Exploration of Rural Agroforestry–Pastoral Complex Systems Based on Ecological Footprint*—Taking Zhagana in Yiwa Township as an Example

Abstract

Since 2010, with the rapid development of tourism in Zhagana, Yiwa township, problems with the agroforestry–pastoral complex system and economic development in Zhagana have come to the fore. In order to investigate the sustainability of the agroforestry–pastoral complex system, the ecological footprint model was used to analyse the sustainable development of the ecosystem in Yiwa township from 2005 to 2020 and the ecological security changes in Zhagana from 2010 to 2020 through examining the ecological footprint intensity, the ecosystem diversity index and the ecosystem development capacity index. The results of the study show that the per capita ecological footprint of Yiwa township showed an overall decreasing trend between 2005 and 2020, and the per capita ecological deficit also showed a decreasing trend. Forest land was the most important component of the ecological footprint per capita, and grassland was the most important component of the ecological carrying capacity per capita. The footprint depth tended to increase and then decrease, and the footprint width tended to decrease, with a gentle increase from 2010. The ecological pressure index showed an overall decreasing trend, and the ecological sustainability index showed a sudden upward fluctuation after 2016. Overall, the ecological economy of Zhagana has some capacity for development, but there is a high level of ecological pressure.

1. Introduction

Human development depends on a stable natural ecosystem [1]. Zhagana in Diebe County, Gannan Tibetan Autonomous Prefecture, has a rich heritage of ancient Tibetan villages and natural ecological resources, presenting a distinctive composite system of agriculture, forestry and pastoralism cycles. With the rapid development of the local tourism economy, various ecological problems have become increasingly prominent and human activities pose certain threats to the local environment. Therefore, it is necessary to promote the endogenous and sustainable development of the countryside through moderate, limited and orderly industrial restructuring on the basis of the goal of coordinated development of the agricultural, forestry and pastoral systems.

The ecological footprint theory was proposed by the Canadian ecological economist Rees et al. in the early 1990s, who calculated the ecological footprint from the demand side and the ecological carrying capacity from the supply side, and measured whether the ecological environment of a region was in a sustainable state through a comparison of the two [2]. In turn, the ecological footprint theory and its research methods gradually spread from economics to geography, ecology, management, sociology and other research fields [3,4,5,6]. At present, few relevant studies exploring the dynamic evolution of the ecological footprint and carrying capacity in agriculture, forestry and pastureland can be seen, and the corresponding modelling methods need further improvement.

2. Research Methodology

This paper used time series based on the ecological footprint theory to quantitatively estimate and visualise the dynamic evolution of ecosystems, calculate the ecological pressure index, ecological sustainability index, ecological coordination coefficient, ecological footprint diversity index, and economic system development capacity ratio to assess the natural capital of the study area for ecological security, and explore the driving forces behind the formation of the three-dimensional ecological footprint natural capital pattern.

The ecological footprint theory has a unified system of evaluation indicators that allow for horizontal comparisons at different spatial scales. By comparing the ecological footprint of the study area over the years, a longitudinal comparison can be made over the time scale of the area to grasp dynamic changes in ecology [7]. Through calculating the ecological footprint of Yiwa township over the years, dynamic changes in ecology within Zhagana could be grasped, providing a quantitative analysis index system for the analysis of arable land, grazing land and woodland processes. The upward/downward trend of the ecological carrying capacity surplus or (deficit) would become an important indicator of the ecological dynamics of the study area.

The results of the ecological footprint calculation would be an important basis for judging the ecological development stage and sustainable development capacity of Yiwa township, and at the same time provide a control basis for the direction and objectives of development of the agroforestry–pastoral complex system; they would provide a basis for prediction and comparative analysis of the ecological effects on local ecological security.

2.1. Ecological Footprint Calculation

Many academics considered the ecological footprint to be the total biologically productive area (including land and water) needed to produce all the resources consumed by the population in a given region and to absorb all the waste generated by that population [8,9,10]. It is the biologically productive land area needed to produce all the resources consumed by the population of a region and to absorb all the waste generated by the region. It is calculated as:

$$EF=N*ef=N*{\displaystyle \sum \left(ri*\frac{ci}{pi}\right)}$$

(1)

In the equation, $EF$ is the total ecological footprint, $N$ is the number of people; $ef$ is the ecological footprint per capita; $ci$ is the per capita consumption of $i$ commodity, $pi$ is the average productive capacity of $i$ consumer commodity, and $i$ is the type of consumer commodity and input. The ecological footprint analysis method accounts for biologically productive land on the earth’s surface in six main categories (fossil energy land, arable land, pasture land, forest land, construction land, and water), based on differences in productivity magnitude.

2.2. Ecological Carrying Capacity Calculation

Ecological footprint supply (ecological carrying capacity) is calculated by the following formula:

$$EC=N*ec=N*{\displaystyle \sum (ri+yi+ai)}$$

(2)

where $EC$ is the total ecological carrying capacity of the region, $N$ is the population, $ec$ is the ecological carrying capacity per capita (hm²/person), $ai$ is the biological production area per capita, $ri$ is the equilibrium factor, and $yi$ is the yield factor. The balance factor is based on data from the China Ecological Footprint Report 2019, as shown in

Table 1. Equilibrium factors and yield factors for each type of productive land.

Land Type	Equilibrium Factors	Yield Factors
Arable land	2.39	1.66
Grassland	0.51	0.19
Woodland	1.25	1.1
Water	0.41	0.2
Construction land	2.39	2.8
Fossil energy land	1.25	0

below.

2.3. Ecological Deficit/Profit and Loss

Ecological deficit is the difference between the ecological footprint and the ecological carrying capacity [11,12]. It is calculated by the formula:

$$ED=EC-EF$$

(3)

where $ED$ is the ecological deficit or surplus. When $ED$ > 0, it denotes an ecological surplus, i.e., the resources needed for production and living are less than the resources the region can provide, indicating that the land use and environmental conditions in the region are good. When $ED$ < 0, it denotes an ecological deficit, indicating that the ecological environment is overloaded. In other words, the resources required for production and living are greater than the resources the region can provide, and the region is under high ecological pressure. This determines whether the development of the region is within the ecological carrying capacity.

2.4. Three-Dimensional Ecological Footprint Calculation

The three-dimensional ecological footprint is expressed using footprint depth and footprint breadth. Footprint depth refers to the extent to which humans consume natural resources and the level of human use of the capital stock. Footprint breadth refers to the size of the output of natural resources and the level of utilisation of capital flows.

$$E{F}_{\mathrm{depth} }=1+\frac{EF-EC}{EC}=1+\frac{{\displaystyle \sum \max }\left(E{F}_i-E{C}_i,0\right)}{EC}$$

(4)

$$E{F}_{\mathrm{size} }=\frac{EF}{E{F}_{\mathrm{depth} }}$$

(5)

In the above equation $E{F}_{\mathrm{depth} }$ and $E{F}_{\mathrm{size} }$ are the depth and breadth of the footprint; $E{F}_i$ refers to the ecological footprint of Class i land, while $E{C}_i$ denotes the ecological carrying capacity of Class i land. When $EF$ ≤ $EC$, it indicates an ecological surplus, and $E{F}_{\mathrm{depth} }$ = 1, and when $EF$ > $EC$, it indicates an ecological deficit, and $E{F}_{\mathrm{depth} }$ > 1 [13].

2.5. Ecological Pressure Index

The ecological pressure index $Epi$ reflects the intensity of the disturbance to ecosystems caused by human activities, using the capacity of the “natural–economic–social” complex ecosystem as a reference point. It is calculated using the formula [14,15]:

$$Epi=\frac{EF}{EC}$$

(6)

where $Epi$ < 1 indicates that the intensity of disturbance caused by human activities has not yet exceeded the self-feedback threshold of the regional ecosystem under specific conditions, and ecological security is still guaranteed, while the opposite will affect the ecosystem balance. The higher the ecological pressure index, the greater the intensity of the disturbance to the ecosystem’s equilibrium, and the greater the threat to ecological security [16].

Based on the acquired basic and standard data, the ecological safety assessment is graded according to the following grading criteria, as shown in

Table 2. Eco-safety assessment grading.

Level	I	II	III	IV	V
$Epi$	<0.50	0.51–1.00	1.01–1.50	1.51–2.00	>2.00
Representation status	Secure	More secure	Less secure	Insecure	Extremely insecure

below.

2.6. Ecological Sustainability Index

The Ecological Sustainability Index ($ESI$) indicates the extent to which a region is ecologically sustainable in its use. The formula is:

$$ESI=\frac{EC}{EC+EF}$$

(7)

The meanings of $EF$ and $EC$ are the same as before. 0 < $ESI$ < 1, where the smaller the $ESI$ value, the weaker the ecological sustainability, and vice versa.

2.7. Ecological Coordination Coefficient

Ecological deficits/surpluses do not well reflect the resource endowment conditions of different regions, and are prone to yielding biased results when performing cross-sectional comparisons between regions. For example, the same ecological deficit value has a different meaning for the western arid region than for the southeastern coastal region; in addition, in underdeveloped regions, lower consumption levels often result in ecological surpluses, but the conclusion that local development is more sustainable may be erroneous. Therefore, in evaluating the regional ecological footprint, the regional per capita ecological coordination coefficient (DS) can be introduced to compensate for the inadequacy of using the ecological deficit/surplus for evaluation.

$$DS=\frac{EF+EC}{\sqrt{E{F}^2+E{C}^2}}$$

(8)

When $DS$ = 1.414, regional ecological demand and supply are balanced and in the best state of coordination; when 1 ≤ DS < 1.414, there are two cases: if $EF$ > $EC$, regional ecological demand is greater than supply, development attempts to make up for the lack of ecological carrying capacity by depleting the stock of natural capital, and the region is in a state of ecological incoherence.

2.8. Ecological Diversity Index and Index of Development Capacity of Ecological and Economic Systems

The Shannon–Weaver formula was used to calculate the diversity index of the ecological footprint by introducing the economic system development capacity formula into the ecosystem, and different land types were used as indicators to measure the diversity of the ecological and economic system [17], calculated as follows:

$$H=-{\displaystyle \sum \left(p_i\ln p_i\right)}$$

(9)

In the above equation, $H$ is the ecological footprint diversity index; $p_i$ is the proportion of the total footprint accounted for by the $i$ land type. The ecological footprint diversity in the above equation is made up of two components: richness (the amount of different land types utilised) and evenness (a measurement of the distribution of ecological footprint components). According to this formula, the closer the distribution of the ecological footprints in an ecosystem is to equality, the more diverse the ecosystem is for a given system component, and the more stable the system is, in line with the ecological concept that “diversity leads to stability” [18,19].

The developmental capacity of an ecosystem can be obtained by multiplying the ecological footprint by the ecological footprint diversity index, using the following formula:

$$C=ef\times \left[-\sum \left(p_{i}ln{p}_i\right)\right]i=1,2,3,4,5,6$$

(10)

In the above equation, $C$ is the Ecosystem Development Capacity Index.

3. Spatial Identification of Agroforestry–Pastoral Complex Systems

3.1. Overview of the Study Area

The township of Yiwa is located in the northwestern part of Diebe County, Gannan Tibetan Autonomous Prefecture, Gansu Province, and lies in the middle and upper reaches of the Bailong River, which is one of the temperate forest areas with the richest seed plant species diversity in China as well as the area with the highest concentration of coniferous species distribution in Gansu Province, as shown in Figure 1. In May 2013, Zhagana was named in the first batch of China’s Important Agricultural Cultural Heritage and, in March 2016, it was inscribed on the Preliminary List of China’s Globally Important Agricultural Cultural Heritage [20,21]. In 2017, the “Diebe Zhagana Agroforestry–Pastoral Complex System” in Gansu Province was selected for inclusion in the list of globally important agricultural cultural heritage systems (GIAHS) by FAO experts. While improving the economy, society and people’s living standards, protecting the local ecological environment and biodiversity and achieving sustainable economic and social development is an important challenge for Yiwa township.

Local agriculture is at risk from biodiversity reduction, loss of traditional agricultural techniques and knowledge, agro-ecological degradation, and even imbalance in complex systems due to excessive tourism. The increase in surface facilities built for tourism disturbed traditional agricultural and pastoral planting areas, and the population of Yiwa township has risen steadily in recent years, as shown in Figure 2. In 2017, Zhagana topped the ranking of scenic heat gain within Gansu with a 305.2% increase, and rose from fourth to first place in the province, as shown in Figure 3.

3.2. Data Sources

The statistical data used in this study were obtained from statistical yearbooks and the remote sensing data were Landsat images from the GEE platform used to construct the China Land Cover Dataset (CLCD) for the period 1985–2020. Comparisons were made with the current state-of-the-art 30 m thematic products, including impermeable surface area (ISA), surface water and forests, to assess the quality of the CLCD in an integrated manner. Finally, the accuracy of the CLCD was assessed by visually interpreting independent samples and third-party test samples to obtain data on various productive land types for a 30 m × 30 m grid from 2005–2020 [22,23,24,25]. As Figure 4 shows, the glacial erosion topography and mounded landforms in Yiwa town are both typical and have special ecological protection functions.

The data for global average yields were mainly obtained from the Food and Agriculture Organization of the United Nations (FAO) statistical database. The area balance factors and yield factors for each land type were obtained from the Working Guidebook to the National Footprint and Biocapacity Accounts, published by the Global Ecological Footprint Network (GEFN) [26,27]; for statistical convenience, this paper combines raw coal, coke, gasoline, oil and natural gas into fossil energy land, and includes electricity as construction land, as shown in

Table 3. Composition of biological resources and energy pollution sources.

Ecological Footprint Components	Land Type	Category	Indicator
Ecological Resource Account	Arable land	Agricultural products	Wheat, rice, maize, soybeans, cotton, potatoes, rapeseed, peanuts, vegetables, poultry and eggs (grains, vegetables, oilseeds, herbs, sugar beets, pork)
	Grassland	Livestock products	Lamb, beef, sheep’s wool, milk, poultry and eggs, meat, dairy, wool, honey
	Woodland	Forest Products	Fruits (apples, pears, grapes, peaches, apricots), walnuts, peppercorns, wood
	Water	Aquatic products	Water products
Energy accounts	Construction land	Electricity	Electricity
	Fossil energy land	Fossil fuels	Coal, coke, crude oil, natural gas (gasoline, paraffin, diesel)

below.

4. Analysis of Results

Ecological problems emerge as a dynamic and cumulative process over time, and the ecological footprint, as a quantitative measure of sustainable development status, reflects the extent of human use of nature [28]. Ecological status was analysed using a time-series approach combined with an ecological footprint model, and the spatial visualisation function in ArcGIS10.8 was used to spatially analyse the composition of arable land, forest land, grassland, construction land and water in Yiwa township from 2005 to 2020, as shown in Figure 5.

4.1. Analysis of the Temporal Dynamics of the Ecological Footprint per Capita

As can be seen from

Table 4. Ecological footprint in Yiwa Township, 2005–2020.

Year	Arable Land (hm2/Person)	Woodland (hm2/Person)	Grassland (hm2/Person)	Water (hm2/Person)	Fossil Fuel land (hm2/Person)	Construction Land (hm2/Person)	Per Capita Ecological Footprint (hm2/Person)
2005	0.2617	4.8656	2.2642	0.0042	0.0103	0.0216	7.4276
2006	0.2462	4.6569	2.1590	0.0042	0.0107	0.0223	7.0994
2007	0.2204	4.3368	2.0054	0.0041	0.0096	0.0201	6.5965
2008	0.2157	4.3332	1.9958	0.0037	0.0093	0.0194	6.5771
2009	0.2014	4.0968	1.8771	0.0017	0.0048	0.0109	6.1927
2010	0.2190	4.5295	2.0685	0.0016	0.0050	0.0114	6.8351
2011	0.2124	4.5959	2.0996	0.0010	0.0038	0.0091	6.9219
2012	0.2068		2.1378	0.0009	0.0021	0.0058	7.0253
2013	0.1997	4.4770	2.0489	0.0006	0.0026	0.0067	6.7355
2014	0.2085	4.4134	2.0153	0.0005	0.0030	0.0075	6.6482
2015	0.2043	4.3749	1.9935	0.0003	0.0034	0.0082	6.5845
2016	0.1964	4.3808	1.9927	0.0001	0.0041	0.0095	6.5835
2017	0.1892	4.4531	2.0197	0.0001	0.0120	0.0247	6.6987
2018	0.1782	4.3646	1.9746	0.0001	0.0334	0.0655	6.6164
2019	0.1797	4.3602	1.9587	0.0001	0.0625	0.1212	6.6824
2020	0.1834	4.3455	1.9358	0.0012	0.0649	0.1257	6.6564

, the per capita ecological footprint of Yiwa township from 2005 to 2020 showed a decreasing trend, with the smallest proportion in the per capita ecological footprint of the water area, with an annual average of 0.02%.

In the overall performance of the ecological footprints of agriculture, forestry and livestock, there was an overall decreasing trend. Among them, arable land had the most significant decreasing trend, from 0.26 hm²/person in 2005 to 0.1834 hm²/person in 2020, and its annual average ecological footprint share was 2.75%. During the same period, grassland declined from 2.2642 hm²/person to 1.9358 hm²/person, with its average annual ecological footprint share being 29.08%. The ecological footprint of fossil fuel land and construction land, in contrast to the change in the total ecological footprint per capita, started to rise after 2017, mainly because the local tourism industry started to increase significantly, resulting in increased motor vehicle travel and construction of tourism facilities. Otherwise, the compound land use of agriculture, forestry and animal husbandry accounted for a high proportion of the six categories of ecologically productive land, reaching 97.12%, mainly contributing to the ecological footprint per capita, with grassland second only to forest land, which is closely related to the nomadic life of local residents in Yiwa town.

4.2. Analysis of the Temporal Dynamics of the Ecological Carrying Capacity per Capita

As can be seen from

Table 5. Ecological carrying capacity in Yiwa township, 2005–2020.

Year	Arable Land (hm2/Person)	Woodland (hm2/Person)	Grassland (hm2/Person)	Water (hm2/Person)	Fossil Fuel Land (hm2/Person)	Construction Land (hm2/Person)	Per Capita Ecological Carrying Capacity (hm2/Person)
2005	0.4345	5.3522	0.4302	0.0008	0.0000	0.0604	6.2781
2006	0.4088	5.1226	0.4102	0.0008	0.0000	0.0624	6.0048
2007	0.3659	4.7705	0.3810	0.0008	0.0000	0.0562	5.5745
2008	0.3580	4.7665	0.3792	0.0007	0.0000	0.0543	5.5588
2009	0.3343	4.5065	0.3566	0.0003	0.0000	0.0304	5.2282
2010	0.3636	4.9824	0.3930	0.0003	0.0000	0.0320	5.7713
2011	0.3525	5.0555	0.3989	0.0002	0.0000	0.0256	5.8327
2012	0.3432	5.1392	0.4062	0.0002	0.0000	0.0163	5.9051
2013	0.3315	4.9247	0.3893	0.0001	0.0000	0.0187	5.6643
2014	0.3461	4.8547	0.3829	0.0001	0.0000	0.0211	5.6049
2015	0.3391	4.8124	0.3788	0.0001	0.0000	0.0229	5.5533
2016	0.3259	4.8189	0.3786	0.0000	0.0000	0.0266	5.5500
2017	0.3140	4.8984	0.3837	0.0000	0.0000	0.0692	5.6653
2018	0.2958	4.8011	0.3752	0.0000	0.0000	0.1835	5.6555
2019	0.2984	4.7962	0.3722	0.0000	0.0000	0.3392	5.8060
2020	0.3044	4.7800	0.3678	0.0002	0.0000	0.3519	5.8044

, the per capita ecological carrying capacity of Yiwa township from 2005 to 2020 showed a continuous decreasing trend. The ecological carrying capacity of forest land > grassland > building land > cultivated land > water area, of which the ecological carrying capacity of forest land accounted for the largest proportion of the average value of the total ecological carrying capacity, with a value of 82.35%. The ecological carrying capacity of cropland was consistent with the change in total ecological carrying capacity per capita, showing a decreasing trend year by year, from 0.4345 hm²/person to 0.3044 hm²/person, with an average annual decrease rate of 0.10%. The share of grassland and water in the total ecological carrying capacity also showed a decreasing trend, with grassland decreasing from 6.85% to 6.34% and water decreasing by 0.01%; only the share of building land showed an increasing trend, from 0.96% to 6.06%, as the total ecological carrying capacity decreased, indicating that the area occupied was arable land. In terms of contribution to ecological carrying capacity, three types of ecologically productive land—arable land, forest land and construction land—were the main contributors.

As can be seen from

Table 6. Changes in the ecological footprint in Zhagana.

Time/Year	Ecological Footprint per Capita	Ecological Carrying Capacity per Capita	Per Capita Ecological Profit and Loss
2010	3.47	3.14	0.33
2015	5.60	4.82	0.78
2020	6.63	6.11	0.53

, the Zhagana ED was consistently negative in 2010, 2015 and 2020, i.e., it showed an ecological deficit. The larger the difference between the ecological carrying capacity per capita energy value and the ecological footprint per capita energy value, the more serious the ecological deficit situation, i.e., the more difficult it is for the study area to develop sustainably. The ecological footprint of the per capita arable land in Zhagana increased each year between 2010 and 2020 and reached a peak, but then dropped to a ten-year low in 2015.

4.3. Analysis of the Temporal Dynamics of Ecological Surplus and Deficit per Capita in Yiwa Township from 2005 to 2020

As can be seen from

Table 7. Ecological deficit or surplus by land type in Yiwa township, 2005–2020.

Year	Arable Land (hm2/Person)	Woodland (hm2/Person)	Grassland (hm2/Person)	Water (hm2/Person)	Fossil Fuel Land (hm2/Person)	Construction Land (hm2/Person)	Ecological Deficit (hm2/Person)
2005	0.1728	0.4866	−1.8340	−0.0034	−0.0103	0.0388	1.1495
2006	0.1625	0.4657	−1.7488	−0.0034	−0.0107	0.0401	1.0946
2007	0.1455	0.4337	−1.6244	−0.0033	−0.0096	0.0361	1.0220
2008	0.1423	0.4333	−1.6166	−0.0030	−0.0093	0.0349	1.0183
2009	0.1329	0.4097	−1.5204	−0.0014	−0.0048	0.0195	0.9645
2010	0.1446	0.4529	−1.6754	−0.0013	−0.0050	0.0206	1.0637
2011	0.1402	0.4596	−1.7007	−0.0008	−0.0038	0.0164	1.0891
2012	0.1365	0.4672	−1.7316	−0.0007	−0.0021	0.0105	1.1202
2013	0.1318	0.4477	−1.6596	−0.0005	−0.0026	0.0121	1.0712
2014	0.1376	0.4413	−1.6324	−0.0004	−0.0030	0.0136	1.0433
2015	0.1348	0.4375	−1.6147	−0.0002	−0.0034	0.0147	1.0313
2016	0.1296	0.4381	−1.6141	−0.0001	−0.0041	0.0171	1.0335
2017	0.1248	0.4453	−1.6359	−0.0001	−0.0120	0.0445	1.0334
2018	0.1176	0.4365	−1.5994	−0.0001	−0.0334	0.1179	0.9609
2019	0.1186	0.4360	−1.5866	−0.0001	−0.0625	0.2181	0.8764
2020	0.1210	0.4345	−1.5680	−0.0010	−0.0649	0.2262	0.8520

, the ecological surplus and deficit of Yiwa Township from 2005 to 2020 showed a deficit, but this decreased year by year from 2017 onwards. The overall average annual decline rate was 1.62%, from 1.1495 hm²/capita in 2005 to 0.8520 hm²/capita in 2020. Only arable land, forest land and construction land were in ecological surplus, while the other four categories were in ecological deficit. The proportion of ecologically productive land in ecological surplus was grassland (95.97%) > fossil fuel land (3.97%) > water (0.06%). The ecological surplus of cropland decreased from 0.1728 hm²/person to 0.1210 hm²/person, with an average annual decline rate of 1.87%; the ecological deficit of grassland decreased from 1.8340 hm²/person to 1.5680 hm²/person, with an average annual decline rate of 0.91%; the ecological surplus of forest land decreased from 0.4866 hm²/person to 0.4345 hm²/person, with an average annual decline rate of 0.67%. The study shows that the overall surplus and deficit in the region changed for the better from 2017 onwards, mainly due to a gradual increase in agricultural production offsetting consumption in the ecological footprint calculation; the improvement in the ecological deficit was not due to an increase in the ecological carrying capacity of the local agroforestry–pastoral complex.

4.4. Dynamic Analysis of Three-Dimensional Ecological Footprint

As can be seen from Figure 6, the depth of the footprint of Yiwa township showed a trend towards increasing and then decreasing from 2005 to 2020, while the breadth of the footprint showed a gradual decrease followed by an increasing trend from 2010 onwards. The breadth of the footprint in Yiwa was lower and more moderate, and the increasing trend year on year indicated that Yiwa took up more and more capital flows in the development process. This finding suggests a change in the development model of Yiwa township, whereby development gradually shifted towards capital stock for economic development while the sustainable use of natural capital diminished. The years 2010–2013 saw an increase in the depth of the footprint, indicating that too much capital stock was consumed during this period and resources were gradually reduced; 2017–2020 saw a gradual decrease, indicating a change in the development model of Yiwa township, with the consumption of capital stock gradually decreasing under the vigorous promotion of ecological development. The depth of the footprint in Yiwa township was more balanced, indicating that Yiwa township currently has less demand than supply in the use of resources and can rely on its own capital stock to supplement it.

4.5. Dynamic Analysis of Ecological Pressure Index and Ecological Sustainability Index

The ecological pressure index and ecological sustainability index of Yiwa township from 2005 to 2020 were calculated from Equations (6) and (7), as shown in Figure 7. The Ecological Pressure Index EPI started to show a decreasing trend from 2012, from 1.1897 to 1.1468, a decrease of 0.96 times with an average annual decrease rate of 0.54%, indicating that the ecological overload in Yiwa township eased in 2017 and the ecological pressure decreased. The Ecological Sustainability Index (ESI) for Yiwa township showed a decline until 2012 and a sudden upward fluctuation after 2016. The ESI for Yiwa township increased from 0.4582 in 2017 to 0.4658 in 2020, and continued to fluctuate in the range of 0.4609–0.4658 in the intervening years. Overall, the ecological sustainability index for Yiwa township was generally low over the study period, but the pressure on sustainable development eased in recent years.

5. Analysis of Ecological Security Changes in Zhagana

In order to more accurately describe the status of the resource and environmental carrying capacity of the study area, the ecological pressure index can be used to measure the degree of overloading of the ecological footprint of the energy value [29]. This model is different from the absolute perspective of ecological deficit/surplus, as it considers the changes in ecological pressure in Zhagana in 2010, 2015 and 2020 in terms of relative numbers; the calculation results are shown in

Table 8. Changes in ecological pressure index in Zhagana.

Year	Ecological Pressure Index	Degree
2010	1.10	III
2015	1.16	III
2020	1.09	III

.

The ecological coherence coefficient for Zhagana changed smoothly between 2010 and 2020, slightly above 1.4, indicating average ecological coherence of development. Zhagana’s ecological footprint diversity index decreased year by year from 0.86 in 2010 to 0.49 in 2020, indicating that Zhagana’s ecological footprint uniformity (which measures the distribution status of ecological footprint components) was poor. In addition, the mean value of Zhagana’s ecosystem development capability index was 3.41 between 2010 and 2020, with an overall slow increase except for an abrupt increase in 2017, indicating that Zhagana’s ecosystem development capability gradually increased (

Table 9. Ecological sustainability analysis of Zhagana.

Time	Ecological Coordination Factor	Ecosystem Development Capability Index	Ecological Footprint Diversity Index
2010	1.41	2.98	0.86
2015	1.41	4.04	0.72
2020	1.41	3.22	0.49

).

6. Conclusions and Discussion

6.1. Discussion

Comparing the measured natural capital results with existing studies that use the ecological footprint model with refined equilibrium and yield factors to calculate the ecological safety assessment [30,31], there is a deficit in capital and differences in the natural capital values, but the overall trend change is consistent. The reason may be related to the time sequence of the study, the refinement of the equilibrium and yield factors and the calculation of footprint account items. In terms of capital use tracking, the study area has low natural capital and high consumption of water resources, and needs to respond to the call for management and rational exploitation of water resources; in addition, the industrial structure needs to be optimized [32,33,34,35], with equal emphasis on ecological protection and resource development, so that capital mobility could be improved and stock consumption reduced; finally, relevant policies and regulations on environmental protection and environmental protection mechanisms need to be established to promote sustainable ecological development. From the perspective of the driving mechanism of the evolution of natural capital in the three-dimensional ecological footprint, the economic, social and technological development of the study area has a transmission mechanism for the appropriation of capital, and economic development is still dependent on the consumption of capital and energy. In summary, this study does a good job in assessing and calculating the ecological security of the study area in terms of driving force analysis, but there are still some shortcomings, and future studies should choose a longer time series; the selection of footprint account items and driving force factors also needs to be more comprehensive. In addition, the lack of water resources in the study area and the overall small results of the improved watershed equilibrium factor lead to an overall small ecological footprint for water resources, and subsequent measurement of the water footprint needs to be increased.

6.2. Conclusions

(1) The per capita ecological footprint of Yiwa township showed a general trend of decrease during 2005–2020, and the per capita ecological footprint of all types of ecological land was accounted for mainly by forestry land with the smallest amount being water. At the same time, the ecological carrying capacity per capita also showed a decrease, and the rate of decline was faster than the ecological footprint per capita, so the ecological deficit of Yiwa township became gradually significant. The ecological pressure gradually eased during the post-2017 period, where the ecological deficit was mainly due to the increase in fossil energy consumption and construction land. The footprint depth showed a trend of increasing and then decreasing, indicating that the problem of capital stock being continuously depleted became improved, while the change in footprint breadth flattened out the upper body trend, indicating that the appropriation of capital flow increased year by year.

(2) The sustainable development of Yiwa township was assessed by calculating its ecological pressure index (EPI) and ecological sustainability index (ESI) from 2005 to 2020. The ecological pressure index (EPI) was found to generally decrease over the last decade, and the ecological overload was reduced; the ecological sustainability index (ESI) showed a decline before 2012 and an increase and fluctuation after 2016, and was generally in a weakly unsustainable development stage.

(3) The driving force analysis model showed that there was a transmission mechanism for the economic, social and technological development of the study area via the appropriation of capital. Zhagana has a large share of forests and water and a high biological richness index, but the watershed ecosystem is affected by the poor storage capacity of the river network, while the demand for water resources increases. In the more economically developed and densely populated villages, due to the pollution of land and water resources caused by the massive discharge of tourism pollutants, the environmental pressure per their unit area remains high. Economic development still relies on the consumption of capital energy and investment in the level of science and technology needs to increase, the energy structure needs to improve, and the efficiency of energy use needs to increase; the industry needs to accelerate its transformation, improve the economic system and reduce its dependence on capital.

(4) The overall ecological resources of the study area are under great pressure and the efficiency of resource use is low. It is urgent to maintain the integrity of the spatial pattern of Zhagana’s agricultural, forestry and pastoral systems, to strengthen the continuity of natural processes to achieve regional ecological security, and to establish a Zhagana ecological spatial system. A networked, highly connected ecological infrastructure framework should be constructed with important agricultural, forestry and pastoral systems as panels and trunk streams and main roads as corridors, allowing important ecological functions such as biodiversity maintenance, water connotation and soil conservation to be properly exercised.