Coupling Coordination Degree of Land, Ecology, and Food and Its Influencing Factors in Henan Province

Abstract

Studying the spatiotemporal evolution characteristics of the coupling coordination of the land–ecology–food system (LEF) aids in promoting green agricultural development and regional resource management. This study enriches food indicators under the dietary structure and uses the coupling coordination degree model to analyze the coupling coordination relationship among the LEF of 18 cities in Henan Province from 2011 to 2020. The gray relational degree model is used to investigate the main influencing factors determining the synergistic development of the system. The results show that the comprehensive development index of the LEF in Henan Province ranges between 0.4 and 0.6. The overall comprehensive evaluation index of various cities is ranked as Southern Henan > Eastern Henan > Central Henan > Northern Henan > Western Henan, with the greatest fluctuation observed in the food subsystem. During the study period, the coupling degree of Henan’s LEF ranged from 0.277 to 0.996, indicating stages from low- to high-level coupling. The coupling coordination degree ranged from 0.338 to 0.775, generally bordering on imbalance and barely coordinated. The impact of each subsystem evaluation index on the system’s coupling coordination degree can be ranked as food subsystem > ecology subsystem > land subsystem, with the correlation degree of internal indicators of the food and ecology subsystems with the system’s coupling coordination degree being over 85%, emphasizing the importance of strict management. In summary, the coupling coordination of the LEF system in Henan Province urgently needs to be improved; especially, the coordination of the agricultural system is particularly important. Clarifying the spatiotemporal pattern of the LEF coupling and its coordination can provide a scientific basis for the coordinated development of land use, agricultural ecology, and grain production in Henan Province.

1. Introduction

Food security is the foundation of national security, and ensuring a stable supply of food and sustainable agricultural development is a significant challenge currently faced. Land is the primary carrier of food production and a necessary prerequisite for realizing the national food security strategy [1]. Ecological security is a crucial support for food production. The increase in food yield exacerbates issues such as soil erosion and agricultural non-point source pollution, resulting in negative externalities for the ecological environment [2]. Land, ecology, and food are vital strategic assurances related to human survival and sustainable development. These three elements are interdependent, forming a complex network of causal relationships [3,4]. As a major agricultural province in China, Henan plays a significant role in the nation’s food security and ecological sustainability. The province is rich in arable land resources, though the overall quality is not high. While the planting structure is well-developed, there are mismatches between the supply and demand sides of food provision. With rapid economic development and continuous improvements in living standards, the dietary structure of residents in Henan Province has undergone significant changes. The traditional grain-based diet is gradually shifting towards a more diversified diet with higher protein and fat content. This transformation in dietary structure not only impacts the total demand and composition of food but also imposes new requirements on land resource utilization and ecological environmental protection [5,6,7]. Therefore, exploring the relationship between land, ecology, and food in Henan Province under the changing dietary structure is crucial for ensuring high-quality regional development.

Green sustainable development in agriculture aims for the coordinated and mutually reinforcing development of land, ecology, and food. The coupling coordination degree model emphasizes understanding the connections between system elements to achieve synergies and trade-offs among different subsystems. It has been used to address global sustainable development issues [8]. The concept of “coupling” was first introduced at the 2011 conference on the Water–Energy–Food Nexus held in Bonn, Germany. This concept, which emphasizes the integrated management of multiple environmental and resource elements based on systemic interconnections, has since been widely applied [9,10,11]. Subsequently, scholars have focused on the interrelationships within the water–energy–food system, progressively applying these concepts to various fields such as economic development [12], carbon emissions [13], and ecosystem service values [14,15]. Previous studies on agricultural production relationships have primarily focused on water–land–food and land–economy–ecology interactions [16,17], with few incorporating ecological aspects into the research. Moreover, these studies had mainly concentrated on national [18,19] and watershed scales [20,21,22], with fewer investigations conducted at smaller, municipal scales. Therefore, considering the land–food–ecology relationship in agricultural production as a means to elucidate the complex interactions among multiple resource systems will help maximize synergies between different sectors. This approach is also crucial for ensuring food security and addressing ecological environmental challenges. Currently, most scholars, when studying the coupling relationship between the food system and other related systems, select single indicators for the food system. These indicators mainly include per capita grain output, grain yield per unit area, grain planting area, and the grain consumer price index [23,24,25]. Dietary structure, which reflects a region’s agricultural practices, ecological environment, and socio-economic conditions, is a critical factor influencing the LEF. Therefore, this paper constructs food system indicators from the perspective of dietary structure, focusing on food supply. It includes not only the yield of grains such as corn and wheat but also the production of livestock products, vegetables, and fruits. By enriching food system indicators, this study explores the relationships among the LEF. Henan Province is a major grain-producing region in China, rich in resources. However, the uneven development among its cities has constrained the sustainable development of Henan Province. Therefore, exploring the coupling and coordinated development in Henan Province is key to promoting sustainable development in the region.

Based on the consideration of the relationship between resources and ecosystems, this study utilizes data from 18 cities in Henan Province from 2011 to 2020 to construct three evaluation indicator systems for land, ecology, and food. Calculating the development levels reveals the impact mechanisms of dietary structure changes on land use, the ecological environment, and food production. This provides a scientific basis for optimizing land resource allocation, protecting the ecological environment, and ensuring food security. Additionally, it contributes to promoting the sustainable development of agriculture in Henan Province and achieving the synergistic enhancement of economic, social, and ecological benefits.

2. Data Sources and Methodology

2.1. Study Area

Henan Province is located in the central-eastern part of China, between latitudes 31°23′ and 36°22′ N and longitudes 110°21′ and 116°39′ E (Figure 1). The average elevation is 283 m, and the annual precipitation ranges from 407.7 to 1295.8 mm. The province consists of 18 municipalities directly under the central government, with a total area of 167,000 square kilometers, accounting for 1.73% of the total area of China. The terrain is high in the west and low in the east. From the perspective of land resources, Henan Province comprises plains, basins, mountains, hills, and water bodies. The total cultivated land area is 7.5141 million hectares; mountains and hills account for 44.3% of the province’s area, reaching 74,000 square kilometers; plains and basins account for 55.7%, reaching 93,000 square kilometers. From an ecological perspective, the forest coverage rate in Henan Province reached 24.14% in 2020, with the overall ecological environment quality continuously improving. From a food perspective, the total grain output of Henan Province in 2020 was 68.258 million tons, contributing to 23.07% of the national grain output’s increase. Henan is an important grain production base in China, continuously improving its planting structure to meet the dietary consumption needs for vegetables, fruits, meat, eggs, and dairy products.

2.2. Data Sources and Preprocessing

This study aims to investigate the coupling and harmonization relationship among land, ecology, and food. The data used in this paper is sourced from the “Henan Statistical Yearbook” and the statistical yearbooks of various cities in Henan Province from 2011 to 2020, as well as the bulletins on national economic and social development. To address the issue of inconsistent units of the selected indicators, the data were normalized as follows [26]:

For positive indicators:

$$Y={\displaystyle \frac{X-X\mathrm{m}\mathrm{i}\mathrm{n}}{X\mathrm{m}\mathrm{a}\mathrm{x}-X\mathrm{m}\mathrm{i}\mathrm{n}}}$$

(1)

For negative indicators:

$$Y={\displaystyle \frac{X\mathrm{m}\mathrm{a}\mathrm{x}-X}{X\mathrm{m}\mathrm{a}\mathrm{x}-X\mathrm{m}\mathrm{i}\mathrm{n}}}$$

(2)

where $X$ and $Y$ are the initial and normalized values of the indicators, and $X\mathrm{m}\mathrm{a}\mathrm{x}$ and $X\mathrm{m}\mathrm{i}\mathrm{n}$ are the maximum and minimum values of the indicators, respectively.

2.3. Integrated Evaluation Model

Considering the interdependence and the need for coordinated development of the land, ecology, and food subsystems, the larger the comprehensive index value, the better the development level of each subsystem. Conversely, a smaller value indicates slower development in each subsystem. The expression is as follows:

$$U\left(l\right)={\sum }_{i=1}^n{L}_i{P}_i$$

(3)

$$U\left(e\right)={\sum }_{i=1}^n{E}_i{R}_i$$

(4)

$$U\left(f\right)={\sum }_{i=1}^n{F}_i{Z}_i$$

(5)

where $U\left(l\right)$, $U\left(e\right)$, and $U\left(f\right)$ are the comprehensive values of the land, ecological, and food systems, respectively, and their higher values indicate better operational effectiveness of the subsystems. $L_i$, $E_i$, and $F_i$ are the weights of each indicator within the systems, while $P_i$, $R_i$, and $Z_i$ are the standardized data of each indicator.

2.4. Coupling Coordination Degree

Wang et al. [27] argued that the coupling degree (C) is not evenly distributed within the range [0, 1], and the traditional coupling coordination degree model itself has validity issues. Hence, they proposed a revised coupling coordination degree model. This study draws on the experience of Wang Shujia et al., adopting the revised model to represent the coupling coordination level among the LEF. The strength of interaction between subsystems is reflected by the coupling degree, and the level of coordinated development among systems can be quantitatively described using the coupling coordination degree. The revised model is

$$C=\sqrt{\left[1-{\displaystyle \frac{\sqrt{{\left(U_3-U_1\right)}^2}+\sqrt{{\left(U_2-U_1\right)}^2}+\sqrt{{\left(U_3-U_2\right)}^2}}{3}}\right]\times \sqrt{{\displaystyle \frac{U_1}{U_3}}\times {\displaystyle \frac{U_2}{U_3}}}}$$

(6)

$$T=a{U}_1+\mathrm{b}{U}_2+\mathrm{c}{U}_3,\mathrm{a}+\mathrm{b}+\mathrm{c}=1$$

(7)

$$D=\sqrt{C\times T}$$

(8)

where $C$ is the coupling degree, $D$ is the coupling coordination degree, and $T$ is the comprehensive evaluation index of the land–ecology–food system, ranging from 0 to 1. A higher value indicates a greater degree of association, coordination, and comprehensive development among subsystems. The weights $\mathrm{a}$, $\mathrm{b}$, and $\mathrm{c}$ represent the importance of the four subsystems, and this paper considers the land, ecology, and food subsystems to be equally important, thus assigning each a weight of 1/3. $U_1$, $U_2$, and $U_3$ represent the comprehensive scores of the land, ecology, and food subsystems. The classification standards for $C$ and $D$ are shown in

Table 1. The division standard of coupling degree stages.

Index	Value	Type	Explanation
Coupling degree (C)	0–0.3	Low-level Coupling	The correlation between land, ecology, and food is very weak, and when C = 0, it implies that there is no correlation at all between them.
	0.3–0.5	Antagonistic Period	The correlation between land, ecology, and food is strengthening, showing a trend in mutual influence.
	0.5–0.8	Running-in Period	The relationship between land, ecology, and food is gradually trending towards cooperation, exhibiting a positive coupling trend.
	0.8–1	High-level coupling	The positive interactions between land, ecology, and food are increasing, and the coupling is becoming stronger. When C = 1, the system is in a resonance state.

and

Table 2. The division standard of coupling coordination degree stages.

Index	Value	Degree of Coordination	Type
Coupling coordination degree (D)	0–0.1	Dysfunctional Decline Type	Extreme Unbalance
	0.1–0.2		Serious Unbalance
	0.2–0.3		Moderate Unbalance
	0.3–0.4		Mild Unbalance
	0.4–0.5	Transitional Type	Imminent Unbalance
	0.5–0.6		Near Coordination
	0.6–0.7	Coordinated Development Type	Primary Coordination
	0.7–0.8		Moderate Coordination
	0.8–0.9		Good Coordination
	0.9–1		Extreme Coordination

below.

2.5. Gray Relational Analysis

Gray relational analysis is a multifactor statistical analysis method that can determine the degree of correlation between two factors in a system by calculating the consistency of their trend in change, even with incomplete information. It identifies the reference and comparison sequences, with higher gray relational values indicating stronger correlations [28,29]. In this paper, the indicators in the three subsystems are taken as influencing factors. To further determine which factors within the subsystems have a stronger or weaker influence on the system’s coupling coordination degree, the correlation coefficients of the sequences after normalization are calculated, ranked, and used to judge the influence of each factor.

The reference and comparison sequences for gray relational analysis are

$$x_0\left(k\right)=\left\{x_0^1,x_0^2,\cdots ,x_0^m\right\}k=\mathrm{1,2},\cdots ,m$$

(9)

$$x_i\left(k\right)=\{x_1^1,x_1^2,\cdots ,x_1^n\}k=\mathrm{1,2},\cdots ,n$$

(10)

where $x_0\left(k\right)$ represents the reference sequence and $x_i\left(k\right)$ is the comparison sequence. When calculating the gray relational coefficient, $x_0\left(t\right)$ is the sequence after normalization, and its sub-sequence is $x_i\left(t\right)$. When $t$ = $k$, the gray relational degree between $x_0\left(t\right)$ and $x_i\left(t\right)$ is calculated using the following formula:

$${\zeta }_{0i}(k)=|{\displaystyle \frac{{\Delta }_{min}+\rho {\Delta }_{max}}{{\Delta }_{0i}\left(k\right)+\rho {\Delta }_{max}}}|$$

(11)

where ${\Delta }_{0i}\left(k\right)$ is the absolute difference between the two sequences at the k item, ${\Delta }_{max}$ is the maximum value of all absolute differences, and ${\Delta }_{min}$ is the minimum value of all absolute differences.

The gray relational degree is further calculated using the formula:

$$E_{0i}={\displaystyle \frac{1}{m}}{\sum }_{k=1}^m{\zeta }_{0i}(k)$$

(12)

2.6. Construction of the Indicator System for the LEF Nexus

The coordinated development of the LEF impacts the high-quality development of Henan Province, with these three elements being interdependent and mutually influential. Clarifying the relationships among them can promote intensive land use, increase grain yield, and foster the construction of an ecological civilization. Land is the foundation of grain production; the quality and quantity of land directly determine the yield and quality of grain. Reasonable farming practices can enhance both grain production and land use efficiency. The ecosystem, as the carrier of social production, supports the utilization of land resources and the demands of grain production. A healthy ecological environment provides favorable conditions for grain production, while improper grain production methods may disrupt the ecological balance. Therefore, adopting reasonable land use practices not only facilitates the effective allocation of various resources but also achieves coordinated regional resource development, offering approaches for the comprehensive development and utilization of regional resources and their coordinated coupling development.

Constructing a scientific and reasonable evaluation index system is the foundation for assessing the coupled and coordinated development level of the regional LEF [30]. Based on existing studies and comprehensively considering the interaction mechanisms among LEF, this paper constructs the Henan Province LEF coupling coordination evaluation index system, which includes 18 indicators across two layers of indices [31,32] (

Table 3. Indicators for LEF system.

Dimension	Primary Indicator	Secondary Indicator	Unit	Type
Land Subsystem	Production Guarantee	Per Capita Arable Land Area	mu/person	+
		Effective Irrigation Area	thousand ha	+
		Crop Sowing Area	thousand ha	+
	Utilization Efficiency	Population Density	persons/km2	−
		Rural Household Disposable Income	yuan	+
		Per Capita GDP	billion yuan/km2	+
Ecological Subsystem	Ecological Basis	Per Capita Green Area	m2	+
		Green Coverage of Built-up Areas	%	+
	Ecological Pressure	Agricultural Fertilizer Use	ton	−
		Agricultural Plastic Film Use	ton	−
		Pesticide Use	ton	−
Food Subsystem	Production	Grain Output	million tons	+
		Vegetable Output	million tons	+
		Melon and Fruit Output	million tons	+
		Meat Output	million tons	+
	Demand	Natural Population Growth Rate	%	−
		Urban Residents Engel’s Coefficient	%	−
		Rural Residents Engel’s Coefficient	%	−

Note: +/− represent positive and negative indicators, respectively.

).

In the comprehensive evaluation index system, the land subsystem is considered from the perspectives of production guarantee and land utilization efficiency. The per capita arable land area, irrigated area, and sown area of crops ensure the land production capacity of a region, while population density, per capita disposable income of rural residents, and GDP per unit area reflect the land utilization efficiency of a region. The ecological subsystem is considered from the perspectives of ecological basis and ecological pressure, where the usage of agricultural fertilizers, agricultural plastic film, and pesticides can reflect the ecological pressure of the agricultural ecosystem in the region. The food subsystem selects indicators from two interrelated social reproduction aspects: production and demand. The indicators for the production level include grain, vegetable, fruit, and meat production, which can more comprehensively describe the relationships among the systems. For the demand level, the natural population growth rate, Engel’s coefficient of urban residents, and Engel’s coefficient of rural residents are selected as indicators.

3. Results

3.1. Spatiotemporal Pattern of the Comprehensive Index of LEF

The comprehensive evaluation index for the LEF in Henan Province shows significant spatial differences among its 18 cities, with most cities having an index between 0.4 and 0.6. The overall trend indicates Southern Henan > Eastern Henan > Central Henan > Northern Henan > Western Henan. Eastern Henan includes Kaifeng, Shangqiu, and Zhoukou; Southern Henan includes Nanyang, Xinyang, and Zhumadian; Western Henan includes Luoyang and Sanmenxia; Northern Henan includes Anyang, Hebi, Xinxiang, Jiaozuo, Puyang, and Jiyuan; and Central Henan includes Zhengzhou, Pingdingshan, Xuchang, and Luohe (Figure 2). The index trends can be divided into two phases: From 2011 to 2018, most cities exhibited a fluctuating upward trend, indicating an increasing comprehensive development capability across systems. From 2017 to 2020, the index for all cities showed a downward trend. In the western plain city of Sanmenxia, the index dropped from 0.447 in 2011 to 0.252 in 2020. This low index is primarily due to its topography, consisting mainly of mountains, hills, and loess plateaus, leading to limited arable land and low grain output while grain demand continues to rise, deteriorating the comprehensive development capability of its grain system. Luoyang’s index decreased from 0.362 to 0.300, mainly due to rapid economic development and urbanization, which consumed arable land and weakened the comprehensive development capability of its land and food systems. Eastern and southern regions such as Kaifeng, Shangqiu, Zhoukou, and Zhumadian had relatively high indices, indicating favorable development trends and significant potential in their LEF. The central cities of Zhengzhou, Pingdingshan, Xuchang, and Luohe had mid-level indices, with Zhengzhou showing a rapid increase from 2014 to 2018. Specifically, cities like Luoyang, Anyang, Hebi, Xinxiang, Jiaozuo, Puyang, Xuchang, Luohe, and Nanyang have shown increasing trends, while cities like Kaifeng, Shangqiu, Zhoukou, Zhumadian, Xinyang, Pingdingshan, and Jiyuan have shown decreasing trends. Overall, the improvement in Eastern Henan and Southern Henan was more significant, reflecting differences in resource allocation, policy effectiveness, or infrastructure development. Cities like Zhoukou, Nanyang, and Zhengzhou have exhibited notable growth, while others remained stable.

To clarify the development levels of each subsystem, the LEF system coupling coordination degree model was applied to calculate the safety evaluation indices for the land, ecological, and food subsystems of the 18 prefecture-level cities from 2011 to 2018. The results are shown in Figure 3. During the period from 2011 to 2021, the subsystems’ evaluation indices indicated that food > ecology > land, demonstrating that the development speed of the food and land systems surpassed that of the ecological system, with varying growth patterns. Due to differences in geographical location and natural and social conditions, there were significant disparities among the subsystems. From the perspective of the land subsystem, the safety evaluation indices for Zhengzhou, Nanyang, and Zhoukou were relatively high. Specifically, Zhengzhou’s land subsystem safety evaluation index was the highest in Henan Province for many years, indicating a high level of land safety. Nanyang follows, reflecting high land quality and government support for agriculture, which promotes the coordinated development of agricultural production and the ecological environment. Regarding the ecological subsystem, in 2011, there were significant differences in the ecological safety evaluation indices among the prefecture-level cities. However, with the continuous promotion of the national ecological civilization construction starting in 2012, the disparity in ecological safety evaluation indices among these cities gradually narrowed, and the overall ecological safety level significantly improved. Hebi, Sanmenxia, Zhumadian, and Jiyuan consistently ranked among the top four in terms of ecological safety evaluation indices over the years, indicating a high level of ecological safety in these cities. In contrast, Nanyang and Zhoukou had lower ecological safety evaluation indices, but their food subsystem comprehensive evaluation indices were relatively high, reflecting a focus on grain development in these two cities. From the perspective of the food subsystem, Shangqiu, Zhoukou, and Nanyang had the highest comprehensive evaluation indices, attributable to their advantageous geographical locations, well-developed agricultural industries, and high levels of agricultural modernization. Conversely, Hebi and Zhumadian had lower comprehensive evaluation indices, limited by natural conditions and the quantity and quality of arable land.

3.2. Analysis of Coupling and Coupling Coordination

3.2.1. Evaluation of Coupling

From 2011 to 2020, the coupling degrees of the LEF in various cities of Henan Province ranged from 0.277 to 0.996. This range indicates fluctuations from low-level coupling to high-quality coupling. The coupling degrees varied significantly among different cities, showing multi-segment changes in their numerical values. Overall, the coupling degrees in most cities increased over the decade (

Table 4. Development trends in LEF coupling degree in 18 cities of Henan Province.

City	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020
Zhengzhou	0.681	0.645	0.639	0.474	0.655	0.645	0.616	0.433	0.606	0.487
Kaifeng	0.809	0.829	0.785	0.773	0.809	0.829	0.745	0.746	0.757	0.740
Luoyang	0.584	0.610	0.555	0.531	0.553	0.610	0.574	0.660	0.843	0.879
Pingdingshan	0.535	0.556	0.535	0.511	0.519	0.556	0.541	0.556	0.869	0.783
Anyang	0.848	0.888	0.894	0.805	0.801	0.888	0.814	0.795	0.938	0.880
Hebi	0.332	0.320	0.320	0.310	0.334	0.320	0.405	0.363	0.769	0.742
Xinxiang	0.689	0.722	0.722	0.731	0.723	0.722	0.774	0.733	0.854	0.914
Jiaozuo	0.561	0.581	0.532	0.530	0.489	0.581	0.477	0.426	0.775	0.811
Puyang	0.479	0.488	0.502	0.516	0.504	0.488	0.485	0.430	0.855	0.825
Xuchang	0.614	0.666	0.629	0.631	0.595	0.666	0.518	0.448	0.761	0.846
Luohe	0.426	0.456	0.435	0.435	0.449	0.456	0.477	0.426	0.918	0.913
Sanmenxia	0.311	0.348	0.339	0.434	0.425	0.348	0.417	0.505	0.705	0.748
Nanyang	0.454	0.633	0.615	0.544	0.643	0.633	0.425	0.381	0.694	0.642
Shangqiu	0.457	0.469	0.465	0.481	0.521	0.469	0.674	0.606	0.738	0.833
Xinyang	0.746	0.769	0.756	0.636	0.718	0.769	0.719	0.684	0.996	0.929
Zhoukou	0.456	0.469	0.455	0.407	0.518	0.469	0.526	0.465	0.448	0.390
Zhumadian	0.906	0.886	0.913	0.703	0.947	0.886	0.872	0.717	0.956	0.864
Jiyuan	0.283	0.295	0.277	0.278	0.293	0.295	0.372	0.323	0.675	0.650

). Most cities were in the running-in stage, suggesting that the systems were adjusting and adapting to each other. However, due to factors such as changes in the natural environment, government control, and regional geographical differences, there were disparities in the coupling degrees across regions. These can be roughly divided into three stages: the first stage (2011–2017), the second stage (2018–2019), and the third stage (2019–2020). Specifically, Zhumadian, Anyang, Kaifeng, and Xinyang maintained high-level coupling degrees throughout 2011–2020, indicating a strong and stable interaction between land, ecology, and food systems in these regions. The coupling degrees of Luohe, Sanmenxia, and Hebi improved significantly, showing a stable and positive development trend. From 2011 to 2020, Xinxiang, Jiaozuo, and Luoyang exhibited a steady and slight increase in their coupling degrees, gradually transitioning from the running-in stage to the high-level coupling stage, and maintaining stability. Conversely, Zhengzhou, Hebi, Jiaozuo, and Zhoukou showed a downward trend in coupling degrees. Notably, Zhoukou experienced the most significant fluctuations, remaining stable from 2011 to 2016 but then markedly declining from 0.526 in 2017 to 0.390 in 2020, transitioning from the running-in stage to the antagonistic stage. The coupling degree of Nanyang showed fluctuating increases, gradually shifting from the antagonistic stage to the running-in stage, indicating an enhanced interaction between subsystems. In summary, the cities in Henan Province exhibited close interrelationships, emphasizing the necessity for integrated management to support high-quality comprehensive development in Henan. Although the coupling degrees in most cities have improved overall, regional development remains uneven. Future policies should be tailored to the specific conditions of each city to achieve the coordinated and sustainable development of the LEF in Henan Province.

3.2.2. Spatial Pattern of the Coupling Coordination Degree

From 2011 to 2020, the coupling coordination status of the LEF in various cities of Henan Province, as shown in Figure 4, exhibit values ranging from 0.338 to 0.775. The overall level of coordinated development has gradually improved, progressing from a state of mild disorder to a stage of good coordination. Generally, the southeastern region showed a higher degree of coupling coordination of the LEF than the northwestern region, which aligned with the spatial distribution of the LEF security evaluation index, showing an overall upward trend. The spatiotemporal differentiation of coordination degrees in Henan Province is evident, with most cities showing improvements in coordination levels. From 2011 to 2012, Luoyang and Pingdingshan in the western part of Henan were in the initial coordination stage, but their coupling coordination degrees declined after 2013. Zhumadian, Nanyang, and Xinyang gradually improved their coupling coordination from a state of disorder in 2011 to coordination by 2020. Hebi experienced a mild disorder state from 2011 to 2016, but its coupling coordination degree increased to an average of 0.449 from 2017 to 2020. The coupling coordination degrees in Puyang and Xinxiang remained unchanged. The coupling coordination degree of Shangqiu rose from 0.458 in 2011 to 0.707 in 2020, while Jiyuan mostly stayed in a state of mild disorder. Overall, there are significant regional differences in the coupling coordination degree of the LEF in Henan Province. The coupling coordination degree generally increases from the west to the east, with the western part in a state of disorder and the central and eastern parts in a stage of coordination. From 2011 to 2020, the coupling coordination of the LEF in the central region showed a declining trend, remaining at a barely coordinated stage. Despite the minimal difference in coordination levels between the central and eastern regions, the central region showed a downward trend. This indicates that although the central and eastern regions have favorable natural conditions and advanced agriculture, the levels of coordination in the LEF were significantly affected by economic development, land expansion, and high resource demand.

3.3. Analysis of Factors Affecting Coupling Coordination

The coupling coordination degree of the LEF was used as the explained variable, while the indicators within each subsystem were used as explanatory variables. The correlations between the coupling coordination degree of the system and each factor were calculated (

Table 5. System coordination degree and correlation with each subsystem indicator.

System Items	Evaluation Item	Correlation Degree	Overall Ranking
Land Subsystem	Per Capita Arable Land Area	0.901	9
	Effective Irrigation Area	0.962	2
	Crop Sowing Area	0.968	1
	Population Density	0.882	12
	Rural Household Disposable Income	0.574	18
	Per Capita GDP	0.640	17
Ecological Subsystem	Per Capita Green Area	0.844	13
	Green Coverage of Built-up Areas	0.958	3
	Agricultural Fertilizer Use	0.937	5
	Agricultural Plastic Film Use	0.927	8
	Pesticide Use	0.892	11
Food Subsystem	Grain Output	0.932	7
	Vegetable Output	0.938	4
	Melon and Fruit Output	0.935	6
	Meat Output	0.894	10
	Natural Population Growth Rate	0.840	14
	Urban Residents Engel’s Coefficient	0.822	15
	Rural Residents Engel’s Coefficient	0.818	16

). From the results of the correlation values, it can be seen that the factors in the grain resource subsystem have the greatest overall impact on the coupling coordination degree of the LEF, all exceeding 80%. The overall influence of the factors in the grain subsystem was greater than that of the land subsystem and the ecological subsystem, indicating that grain production and ecological protection play a crucial role in improving the coupling coordination degree of the system.

In the land resource subsystem, the top three factors in terms of correlation ranking were crop sowing area, effective irrigation area, and per capita arable land area, all of which exceeded 90%. The first two factors were related to production security. The reasonable allocation and efficient use of land resources, along with sufficient arable land and irrigation facilities, could enhance land production efficiency and are vital to the coupling coordination degree of the system. In the ecological subsystem, the correlations with the green coverage of built-up areas, agricultural fertilizer usage, and agricultural plastic film usage also exceed 90%. The green coverage of built-up areas represents ecological infrastructure, contributing to the improvement in the ecological environment and having a significant positive relationship with the coupling coordination degree of the ecological subsystem. Agricultural fertilizer and plastic film usage represent ecological pressure, with their high correlation reflecting the balance between agricultural production efficiency and environmental protection. While pursuing production efficiency, attention must also be paid to the ecological environment and sustainable development. In the food subsystem, the correlations with various food production volumes were all above 85%. Grain output was an important indicator of a region’s food security, while vegetable, melon, fruit, and meat outputs indicated the living standards of the residents in a region. Their high correlation indicated that food production capacity positively influences the CCD of the grain subsystem, reflecting the importance of agricultural product supply in meeting residents’ needs and promoting economic development.

4. Discussion

4.1. Spatial Pattern Analysis of Coupling Coordination Degree

This study explores the coupling coordination degree of LEF in Henan Province from the perspective of dietary structure. With the acceleration of urbanization and population growth, the imbalance in regional development has become more prominent. The dietary structure of residents is gradually shifting from a traditional grain-based diet to a diversified diet rich in meat, eggs, and dairy products. This transformation has put forward higher demands on grain production and land in Henan Province [33]. The research findings indicate that areas with higher coupling coordination degrees are mainly concentrated in Zhumadian and Xinyang in the southern part of Henan Province. The level of coupling coordination decreases from the east to the west, a conclusion that is basically consistent with the research by He [34]. These regions have superior geographical locations and good economic infrastructure. In contrast, areas with lower coupling coordination degrees are mainly distributed in the western part of Henan Province, especially in Sanmenxia and Jiyuan. This is mainly due to the constraints of natural geographical conditions, lower levels of economic development, and unreasonable industrial structures, which lead to a lower degree of coupling and coordination between the various subsystems. Therefore, as major grain-producing areas, interventions should be made in the coupling and coordination process of the land use subsystem through the implementation of environmental protection measures and public awareness [35]. Most of the prefecture-level cities’ LEF systems are in the primary coordination stage, as there is a mismatch between food supply and demand, mainly manifested by the fact that food production cannot fully adapt to the increasingly diversified food consumption needs of residents. The coordination level remains at the primary stage, mainly concentrated in Zhengzhou and Xuchang in the central part of Henan, mainly because the evaluation index of the grain subsystem in these areas is relatively low, which affects the coupling coordination degree of the system. This is similar to the research results of Luo on the food subsystem [36]. Efforts should be increased to promote healthy eating, paying more attention to residents’ dietary nutrition and health, as well as the diversification of diets [37].

4.2. Analysis of Influencing Factors for Coordinated System Development

Through the analysis of the influencing factors of the LEF system’s coupling coordination degree in Henan Province, it is known that the correlation between various factors of the grain subsystem and the ecological subsystem and the LEF system’s coupling coordination degree is above 80%. This implies that the indicators of these two systems will significantly affect the coupling coordination level of Henan Province’s LEF system. Key influencing factors include crop sowing area, effective irrigated area, and green coverage rate in built-up areas. The government should increase funding to support agricultural production, encourage policies that incentivize farmers to expand crop sowing, and invest in water conservancy projects and irrigation facility maintenance [38]. Under the transformation of residents’ dietary structures, the contradiction between the food supply side and the residents’ consumption side is prominent. Therefore, it is necessary to scientifically plan the grain production in Henan Province, optimize the land use structure, improve the ecological environment, and achieve high-quality green grain production [39]. Due to the differences in geographical location and production conditions, each prefecture-level city has its unique positioning. In line with the research results of this paper, for areas such as Zhengzhou and Puyang, it is essential to vigorously develop their industry and strengthen grain circulation and trade; for cities like Nanyang, Zhoukou, and Shangqiu, it is important to fully leverage their geographical advantages, enhance agricultural infrastructure and ecological protection, and increase grain yield. Economically lagging areas can promote their development by improving the level of industrialization, achieving the rational use of regional resources, and thus promoting the coordinated development of the LEF system in Henan Province.

4.3. Limitations

Due to limitations in the data acquisition and research methods, this research also has some shortcomings. First, the research period was from 2011 to 2020, which is relatively short. In subsequent studies, the time span can be further extended to provide more reliable suggestions and a basis for the coordinated development of the LEF system in Henan Province. Second, this study only focuses on the coupling relationship between land, ecology, and grain at the city level, lacking micro-level analysis at the county level. Finally, the selection of indicators needs to be improved and optimized. The LEF is a complex system influenced by multiple factors. Based on the availability of data, the selected evaluation index system is not comprehensive enough. In future research, it should be further perfected.

5. Conclusions and Suggestion

This study analyzed the LEF security and its coupling coordination across 18 cities in Henan Province from 2011 to 2020. The analysis included an evaluation of the overall LEF security index, the security indices of its subsystems, the degree of coupling, and the degree of coupling coordination, leading to the following conclusions:

(1)

Development Index: The security levels of the LEF and its subsystems in Henan Province’s 18 cities were generally low, with overall security evaluation indices below 0.85. The trends in the comprehensive development index were consistent across Eastern, Southern, Western, Northern, and Central Henan. The comprehensive evaluation indices of the subsystems peaked in 2018, indicating strong interconnections among subsystems and an overall upward trend.

(2)

Coupling Coordination Degree: From 2011 to 2020, the coupling degree of the LEF across Henan’s cities ranged from 0.277 to 0.996, with significant variations among different cities. Most cities experienced slight fluctuations in their coupling degree, exhibiting a generally stable development trend. The coupling coordination degree gradually improved over time, showing a spatial increase from Western to Eastern Henan. The coordination degree improved from primarily near-disorder and barely coordinated development in 2011 to predominantly barely coordinated development in 2020. However, the overall level of coupling coordination remained low.

(3)

Influencing Factors: From 2011 to 2020, the coupling coordination degree of the LEF in Henan Province was most strongly associated with the food subsystem, followed by the ecological subsystem, and lastly, the land subsystem. Analysis of the influencing factors with strong correlations revealed that key factors include crop sowing area, effective irrigated area, green coverage rate in built-up areas, vegetable production, agricultural fertilizer usage, and fruit production.

In summary, the degree of coupling coordination in various prefecture-level cities of Henan Province is not high. Therefore, when formulating policies in the future, the Henan provincial government should carefully consider regional development disparities, optimize the allocation of resources, and, while increasing grain yield, also focus on the protection of the ecological environment.

Based on the main factors affecting the coordination of the LEF system in Henan Province, the following suggestions are proposed:

(1)

Cities in the stage of disequilibrium must make rational use of land resources and strengthen the management of land, ecology, and grain. Among them, Nanyang City, as a major grain-producing area, must strictly control its land ecological security, optimize the structure of land use, ensure the quantity and quality of arable land, and, at the same time, promote advanced technology to improve the efficiency of land use.

(2)

Cities in the over-coordination stage are mainly concentrated in Zhengzhou, Luoyang, and Xuchang, where the rapid development of urbanization has led to a decline in the quantity and quality of land, and the ecological environment has been damaged. Leveraging scientific and technological power to reduce environmental pollution and developing green agriculture, as well as the government’s ecological and environmental protection policies to promote ecological protection, will encourage a transformation towards a coordinated development model.

(3)

Cities in the coordinated development stage should pursue higher-quality development while maintaining their current development. Grain-producing areas such as Xinyang and Zhumadian should comprehensively strengthen the ecological protection of arable land, develop modern agriculture, and reduce the use of chemical fertilizers and pesticides. At the same time, according to the resource advantages of each city, they should formulate targeted development strategies that are appropriate to local conditions to promote the sustainable use of resources and achieve the green and high-quality development of the region.