Spatial Differentiation and Driving Mechanism of Agricultural Multifunctions in Economically Developed Areas: A Case Study of Jiangsu Province, China

Abstract

Revealing the spatial patterns of differentiation and the driving mechanism of agricultural multifunctional patterns is an important aspect of coordinating the functional optimisation and coordinated development of different agricultural regions. On the basis of understanding the connotation of agricultural multiple functions, this paper constructed an evaluation index system of agricultural multiple functions. Taking Jiangsu Province as a typical case, the spatial patterns of agricultural multifunctions in Jiangsu since 1978 were analysed by using the entropy weight TOPSIS (technique for order preference by similarity to ideal solution) method and ESDA (exploratory spatial data analysis) model, and the influencing mechanism of agricultural multifunction spatial differentiation was revealed by a geographic detector model. The results showed that (1) the cities with higher agricultural grain production functions were mainly concentrated in Yancheng and Huai’an; cities with higher agricultural economic development functions were mainly distributed in the coastal areas of Jiangsu; cities with higher agricultural social security functions were mainly concentrated in the Suzhou–Wuxi–Changzhou metropolitan area; and cities with higher agricultural ecotourism functions evolved from Nanjing–Zhenjiang to Suzhou–Wuxi–Changzhou. (2) The H–H (high–high) cluster pattern of the agricultural grain production function shifted from southern Jiangsu to northern Jiangsu. The H–H clusters of the agricultural economic development function and social security function were mainly distributed in Suzhou–Wuxi–Changzhou, while the L–L (low–low) cluster was mainly distributed in northern Jiangsu. The H–H cluster of agricultural ecotourism functions was mainly distributed in the areas with rich mountain and hill resources or dense water networks in Jiangsu. (3) The agricultural multifunction pattern differentiation was affected by the natural environment and economic and social comprehensive factors; the level of economic development and population employment structure were the leading factors of agricultural multifunction spatial differentiation; industry structure and people’s living conditions were the important driving forces of agricultural multifunction spatial differentiation; and the natural environment and population density were the basic factors underlying agricultural multifunction spatial differentiation.