The Spatiotemporal Evolution Characteristics of Cultivated Land Multifunction and Its Trade-Off/Synergy Relationship in the Two Lake Plains

Abstract

The material foundation of sustainable agricultural development is cultivated land resources, and their sustainable use is critical to fostering agricultural sustainability and guaranteeing national food security. In this paper, the multifunctional evaluation framework of the cultivated land system based on the “GESEL” model at the grid scale (5 km × 5 km) is constructed to explore the spatiotemporal evolution characteristics of a multifunctional cultivated land system in two lake plains and the trade-off and synergy between the functions. The five functions are all unstable in time scales, and their spatial distribution characteristics are also different. The trade-off and synergy between the multiple functions of the cultivated land system in the two lake plains from 2000 to 2019 showed significant spatial heterogeneity. Most of the functions were mainly collaborative, and a few were trade-offs. The two lake plains can be divided into four multi-functional cultivated land zones: a grain production leading zone, a distinctive agricultural planting zone, a high-efficiency agricultural development zone, and an ecological agricultural construction zone. This research puts forward some countermeasures and suggestions to promote the sustainable utilization of cultivated land resources.

Optimizing land-use zonation in coastal areas: revealing the spatio-temporal patterns and trade-off/synergy relationships among farmland functions

“…This result can provide a clear indication of the areas where synergies and trade-offs occur. Moreover, we find that, although food production has been increasing over the past two decades, the reduction of farmland due to the farmland return program has also forced more and more farmers to lose their land to non-agricultural activities and migrate from the countryside to the cities, leading to a decrease in food selfsufficiency and agricultural employment and a decrease in the value of the social function (Xigui et al, 2022). Moreover, in recent years, the number of sightseeing gardens for agricultural products has been increasing, and fruits, vegetables and other cultivated agricultural products are offered to the outside world for picking in greenhouses, and the number of visits to the countryside has been increasing, and the number of visits to the countryside and the annual business income have been increasing abruptly.…”

“…In addition to the spatial and temporal patterns of multifunctions of farmland, the spatial characteristics of multifunctional relationships are crucial factors for decisionmakers to consider when developing sustainable management options for farmland (Yu et al, 2023). Previous researches primarily used static spatial correlation coefficients to quantify the synergies and trade-offs among functions of farmland (Xigui et al, 2022). However, the processes of agricultural history have been ignored by this method and the present situation is the consequence of long-term synergies and trade-offs between functions.…”

“…As stated above, two aspects, the spatial patterns of multifunctional values and synergistic or trade-off intensity should be included in a scientific farmlandzoning program. However, current research tends to approach farmland zoning based only on multifunctional values, which might limit the coordinated development of diverse functions of farmland (Xigui et al, 2022).…”

“…These interactions can manifest as mutually beneficial synergies, where an increase in one function promotes an increase in another, or as antagonistic trade-offs, where an increase in one function results in a decrease in another. For instance, agricultural machinery and equipment inputs can enhance agricultural output, contributing to economic development and social functions (Xigui et al, 2022). However, excessive application of pesticides and fertilizers, while improving farmland yield, may have detrimental effects on the ecological function (Su et al, 2014).…”

Spatiotemporal differences, dynamic evolution and trend of cultivated land use efficiency: Based on three food functional areas

“…Nevertheless, measuring their efficiency becomes somewhat inaccurate in the presence of non-zero slack in inputs or outputs. To address these issues, Tone [ 31 ] constructed the super-efficient SBM model [ [32] , [33] , [34] , [35] , [36] ]. This model effectively addresses the issue of all DMU efficiencies being 1, which complicates the differentiation between efficient DMUs.…”