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Yu, H. Forest Ecological Security in China: A Provincial-Level Analysis. Encyclopedia. Available online: https://encyclopedia.pub/entry/17134 (accessed on 07 August 2024).
Yu H. Forest Ecological Security in China: A Provincial-Level Analysis. Encyclopedia. Available at: https://encyclopedia.pub/entry/17134. Accessed August 07, 2024.
Yu, Honghong. "Forest Ecological Security in China: A Provincial-Level Analysis" Encyclopedia, https://encyclopedia.pub/entry/17134 (accessed August 07, 2024).
Yu, H. (2021, December 15). Forest Ecological Security in China: A Provincial-Level Analysis. In Encyclopedia. https://encyclopedia.pub/entry/17134
Yu, Honghong. "Forest Ecological Security in China: A Provincial-Level Analysis." Encyclopedia. Web. 15 December, 2021.
Forest Ecological Security in China: A Provincial-Level Analysis
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This entry is adapted from the peer-reviewed paper 10.3390/f12111526

Under the background of China’s proposal to achieve “carbon neutralization and carbon peak”, it is an important task for each province to clarify their forest ecological security (FES) status. However, there is little understanding of the temporal and spatial evolution of forest ecological security and its influencing factors.Based on the Pressure-State-Response (PSR) model, this paper constructed a comprehensive evaluation index system for forest ecological security and used the CRITIC method and panel data to estimate the dynamic changes in FES for 31 provinces in China (excluding Hong Kong, Macao, and Taiwan) between 2009 and 2018. Furthermore, the obstacle degree model was used to determine the important obstacle factors affecting FES. The results showed that: (1) The comprehensive indices of FES of most provinces in mainland China were increasing, showing a good development trend during the study period; (2) subject to the limitations of resources and economic conditions, the FES at the provincial level showed significant spatial heterogeneity, which generally presents a distribution characteristic of “low in the western region and high in the central and eastern regions”; and (3) the primary obstacles restricting the improvement of FES level in most provinces of China were forest state indicators or input response indicators, followed by pressure indicators. Therefore, it is recommended to take targeted measures to reduce the intensity of forest cutting and the incidence of forest disasters, improve the utilization efficiency of forest resources, the productivity of forestland and the input-output level of forestry industry, and strengthen the training of professional talents and technical input according to the resource endowment condition of each province so as to improve the level of forest ecological security.

forest ecosystem ecological security assessment PSR model spatiotemporal changes obstacle factors

1. Introduction

China aims to reach a carbon peak by 2030 and achieve carbon neutrality by 2060. Forest resources have played a positive role in protecting biodiversity and reducing carbon emissions. Ensuring forest ecological security (FES) is a prerequisite for maintaining national ecological security, promoting green development, and effectively responding to climate change [1]. In the process of human economic development, forest resources continue to provide raw materials for forestry-related industries, which has increased the pressure on FES [2]. In addition, the increase of human industrial occupation and unplanned deforestation has continuously reduced forest area and stock [3], resulting in soil erosion, abnormal climate, frequent disasters, and other consequences [4], which adversely affect the sustainable development of human beings [1]. In order to alleviate the environmental problems and promote the harmonious coexistence of man and nature, the Chinese government has implemented ecological projects such as the Natural Forest Protection Program, the Conversion of Cropland into Forests Program, and the Key Shelterbelt Development Programs in the Three-North Region [5]. In these endeavors, the development of FES measurement and the diagnosis of obstacle factors are helpful for the government to formulate forest ecological security monitoring and early warning standards so as to provide decision-making references for the realization of sustainable economic and social development.
The term ecological security first appeared in the 1970s [6] and has since attracted the attention of domestic and foreign scientists. As a cross-discipline of natural and social sciences, ecological security has not yet come by a unified definition. However, scientists generally agree that it can be understood either broadly or narrowly. In a broad sense, ecological security includes natural, economic, and social ecological security [7]. In a narrower sense, ecological security refers to the security of natural and semi-natural ecosystems, which is the overall level of ecosystem integrity and health [8][9]. Most evaluations of ecological security are aimed at a particular ecosystem either at the country level [10], at the administrative regional level [11][12][13], or at a certain field level, involving land [14][15][16], forest [17], forestry [18], wood [19], etc., as the target ecosystem category. As the largest ecosystem on land, the forest has been evaluated extensively by scientists. In particular, since China’s reform and opening up in 1978, the speed of economic development and urbanization has accelerated [20], which has had a serious negative impact on the ecological environment [21], resulting in the degradation of the forest ecosystem services [22]. Under this background, how to scientifically and reasonably evaluate FES in China has become a research hotspot in the academic circle.
FES includes not only the state that the forest ecosystem can generate ecological benefits, improve the human living environment, and support economic and social development through self-regulation and recovery, but also the state under which mankind can take active measures to make the forest ecosystem provide continuous and stable ecological and forest resources to support sustainable development of the human society [23][24]. The current FES assessment studies mainly are based on regions [25], specific areas [26], or counties [27][28]. Scientists generally select three or four sets of forest ecology-related data with a time interval of five years to study the dynamic changes [29], but due to the relatively long selected time interval these studies cannot accurately determine the detailed change process of FES. In terms of research content, scientists have quantitatively analyzed the important influencing factors based on certain comprehensive index of FES. For example, Cai et al. introduced the obstacle degree model to quantitatively calculate the influencing factors of FES in China [30], but they failed to further analyze the specific influencing factors of FES in each province.
The establishment of an FES evaluation index system is a complex task, with the central idea being to clarify the relationship between the forest ecological environment and human society [31]. At this stage, there is no unified standard for the index system construction of FES. Scientists mainly establish an evaluation index system based on the pressure-state-response (PSR) theoretical framework [12][32][33]. However, most of these index systems selected forest disasters and resource endowment as indicators [34], largely ignoring the impact of the forestry industrial development on FES. For the response aspect, the existing literature mainly considers capital investment responses [23], largely ignoring the human resource and technological development responses.

The main goal of this paper is to construct an FES evaluation index system based on the traditional definition of FES and the PSR framework that also takes into account the impact of the forestry industry and the support responses from talents and technology development on the FES. Using the constructed index, we compared and analyzed the FES status of 31 provinces in China (excluding Hong Kong, Macao, and Taiwan) from 2009 to 2018, and explored the changes and spatial distribution of FES in different provinces. Furthermore, the obstacle degree model was used to analyze the key factors affecting FES in China’s provinces. We believe that the results herein provide an important reference for the formulation of forest ecological strategic planning in related areas.

2. Time-Series Change Characteristics of Regional FES Levels

According to administrative divisions, China’s 31 provinces are divided into 7 areas: the north area, northeast area, east area, central area, south area, southwest area, and northwest area. The FES status and dynamic changes in China and its seven areas during 2009–2018 were depicted in Table 1 and Figure 1 below.
Forests 12 01526 g001 550
Figure 1. The changes of FES index in China and various regions. (A) The changes of FES index in China; (B) the changes of FES index in the north area; (C) the changes of FES index in the northeast area; (D) the changes of FES index in the east area; (E) the changes of FES index in the central area; (F) the changes of FES index in the south area; (G) the changes of FES index in the southwest area; (H) the changes of FES index in the northwest area.
Table 1. The calculated results of FES indices of 31 provinces in China, 2009–2018.
Area Province 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018
North area Beijing 0.406 0.401 0.437 0.462 0.495 0.474 0.446 0.459 0.489 0.495
Tianjin 0.381 0.322 0.351 0.334 0.337 0.365 0.379 0.377 0.428 0.373
Hebei 0.459 0.453 0.438 0.437 0.448 0.453 0.445 0.485 0.477 0.491
Shanxi 0.456 0.440 0.421 0.440 0.429 0.427 0.414 0.436 0.452 0.458
Inner Mongolia 0.374 0.369 0.377 0.391 0.391 0.377 0.382 0.392 0.384 0.392
Northeast area Liaoning 0.425 0.435 0.449 0.452 0.456 0.452 0.438 0.437 0.443 0.463
Jilin 0.431 0.443 0.493 0.492 0.496 0.481 0.493 0.437 0.517 0.519
Heilongjiang 0.458 0.436 0.473 0.479 0.474 0.483 0.478 0.475 0.481 0.476
East area Shanghai 0.386 0.484 0.465 0.499 0.537 0.563 0.596 0.621 0.566 0.558
Jiangsu 0.440 0.410 0.418 0.415 0.448 0.460 0.451 0.446 0.454 0.443
Zhejiang 0.485 0.488 0.494 0.491 0.511 0.510 0.521 0.528 0.529 0.531
Anhui 0.403 0.406 0.409 0.416 0.446 0.449 0.455 0.445 0.463 0.466
Fujian 0.426 0.457 0.504 0.483 0.517 0.523 0.523 0.538 0.537 0.537
Jiangxi 0.489 0.485 0.457 0.501 0.487 0.483 0.481 0.505 0.522 0.528
Shandong 0.419 0.416 0.433 0.435 0.455 0.500 0.495 0.475 0.463 0.459
Central area Henan 0.476 0.445 0.449 0.448 0.464 0.466 0.454 0.451 0.459 0.463
Hubei 0.450 0.481 0.429 0.440 0.449 0.447 0.459 0.466 0.490 0.473
Hunan 0.398 0.425 0.426 0.443 0.489 0.496 0.485 0.427 0.479 0.489
South area Guangdong 0.399 0.401 0.404 0.419 0.423 0.427 0.433 0.454 0.456 0.460
Guangxi 0.389 0.385 0.384 0.385 0.371 0.391 0.391 0.366 0.369 0.379
Hainan 0.433 0.457 0.401 0.457 0.422 0.444 0.435 0.442 0.452 0.442
Southwest area Chongqing 0.473 0.499 0.475 0.468 0.462 0.455 0.468 0.445 0.504 0.512
Sichuan 0.498 0.497 0.463 0.485 0.458 0.485 0.497 0.500 0.500 0.488
Guizhou 0.449 0.416 0.426 0.448 0.480 0.489 0.501 0.490 0.529 0.515
Yunnan 0.511 0.508 0.511 0.517 0.529 0.529 0.533 0.535 0.533 0.535
Tibet 0.378 0.407 0.418 0.439 0.507 0.492 0.481 0.480 0.479 0.444
Northwest area Shaanxi 0.470 0.465 0.455 0.467 0.489 0.498 0.490 0.485 0.495 0.496
Gansu 0.445 0.438 0.404 0.402 0.422 0.419 0.421 0.427 0.441 0.446
Qinghai 0.383 0.371 0.366 0.359 0.370 0.378 0.375 0.394 0.424 0.439
Ningxia 0.387 0.396 0.392 0.373 0.405 0.404 0.389 0.416 0.408 0.448
Xinjiang 0.391 0.374 0.375 0.374 0.354 0.356 0.383 0.382 0.391 0.401
China China 0.431 0.433 0.432 0.440 0.452 0.457 0.458 0.459 0.471 0.472
As can be seen from the last row of Table 1, the comprehensive index of China’s FES has increased from 0.431 to 0.472 from 2009 to 2018 (i.e., has improved from a critically safe state to a comparatively safe state), indicating that the FES index in China shows a slow upward trend but there is still a large room for progress. The improvement of the comprehensive FES index was mainly due to the improvement in the FES state index and response index. This shows that people have been increasingly aware of the importance of protecting forest ecology and that they have gradually increased investment in human resource, financial, and material input to rectify the ecological environmental problems, thus further improving the state index and response index of FES. At the current stage of economic development, it is difficult to reduce the ecological pressure by reducing the speed of economic development. At the same time, technological bottlenecks also limit the further improvement of the utilization efficiency of forest resources. Therefore, the change range of the FES pressure index has been small (Figure 1A).
The overall FES index in the north area had been slowly increasing. The FES level of Beijing, Hebei, and Shanxi provinces upgraded from a critically safe state to a comparatively safe state, but Tianjin and Inner Mongolia’s FES levels fluctuated slightly during the observation period and were still in a critically safe state (Figure 1B).
The FES situation in the northeast area, which is rich in forest resources, is generally good. The comprehensive FES indexes of Jilin and Heilongjiang were slightly higher than that of Liaoning, most of which were at the comparatively safe level. The FES level of Liaoning was basically at the critical safety level, but it also reached a comparatively safe level in 2018 (Figure 1C).
The comprehensive index of FES in the east area shows an overall upward trend, indicating that the FES status in the east area greatly improves during the study period. The comprehensive index of Shanghai’s FES was much higher than that of other provinces in the east area, with its FES level rising from a critically safe state to a safe state due to the fact that Shanghai’s response index scores were higher than other regions. With relatively better economic development, Shanghai invested a lot in human resources, capital, and technology, which made up for Shanghai’s deficiency in forest resources. However, it should be noted that the man-made ecosystem built with heavy investment in Shanghai has a certain vulnerability. In addition, the comprehensive indexes of FES in Zhejiang, Fujian, and Jiangxi are generally higher than that in Jiangsu and Shandong. This is due to the fact that the former are all provinces with large forest resources that also attach higher importance to forest ecological protection (Figure 1D).
The overall change of FES index in Hubei and Henan are similar, showing a slow growth trend. The FES situation in Henan was better than that in Hubei in the early stage, but it turned around in 2015 and after due to the improvement of the quality of forest resources and the rapid increase of FES state index in Hubei. The provinces in Central area were basically in a comparatively safe state during the study period (Figure 1E).
The comprehensive index of FES in Guangxi decreases year by year and remains in a critically safe state. With the acceleration of the urbanization level in Guangxi, forest cutting and wood consumption increases year by year, and the disturbance of economic development to forest ecology intensifies continuously, resulting in the decrease of FES index. In addition, the comprehensive index of FES in Guangdong and Hainan are generally on the rise. Guangdong and Hainan revised the Regulations of Guangdong Province on Forestland Protection and Management and the Regulations of Hainan Special Economic Zone on Forestland Management respectively in 2014, gradually paying attention to forestland protection. Their state of ecological security gradually has improved (Figure 1F).
The comprehensive index of FES in Yunnan is relatively high due to the rich virgin forest resources and natural forest protection measures, being improved from a comparatively safe level to a safe level. The FES index of Tibet and Guizhou have increased greatly. Guizhou has carried out a lot of work in improving forest resources and increasing forestry investment to increase the FES index. They had actively implemented ecological projects such as afforestation and forest tending, as well as constructed forestry industrial bases such as industrial raw material forest and national reserve forest, leading to the improvement of Guizhou’s FES index year by year. In recent years, Tibet has concentrated on the development of eco-tourism, characteristic animal husbandry, and processing industries of agricultural and pastoral products. The forest resources are therefore occupied less, and the pressure on the FES is gradually reduced, further improving its FES status. The FES levels of Chongqing and Sichuan have always been in a comparatively safe state, due to the rich forest resources in the two provinces. However, the rapid development of high-tech industries, service industries, characteristic agriculture, and other industries in Chongqing and Chengdu have put much pressure on their FES. At the same time, the inclination of funds in related industries has led to reduced intensity of forestry investment, resulting in greater changes in the comprehensive index of FES in Chongqing and Sichuan, indicating that the policy has great impact on the FES (Figure 1G).
The comprehensive index of FES in the northwest area was in a downward trend from 2009 to 2011, and began to rise gradually in 2012, indicating that the overall FES situation has been gradually improving recently. Among them, Shaanxi has always been in a comparatively safe state, and its comprehensive index of FES is far higher than that of other provinces in the region, largely due to the fact that Shaanxi has accelerated the construction of forest ecology through implementation of national forestry projects such as the natural forest resource protection project, the three north Yangtze River shelterbelt project, and the Returning farmland to forest (grassland) projects. The FES index of Gansu is slightly higher than that of Qinghai, Ningxia, and Xinjiang, due to the fact that Gansu’s investment in forestry science and technology talents and afforestation is much higher than other provinces in the region, which also testifies that it is necessary for regions to take active measures to improve the ecosystem (Figure 1H).

3. Spatial Differences of FES in Provinces

Our results also showed that China’s FES levels exhibited a spatial distribution pattern of low in the western region and high in the middle and east (Figure 2). In 2009, the (FES) comparatively safe provinces were mainly distributed in the central region, as well as parts of southwest and east China. By 2018, comparatively safe levels were basically spread over the central and eastern regions, showing an overall trend of expansion and evolution from the inland to the surrounding areas. However, some provinces at comparatively safe levels are still confronted with some problems such as the reduction of forest resources and the deterioration of the ecological environment, and some provinces still have a high risk of degrading into a critical safety level. Therefore, such areas should increase investment in ecological protection and increase resource utilization to maintain and improve their FES levels.
Forests 12 01526 g002a 550Forests 12 01526 g002b 550
Figure 2. The spatial layout of China’s FES levels.
During the observation period, the regions at a critical safety level of FES have gradually reduced from the zonal distribution in the western area and the patchy distribution in the northeast, southwest and east area to the northwest area, showing that the improvement of FES levels in the northwest area is relatively low, which may be related to the level of local economic development. Restricted by their economic resources, the forest ecological maintenance in the northwest area has been inadequate. Thus, relevant government agencies should attach importance to the sustainable development of forests, so as to control and reduce the pressure that human activities put on the forest ecosystem. At the same time, according to the characteristics of the large area and sparse population in the northwest area, the planting area of artificial forests should be increased to improve the richness of forest resources. It is worth noting that, as the province with the highest forest coverage rate in China, Tibet’s FES level entered a critically safe level again from the comparatively safe level in 2015. This was due to the reduction of its response index, which indicated that Tibet’s forest ecological system maintenance work still needed to be further strengthened.
The FES levels of Yunnan, Fujian, and Zhejiang began to reach the safe level in 2015, and Jiangxi was added to that list in 2018. The above-mentioned provinces are scattered in southwest and east areas. In general, with the passage of time, the levels of FES in China have improved significantly, but there still is some regional polarization.

4. Diagnosis of Barrier Factor

Considering the large number of obstacle factors, this paper sorted out the top five indicators in each province as the main obstacle factors according to the ranking of obstacles. At the same time, due to the large sample size, the data in 2018 were selected for the analysis (Table 2). In order to analyze the obstacles of FES of the 31 provinces in China, this paper analyzed the situation of each province according to the administrative division. In North China, as the economic, political and cultural center of China, Beijing’s urbanization rate is the primary obstacle factor that affects its FES. The reduction of the proportion of new afforestation has a strong hindering effect on FES in Tianjin, Hebei, Shanxi, and Inner Mongolia. Among them, the proportion of new afforestation has a stronger hindering effect on FES in Tianjin, Hebei, and Shanxi than that in Inner Mongolia due to the more abundant forest resources in the latter. The decreased indicators including forest stock volume per unit area, the forestry output value per unit forest area, and the proportion of the number of forestry technological exchange personnel to the total number of forestry units are the main factors hindering the improvement of FES levels in north area. Although restricted by economic and resource conditions, achieving high quality development of forest-related industries and increasing forestry science and technology talents could effectively improve their forest ecological security status.
Table 2. The obstacle factors and obstacle degrees of FES of the 31 provinces (2018).
Province Index Ranking (Obstacle Factor/Obstacle Degree) Province Index Ranking (Obstacle Factor/Obstacle Degree)
1 2 3 4 5 1 2 3 4 5
Beijing X1 X5 X14 X10 X8 Hubei X14 X5 X13 X1 X4
18.88 14.93 13.32 12.41 11.23 12.46 12.44 11.11 10.67 10.52
Tianjin X4 X1 X5 X8 X14 Hunan X5 X14 X13 X10 X8
17.80 14.41 12.05 9.10 8.99 14.17 11.81 11.29 10.88 10.74
Hebei X4 X5 X13 X8 X10 Guang-dong X14 X1 X5 X13 X10
16.03 15.63 11.42 11.11 10.27 13.67 13.29 12.16 11.52 9.99
Shanxi X4 X5 X13 X10 X8 Guangxi X14 X12 X2 X5 X10
17.42 13.18 11.19 10.75 10.70 12.80 11.91 11.03 10.78 9.93
Inner Mongolia X4 X14 X10 X13 X5 Hainan X14 X12 X13 X10 X8
14.99 12.61 10.46 10.42 9.87 15.32 11.23 11.21 10.97 10.06
Liaoning X14 X1 X5 X13 X8 Chong-qing X1 X5 X13 X10 X8
13.68 12.64 11.92 11.69 10.73 13.11 12.31 12.15 11.58 11.44
Jilin X14 X10 X13 X8 X1 Sichuan X14 X13 X4 X8 X10
16.71 13.31 12.84 12.01 10.83 14.90 11.98 11.46 11.23 11.21
Heilongjiang X14 X10 X13 X8 X1 Guizhou X14 X5 X10 X13 X8
16.37 12.37 11.98 11.24 10.67 13.53 13.36 12.48 11.81 11.43
Shanghai X4 X1 X14 X5 X9 Yunnan X14 X13 X10 X8 X11
24.34 22.12 15.89 14.70 5.91 17.05 13.52 13.01 12.59 10.20
Jiangsu X4 X14 X1 X5 X10 Tibet X4 X14 X12 X13 X10
18.89 13.33 12.59 12.27 10.35 20.04 15.41 12.82 11.47 11.39
Zhejiang X14 X1 X5 X13 X8 Shaanxi X14 X5 X13 X8 X1
17.68 14.73 14.39 13.04 10.84 13.56 12.43 12.16 11.50 10.49
Anhui X4 X14 X5 X13 X10 Gansu X4 X5 X13 X8 X10
14.57 13.23 11.51 10.95 9.38 20.41 11.85 10.99 10.59 9.35
Fujian X14 X1 X10 X13 X8 Qinghai X4 X5 X14 X13 X8
16.43 13.89 13.43 12.93 11.15 22.16 15.95 11.33 11.21 10.61
Jiangxi X14 X5 X13 X10 X8 Ningxia X4 X5 X13 X8 X1
15.48 13.88 13.04 12.66 11.63 20.01 16.08 11.12 10.33 9.80
Shandong X4 X5 X14 X1 X11 Xinjiang X4 X14 X5 X13 X8
18.54 13.86 11.15 10.62 8.69 21.08 12.18 11.02 10.39 9.75
Henan X4 X14 X5 X13 X8            
16.20 12.40 12.00 11.28 10.05            
The low proportion of new afforestation is the main obstacle factor of FES in the northeast area, showing that the decrease of new afforestation area in the northeast area is not conducive to the improvement of its FES level. Although forest resources are relatively abundant in the region, the high rate of deforestation in the northeast area threatens the local FES. In addition, the low level of the proportion of forestry science and technological exchange personnel to the total number of forestry units and the low intensity of forestry investment are important factors restricting the improvement of the FES level in Jilin and Heilongjiang. Therefore, to improve the forestry scientific and technological personnel and increase investment in ecological construction funds would be effective ways to improve the FES situation in Jilin and Heilongjiang.
In the east area, the forest coverage rate is the top obstacle factor of FES in Shanghai, Jiangsu, Anhui, and Shandong, indicating that the low forest coverage rate has the greatest impact on FES in these regions. Due to the limited forest resources, it is not in line with reality to significantly increase the forest coverage rate in the short term. Therefore, FES levels could be effectively advanced by increasing the proportion of new afforestation and forest stock per unit area and slowing down the urbanization process. The proportion of newly increased afforestation is the primary obstacle factor of FES in Zhejiang, Fujian, and Jiangxi, which indicates that the low level of the proportion of new afforestation is the primary factor restricting the improvement of their FES levels. The low level of the stock volume per forest area, forestry output value per forest area, and forestry investment intensity are all important factors restricting the improvement of FES in the above-mentioned areas. In general, Zhejiang, Fujian, and Jiangxi are rich in forest resources, especially some areas are the pilot provinces for China’s forestry policy reform. By increasing the afforestation area, enhancing forest management and protection level, changing industrial development mode, and increasing capital investment, forest ecological benefits could be effectively improved and the FES levels could be further enhanced.

In the central area, the main obstacle factors affecting FES in Henan are the forest coverage rate, the proportion of new afforestation and the volume of forest per unit area. Henan, as a large food production province with a long history, has few forest resources, so insufficient investment in forest resources could easily have an adverse impact on its FES. The low level of the proportion of new afforestation, forest stock per unit area and forestry investment intensity are the main factors that hinder the improvement of FES in Hubei and Hunan, indicating that the maintenance and improvement of FES response indexes in Hubei and Hunan has not been in place.

The proportion of newly increased afforestation is the primary obstacle factor in South area, showing that the overall afforestation area in the South area needs to be further strengthened. Guangdong’s economy has developed rapidly over years, with urbanization being an important factor that hinders the improvement of its FES. The important obstacle factors of FES in Guangxi and Hainan include the rate of pest control in forestry and the proportion of the number of scientific and technological exchange personnel to the total number of forestry units. Those two provinces have abundant forest resources, but their economic development speeds are slightly backward compared with other provinces, resulting in insufficient technology and talent responses in these two provinces.

In the southwest area, the primary obstacle factor of FES in Chongqing is the ratio of urbanization, indicating that the acceleration of the urbanization process is not conducive to the maintenance of FES. In addition, the decline of forest stock per unit area and forestry investment intensity also restricts the improvement of FES level in Chongqing.

The primary obstacle factor of FES in Sichuan, Guizhou, and Yunnan is the proportion of new afforestation, showing that the reduction of afforestation restricts the improvement of their FES levels. The decline of the intensity of forestry investment, the value of forestry output per unit of forest area, and the proportion of forestry science and technological exchange personnel to the total number of forestry units are also important factors hindering the improvement of FES levels in these provinces. The above-mentioned areas are rich in forest resources, but it is necessary to maintain forest resources and develop forestry industries. The low forest coverage rate is the most important factor restricting the FES in Tibet, the largest forest area in China, indicating that the quality of Tibet’s forests needs to be further improved. At the same time, the reduction of the proportion of new afforestation and the intensity of forestry investment are also the main factors affecting Tibet’s FES, indicating that the response level of FES in Tibet still needs to be further strengthened.

The indicators including forest coverage rate, new afforestation proportion, forest stock per unit area, forestry investment intensity, and forestry output value per unit area are the main factors affecting the FES level in northwest area. The forest resources in the Northwest area are relatively small and the ecology there is relatively fragile. The obstacle factors all involve forest ecological state and response indicators, indicating that it is necessary for northwest area to expand the area of artificial forests, improve the level of forest management and protection, and further enhance the forest quality, so as to alleviate the conflict between forest ecology and economic development in the region.

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Honghong Yu
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