laboratory of Agricultural Water-Saving, Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang 050001, China
Chunyu Zhu: Key Laboratory of Agricultural Water Resources, Hebei Key Laboratory of Agricultural Water-Saving, Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang 050001, China
Jiansheng Cao: Key Laboratory of Agricultural Water Resources, Hebei Key Laboratory of Agricultural Water-Saving, Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang 050001, China

Land, 2024, vol. 13, issue 4, 1-13

Abstract: Provisioning services are essential components of ecosystem services. Food production is usually a driver of land use change, which has the effect on altering the provisioning services of ecosystems. As one of the main areas of food production in China, the provisioning services of the Songhua River Basin (SHRB) should be taken seriously. In view of this, it is urgent to carry out a study on the assessment of provisioning services in the SHRB to provide data support and scientific reference for the optimization of the spatial pattern of land use in the basin, the sustainable development of agriculture, and the formulation of differentiated protection policies. In this study, based on the equivalent factor method for the unit area value and spatial autocorrelation with the Moran’s I, we assessed the provisioning services values (PSV) of the SHRB every ten years during the period of 2000–2020 under different land use types and analyzed the relationships between different PSV and the production of four different food types, including rice, wheat, corn, and soja. The main conclusions are as follows: (1) From 2000 to 2020, the area of paddy fields in the SHRB increased and then decreased, while the area of dry lands continued to increase. The land use transfer matrix showed a significant expansion of paddy fields (+0.55 × 10 4 km 2 ), shrinkage of grassland (−0.72 × 10 4 km 2 ), and loss of water body (−0.43 × 10 4 km 2 ) in the SHRB from 2000 to 2020; (2) The PSV in the SHRB showed an increasing trend from 2000 to 2020, growing by 16.73 × 10 10 RMB, with the growth in 2010–2020 being greater than in 2000–2010. The order of increase in each type of PSV was: water supply > food supply > raw material supply; (3) Spatially, the increase in PSV per unit and total PSV in the SHRB was lesser in the center and greater in the east and west. Meanwhile, the spatial distribution of various PSV showed that the value of unit area food supply was higher in the central and eastern plains, while the raw material supply and water supply were higher in the western and eastern hilly areas. (4) In terms of spatial correlation, the distribution of soja production with the total PSV, food supply, raw materials supply, and water supply services values were positively spatially correlated. However, the production of rice, wheat, and corn with the total PSV, food supply, and raw materials supply services values were negatively spatially correlated. Cluster analysis revealed that changing the crop cultivation structure could protect the ecosystem and increase the value of ecosystem services.

Keywords: ecosystem provisioning services; land use; food production; value equivalent factor; spatial distribution; Moran’s I (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2024
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