A Study on Spatiotemporal Differentiation Characteristics of Ecological Security and Sustainable Utilization of Cultivated Land in Sichuan Province Based on Emergy–Ecological Footprint Model

Abstract

Ecological security and sustainable utilization of cultivated land are the fundamental guarantee for agricultural production and a key link in maintaining ecological balance. Based on the emergy analysis theory, this study adopted the modified emergy–ecological footprint model, taking counties as the evaluation unit, to analyze the spatiotemporal differentiation characteristics of ecological security and sustainable utilization of cultivated land in Sichuan Province from 2010 to 2020. The results indicated that (1) in hilly regions, emergy output increased the most, despite a decrease in emergy input. Overall, both emergy input and output of cultivated land in Sichuan Province showed an increasing trend, with average growth rates of 6.3% and 32.6%, respectively. (2) The overall ecological security of cultivated land in the province was at risk. The at-risk area was mainly concentrated in plain, hilly and peripheral mountainous regions. The spatial pattern presented an evolutionary characteristic where the safe area contracted northwestward while the at-risk area expanded northwestward–southwestward. (3) The overall sustainable utilization of cultivated land in the province degraded from strong to weak. The spatial pattern showed an evolutionary characteristic where plain, hilly and peripheral mountainous regions tended to stabilize, while southwestern mountainous regions and northwestern plateau regions degraded. The ecological security and sustainable utilization of cultivated land in Sichuan Province both show a degradation trend. It is necessary to optimize the input structure of cultivated land systems, improve agricultural production efficiency, and formulate targeted optimization and regulation measures in combination with the actual conditions of each region.

1. Introduction

As global climate change intensifies and the world population continues to grow, sustainable utilization of cultivated land resources has become a core issue for the international community to address the dual challenges of food security and ecological security. Data from the Food and Agriculture Organization (FAO) show that approximately 33% of global cultivated land faces the risk of productivity decline due to over-exploitation, soil degradation and pollution [1].

As the world’s largest grain producer and consumer, China faces systemic degradation of cultivated land driven by high-intensity input. This degradation is characterized by non-agriculturalization [2,3], non-grainization [4], fragmentation [5,6], marginalization [7,8] and ecological degradation [9,10]. Since China first proposed keeping the 1.2 million km² cultivated land red line and elevated cultivated land protection to the national strategic level, it has emphasized achieving efficient utilization and ecological restoration of cultivated land resources through technological empowerment. As the only major grain-producing province in western China, an important water conservation area in the upper reaches of the Yangtze River, and an important water supply area in the upper reaches of the Yellow River, sustainable utilization of cultivated land in Sichuan Province is not only related to regional food security, but is also the key to maintaining the stability of the ecosystem in the upper reaches of the two major rivers in the country. However, relevant data [11,12] and studies [13] show that cultivated land in the province is concentrated in eastern basin, low mountain and hilly regions. Medium- and low-yield fields are mostly concentrated in basin hilly region and peripheral mountainous region. Per capita cultivated land is only 0.06 hm², far below the national average. Cultivated land resources in Sichuan Province exhibit the characteristics of low per capita possession, uneven distribution and quality differentiation. Sichuan still faces many challenges in maintaining quantity, improving quality, protecting ecology, and achieving sustainable utilization of cultivated land.

In recent years, China has experienced a rapid urbanization stage. Urban expansion has encroached on a large amount of high-quality fertile land. Meanwhile, affected by rapid population growth, grain demand has increased rigidly. The man–grain–land contradiction has intensified. Ecological damage and reduced productivity of cultivated land are increasingly serious problems. Under such circumstances, scientifically evaluating the ecological security of regional cultivated land systems and further exploring regional sustainable utilization of cultivated land have become research hotspots. In 1988, Odum [14] proposed the emergy analysis theory, opening up a new approach for quantitative research on ecosystems. In the 1990s, Rees [15] proposed the ecological footprint model and Wackernagel [16] improved it. It has become an important method for quantitative research on regional ecological security [17,18,19,20,21,22] and sustainable development [23,24,25,26,27,28]. On the basis of the traditional ecological footprint model, researchers have revised it in various ways. These include setting equivalence factors [29], adjusting regional yield factors [30,31], and developing new types such as water footprint, carbon footprint and nitrogen footprint [32,33,34]. To avoid controversies over parameters such as equivalence factor and yield factor in the traditional ecological footprint model [35], Zhao et al. [36] first introduced emergy analysis theory into ecological footprint model research. They used solar transformity to calculate per capita solar emergy of various regional consumption items, and then converted it into emergy ecological footprint. The ecological footprint model based on emergy analysis provides a common measurement standard for evaluating environmental resources and economy. It adopts relatively stable parameters such as solar transformity and emergy density. It converts natural resources and human resource use into solar emergy for uniform comparison. This makes the results more comparable and reflects regional characteristics more truly and objectively [35]. Therefore, the emergy–ecological footprint model has been widely applied and practiced in various research fields [37,38,39,40,41,42]. Among them, some scholars have applied it to cultivated land for in-depth research and proposed regional improvement methods. However, internationally, there have been few studies specifically applying the emergy–ecological footprint model to cultivated land. Based on the emergy ecological footprint model, Liu et al. [43] established a new modified ecological footprint model. It took storage energy of soil, solar radiation and chemical energy of rainfall as the natures of cropland ecological capacity, and they studied the ecological footprint of croplands in Jiangsu Province. Wang et al. [44] used the traditional ecological footprint model and two modified ecological footprint models (regional emergetic ecological footprint and cropland emergetic ecological footprint) to evaluate the utilization of cultivated land resources in Xinjiang from a time series, and analyzed the advantages and disadvantages of the three models. Tong et al. [45] applied a modified emergy–ecological footprint model, revised yield factor of the cultivated land from the perspective of national hectare and provincial hectare, and analyzed the dynamic changes in sustainable utilization of the cultivated land in Zhejiang Province.

The emergy–ecological footprint model has limitations because it does not include the input, output and circulation of biological materials [35] and fails to reflect the actual required biological productive area [46]. For this reason, based on the emergy–ecological footprint model, this paper adds yield factor and multiple-crop index for revision, aiming to make the evaluation model more comprehensive and improved. This paper takes a county in Sichuan Province as the research unit. Based on the modified emergy–ecological footprint model, it measures the emergy input and output of cultivated land system from 2010 to 2020. It analyzes ecological carrying capacity and ecological footprint of regional cultivated land. It uses ecological pressure index (EFI) and modified emergy sustainability index (ESI) to evaluate ecological security and sustainable utilization of cultivated land, and analyzes the differentiation characteristics of the two from temporal and spatial dimensions. Then, Moran’s I is introduced to analyze the evolution characteristics of the spatial pattern of sustainable utilization of cultivated land. The study provides scientific basis and decision support for realizing sustainable utilization of cultivated land resources in Sichuan Province (Figure 1). The structure of this paper is organized as follows. Section 2 (Materials and Methods) begins with an introduction to the case study area, Sichuan Province, followed by a description of the data sources employed, and concludes with a detailed elaboration of the modified emergy–ecological footprint model. Section 3 (Results) systematically presents the spatiotemporal differentiations of ecological security and sustainable utilization of cultivated land. In Section 4 (Discussion), the findings are analyzed and compared with those of similar studies. Finally, Section 5 (Conclusions) summarizes the key insights and proposes the study limitation and future prospects.

2. Materials and Methods

2.1. Study Area Overview

Sichuan Province is located in southwestern China and the upper reaches of the Yangtze River, between 97°21′ E~108°33′ E and 26°03′ N~34°19′ N, with a total land area of 486,000 km². The terrain is high in the west and low in the east, sloping from northwest to southeast. As one of the 13 major grain-producing provinces in China, the only major grain-producing province in western China, and a major grain-producing province in southern China, Sichuan has a current cultivated land area of 52,526 km², concentrated in eastern basin and low mountain hilly region. In 2024, its total grain output reached 36.34 billion kg. Led by the construction of a higher-level Tianfu Granary in the new era, grain production of Sichuan has reached a new level. Meanwhile, Sichuan is an important water conservation area in the upper reaches of the Yangtze River and an important water supply area in the upper reaches of the Yellow River. It is listed as a global biodiversity hotspot, possessing ecological functions such as climate regulation, soil and water conservation, and biodiversity conservation. Thus, it holds an irreplaceable strategic position in the national pattern of food security and ecological security. Based on factors such as regional climate types, topography and geomorphology, soil and water conditions, and farming systems, this study divides the province into five regions: plain region, hilly region, peripheral mountainous region, southwestern mountainous region and northwestern plateau region. Since the five main urban districts of Chengdu (Jinjiang, Qingyang, Jinniu, Wuhou and Chenghua), and East District and West District of Panzhihua are non-agricultural counties with little cultivated land area, they are not included in the study area (Figure 2).

2.2. Data Sources

The data used in this study and their sources are shown in

Table 1. Data sources.

Data Type	Data Name	Year	Sources
Vector data	Administrative divisions of counties in Sichuan	2023	Southwest Mountain Science Data Center, National Earth System Science Data Center, National Science & Technology Infrastructure of China (http://www.geodata.cn, accessed on 8 November 2024)
	Annual solar radiation	2000–2022	Southwest Mountain Science Data Center, National Earth System Science Data Center, National Science & Technology Infrastructure of China (http://www.geodata.cn, accessed on 1 November 2024)
	Annual precipitation	2010, 2015, 2020	National Earth System Science Data Center, National Science & Technology Infrastructure of China (http://www.geodata.cn, accessed on 8 November 2024)
Raster data	DEM	2019	National Earth System Science Data Center, National Science & Technology Infrastructure of China (http://www.geodata.cn, accessed on 29 October 2024)
	Soil thickness	2010–2018	National Earth System Science Data Center, National Science & Technology Infrastructure (http://www.geodata.cn, accessed on 1 November 2024) [47]
	Soil bulk density	2010–2018	National Earth System Science Data Center, National Science & Technology Infrastructure (http://www.geodata.cn, accessed on 1 November 2024) [47]
	Soil organic carbon	2010–2018	National Earth System Science Data Center, National Science & Technology Infrastructure (http://www.geodata.cn, accessed on 1 November 2024) [47]
	Soil erosion	2010, 2015, 2020	Science Data Bank (https://doi.org/10.57760/sciencedb.12876, accessed on 23 November 2024) [48]
Socio-economic data	Net irrigation water quota	2021	Water Quota of Sichuan Province (Sichuan Provincial Government Letter [2021] No. 8)
	Seeding amount of crops	-	National and Sichuan province technical guidelines for crop production
	Global average yield of crops	2010, 2015, 2020	FAOSTAT (https://www.fao.org/faostat/, accessed on 11 February 2025)
	Cultivated land area, total power of agricultural machinery, agricultural diesel consumption, usage of agricultural chemical fertilizers, pesticide usage, usage of agricultural plastic film, agricultural workforce, crop yield	2010, 2015, 2020	Sichuan Statistical Yearbook, Sichuan Agricultural Statistical Yearbook, and Sichuan Rural Statistical Yearbook

. ArcGIS 10.6 software was used to preprocess the data, such as projection transformation to make the coordinate system consistent, cropping the area and converting vector data to raster, etc.

2.3. Methods

2.3.1. Compilation of Emergy Analysis Table

To uniformly measure the energy and material flows of regional cultivated land systems and calculate emergy ecological carrying capacity and emergy ecological footprint accordingly, this study first compiles an emergy analysis table. In emergy analysis theory, solar emergy is defined as the total amount of solar energy directly or indirectly consumed in the formation process of any resource, product, or service, measured in solar emjoules (sej) [49]. Based on this, combined with the characteristics of cultivated land use, the energy flow of the cultivated land system is clarified from both input and output aspects, and emergy elements are selected. Among them, emergy input elements include four categories: renewable environmental resources, non-renewable environmental resources, non-renewable industrial auxiliary energy, and renewable organic energy. Emergy output elements include food crops and cash crops. Physical quantity or converted energy of elements are used as raw data, which is converted into emergy through solar transformity. Emergy input and emergy output are the sum of emergy of the included elements. E_U = E_R + E_N + E_F + E_T, and E_Y = E_Y1 + E_Y2. The calculation formulas for raw data, energy conversion coefficients, and solar transformity involved are shown in

Table 2. Analysis of emergy input and output of cultivated land system.

Item			Formula	Energy Conversion Coefficients	Solar Transformity (sej/J or sej/g)
Emergy input /EU	Renewable environmental resources/ER	Solar radiation	Cultivated land area (m2) × annual solar radiation (J·m−2·a−1)	-	1 [49]
		Rainwater chemical energy	Cultivated land area (m2) × precipitation (m) × rainwater density (106 g/m3) × rainwater Gibbs free energy (J/g)	Rainwater Gibbs free energy (4.94 J/g) [49]	6.36 × 103 [50]
		Rainwater potential energy	Cultivated land area (m2) × average altitude (m) × precipitation (m) × rainwater density (103 kg/m3) × gravitational acceleration (9.8 m/s2)	-	1.0909 × 104 [50]
		Farmland irrigation water	Farmland irrigation water (m3/a) × water density (106 g/m3) × Gibbs free energy of river water (J/g)	Gibbs free energy of river water (4.77 J/g) [49]	5.01 × 104 [51]
		3% topsoil energy	Cultivated land area (m2) × effective soil thickness (mm) × soil bulk density (g/cm3) × topsoil organic matter content (g/kg) × topsoil Gibbs free energy (J/g) × 3%	Topsoil Gibbs free energy (2.26044 J/g) [49]	6.25 × 104 [43,50]
	Non-renewable environmental resources/EN	Topsoil loss energy	Cultivated land area (m2) × soil erosion rate (g·m−2·a−1) × topsoil organic matter content (g/kg) × organic matter energy (J/g)	-	6.25 × 104 [49]
	Non-renewable industrial auxiliary energy/EF	Agricultural machinery	Total power of agricultural machinery (kW) × energy conversion coefficient of total power of agricultural machinery (J/kW)	3.60 × 106(J/kW) [52]	7.50 × 107 [53]
		Agricultural diesel	Agricultural diesel consumption (kg) × energy conversion coefficient of agricultural diesel (J/kg)	3.30 × 107(J/kg) [52]	6.60 × 104 [52]
		Agricultural fertilizer	Usage of agricultural chemical fertilizers (in 10,000 tons)	-	2.80 × 109 [53]
		Pesticide	Pesticide usage (in 10,000 tons)	-	1.62 × 109 [53]
		Agricultural film	Usage of agricultural plastic film (in 10,000 tons)	-	3.80 × 108 [53]
	Renewable organic energy/ET	Agricultural labor force	Agricultural workforce (10,000 people) × energy conversion coefficient of agricultural labor force (J/pp)	3.50 × 109(J/pp) [53]	3.80 × 105 [53]
		Seed	Average Seeding amount of a certain crop (kg/m2) × sown area (m2) × energy conversion coefficient of seed (J/kg)	1.60 × 107(J/kg) [54]	6.60 × 104 [54]
Emergy output /EY	Food crops/EY1	Rice	Physical quantity (10,000 tons) × energy conversion coefficient of rice	1.51 × 107(J/kg) [54]	3.59 × 104 [49]
		Wheat	Physical quantity (10,000 tons) × energy conversion coefficient of wheat	1.63 × 107(J/kg) [54]	6.80 × 104 [49]
		Maize	Physical quantity (10,000 tons) × energy conversion coefficient of maize	1.63 × 107(J/kg) [54]	2.70 × 104 [49]
		Soybeans	Physical quantity (10,000 tons) × energy conversion coefficient of soybeans	2.09 × 107(J/kg) [54]	6.90 × 105 [49]
		Potatoes	Physical quantity (10,000 tons) × energy conversion coefficient of potatoes	4.20 × 106(J/kg) [55]	8.30 × 104 [49]
		Sweet potatoes	Physical quantity (10,000 tons) × energy conversion coefficient of sweet potatoes	3.80 × 106(J/kg) [55]	8.30 × 104 [49]
	Cash crops/EY2	Groundnuts	Physical quantity (10,000 tons) × energy conversion coefficient of groundnuts	2.63 × 107(J/kg) [54]	6.90 × 105 [49]
		Rapeseed	Physical quantity (10,000 tons) × energy conversion coefficient of rapeseed	2.63 × 107(J/kg) [54]	6.90 × 105 [49]
		Vegetables	Physical quantity (10,000 tons) × energy conversion coefficient of vegetables	2.50 × 106(J/kg) [54]	2.70 × 104 [49]

Since solar radiation, rainwater potential energy, and rainwater chemical energy are all forms of solar energy conversion, only the maximum value is considered to avoid double counting.

.

2.3.2. Emergy–Ecological Footprint Model of Cultivated Land

1.

Ecological Carrying Capacity of Cultivated Land

Based on emergy theory, ecological carrying capacity of cultivated land (EC) is defined as the biologically productive cultivated land area that provides renewable environmental resources (such as solar radiation and rainwater energy) for human consumption in a region [56]. To evaluate ecosystem functions of cultivated land from different aspects, combined with the research of Shi [56], the yield factor representing biological production is added to modify EC. The formulas are as follows:

$$EC=N\times ec$$

(1)

$$ec={\displaystyle \frac{e}{P}}\times y\times 0.88$$

(2)

$$y=\sum \left({\displaystyle \frac{C_i}{G_i}}\times p_i\right)$$

(3)

EC is the emergy ecological carrying capacity of cultivated land in the study area (hm²); N is the regional population; ec is the per capita ecological carrying capacity of cultivated land (m²); e is the per capita emergy of input elements (sej); P is the global surface emergy density (sej/hm²), with a value of 3.11 × 10¹⁵ sej/hm² [43]; $y$ represents the yield factor of cultivated land, which is the ratio of the agricultural output of a certain region to the global average output, reflecting the efficiency of cultivated land utilization in the region; $C_i$ is the annual average yield of the i-th crop in each county (kg/hm²); $G_i$ is the global annual average yield of the i-th crop (kg/hm²); $C_i∕G_i$ is the yield factor of the i-th crop; $p_i$ is the proportion of the sown area of the i-th crop to the total sown area in the county (%). Considering that 12% of the total biologically productive area needs to be reserved for biodiversity conservation [57], a correction factor of 0.88 is applied.

2.

Ecological Footprint of Cultivated Land

Based on emergy theory, ecological footprint of cultivated land is defined as the biologically productive cultivated land area converted from the solar emergy of agricultural products produced on cultivated land within the study area. [43]. To obtain the real ecological footprint of cultivated land, combined with the research of Wang [46], the model is modified using the multiple-crop index (CI). The formulas are as follows:

$$EF=N\times ef$$

(4)

$$ef={\displaystyle \frac{\sum \left(e_i∕P\right)}{CI}}$$

(5)

EF is the emergy–ecological footprint of cultivated land (hm²); N is the total population; ef is the per capita emergy ecological footprint of cultivated land (m²); $i$ represents types of agricultural product consumption, mainly including 9 categories: rice, wheat, maize, soybeans, potatoes, sweet potatoes, groundnuts, rapeseed and vegetables; $e_i$ is the per capita emergy of the i-th agricultural product (sej); P is the global surface emergy density (sej/hm²); CI is the annual multiple-crop index.

3.

Ecological Pressure Index of Cultivated Land

Ecological pressure index of cultivated land (EFI) is the ratio of ecological footprint to ecological carrying capacity of cultivated land, used to characterize the ecological security of cultivated land in the study area. When 0 < EFI < 1, it indicates that the cultivated land ecology is in a safe state; when EFI > 1, it indicates that the ecological security of cultivated land is threatened. The formulas are as follows:

$$EFI=EF/EC$$

(6)

According to the global ecological environment and socio-economic development status [40], the ecological security of cultivated land is divided into 6 levels, as shown in

Table 3. Classification standards for ecological security of cultivated land.

Level	Index Range	Level	Index Range
Safe	EFI < 0.5	Relatively unsafe	1.0 ≤ EFI < 1.5
Comparably safe	0.5 ≤ EFI < 0.8	Unsafe	1.5 ≤ EFI ≤ 2.0
A bit unsafe	0.8 ≤ EFI < 1.0	At risk	EFI > 2.0

.

4.

Evaluation of Sustainable Utilization of Cultivated Land

This study applies the emergy sustainability index [58] to eco-economic system of cultivated land to evaluate the degree of regional sustainable development of cultivated land. The emergy sustainability index of cultivated land (ESI) is the ratio of net emergy yield ratio (EYR) to environmental load ratio (ELR). Compared with the traditional emergy sustainability index, the modified ESI incorporates both renewable environmental resources and renewable organic energy in the calculation of environmental load ratio. It more accurately reflects the sustainable characteristics of regional cultivated land eco-economic systems [56]. The formulas are as follows:

$$ESI=EYR/ELR$$

(7)

$$EYR=E_Y/\left(E_T+E_F\right)$$

(8)

$$ELR=\left(E_N+E_F\right)/\left(E_R+E_T\right)$$

(9)

ESI is the emergy sustainability index of cultivated land, EYR is the net emergy yield ratio, ELR is the environmental load ratio, $E_Y$ is the emergy output, $E_T$ is the renewable organic energy, $E_F$ is the non-renewable industrial auxiliary energy, $E_N$ is the non-renewable environmental resources, and $E_R$ is the renewable environmental resources. When ESI < 1, the system is a consumption-oriented eco-economic system with high environmental pressure and is in an unsustainable state. When 5 ≤ ESI ≤ 10, a larger value indicates that the system’s economy is more dynamic and has greater development potential, with a higher degree of sustainable development of cultivated land. When ESI > 10, it indicates underdeveloped system economy, insufficient exploitation and utilization of cultivated land resources, and backward agricultural economic level, which is not conducive to agricultural sustainable development. The sustainable utilization of cultivated land is divided into 3 levels according to ESI values, as shown in

Table 4. Classification standards for sustainable utilization of cultivated land.

Level	Index Range
Unsustainable	ESI < 1 or ESI > 10
Weak sustainability	1 ≤ ESI < 5
Strong sustainability	5 ≤ ESI ≤ 10

.

5.

Moran’s I

Moran’s I is an important index for measuring spatial correlation, generally divided into Global Moran’s I and Local Moran’s I. Global Moran’s I tests the presence of significant spatial autocorrelation of a specific attribute value across the entire study area at the macro level. Local Moran’s I identifies the local agglomeration type of each spatial unit relative to its neighboring areas at the micro level. Moran’s I has been widely applied in various research fields to analyze regional spatial correlation. Therefore, by introducing Moran’s I, this study fully considers the spatial autocorrelation of sustainable utilization patterns of cultivated land and conducts in-depth analysis of their evolutionary characteristics. According to ArcGIS software, the Moran’s I statistic is as follows:

$$I={\displaystyle \frac{n{\sum }_{i=1}^n{\sum }_{j=1}^n{w}_{i, j} z_i z_j}{S_0{\sum }_{i=1}^n{z}_i^2}}$$

(10)

$$S_0={{\displaystyle \sum }}_{i=1}^n{{\displaystyle \sum }}_{j=1}^n{w}_{i, j}$$

(11)

$z_i$ represents the deviation of the attribute of element $i$ from its average value $\left(x_i - \overline{X}\right)$; is the spatial weight between element $i$ and element $j$; n equals the total number of elements; and $S_0$ is the sum of all spatial weights.

3. Results

3.1. Analysis of Emergy Composition and Change Characteristics of Cultivated Land System

From 2010 to 2020, the emergy input and output of cultivated land in Sichuan Province increased by 3.85 × 10²¹ sej and 2.61 × 10²² sej, with growth rates of 6.3% and 32.6%, respectively. In terms of regional variation characteristics of emergy input, hilly region showed a negative growth, with a variation amplitude of −2.1%, while the other four regions exhibited positive growth. Southwestern mountainous region had the largest increase, reaching 32.8% (Figure 3). Regarding the composition of input elements, agricultural machinery within non-renewable industrial auxiliary energy was the key factor driving input growth in various regions. Southwestern mountainous region showed the most significant increase in agricultural machinery input, reaching 1.66 × 10⁶%. Topsoil loss, agricultural labor and agricultural film were the main factors causing the decrease in emergy input (

Table 5. Rate of change in emerge input and output of cultivated land system (2010–2020).

Item	Sichuan Province (%)	Plain Region (%)	Hilly Region (%)	Peripheral Mountainous Region (%)	Southwestern Mountainous Region (%)	Northwestern Plateau Region (%)
Solar energy	32.2	−17.2	35.6	49.2	78.6	11.2
Farmland irrigation Water	11.6	−23.8	14.3	35.8	11.2	86.2
3% topsoil energy	9.9	−18.7	25.7	4.3	3.1	5.8
Renewable environmental resources	27.0	−20.0	26.3	46.4	65.8	14.8
Topsoil loss energy	−4.3	−56.1	3.4	−16.7	32.8	−0.5
Non-renewable environmental resources	−4.3	−56.1	3.4	−16.7	32.8	−0.5
Agricultural machinery	1.51 × 106	1.00 × 106	1.65 × 106	1.56 × 106	1.66 × 106	1.32 × 106
Agricultural diesel	8.1	−11.8	−0.4	68.5	27.7	22.9
Agricultural fertilizer	−15.0	−17.6	−15.1	−12.1	−15.2	8.9
Pesticide	−35.2	−48.6	−32.3	−25.0	−24.4	−27.6
Agricultural film	0.3	−1.8	2.3	−38.5	43.9	−27.2
Non-renewable industrial auxiliary energy	144.7	102.3	125.2	219.7	197.3	829.6
Agricultural labor force	−30.0	−17.5	−33.7	−34.1	−21.4	−17.1
Seed	−7.7	−10.6	−18.8	−12.5	135.0	1944.6
Renewable organic energy	−22.4	−15.9	−27.3	−26.5	−8.8	−9.2
Emergy input	6.3	4.3	−2.1	9.6	32.8	26.3
Rice	−4.3	−43.0	2.9	30.2	−22.4	555.0
Wheat	−55.8	−51.4	−62.8	−32.3	−27.6	51.0
Maize	49.4	179.7	41.0	33.1	94.9	13.9
Soybeans	51.1	124.5	40.5	84.9	42.8	−8.5
Potatoes	105.3	119.3	170.4	420.6	16.3	35.1
Sweet potatoes	−23.8	7.8	−26.7	−17.7	−26.6	2508.6
Food crops	10.1	−6.1	7.1	38.0	17.1	23.8
Groundnuts	18.8	60.1	19.3	0.7	29.4	35.5
Rapeseed	53.6	19.6	66.3	58.1	−17.8	100.2
Vegetables	41.2	31.9	34.9	56.5	73.3	128.5
Cash crops	45.4	23.3	53.0	43.7	2.3	103.8
Emergy output	32.6	14.8	36.0	41.7	10.9	72.0

).

Province-wide emergy output showed positive growth, with hilly region having the largest increase (1.96 × 10²² sej) and northwestern plateau region showing the most prominent growth rate (72.0%). Specifically, the emergy growth of cash crops was the main factor driving the increase in emergy output across regions, such as northwestern plateau region with an increase of 103.8%. Among cash crops, outputs of rapeseed and vegetables showed a significant increasing trend. Among food crops, potatoes and corn had notable growth, while outputs of wheat and sweet potatoes decreased significantly.

The results showed that with socio-economic development and improvements in agricultural science and technology, agricultural machinery has gradually become popular in agricultural production, possibly leading to the replacement of some traditional agricultural labor. The reduction in topsoil loss and input of production materials such as agricultural film and pesticides indicated that awareness of ecological environment protection in agricultural production has gradually gained attention.

3.2. Analysis of Ecological Security Characteristics of Cultivated Land

3.2.1. Changes in Ecological Security of Cultivated Land

In 2010, 2015 and 2020, the average ec values in Sichuan Province were 335.4 m², 461.2 m² and 362.0 m², respectively, while the average ef values were 1311.5 m², 2906.1 m² and 2136.8 m², respectively. The average EFI values were 3.91, 6.30 and 5.90 (

Table 6. Changes in ecological security of cultivated land in Sichuan Province.

Year	2010						2015						2020
Region	Sichuan Province	Plain Region	Hilly Region	Peripheral Mountainous Region	Southwestern Mountainous Region	Northwestern Plateau Region	Sichuan Province	Plain Region	Hilly Region	Peripheral Mountainous Region	Southwestern Mountainous Region	Northwestern Plateau Region	Sichuan Province	Plain Region	Hilly Region	Peripheral Mountainous Region	Southwestern Mountainous Region	Northwestern Plateau Region
Population /10,000 people	8042.1	1335.1	4338.4	1065.4	517.2	203.9	8204.0	1386.2	4386.4	1089.4	533.6	213.9	8367.5	1811.4	4142.5	977.5	549.1	196.9
EC/106 hm2	2.70	0.38	0.89	0.33	0.34	0.19	3.78	0.42	1.24	0.58	0.46	0.15	3.03	0.30	1.01	0.50	0.48	0.15
EF/106 hm2	10.55	1.61	6.63	1.22	0.37	0.11	23.80	3.23	15.17	3.34	0.92	0.25	17.90	1.79	10.18	2.00	0.58	0.17
ec/m2	335.4	283.3	204.5	309.8	651.6	932.1	461.2	302.7	282.6	535.2	869.8	705.3	362.0	168.3	244.0	515.2	879.5	752.4
ef/m2	1311.5	1206.6	1527.9	1141.1	706.1	542.3	2906.1	2328.2	3458.0	3061.5	1731.3	1169.7	2136.8	990.9	2457.6	2043.1	1058.8	868.2
EFI	3.91	4.26	7.47	3.68	1.08	0.58	6.30	7.69	12.24	5.72	1.99	1.66	5.90	5.89	10.07	3.97	1.20	1.15
Ecological security level	At risk	At risk	At risk	At risk	Relatively unsafe	Comparably safe	At risk	At risk	At risk	At risk	Unsafe	Unsafe	Unsafe	At risk	At risk	At risk	Relatively unsafe	Relatively unsafe

). Over the decade, the overall ecological security of cultivated land in the province remained at risk. And ec, ef and EFI all showed a trend of first increasing and then decreasing (Figure 4).

At the regional scale, ec and ef decreased in plain region. In northwestern plateau region, ec decreased while ef increased. Both ec and ef increased in hilly region, peripheral mountainous region and southwestern mountainous region. Among these, southwestern mountainous region had a significant increase in ec (228.0 m²). Hilly region and peripheral mountainous region showed prominent increases in ef, reaching 970.2 m² and 947.6 m², respectively. During the 10 years, EFI values in plain region, hilly region and peripheral mountainous region remained above 2.0 and showed an upward trend. Their ecological security of cultivated land was at risk with increasing risks. Southwestern mountainous region and northwestern plateau region degraded from relatively unsafe and relatively safe to unsafe, respectively, and then improved to relatively unsafe.

At the county scale, counties with safe and relatively safe levels first decreased and then increased, while those with unsafe and at-risk levels first increased and then decreased. Northwestern plateau region consistently retained a certain number of counties with safe and relatively safe levels. Plain region, hilly region and peripheral mountainous region faced prominent contradictions in cultivated land resources, with no counties achieving safe or relatively safe levels during the study period (

Table 7. The quantitative changes in ecological security of cultivated land in counties of Sichuan Province.

Year	2010						2015						2020
Region	Sichuan Province	Plain Region	Hilly Region	Peripheral Mountainous Region	Southwestern Mountainous Region	Northwestern Plateau Region	Sichuan Province	Plain Region	Hilly Region	Peripheral Mountainous Region	Southwestern Mountainous Region	Northwestern Plateau Region	Sichuan Province	Plain Region	Hilly Region	Peripheral mountainous region	Southwestern Mountainous Region	Northwestern Plateau Region
Safe	15	0	0	0	1	14	3	0	0	0	0	3	1	0	0	0	0	1
Comparably safe	13	0	0	0	9	4	2	0	0	0	0	2	10	0	0	0	0	10
A bit unsafe	6	0	0	0	3	3	3	0	0	0	0	3	3	0	0	0	1	2
Relatively unsafe	11	0	0	2	2	7	10	0	0	0	5	5	25	0	1	3	16	5
Unsafe	6	0	0	1	4	1	12	0	0	0	6	6	8	0	0	2	3	3
At risk	123	22	68	30	1	2	146	22	70	33	9	12	129	22	69	28	0	10

).

Analysis combined with changes in cultivated land emergy showed that the combined effect of increased crop yield per unit area and decreased multiple-crop index exceeded the contribution of renewable environmental resource increments, intensifying cultivated land ecological pressure in hilly region, peripheral mountainous region and southwestern mountainous region. In addition, plain region and northwestern plateau region were affected by reduced renewable environmental resources and decreased yield factors, respectively, weakening ecological carrying capacity of cultivated land and further increasing cultivated land ecological pressure (Table 5).

3.2.2. Analysis of Ecological Security Patterns of Cultivated Land

In 2010, safe and relatively safe levels were mainly distributed in northwestern plateau region and southwestern mountainous region, while the at-risk level was concentrated in plain region, hilly region and peripheral mountainous region. In 2015, safe and relatively safe levels were only scattered in northwestern plateau region. The at-risk level covered the entire area of plain region, hilly region and peripheral mountainous region, with parts located in southwestern mountainous region and northwestern plateau region. In 2020, safe and relatively safe levels were still only distributed in northwestern plateau region. The at-risk level was concentrated in plain region, hilly region and peripheral mountainous region, with parts located in northwestern plateau region.

From 2010 to 2015, the ecological security level of cultivated land in southwestern mountainous region and northwestern plateau region decreased significantly. By 2020, ecological security of cultivated land in some counties of southwestern mountainous region and northwestern plateau region improved, while cultivated land in plain region, hilly region and peripheral mountainous region remained under high ecological pressure.

During the study period, the ecological security patterns of cultivated land in Sichuan Province exhibited significant spatial evolution characteristics. Specifically, the area of safe levels contracted northwestward, and the area of at-risk levels expanded northwestward–southwestward. The area of safe levels contracted and aggregated from the edge of northwestern plateau region and southwestern mountainous region to northwestern plateau region. Meanwhile, the area of at-risk levels continued to be contiguous in plain region, hilly region and peripheral mountainous region, and expanded toward the edge of northwestern plateau region (Figure 5).

3.3. Analysis of Sustainable Utilization Characteristics of Cultivated Land

3.3.1. Changes in Sustainable Utilization of Cultivated Land

In 2010, 2015 and 2020, the average EYR values in Sichuan Province were 1.54, 1.48 and 1.96, respectively; the average ELR values were 0.21, 0.46 and 0.52, respectively; and the average ESI values were 7.30, 3.19 and 3.77, respectively. Over the 10-year period, EYR and ELR increased by 28.1% and 147.6%, respectively, indicating an overall shift from strong to weak sustainability of cultivated land in the province (

Table 8. Changes in sustainable utilization of cultivated land in Sichuan Province.

Year	2010						2015						2020
Region	Sichuan Province	Plain Region	Hilly Region	Peripheral Mountainous Region	Southwestern Mountainous Region	Northwestern Plateau Region	Sichuan Province	Plain Region	Hilly Region	Peripheral Mountainous Region	Southwestern Mountainous Region	Northwestern Plateau Region	Sichuan Province	Plain Region	Hilly Region	Peripheral Mountainous Region	Southwestern Mountainous Region	Northwestern Plateau Region
EYR	1.54	2.13	1.59	1.27	0.63	0.32	1.48	1.79	1.71	1.13	0.49	0.31	1.96	2.21	2.26	1.70	0.56	0.41
ELR	0.21	0.29	0.22	0.17	0.19	0.07	0.46	0.66	0.50	0.43	0.39	0.34	0.52	0.61	0.56	0.54	0.44	0.38
ESI	7.36	7.45	7.26	7.26	3.26	4.65	3.19	2.71	3.39	2.59	1.24	0.92	3.77	3.63	4.04	3.12	1.27	1.09
Sustainable utilization level	Strong sustainability	Strong sustainability	Strong sustainability	Strong sustainability	Weak sustainability	Weak sustainability	Weak sustainability	Weak sustainability	Weak sustainability	Weak sustainability	Weak sustainability	Unsustainability	Weak sustainability	Weak sustainability	Weak sustainability	Weak sustainability	Weak sustainability	Weak sustainability

).

At the regional scale, the sustainability of cultivated land in plain region, hilly region and peripheral mountainous region shifted from strong to weak, while southwestern mountainous region and northwestern plateau region maintained weak sustainability. Index results analysis showed that EYR increased in all regions except southwestern mountainous region. In hilly region, it had a significant increase of 45.9%. ELR rose noticeably across all regions. In northwestern plateau region and peripheral mountainous region, it showed prominent growth rates of 454.5% and 212.3%, respectively. ESI exhibited a downward trend in all five regions, and in peripheral mountainous region ESI experienced the most significant decline (Figure 6).

At the county scale, counties with strong sustainability first decreased and then increased, counties with weak sustainability continued to increase, and unsustainable counties first increased and then decreased (

Table 9. The quantitative changes in sustainable utilization of cultivated land in counties of Sichuan Province.

Year	2010						2015						2020
Region	Sichuan Province	Plain Region	Hilly Region	Peripheral Mountainous Region	Southwestern Mountainous Region	Northwestern Plateau Region	Sichuan Province	Plain Region	Hilly Region	Peripheral Mountainous Region	Southwestern Mountainous Region	Northwestern Plateau Region	Sichuan Province	Plain Region	Hilly Region	Peripheral Mountainous Region	Southwestern Mountainous Region	Northwestern Plateau Region
Strong sustainability	77	12	36	17	4	8	12	1	10	1	0	0	16	1	15	0	0	0
Weak sustainability	61	4	18	11	14	14	125	20	58	26	10	11	129	20	52	26	15	16
Unsustainability	36	6	14	5	2	9	39	1	2	6	10	20	31	1	3	7	5	15

). Combined with emergy change analysis, the common factors for ESI decline included increased agricultural machinery input and reduced renewable organic energy (agricultural labor, seeds) (Table 5). In addition, differentiated factors contributed to ESI decline across regions. For example, environmental resource attenuation in plain region; increased agricultural diesel consumption in peripheral mountainous region, southwestern mountainous region, and northwestern plateau region; increased topsoil loss and agricultural film usage in hilly region and southwestern mountainous region; and increased chemical fertilizer application in northwestern plateau region. These factors worked together more strongly than the benefits from increased agricultural output. This caused sustainable utilization of cultivated land to decline to a different degree.

3.3.2. Analysis of Sustainable Utilization Patterns of Cultivated Land

In 2010, strong sustainability areas were concentrated in plain region, hilly region and peripheral mountainous region. Weak sustainability areas were mainly distributed in hilly region, northwestern plateau region and southwestern mountainous region. Unsustainability areas were primarily located in eastern hilly region and northwestern plateau region. In 2015, strong sustainability areas were mainly scattered in hilly region. Weak sustainability areas were predominantly in eastern Sichuan, including plain region, hilly region and peripheral mountainous region, with a few in western Sichuan. Unsustainability areas were concentrated in northwestern plateau region and southwestern mountainous region. In 2020, strong sustainability areas were only scattered in hilly region. Weak sustainability areas included most areas of plain region, hilly region and peripheral mountainous region. Unsustainability areas were mainly concentrated in northwestern plateau region, and the remaining were in adjacent southwestern mountainous region and peripheral mountainous region.

From 2010 to 2015, strong sustainability areas decreased significantly, mainly scattered in hilly region. Weak sustainability areas shifted from scattered distribution to contiguous concentration in plain region, hilly region and peripheral mountainous region. Unsustainability areas expanded to southwestern mountainous region and northwestern plateau region. All counties with strong sustainability in southwestern mountainous region and northwestern plateau region degraded to weak sustainability/unsustainability. It indicated obvious deterioration in cultivated land sustainability (Table 9). From 2015 to 2020, strong sustainability areas slightly increased and concentrated in hilly region. Weak sustainability areas continued to expand, with enhanced contiguity in southwestern mountainous region and northwestern plateau region. Unsustainability areas shrank, and some recovered to weak sustainability.

During the study period, in Sichuan Province, the evolution of sustainable utilization patterns of cultivated land showed spatial characteristics. Changes in plain region, hilly region and peripheral mountainous region tended to stabilize, while sustainability in southwestern mountainous region and northwestern plateau region degraded. In plain region, hilly region and peripheral mountainous region, sustainable utilization of cultivated land decreased but remained in a sustainable state overall. In peripheral mountainous region, multiple sustainability levels transformed to weak sustainability/unsustainability. In southwestern mountainous region and northwestern plateau region, some counties degraded to unsustainability, then gradually recovered to weak sustainability, showing fluctuating degradation (Figure 7).

3.3.3. Spatial Correlation Analysis

• Global Spatial Autocorrelation Analysis

In 2010, 2015 and 2020, Global Moran’s I for sustainable utilization of cultivated land were 0.1777, 0.4477 and 0.4326, respectively (p < 0.01). These values indicated positive spatial correlations. There was a spatial agglomeration trend in sustainable utilization of cultivated land in Sichuan Province. Among them, the spatial correlation was weak in 2010, while strong positive spatial correlations were observed in 2015 and 2020. In 2010–2020, Global Moran’s I showed a significant upward trend, indicating a continuous enhancement of spatial agglomeration effects in sustainable utilization of cultivated land in Sichuan (Figure 8).

2.

Local Spatial Autocorrelation Analysis

In 2010–2020, the number of counties with High–High and Low–Low clusters in sustainable utilization continued to increase, while the number of counties with High–Low and Low–High clusters generally decreased. This indicated that spatial clustering effects of high-value and low-value areas significantly strengthened, and the overall spatial heterogeneity weakened. During the study period, the Low–Low clusters showed enhanced contiguity and eastward expansion in southwestern mountainous region and northwestern plateau region. The High–High clusters concentrated in plain region and southern hilly region. The Low–High and High–Low outliers remained isolated (Figure 9). The results showed that the radiation capacity of high-value areas and the catch-up effect of low-value areas gradually emerged, and local High–Low and Low–High outliers transformed into High–High or Low–Low cluster patterns. Low-value areas concentrated in northwestern plateau region and southwestern mountainous region, while high-value areas concentrated in plain region and surrounding hilly region. The spatial pattern of clusters for sustainable utilization of cultivated land shifted from scattered to concentrated distribution, and high-value and low-value areas showed east–west differentiation characteristics.

4. Discussion

4.1. Analysis of Causes for Changes in Emergy Input and Output of Cultivated Land

The emergy calculation results of the cultivated land system from 2010 to 2020 show that the emergy input in hilly region decreased, while its emergy output increased the most. In terms of input elements, the reduced parts included agricultural production materials (agricultural diesel, chemical fertilizers, pesticides) and renewable organic energy (agricultural labor, seeds). Among these, agricultural labor decreased the most, while agricultural machinery increased the most. Studies [59,60,61] indicate that the contribution rate of agricultural machinery to agricultural output improvement is much higher than that of production factors such as land and labor. Therefore, despite the negative growth in emergy input in hilly region, driven by the structural optimization of agricultural machinery input and technological progress, the growth value of emergy output still reached the highest level in the province. Its emergy input intensity and output efficiency showed significant asynchronous growth characteristics, and the marginal benefits of input elements exhibited unique regional differences.

Agricultural machinery input for cultivated land in the province surged, while topsoil loss, agricultural labor, and agricultural film were the main factors causing the reduction in emergy input. To some extent, these changes were all driven by policy orientation. In 2011, the People’s Government of Sichuan Province introduced policies [62] to promote agricultural mechanization. By strengthening agricultural machinery infrastructure, increasing financial subsidies, optimizing financial services, and implementing tax incentives, it provided institutional guarantees for the increase in total agricultural machinery. In addition, studies [63] show that there is a significant substitution relationship between agricultural machinery and labor. The purchase subsidy policy not only amplified the substitution effect of agricultural machinery on labor, but also significantly improved the level of agricultural mechanization. In 2015, the Ministry of Agriculture and Rural Affairs launched national agricultural non-point source pollution control [64]. It required reducing chemical fertilizers and pesticides, promoting soil testing and formulated fertilization, and improving agricultural film recovery rates. Those policies guided the reduction, efficiency improvement and green transformation of agricultural production factor inputs.

4.2. Analysis of Causes for Dynamic Changes in Ecological Security and Sustainable Utilization of Cultivated Land

In 2010–2020, EFI showed in Sichuan an upward trend in all regions. It meant the ecological pressure on cultivated land continued to intensify. The main reasons are the increase in crop yield per unit area, the reduction in renewable environmental resources, and the decrease in multiple-crop index and yield factors. At the same time, the spatial pattern of ecological security of cultivated land was characterized by the contraction of the safe level to the northwest and the expansion of the at-risk level to the northwest–southwest. This may be the result of the combined effects of policy intervention, human activities and topographic constraints. In 2018, Sichuan clarified the scope of ecological conservation red lines [65], which are mainly distributed in the northwestern plateau region, southwestern mountainous region and peripheral mountainous region. During the study period, the survival of counties with ecological security of cultivated land in northwestern plateau region may depend on strict ecological protection policies. The expansion of the at-risk level area is affected by agricultural development in southwestern mountainous region and human interference in the marginal zone of northwestern plateau region.

The ESI of the five regions showed a downward trend. The common factors of the trend are the increase in agricultural machinery input and the reduction in renewable organic energy. The main factors are the attenuation of environmental resources and the increase in the use of agricultural materials (agricultural diesel, agricultural film and chemical fertilizers). The combined effect of these factors leads to varying degrees of degradation in sustainable utilization of cultivated land in each region. The spatial evolution of sustainable utilization of cultivated land was characterized by the stabilization of plain region, hilly region and peripheral mountainous region, and the degradation of southwestern mountainous region and northwestern plateau region. Cultivated land in plain and hilly regions maintained sustainable development. It relies on relatively favorable terrain and intensive management. In northwestern plateau region and southwestern mountainous region, it showed fluctuating changes due to the fragility of the plateau and mountainous areas and the dynamic intervention of ecological protection policies. In the future, policy measures need to be optimized according to topographic differences.

The hotspots of declining ecological security in cultivated land identified in this study highly overlap with areas of rapid urbanization and traditional agricultural transformation zones. This finding parallels Carter et al.’s [66] research on North American grasslands, which used high-resolution monitoring to confirm the continuous expansion of cumulative croplands eroding native ecosystems. Despite the stark differences in socio-economic contexts and ecosystem types between Sichuan and the North American prairies, both regions clearly reveal the same core driving mechanism. Increasing human demand for agricultural products is continuously squeezing natural ecological space through both spatial expansion and intensification pathways, threatening biodiversity and critical ecosystem services. Our emergy–ecological footprint model provides a quantifiable measure of the intensity of this squeezing effect from an eco-economic perspective.

4.3. Comparison with Other Studies Applying Footprint Models

Wang et al. [67] analyzed the changes and trends of cultivated land ecological deficits in Sichuan Province from 2006 to 2013 based on the traditional ecological footprint model. Compared with results from studies using the traditional ecological footprint model, the advantage of this study, based on emergy analysis, lies in its ability to convert different types and levels of energy and material flows into unified solar emergy values. This approach more scientifically reveals the fundamental contribution of environmental resources to the sustainable development of cultivated land systems. This may also explain why the ecological carrying capacity calculated in this study for 2010 is generally higher than that in studies using the traditional ecological footprint model. However, Wang et al. did not further analyze the spatial distribution of the ecological deficit of cultivated land in Sichuan Province. This study makes significant contributions by improving the ecological model, updating the time series data, and exploring regional variations in the ecological carrying capacity of cultivated land in Sichuan Province.

This study finds that Sichuan Province overall faces severe ecological overshoot of its cultivated land. The ecological carrying capacity of cultivated land is low in plain and hilly regions but high in northwestern plateau regions. The ecological footprint is low in plain regions but high in hilly regions. This contrasts sharply with the findings of Xiang et al. [68] for Shandong Province. Shandong Province exhibits an ecological surplus of cultivated land across the entire province. The high-value areas of ecological carrying capacity are distributed in the northwestern plains, while low-value areas are found in the central and southern mountainous hills. The ecological footprint is generally low overall and shows a pattern of being low in the northwest and high in the southeast. This spatial pattern difference reflects the regional characteristics of the mechanisms influencing ecological security of cultivated land. The main reasons for the difference likely include fundamental differences in natural geographical conditions and variations in human activity intensity and agricultural models.

Sichuan’s topography is predominantly mountainous, plateau and hilly. The plain regions, such as the Chengdu Plain, are actually regions with highly concentrated population, economy and agricultural activity. Although the land is fertile, the area is limited and suffers from intense human pressure, thus exhibiting characteristics of low ecological carrying capacity and high ecological footprint. In contrast, the northwestern plateau region, despite having lower biomass productivity per unit area, is sparsely populated. The direct pressure from human consumption on cultivated land is low, leading to a higher calculated ecological carrying capacity. Shandong’s topography is primarily plain and hilly, with flat and open terrain. Its northwestern plain is part of the North China Plain, characterized by fertile soil, relatively sufficient water, and good light and temperature conditions. It is a traditional high-yielding agricultural area, thus capable of supporting a very high ecological carrying capacity and achieving a surplus. Conversely, the agricultural conditions in the central and southern mountainous hills are relatively poor, resulting in lower carrying capacity.

The hilly region is an important agricultural zone. However, due to fragmented terrain, large-scale mechanized production is difficult to achieve. This likely relies on higher inputs of fertilizers, pesticides and other intensive inputs to maintain yields, directly leading to a higher ecological footprint. Furthermore, consumption pressure from the large population base is a key factor causing the overall provincial overshoot. As one of China’s major grain-producing regions, Shandong’s large-scale, intensive agricultural production model in its northwestern plains is more efficient. This may result in a lower ecological footprint for equivalent output. Simultaneously, its per capita cultivated land resources are likely superior to those of Sichuan, and consumption pressure is relatively smaller, making it easier to achieve an ecological surplus.

The comparison with Shandong Province clearly demonstrates that the ecological security status of cultivated land is not determined by a single factor. It is rather the product of the interaction of regional natural geographical background, socio-economic structure and agricultural production models. The unique basin–hilly–plateau topographic structure of Sichuan determines that its cultivated land ecological security pattern is fundamentally different from that of Shandong, which is dominated by plains. This comparison reinforces the core finding of this study: formulating policies for the sustainable use of cultivated land must adhere to the principle of adaptation to local conditions. Successful experiences from plain regions cannot be simply applied to complex geographical units like Sichuan.

4.4. Suggestions for Future Development of the Study Area

Sichuan Province’s cultivated land system faces challenges of low resource utilization efficiency and increasing ecological pressures. Optimizing the system’s emergy input structure is a key pathway to enhancing agricultural sustainability. Drawing on international experience, precision agriculture based on sensors [69,70,71], GIS [72,73] and variable-rate fertilization technologies [74,75] should be vigorously promoted province-wide, particularly in plain region and peripheral mountainous region. This will improve fertilizer and pesticide application efficiency while controlling inefficient inputs of non-renewable industrial auxiliary. Drawing inspiration from Germany’s biogas projects [76] and China’s pig–biogas–fruit model, it will encourage farm-level or village-level establishment of crop–livestock–biogas circular systems in plains and hilly areas. Converting renewable organic energy sources like livestock manure and crop straw into clean energy and organic fertilizers will achieve closed-loop material and energy flows while boosting regional resource utilization rates for agricultural waste. Aligned with the objectives of the Convention on Biological Diversity (CBD), it will establish gene banks and seed breeding bases for Sichuan’s specialty crops, such as local rice and rapeseed varieties. This will strengthen the conservation and utilization of indigenous germplasm resources, promote high-quality seed resources with superior photosynthetic efficiency and stress resistance, and enhance the conversion efficiency of solar radiation and rainwater chemical energy at the source.

Due to the large differences in natural conditions and economic development levels among various regions in Sichuan Province, targeted optimization and regulation should be carried out in combination with local actual conditions to realize the sustainable utilization and development of cultivated land. The hilly region has reduced input but significantly increased output of cultivated land. It is suggested to maintain the advantage in input efficiency and further increase output. We should expand the application of conservation tillage practices, e.g., reduced tillage, no-till farming, straw mulching, through subsidy policies to conserve soil and water resources and enhance soil fertility, and promote fully biodegradable mulch films to gradually replace traditional agricultural films. Agroforestry systems can be promoted, such as intercropping legumes in orchards or tea-forest intercropping, to enhance biodiversity and system stability. The southwestern mountainous region has a significant increase in input. It should control input intensity, reduce dependence on fossil energy, replace agricultural film with degradable materials, pay attention to soil and water conservation, and balance resource development and ecological carrying capacity. In peripheral mountainous region, low-fuel-consumption agricultural machinery should be promoted, and special subsidies should be provided for mechanized operations on sloping cultivated land. This will encourage the deployment of machinery toward sloping cultivated land, thereby reducing overall agricultural diesel consumption. The plain region needs to improve the utilization efficiency of production materials, alleviating the ecological pressure caused by the reduction in renewable resources. In this region, green infrastructure such as ecological ditches and buffer zones should be implemented to reduce non-point source pollution. Vertical farming and facility agriculture should be developed in the urban fringe to supply fresh vegetables to the city, shorten food miles, and alleviate the pressure on cultivated land resources. The northwestern plateau region has a large increase in output but an increase in chemical fertilizer usage. It is suggested to reduce dependence on chemical fertilizers, implement the initiative to replace chemical fertilizers with organic fertilizers and establish specific targets. Organic animal husbandry and ecological agriculture should be developed, focusing on yak, plateau-specific Chinese medicinal herbs, vegetables, and edible fungi. Efforts should be made to actively pursue certification for products under the National Geographical Indication Protection Program. Branded marketing should be leveraged to enhance the value of agricultural products, achieving a win-win outcome for ecological conservation and economic benefits.

5. Conclusions

This study employed an emergy–ecological footprint model modified by yield factors and multiple-crop index, and modified the emergy sustainability index (ESI) by incorporating organic energy and environmental resources. Using the ecological pressure index (EFI) and the modified emergy sustainability index (ESI) the spatiotemporal differentiation characteristics of ecological security and sustainable utilization of cultivated land was analyzed at the county scale in Sichuan Province from 2010 to 2020. Moran’s I was used to reveal the evolutionary characteristics of their patterns.

(1)

The overall emergy input and output of cultivated land in Sichuan Province showed increasing trends, with growth rates of 6.3% and 32.6%, respectively. Emergy input in hilly region decreased by 2.1% (negative growth). The other regions showed positive growth, with southwestern mountainous region recording the highest increase at 32.8%. Increased agricultural machinery input was the key driver of regional input growth. Topsoil loss, agricultural labor and agricultural film were the main factors causing reduced emergy input. All regions achieved positive emergy output growth, with northwestern plateau region showing the most significant growth rate (72.0%). The emergy growth of cash crops primarily drove regional output increases. And northwestern plateau region reached 103.8% emergy growth in cash crop. These results indicate that agricultural machinery gradually became popular in agricultural production, potentially replacing some traditional agricultural labor. The results also reflect growing awareness of ecological environmental protection in agricultural production.

(2)

In Sichuan Province, ec, ef and EFI showed upward trends, with an initial rise followed by a decline, with the overall ecological security of cultivated land remaining at risk. In plain region, hilly region and peripheral mountainous region, ecological security of cultivated land consistently stayed at risk, while in southwestern mountainous region and northwestern plateau region it exhibited phased changes. The spatial evolution was characterized by the contraction of safe-level areas toward the northwest and the expansion of at-risk-level areas toward the northwest–southwest.

(3)

The sustainable utilization of cultivated land in Sichuan Province shifted from strong to weak sustainability. The sustainability of cultivated land in plain region, hilly region and peripheral mountainous region shifted from strong to weak, while southwestern mountainous region and northwestern plateau region maintained weak sustainability. The spatial evolution was characterized by the stabilization of plain region, hilly region and peripheral mountainous region, alongside the degradation of southwestern mountainous region and northwestern plateau region. High–High clusters concentrated in plain region and surrounding hilly region, while Low–Low clusters concentrated in northwestern plateau region and southwestern mountainous region.

This study found that in certain areas such as northwestern plateau region, the ecological security of cultivated land has stabilized or improved. This is closely linked to the implementation of ecological agriculture, agroforestry and forestry models in the region. As proactive conservation measures, these models have effectively maintained regional biodiversity and enhanced soil fertility. It is recommended that these models be promoted in other ecologically fragile areas. In highly intensive agricultural regions such as plain region, our research indicated that ecological pressures continue to mount. More critically, this model is reliant on chemical fertilizers, pesticides and intensive development, and may lead to environmental resource degradation, including soil degradation, water pollution and loss of agricultural biodiversity. The recovery cycles for these degraded environmental resources are difficult to predict, and restoration is challenging, posing a long-term threat to regional sustainable development.

The modified emergy–ecological footprint model incorporates the input, output and circulation of biological materials while reflecting the actual required biological productive area. Although it more comprehensively reveals the degree of dependence of human economies on natural capital, it remains unable to evaluate the impacts generated by the system from a social perspective. Future enhancements could include metrics for key social benefits related to societal stability and public quality of life, such as the happiness index, thereby increasing the model’s social-level discussability. This study primarily relied on statistical yearbook data at the provincial and prefectural/municipal levels. The spatial resolution and timeliness of these data have somewhat limited the model’s precision. It has not fully reflected variations in the ecological security and sustainable utilization of cultivated land within counties or at smaller scales (e.g., townships, individual plots). Future research could incorporate higher-resolution spatial data such as remote sensing imagery, soil properties and topography, combined with GIS technology. Subsequent studies may further focus on geomorphological regions, cities or counties to reveal the spatial heterogeneity of sustainable cultivated land utilization and its influencing factors, thereby enhancing the practical applicability of research conclusions.