Spatio-Temporal Evolution Characteristics of Tourism Ecological Resilience in China

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Tourism ecological resilience is an important indicator of the healthy and sus-11 tainable development of the tourism industry, which provides a new analytical perspec-12 tive for the anti-fragility and tourism ecological security of the tourism industry. The research can help us learn the Spatio-temporal evolution characteristics of tourism ecological resilience in China. But there are several suggestions to enhance its result.

(1) Indicator relation with Tourism ecological resilience, should introduce to help readers learn their theoratical relationship;

(2)at the same time, the data of Indicators from different sources, and how to ensure their comparability and consistency;

(3) Language still needs polishing and improvement, to meet scientific article requirements

Comments on the Quality of English Language

Tourism ecological resilience is an important indicator of the healthy and sustainable development of the tourism industry, which provides a new analytical perspective for the anti-fragility and tourism ecological security of the tourism industry. The research can help us learn the Spatio-temporal evolution characteristics of tourism ecological resilience in China. But there are several suggestions to enhance its result.

(1) Indicator relation with Tourism ecological resilience, should introduce to help readers learn their theoratical relationship;

(2)at the same time, the data of Indicators from different sources, and how to ensure their comparability and consistency;

(3) Language still needs polishing and improvement, to meet scientific article requirements

Author Response

Reviewer 1

Tourism ecological resilience is an important indicator of the healthy and sustainable development of the tourism industry, which provides a new analytical perspective for the anti-fragility and tourism ecological security of the tourism industry. The research can help us learn the Spatio-temporal evolution characteristics of tourism ecological resilience in China. But there are several suggestions to enhance its result. The specific suggestions are as follows:

Thank you very much for your recognition of the value of the team 's manuscripts, and also for your valuable amendments and suggestions. After careful consideration, our team has modified all of your opinions and made point-to-point modifications to each opinion.

 

Question 1 : Indicator relation with Tourism ecological resilience, should introduce to help readers learn their theoratical relationship.

Revised as:

（1）From the perspective of evolutionary resilience, resilience is a dynamic process in which the system constantly resists and adapts to external disturbances. It is a kind of ability to change, adapt and transform stimulated by the system in response to pressure and constraints. It transforms the original short-term ' result-oriented ' behavior concept into a long-term ' process-oriented ' dynamic behavior concept. It is believed that resilience should not only be regarded as the ability of the system to return to the initial state, but also a process with time attributes in which the system continuously responds to disturbances through a variety of resilience characteristics. Ability includes stability, adaptability, trans-formation ability [47][15]. Resilience can be reflected by observing the change of system identity. The system is composed of a variety of elements. The elements interact with each other to generate temporal and spatial correlations. The dynamic changes of resilience are characterized by the dynamic changes of system elements. A variety of characteristics form a collection of capabilities to cope with the whole process of disturbance [16].

（2）When disturbances occur, individuals, organizations, communities and natural ecosystems in the system must respond to disturbances and changes, and have the ability to adapt, respond and evolve. They can either respond through a specific resilience feature or through a com-bination of multiple features throughout the entire process of disturbance occurrence, thus forming a dynamic set of resilience capabilities [16]. When the system with low resilience encounters external disturbances, the system characteristics will change or even lose due to the lack of elements and the fracture of the relationship. On the contrary, systems with high resilience will maintain or update system characteristics through resilience [48][49].

（3）As a complex system, the tourism ecosystem may be out of the stable state due to the disturbance of uncertain external factors, and its system components will change. In order to avoid the stagnation or collapse of the system operation caused by the excessive external disturbance, the tourism ecosystem realizes the collection and transformation of DPC, ARC and OIC by adjusting and absorbing the self-organization process of elements in the system, so that the system can continuously respond to, quickly recover and adapt to external disturbances. Therefore, this paper draws on the connotation of evolutionary resilience and tries to define TER as follows :

（4）The potential damage and ecological environment pressure caused by pollutant emission intensity to the ecological environment of tourist destinations are mainly manifested in the types of waste water, waste gas, solid waste, domestic waste pollution, etc., which are non-exclusive and indivisible. The system actively resists and absorbs the disturbance caused by internal vulnerability through the robustness and stability of its own functions such as industrial self-regulation and green environment restoration, and adapts to changes, dynamic recovery and timely feedback, reflecting the adaptability, repair ability and self-adjustment feedback mechanism of the system to cope with pressure. Abundant water resources (e.g. precipitation indicators) support higher biodiversity and vegetation cover, better sustain agriculture, forestry and other productive activities, and thus enhance ecosystem resilience [55].

（5）The reflection system can not only minimize or avoid the negative effects of similar disturbances by continuous memory and learning to deal with similar disturbances, but also deal with possible future disturbances by establishing new elements and operating mechanisms.

(6) The indicators show that : 1.The diversity of resources promotes the stability of the system, has the function of natural capital reserve and buffer capacity to cope with shocks, and is characterized by the abundance of tourism resources. The abundance of tourism resources is calculated by assigning 5,2.5,1.75,0.5,0.25 weights to the scenic spots according to the classification of scenic spots [56]. 2.The tourist density index ( tourist population density ) reflects the relative size and potential of the current tourism consumption market, measures the regional tourism carrying capacity, and is expressed as the number of tourist receptions divided by the total number of permanent residents in the region [57] ; 3.Tourism spatial index ( tourism spatial density ) reflects the degree of concentration of tourists per unit area and the degree of utilization of tourism resources, which is characterized by the ratio of the number of tourist receptions to the total area of the region [58] ; 4.Tourism R & D funds are based on the R & D funds of the whole society, combined with the proportion of tourism income in the total national economic output value, and the ratio is calculated [56] ; To im-prove the construction of tourism ecological resilience, in addition to strengthening the investment of funds and policies for environmental protection, it also includes improving the capacity of cultural tourism construction, improving the cultural literacy of residents and tourists, and strengthening the training of tourism service quality management. The study uses cultural construction expenditure ratio, investment in the tertiary industry, tourism management service expenditure ratio and other indicators to characterize the construction capacity of cultural tourism : tourism management service expenditure ratio is calculated by the proportion of tourism management and ser-vice expenditure to GDP ; the cultural construction expenditure ratio is calculated by the proportion of cultural business expenses in the national fiscal expenditure ; the tertiary industry investment intensity is calculated by the proportion of the tertiary industry fixed asset investment to the total investment [59]. 6.Tourism capital productivity is an important indicator to measure the in-put and output efficiency of the tourism industry, which reflects the efficiency level and capital regulation ability of the tourism industry in the use of capital resources [60]. 7.Environmental in-vestment power reflects the investment of tourism destination government in alleviating pollution damage and improving ecology, which is calculated by the proportion of investment in environ-mental pollution control to GDP [61].

 

Question 2 : at the same time, the data of Indicators from different sources, and how to ensure their comparability and consistency.

Revised as:

(1) The specific steps are as follows : 1 In order to ensure the comparability and accuracy of the data, firstly, the definition, calculation method and statistical caliber of each index are clearly defined, and different units are converted into international standard units or re-search general units. On this basis, the data of each index are nondimensionalized, and the original index is converted into non-dimensional index to eliminate the influence of different dimensions and units. For macroeconomic data, the price index is used to eliminate the impact of price fluctuations. The entropy method is used to process the data in depth and solve the weight of each index. Specifically, it includes entropy calculation and difference coefficient calculation, and determines the weight of each index in the comprehensive level index, which provides an important basis for subsequent weighted calculation. The evaluation value of the comprehensive level of tourism ecological resilience of 31 provinces in China from 2010 to 2022 is calculated by using the weighting method.

(2) The data collection of the paper follows the principle of unity of data sources, that is, the same index data is obtained from the same source as far as possible. If there is a lack of individual data, it can be supplemented and improved from other data sources, and the similarity and rationality of the data distribution of each source can be strictly tested to ensure the data quality and the reliability of the research results. For a small number of missing data, appropriate interpolation techniques ( interpolation or fitting values ) are used to fill in.

 

Question 3 : Language still needs polishing and improvement, to meet scientific article requirements.

Revised as:

Thank you very much for your comments and suggestions. We will carefully proofread each grammar of the article, and improve and optimize the language of the article. For example:

(1) “With the increasingly serious problems of the global gas ecological environment” revised as “With the global climate change, the ecological environment problem is becoming more and more serious".

(2) Since 2017, global environmental management has shifted from conceptual and holistic governance to specific and breakthrough rectification. The promotion of numerous international measures reflects the pertinence of global resource conservation and environmental governance, such as the establishment of the ecological civilization system in China, the proposal of carbon neutralization and carbon peak[1].

(3) China 's tourism industry is in a critical period of structural transformation and upgrading from high-speed growth to high-quality development,

And so on.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

Title: Spatio-temporal evolution characteristics of tourism ecological resilience in China
Comment: please clarify the novelty of your study compared to the these studies: 
K Wang, S Zhao, X Chen, Z Lei, X Zhou - Spatio-temporal evolution and influencing factors of the resilience of tourism environmental systems in the Yangtze River economic belt of China. Sustainability, 2023
N Yin, J Zuo, M Yang, J Yang, S Liu, J Wu - Spatio-temporal evolution of social-ecological system resilience in ethnic tourism destinations in mountainous areas and trend prediction: a case study in WulingScientific Reports, 2024
K Wang, X Chen, Z Lei, S Zhao, X Zhou - The effects of tourism development on eco-environment resilience and its spatio-temporal heterogeneity in the Yangtze River economic belt, China. Sustainability, 2023
Abstract
Comment: Based on the theory of evolutionary resilience, this study took 31 provinces in China as the study area, constructed a comprehensive evaluation index system of TER, and analyzed the spatial distribution pattern of China's TER in three dimensions, including the spatiotemporal evolution law and the spatial distribution pattern of defense protection, adaptation and restoration, optimization and innovation, from 2010 to 2022, using comprehensive evaluation index and Dagum Gini coefficient. Reformulate. 
Comment: Please mention the limits of your study and approach.

Introduction
Comment: With the increasingly serious problems of the global gas ecological environment, the construction of ecological civilization has become a hot spot of common concern of the international community. Since 2017, global environmental management has shifted from conceptual and holistic governance to concrete and breakthrough governance, and the establishment of China's ecological civilization system, the proposal for carbon neutrality and carbon peaking (Tang et al., 2021), and the United Nations' call for a "zero-pollution planet" reflect the pertinence of global resource conservation and environmental governance. References.
Comment: please rebuilt the introduction with simple paragraphs with one idea for Each paragraph. Mention the problematic based on the critization of previous studies.
Comment: In view of this, this study takes China as the research object, based on the theory of 89 evolutionary resilience and sustainable development, constructs a theoretical framework 90 of tourism ecological resilience and a comprehensive evaluation index system of tourism  ecological resilience from three dimensions (D-A-O): Defense protection capacity (DPC), Adaptation resilience capacity (ARC) and Optimizing innovation capacity (OIC), and comprehensively uses the comprehensive level index, Dagum-Gini system and kernel density estimation to clarify the spatiotemporal pattern of tourism eco-resilience and its multidimensional spatiotemporal evolution characteristics. This study can enrich the theoretical research on tourism ecological resilience and provide practical insights for the study of tourism ecological resilience in China. Rebuild this paragraph and divide the objective into sub-objectives that are simple and easy to understand. Clarify the novelty of your study, mainly in comparison with previous studies.
Materials and Methods
Theoretical framework
Comment: Enrich it with references and present the previous studies that included the theory. 
Comment: Figure 1. Evolution and Circular Transmission Path of Tourism Ecological Resilience. Clear.
Comment: Clarify the data analysis
Results
Please reformulate your approach to present results. Start with the description of results (figure and table), then mention the differences between parameters and study sites.
Comment: Avoid discussion inside results.
Comment. Discuss results after their interpretations.
Comment: Enrich your discussion with current studies conducted in China on the same topic.
Comment: Mention the specificity of your results.
Figure 5 is not clear.
Figure 6. Combine figure with one legend.
The discussion is poor.
You can combine the results and discussion.
Conclusion
Too long. You can add a subsection after the discussion to include the implications of your results.
In conclusion, it presents only the most important findings.
References
Improve references.

Author Response

Reviewer 2

Thank you very much for your recognition of the value of the team 's manuscripts, and also for your valuable amendments and suggestions. After careful consideration, our team has modified all of your opinions and made point-to-point modifications to each opinion.

 

Question 1 : Comment: please clarify the novelty of your study compared to the these studies:

K Wang, S Zhao, X Chen, Z Lei, X Zhou - Spatio-temporal evolution and influencing factors of the resilience of tourism environmental systems in the Yangtze River economic belt of China. Sustainability, 2023

N Yin, J Zuo, M Yang, J Yang, S Liu, J Wu - Spatio-temporal evolution of social-ecological system resilience in ethnic tourism destinations in mountainous areas and trend prediction: a case study in Wuling. Scientific Reports, 2024

K Wang, X Chen, Z Lei, S Zhao, X Zhou - The effects of tourism development on eco-environment resilience and its spatio-temporal heterogeneity in the Yangtze River economic belt, China. Sustainability, 2023.

Revised as:

（1）We have carefully studied these research papers, cited in the corresponding part of the article, and added the corresponding content in the literature review, theoretical framework and other parts. Specifically :

Research results such as tourism destination resilience [36-39] are constantly emerging.（N Yin, J Zuo, M Yang, J Yang, S Liu, J Wu - Spatio-temporal evolution of social-ecological system resilience in ethnic tourism destinations in mountainous areas and trend prediction: a case study in Wuling. Scientific Reports, 2024）

With the deepening of research, the research results of tourism environmental system resilience [3,29,40-43] have begun to take shape, but the related research on tourism ecological resilience is rarely seen in the literature and is still in its infancy.（K Wang, S Zhao, X Chen, Z Lei, X Zhou - Spatio-temporal evolution and influencing factors of the resilience of tourism environmental systems in the Yangtze River economic belt of China. Sustainability, 2023；K Wang, X Chen, Z Lei, S Zhao, X Zhou - The effects of tourism development on eco-environment resilience and its spatio-temporal heterogeneity in the Yangtze River economic belt, China. Sustainability, 2023.）

 

Question 2 : Abstract. Comment: Based on the theory of evolutionary resilience, this study took 31 provinces in China as the study area, constructed a comprehensive evaluation index system of TER, and analyzed the spatial distribution pattern of China's TER in three dimensions, including the spatiotemporal evolution law and the spatial distribution pattern of defense protection, adaptation and restoration, optimization and innovation, from 2010 to 2022, using comprehensive evaluation index and Dagum Gini coefficient. Reformulate.

Revised as:

(1)This study takes 31 provinces in China as the research area, constructs a comprehensive evaluation index system of TER based on the theory of evolutionary resilience, and uses comprehensive evaluation index, GIS spatial analysis technology, kernel density estimation, Dagum Gini coefficient and other research methods to analyze the spatial and temporal evolution of China 's tourism ecological resilience from 2010 to 2022, and the spatial distribution pattern of three dimensions of defense protection-adaptation recovery-optimization and innovation.

Comment: Please mention the limits of your study and approach.

Revised as:

This study can enrich the theoretical research of tourism ecological resilience, but it mainly uses provincial macro data for analysis. It still needs to be strengthened in depicting regional heterogeneity characteristics, so as to provide Chinese practice for the study of tourism ecological resilience.

 

Question 3 : Introduction：

Comment: With the increasingly serious problems of the global gas ecological environment, the construction of ecological civilization has become a hot spot of common concern of the international community. Since 2017, global environmental management has shifted from conceptual and holistic governance to concrete and breakthrough governance, and the establishment of China's ecological civilization system, the proposal for carbon neutrality and carbon peaking (Tang et al., 2021), and the United Nations' call for a "zero-pollution planet" reflect the pertinence of global resource conservation and environmental governance. References.

Revised as:

Since 2017, global environmental management has shifted from conceptual and holistic governance to specific and breakthrough rectification. The promotion of numerous international measures reflects the pertinence of global resource conservation and environmental governance, such as the establishment of the ecological civilization system in China, the proposal of carbon neutralization and carbon peak[1]。

 

Comment: please rebuilt the introduction with simple paragraphs with one idea for Each paragraph. Mention the problematic based on the critization of previous studies.

Revised as:

We have carefully thought about the introduction part, condensed the theme of each paragraph, put forward the main ideas and key thinking, and put forward questions on the basis of criticism of previous research. Specifically :

(1) The high-quality development of tourism is an important measure to protect the regional ecological environment [3].

(2) The construction of TER provides an important direction and path for the high-quality development of tourism. The impact of the new coronavirus epidemic not only exposes the inherent vulnerability of the tourism industry, but also pro-vides a rare opportunity to break through innovation [8]. Scholars have combined resilience and anti-fragility when examining social ecosystems [9], and countered vulnerability by enhancing resilience. There is a harmonious contradiction between the vulnerability and resilience of tourism ecosystem [10].……………………

(3) "Resilience" is a multidisciplinary concept, and resilience research has attracted attention in many fields, with considerable breadth and depth [12]. The related research on resilience has roughly gone through five stages of development : ' engineering resilience-ecological resilience-social resilience social ecological resilience integration-evolution resilience '.………………

 

Comment: In view of this, this study takes China as the research object, based on the theory of 89 evolutionary resilience and sustainable development, constructs a theoretical framework 90 of tourism ecological resilience and a comprehensive evaluation index system of tourism ecological resilience from three dimensions (D-A-O): Defense protection capacity (DPC), Adaptation resilience capacity (ARC) and Optimizing innovation capacity (OIC), and comprehensively uses the comprehensive level index, Dagum Gini system and kernel density estimation to clarify the spatiotemporal pattern of tourism eco-resilience and its multidimensional spatiotemporal evolution characteristics. This study can enrich the theoretical research on tourism ecological resilience and provide practical insights for the study of tourism ecological resilience in China. Rebuild this paragraph and divide the objective into sub-objectives that are simple and easy to understand. Clarify the novelty of your study, mainly in comparison with previous studies.

Revised as:

In view of this, this study takes 31 provinces in China as the research object. Based on the theory of evolutionary resilience and the theory of sustainable development, the theoretical framework of tourism ecological resilience and the comprehensive evaluation index system of tourism ecological resilience are constructed from three core dimensions : defense and protection ability, adaptation and recovery ability and optimization and in-novation ability. On this basis, the comprehensive level index, Dagum Gini coefficient and kernel density estimation are used to explore the spatial and temporal pattern of China 's tourism ecological resilience and its sub-dimensional spatial and temporal evolution characteristics from the provincial and seven geographical division scales, and to reveal the tourism ecological resilience and its sub-dimensional development level, dynamic evolution characteristics, spatial distribution pattern and regional differences from different scales. This study breaks through the traditional single-dimensional perspective and introduces the concept of ' evolutionary resilience ' into the study of tourism ecosystem. The resilience index system shifts from the traditional static rigid index of natural environment to the dynamic comprehensive index, which makes up for the lack of attention to the complexity and dynamic evolution characteristics of tourism ecosystem in previous studies, and provides a new analytical perspective for tourism ecosystem assessment, tourism an-ti-vulnerability and tourism ecological security. The research uses GIS spatial analysis technology, kernel density estimation, Dagum Gini coefficient and other methods, which are less used in the study of tourism ecosystem resilience.

 

Question 3 : Materials and Methods

Theoretical framework

Comment: Enrich it with references and present the previous studies that included the theory.

Revised as:

(1) The construction of TER provides an important direction and path for the high-quality development of tourism. The impact of the new coronavirus epidemic not only exposes the inherent vulnerability of the tourism industry, but also pro-vides a rare opportunity to break through innovation [8]. Scholars have combined resilience and anti-fragility when examining social ecosystems [9], and countered vulnerability by enhancing resilience. There is a harmonious contradiction between the vulnerability and resilience of tourism ecosystem [10]. The theory of evolutionary resilience undoubtedly provides an important research perspective in analyzing the influence process of external shocks on tourism ecosystem and exploring its recovery and reconstruction mechanism.

(2)"Resilience" is a multidisciplinary concept, and resilience research has attracted attention in many fields, with considerable breadth and depth [12]. The related research on resilience has roughly gone through five development stages : ' engineering resilience ecological resilience-social resilience social ecological resilience integration-evolution resilience '. In the early 21st century, scholars such as Walker B., Folke C. and Carpenters R. integrated previous theories and proposed an evolutionary resilience theory system [13] [14]. Evolutionary resilience integrates the concepts of ecological resilience, social resilience and social ecological resilience. It has the three-dimensional characteristics of persistence, adaptability and transformability, and emphasizes the dynamic process of resilience evolution through ' change-adaptation-transformation ' [15]. Although some early scholars have introduced the dynamic, non-linear and uncertain views of evolutionary resilience in the theory and review of foreign resilience, most of the domestic research still regards the concept of resilience as a short-term result-oriented behavior, and the research on the dynamic evolution perspective of resilience with long-term and periodicity is still in its infancy [16].

 

Comment: Figure 1. Evolution and Circular Transmission Path of Tourism Ecological Resilience. Clear.

Revised as:

（1） Figure 1. further explain “Evolution and Circular Transmission Path of Tourism Ecological Resilience.”

（2） DPC → Provide initial stability → ARC → Dynamic adjustment to alleviate the impact → OIC → Promote long-term system upgrades → DPC.

（3） The corresponding content in Fig.1 is also modified.

 

Figure 1.Evolution and Circular Transmission Path of Tourism Ecological Resilience.

 

Comment: Clarify the data analysis

Revised as:

The specific steps are as follows : In order to ensure the comparability and accuracy of the data, firstly, the definition, calculation method and statistical caliber of each index are clearly defined, and different units are converted into international standard units or research general units. On this basis, the data of each index are nondimensionalized, and the original index is converted into non-dimensional index to eliminate the influence of different dimensions and units. For macroeconomic data, the price index is used to eliminate the impact of price fluctuations. The entropy method is used to process the data in depth and solve the weight of each index. Specifically, it includes entropy calculation and difference coefficient calculation, and determines the weight of each index in the comprehensive level index, which provides an important basis for subsequent weighted calculation. The evaluation value of the comprehensive level of tourism ecological resilience of 31 provinces in China from 2010 to 2022 is calculated by using the weighting method.

Question 4 : Results

Please reformulate your approach to present results. Start with the description of results (figure and table), then mention the differences between parameters and study sites.

Revised as:

(1) China 's TER generally shows a steady growth trend, and regional differences are gradually expanding. It can be seen from Figure 2 that the core density center of China 's TER moved to the right as a whole from 2010 to 2022, and the median line in the box plot showed a fluctuating trajectory to the upper right, and the average value of resilience water increased first and then decreased.

(2) The North China region has always presented a ' main peak + secondary peak ' state, and the distribution curve has obvious right trailing phenomenon, indicating that there are obvious differences in tourism ecological resilience in different regions of North China, and the level of TER in individual provinces is higher.

(3) Delete “From the perspective of distribution ductility, there is obvious right tailing in the distribution curve in North China, while there is no right tailing phenomenon in the distribution curve in other regions, indicating that the level of tourism ecological resilience in some provinces in North China is relatively high.”

(4) Northeast China is an important industrial base. Economic transformation is facing certain difficulties, and investment in tourism development is limited. For example, Jilin, Heilongjiang and other places have low tourism eco-efficiency [66]. In addition, the problem of population aging in Northeast China and Southwest China has a significant impact on the eco-tourism efficiency of both in the long and short term [67].

(5) The economic development of Northwest China is relatively lagging behind, the industrial structure is relatively single, and the support of factor scale is weak. The tour-ism industry in Northwest China, such as Qinghai and Xinjiang, started late, and the tourism eco-efficiency is low. [66] It is subject to the comprehensive influence of factors such as weak economic foundation, low green development efficiency, poor traffic accessibility, and lagging infrastructure construction, which restricts the resilience of the tour-ism ecosystem.

(6) From the perspective of inter-provincial development, except for Tibet, Heilongjiang and Liaoning Province, the tourism ecological resilience decreased slightly, and the remaining provinces showed an upward trend. Among them, Yunnan Province and Jiangxi Province increased significantly, increasing by 56.5 % and 52.4 % respectively compared with 2010, followed by Hubei Province, Qinghai Province and Guizhou Province, which increased by 44.2 %, 41.5 % and 40.4 % respectively. Taking the mean value as a reference, the top six resilience levels are : Shanghai (0.3163) > Beijing (0.2694) > Guangdong (0.2404) > Jiangsu (0.2315) > Zhejiang (0.2201) > Shandong (0.2137). The top 6 rankings are : Chongqing (0.1167) > Shaanxi (0.1119) > Jilin (0.1081) > Hainan (0.1078) > Xinjiang (0.0998) > Ningxia (0.0725). Except for Jilin and Hainan, they are all in the western region.

 

Comment: Avoid discussion inside results.

Revised as:

The paper makes detailed modifications to the conclusion and discussion section to avoid conflicts between the two. The specific revisions are detailed in the ‘5. conclusions’ and ‘4.discussion’ section.

4. Discussion：

(1) From 2010 to 2022, the level of tourism ecological resilience in all provinces in China has improved to varying degrees, mainly due to the fact that China has entered a new era of socialist ecological civilization, deeply practiced the concept of green development and the concept of "lucid waters and lush mountains are invaluable assets", and continuously promoted the strategic action of "ecological civilization construction". ………….

(2) According to the spatial characteristics of ' high in the east and low in the west, high in the south and low in the north ', a hierarchical structure with ' Beijing-Shanghai ' as the dual core is formed, and the regional difference is the main source of the overall difference.………….

(3) In the future, the resilience of tourism ecosystem must pay attention to the full play and improvement of defense and protection ability, adaptation and recovery ability and optimization and innovation ability, deeply understand the connotation of tourism ecological resilience, promote the long board and make up the short board, and adhere to the multi-dimensional value co-creation of tourism ecosystem.………….

(4) Due to the vulnerability of the ecological environment and the relatively low level of economic development in the western region, the tourism ecosystem is vulnerable to external environmental changes and shocks such as natural and human factors.………….

(5) According to the characteristics of multi-polar distribution of optimization and innovation capabilities, we will further strengthen the innovation-driven development strategy of the national tourism industry and strengthen the application of digital technology to enhance system resilience.………….

5. Conclusions：

This study measured the China's TER from 2010 to 2022 from three dimensions: DPC, ARC, and OIC, and explored the spatio-temporal characteristics and regional differences of China's TER. The main conclusions are as follows:

(1) The overall level of China 's TER is low, but it shows a steady-state growth trend. Although the growth is slow, it has strong stability and sustainability. The development trend of the seven major regions is consistent with the national average trend. It shows that the green effect of tourism ecosystem in China 's provinces is enhanced, the ability to resist internal and external potential threats is improved, and the sustainable development ability of tourism industry is enhanced.

(2) The polarization of China 's TER has been alleviated, but there are still some provinces that occupy an absolute leading position, with significant spatial heterogeneity, and the actual development of each region is quite different. The overall characteristics of China 's TER are ' high in the east and low in the west, high in the south and low in the north ', forming a distribution pattern of high in the southeast and low in the northwest, and the change trends in different directions are different. The differentiation characteristics in the north-south direction are more obvious and strong, and the non-equilibrium differentiation characteristics are obvious. The overall formation of ' Beijing-Shanghai ' as a dual-core high-toughness center, with the central and western regions as the outer edge of the hierarchical spatial structure characteristics.

(3) The overall upward trend of DPC is obvious, showing a pattern of gradual attencation from dual core to periphery. The average value of DPC in the northwest China is the lowest, which is closely related to the level of regional economic development and related investment, reflecting that economic driving is the key variable to regulate the improvement of defense and protection capacity. The mean value of ARC in the Northwest China is the lowest, the level of ARC in the western region fluctuates greatly, and other regions re-main relatively stable. The OIC shows a significant overall upward trend, forming a multipolar distribution pattern with ' Beijing - Shanghai - Zhejiang - Guangdong - Ganqing - Tibet ' as the core and gradually decreasing outward radiation.

(4) The regional difference of China 's TER is gradually expanding, and the overall difference degree shows a fluctuating upward trend. The regional differences show the characteristics of high coincidence and fluctuation balance, and the fluctuation range is small, which indicates that the TER has strong stability, balance and self-regulation ability. A dynamic balance mechanism has been formed in the development process of each region, which can maintain the development in a relatively stable difference interval. The difference within the region presents a spatial distribution pattern of ' South China > North China > East China > Northwest > Northeast > Southwest > Central China '. The difference between East China and Northwest China is the largest, and the contribution rate of regional differences is the largest. It has been in a dominant position and is the main source of overall differences.

 

Comment. Discuss results after their interpretations.

Revised as:

(1)From 2010 to 2022, the level of tourism ecological resilience in all provinces in China has improved to varying degrees, mainly due to the fact that China has entered a new era of socialist ecological civilization, deeply practiced the concept of green development and the concept of "lucid waters and lush mountains are invaluable assets", and continuously promoted the strategic action of "ecological civilization construction". ………….

(2) According to the spatial characteristics of ' high in the east and low in the west, high in the south and low in the north ', a hierarchical structure with ' Beijing-Shanghai ' as the dual core is formed, and the regional difference is the main source of the overall difference.………….

(3) In the future, the resilience of tourism ecosystem must pay attention to the full play and improvement of defense and protection ability, adaptation and recovery ability and optimization and innovation ability, deeply understand the connotation of tourism ecological resilience, promote the long board and make up the short board, and adhere to the multi-dimensional value co-creation of tourism ecosystem.………….

(4) Due to the vulnerability of the ecological environment and the relatively low level of economic development in the western region, the tourism ecosystem is vulnerable to external environmental changes and shocks such as natural and human factors.………….

(5) According to the characteristics of multi-polar distribution of optimization and innovation capabilities, we will further strengthen the innovation-driven development strategy of the national tourism industry and strengthen the application of digital technology to enhance system resilience.………….

 

 

Comment: Enrich your discussion with current studies conducted in China on the same topic.

Revised as:

(1)From 2010 to 2022, the level of tourism ecological resilience in all provinces in China has improved to varying degrees, mainly due to the fact that China has entered a new era of socialist ecological civilization, deeply practiced the concept of green development and the concept of "lucid waters and lush mountains are invaluable assets", and continuously promoted the strategic action of "ecological civilization construction". How-ever, there is significant spatial heterogeneity in China's tourism ecological resilience, and the actual development of different regions varies greatly, and the high-resilience areas are mainly distributed in regions with relatively developed economic conditions, abundant environmental protection investment and strict environmental regulations. The higher in-crease in tourism ecological resilience in Yunnan, Jiangxi, Guizhou and other places is mainly due to the rapid economic development and relatively high investment intensity in tourism infrastructure and environmental governance [71]. Therefore, each region should take measures according to local conditions, combine the actual differences in the economic foundation, geographical environment, resource endowment, location conditions and other actual differences in the region, and learn from successful experience on the basis of clarifying the insufficient development of its own tourism ecological resilience, and scientifically formulate tourism ecological resilience improvement strategies.

(2) According to the spatial characteristics of ' high in the east and low in the west, high in the south and low in the north ', a hierarchical structure with ' Beijing-Shanghai ' as the dual core is formed, and the regional difference is the main source of the overall difference. The regional difference between East China and Northwest China is large, and the internal difference between South China and North China is large. This result also fully confirms the conclusion that the level of economic development in North China is quite different, the industrial division of labor and cooperation is not deep enough, the radiation effect of the rapid economic growth of Beijing, Tianjin and Hebei on the surrounding cities of Hebei is not good, and the overall coordination of the region is poor. [72]

 

Comment: Mention the specificity of your results.

Revised as:

3.4 Analysis of regional differences in tourism ecological resilience

This paper uses MATLAB software to measure the Gini coefficient of China 's tourism ecological resilience, and decomposes it according to the seven regions of East China, South China, North China, Central China, Southwest China, Northwest China and Northeast China. The evolution trend of regional differences in China 's tourism ecological resilience during the study period is depicted, and the overall and regional differences of China 's tourism ecological resilience are intuitively grasped, as shown in Figure 9.

(1) Figure 9(a) reflects the evolution trend of China's TER and regional Gini coefficient from 2010 to 2022. During the study period, the overall difference of national TER showed a fluctuating upward trend, and the overall Gini coefficient increased from 0.177 in 2010 to 0.183 in 2022, with little increase. From the perspective of the seven major regions, the intra-regional differences in East China and Northeast China fluctuated and decreased, while other regions showed a fluctuating upward trend. Among them, the decline in East China was 31.67%, and the decline in Northeast China was 32.58%. The increase in Central China, North China, South China, Northwest China and Southwest China was 5%, 19.21%, 10.27%, 59.26% and 2.53%, respectively, indicating that except for the narrowing of the internal differences in East China and Northeast China, the internal differences in other regions showed a significant trend of expansion. The Gini coefficient in the region shows a spatial distribution pattern of ' South China (0.1735) > North China (0.1505) > East China (0.1500) > Northwest China (0.0957) > Northeast China (0.0942) > Southwest China (0.0742) > Central China (0.0314) ', indicating that the difference in provincial TER within South China is the largest, followed by North China and East China, and Central China is the smallest.

(2) From 2010 to 2022, the Gini coefficient of China 's TER shows the characteristics of high coincidence and fluctuation balance. The fluctuation range is small (the rise and fall are all below 7%), which reflects the stability, balance and self-regulation ability of TER. A dynamic balance mechanism has been formed in the development process of each region, which makes the regional differences fluctuate within a small range and can maintain the development within a relatively stable difference range. From the perspective of numerical differences, the average inter-regional Gini coefficients of East China-Northwest, South China-Northwest, North China-Northwest, Northeast China-East China and Central China-Northwest are 0.3211,0.2517,0.2472,0.2416 and 0.2028, respectively, ranking the top five. The inter-regional Gini coefficient of East China-Northwest is the largest, because the level of tourism ecological resilience in East China is much higher than that in Northwest China. With the rapid catch-up of the northwest region, the level of TER has increased rapidly, resulting in a steady decline in the regional Gini coefficient between East China and Northwest China. From the perspective of change trend, the Gini coefficients of Northeast-Northwest, East China-Central China, East China-South China, East China-Southwest, and Central China-Southwest regions all showed a fluctuating downward trend, but the decline was less than 5.5%, indicating that the gap in the level of TER between these regions is shrinking and gradually tends to be balanced. The Gini coefficients of other regions showed a fluctuating upward trend, indicating that the differences between regions showed an expanding trend.

(3) Figure 9(b) reflects the evolution trend of the sources and contribution rates of regional differences in China's TER from 2010 to 2022. From the perspective of the dynamic evolution of the sources of differences, the fluctuation of the contribution rate of inter-regional differences is on the rise as a whole, from 66.76% in 2010 to 71.02% in 2022, an increase of about 6.38%. The contribution rate of regional differences experienced a fluctuation process of ' decline-rise-decline-rise-decline ', and the overall downward trend was about 13.32%. The contribution rate of  hypervariable density showed a significant downward trend, from 21.157% in 2010 to 18.506% in 2022, a decline of about 12.53%. From the perspective of the contribution rate of the source of difference, the average contribution rates of intra-regional difference, inter-regional difference and hypervariable density are 11.47%, 68.87% and 20.66% respectively. It can be seen that the contribution rate of inter-regional difference is the largest and has been in a dominant position. It is the main source of overall difference, followed by the contribution rate of intra-regional difference, and the contribution rate of hypervariable density is the smallest.

 

1. Overall and intra-regional differences.

 

1. Sources of regional differences and their contribution rates.

Figure 9. Regional Differences and Evolutionary Trends of China's Tourism Ecological Resilience

 

Figure 5 is not clear.

Revised as:

 

Figure 5. Spatial trend surface fitting of China's tourism ecological resilience from 2010 to 2022

Note : The green line represents the east-west direction, and the blue line represents the north-south direction.

Figure 6. Combine figure with one legend.

Revised as:

 

Figure 6. Spatial differentiation of China's tourism ecological resilience from 2010 to 2022

 

The discussion is poor.

Revised as:

(1)From 2010 to 2022, the level of tourism ecological resilience in all provinces in China has improved to varying degrees, mainly due to the fact that China has entered a new era of socialist ecological civilization, deeply practiced the concept of green development and the concept of "lucid waters and lush mountains are invaluable assets", and continuously promoted the strategic action of "ecological civilization construction". ………….

(2) According to the spatial characteristics of ' high in the east and low in the west, high in the south and low in the north ', a hierarchical structure with ' Beijing-Shanghai ' as the dual core is formed, and the regional difference is the main source of the overall difference.………….

(3) In the future, the resilience of tourism ecosystem must pay attention to the full play and improvement of defense and protection ability, adaptation and recovery ability and optimization and innovation ability, deeply understand the connotation of tourism ecological resilience, promote the long board and make up the short board, and adhere to the multi-dimensional value co-creation of tourism ecosystem.………….

(4) Due to the vulnerability of the ecological environment and the relatively low level of economic development in the western region, the tourism ecosystem is vulnerable to external environmental changes and shocks such as natural and human factors.………….

(5) According to the characteristics of multi-polar distribution of optimization and innovation capabilities, we will further strengthen the innovation-driven development strategy of the national tourism industry and strengthen the application of digital technology to enhance system resilience.………….

 

You can combine the results and discussion.
Conclusion
Too long. You can add a subsection after the discussion to include the implications of your results.
In conclusion, it presents only the most important findings.
References
Improve references.

Revised as:

(1)Thank you very much for your comments and suggestions. We have revised and improved the discussion and conclusion according to your request.

(2)The number of references has also increased from 41 to 72.

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

The article seems to me to be of considerable scientific interest, both for its methodological originality and, in particular, for the important database used. In this sense, the criticism that it works with territories that are too large, and that within each of them there may be specific areas with a different resilience behaviour than the one evaluated, must be accepted. In any case, it is an excellent approximation. 
In my opinion, some of the figures (Figures 2 and 3) need a more detailed explanation for better understanding, and in others it is very difficult to find significant differences (Figure 5) that serve to clarify what they explain, especially Figure 8, whose content is in Chinese characters.
On another note, the conclusions should be summarised more (more succinctly) and much of the content should be made part of the discussion.

Author Response

Reviewer 3

The article seems to me to be of considerable scientific interest, both for its methodological originality and, in particular, for the important database used. In this sense, the criticism that it works with territories that are too large, and that within each of them there may be specific areas with a different resilience behavior than the one evaluated, must be accepted. In any case, it is an excellent approximation.

Revised as:

(1) Thank you very much for your recognition of the value of the team 's manuscripts, and also for your valuable amendments and suggestions. After careful consideration, our team has modified all of your opinions and made point-to-point modifications to each opinion. At the same time, we also seriously consider and increase the content of regional difference analysis.

(2) 3.4 Analysis of regional differences in tourism ecological resilience

This paper uses MATLAB software to measure the Gini coefficient of China 's tourism ecological resilience, and decomposes it according to the seven regions of East China, South China, North China, Central China, Southwest China, Northwest China and Northeast China. The evolution trend of regional differences in China 's tourism ecological resilience during the study period is depicted, and the overall and regional differences of China 's tourism ecological resilience are intuitively grasped, as shown in Figure 9.

(1) Figure 9(a) reflects the evolution trend of China's TER and regional Gini coefficient from 2010 to 2022. During the study period, the overall difference of national TER showed a fluctuating upward trend, and the overall Gini coefficient increased from 0.177 in 2010 to 0.183 in 2022, with little increase. From the perspective of the seven major regions, the intra-regional differences in East China and Northeast China fluctuated and decreased, while other regions showed a fluctuating upward trend. Among them, the decline in East China was 31.67%, and the decline in Northeast China was 32.58%. The increase in Central China, North China, South China, Northwest China and Southwest China was 5%, 19.21%, 10.27%, 59.26% and 2.53%, respectively, indicating that except for the narrowing of the internal differences in East China and Northeast China, the internal differences in other regions showed a significant trend of expansion. The Gini coefficient in the region shows a spatial distribution pattern of ' South China (0.1735) > North China (0.1505) > East China (0.1500) > Northwest China (0.0957) > Northeast China (0.0942) > Southwest China (0.0742) > Central China (0.0314) ', indicating that the difference in provincial TER within South China is the largest, followed by North China and East China, and Central China is the smallest.

(2) From 2010 to 2022, the Gini coefficient of China 's TER shows the characteristics of high coincidence and fluctuation balance. The fluctuation range is small (the rise and fall are all below 7%), which reflects the stability, balance and self-regulation ability of TER. A dynamic balance mechanism has been formed in the development process of each region, which makes the regional differences fluctuate within a small range and can maintain the development within a relatively stable difference range. From the perspective of numerical differences, the average inter-regional Gini coefficients of East China-Northwest, South China-Northwest, North China-Northwest, Northeast China-East China and Central China-Northwest are 0.3211,0.2517,0.2472,0.2416 and 0.2028, respectively, ranking the top five. The inter-regional Gini coefficient of East China-Northwest is the largest, because the level of tourism ecological resilience in East China is much higher than that in Northwest China. With the rapid catch-up of the northwest region, the level of TER has increased rapidly, resulting in a steady decline in the regional Gini coefficient between East China and Northwest China. From the perspective of change trend, the Gini coefficients of Northeast-Northwest, East China-Central China, East China-South China, East China-Southwest, and Central China-Southwest regions all showed a fluctuating downward trend, but the decline was less than 5.5%, indicating that the gap in the level of TER between these regions is shrinking and gradually tends to be balanced. The Gini coefficients of other regions showed a fluctuating upward trend, indicating that the differences between regions showed an expanding trend.

(3) Figure 9(b) reflects the evolution trend of the sources and contribution rates of regional differences in China's TER from 2010 to 2022. From the perspective of the dynamic evolution of the sources of differences, the fluctuation of the contribution rate of inter-regional differences is on the rise as a whole, from 66.76% in 2010 to 71.02% in 2022, an increase of about 6.38%. The contribution rate of regional differences experienced a fluctuation process of ' decline-rise-decline-rise-decline ', and the overall downward trend was about 13.32%. The contribution rate of  hypervariable density showed a significant downward trend, from 21.157% in 2010 to 18.506% in 2022, a decline of about 12.53%. From the perspective of the contribution rate of the source of difference, the average contribution rates of intra-regional difference, inter-regional difference and hypervariable density are 11.47%, 68.87% and 20.66% respectively. It can be seen that the contribution rate of inter-regional difference is the largest and has been in a dominant position. It is the main source of overall difference, followed by the contribution rate of intra-regional difference, and the contribution rate of hypervariable density is the smallest.

 

1. Overall and intra-regional differences.

 

1. Sources of regional differences and their contribution rates.

Figure 9. Regional Differences and Evolutionary Trends of China's Tourism Ecological Resilience

 

Question 1 : In my opinion, some of the figures (Figures 2 and 3) need a more detailed explanation for better understanding, and in others it is very difficult to find significant differences (Figure 5) that serve to clarify what they explain, especially Figure 8, whose content is in Chinese characters.

Revised as:

(1)China 's TER generally shows a steady growth trend, and regional differences are gradually expanding. It can be seen from Figure 2 that the core density center of China 's TER moved to the right as a whole from 2010 to 2022, and the median line in the box plot showed a fluctuating trajectory to the upper right, and the average value of resilience water increased first and then decreased. The average value of resilience first increased and then decreased, from 0.1302 in 2010 to 0.1866 in 2019, an increase of 43.32%, reaching a peak in 2019, and the impact of the new crown epidemic decreased to 0.1552 in 2022. It can be seen that the level of ecological resilience of China's tourism industry is generally on the rise, with an average annual growth rate of 1.47%, reflecting the continuous optimization of the development momentum and quality efficiency of China's tourism industry, and the improvement of the green effect of the tourism ecosystem and the ability to re-sist potential internal and external threats [65]. The peak value of the kernel density curve of China's tourism ecological resilience decreased, the kurtosis first decreased and then slowly increased, showing a fluctuating downward trend as a whole, and the overall width of the curve expanded as a whole, and the length of the upper and lower limits (in-terquartile ranges) of the box plot tended to increase, indicating that with the passage of the development cycle and the replacement of development stages, the difference degree of TER in different provinces in China gradually increased, and the absolute difference showed a significant expansion trend. (Fig.2 and Fig.3a)

(2) The polarization of China's TER has been alleviated, but individual provinces occupy an absolute leading position in the development of tourism ecological resilience. From the perspective of the number of peaks and the ductility of the distribution, the kernel density curve showed a state of "main peak + double peak" from 2010 to 2017, and a "single peak" state from 2018 to 2022, and there was an obvious right tail characteristic, and the distribution ductility broadened significantly, indicating that the polarization of China's tour-ism ecological resilience has been alleviated, but there are still individual provinces that occupy an absolute leading position in the development of tourism ecological resilience.(Fig.2)

(3) In order to deeply analyze the overall situation of the spatial differentiation of China 's TER, this paper uses ArcGIS10.1 software to simulate and visualize the spatial distribution trend, and analyzes the global spatial distribution trend of resilience from different perspectives.(Fig.5) It can be seen from Figure 5 that the spatial pattern of tourism ecological resilience in China at the provincial level generally shows a layout trend of "high in the east and low in the west, high in the south and low in the north", and the east and south are the regions with high resilience of the tourism ecosystem, forming a distribution pat-tern of high in the southeast and low in the northwest, with significant spatial directionality. Specifically: From 2010 to 2022, China's tourism ecological resilience gradually in-creased from north to south, and decreased from east to west with the increase of geo-graphical distance, and there were differences in the trend line in different directions, with the trend line transition in the north-south direction being steep and the trend line transition in the east-west direction tending to be flat, indicating that the differentiation characteristics of tourism ecological resilience in the north-south direction were more obvious and strong, and there was significant spatial heterogeneity. It is worth noting that with the passage of time, the height of the peak point of the inverted U-shaped fitting curve generally increased, indicating that the overall level of China's tourism ecological resilience is on the rise.

(4) Fig 5 revised as:

 

 

 

Figure 5. Spatial trend surface fitting of China's tourism ecological resilience from 2010 to 2022

Note : The green line represents the east-west direction, and the blue line represents the north-south direction.

(5) Fig 8 revised as:

 

Figure 8. Spatial distribution of various dimensions of China's tourism ecological resilience

 

 

Question 2 : On another note, the conclusions should be summarised more (more succinctly) and much of the content should be made part of the discussion.

Revised as:

The paper makes detailed modifications to the conclusion and discussion section to avoid conflicts between the two. The specific revisions are detailed in the ‘5. conclusions’ and ‘4.discussion’ section.

4. Discussion：

(1)From 2010 to 2022, the level of tourism ecological resilience in all provinces in China has improved to varying degrees, mainly due to the fact that China has entered a new era of socialist ecological civilization, deeply practiced the concept of green development and the concept of "lucid waters and lush mountains are invaluable assets", and continuously promoted the strategic action of "ecological civilization construction". ………….

(2) According to the spatial characteristics of ' high in the east and low in the west, high in the south and low in the north ', a hierarchical structure with ' Beijing-Shanghai ' as the dual core is formed, and the regional difference is the main source of the overall difference.………….

(3) In the future, the resilience of tourism ecosystem must pay attention to the full play and improvement of defense and protection ability, adaptation and recovery ability and optimization and innovation ability, deeply understand the connotation of tourism ecological resilience, promote the long board and make up the short board, and adhere to the multi-dimensional value co-creation of tourism ecosystem.………….

(4) Due to the vulnerability of the ecological environment and the relatively low level of economic development in the western region, the tourism ecosystem is vulnerable to external environmental changes and shocks such as natural and human factors.………….

(5) According to the characteristics of multi-polar distribution of optimization and innovation capabilities, we will further strengthen the innovation-driven development strategy of the national tourism industry and strengthen the application of digital technology to enhance system resilience.………….

5. Conclusions：

This study measured the China's TER from 2010 to 2022 from three dimensions: DPC, ARC, and OIC, and explored the spatio-temporal characteristics and regional differences of China's TER. The main conclusions are as follows:

(1) The overall level of China 's TER is low, but it shows a steady-state growth trend. Although the growth is slow, it has strong stability and sustainability. The development trend of the seven major regions is consistent with the national average trend. It shows that the green effect of tourism ecosystem in China 's provinces is enhanced, the ability to resist internal and external potential threats is improved, and the sustainable development ability of tourism industry is enhanced.

(2) The polarization of China 's TER has been alleviated, but there are still some provinces that occupy an absolute leading position, with significant spatial heterogeneity, and the actual development of each region is quite different. The overall characteristics of China 's TER are ' high in the east and low in the west, high in the south and low in the north ', forming a distribution pattern of high in the southeast and low in the northwest, and the change trends in different directions are different. The differentiation characteristics in the north-south direction are more obvious and strong, and the non-equilibrium differentiation characteristics are obvious. The overall formation of ' Beijing-Shanghai ' as a dual-core high-toughness center, with the central and western regions as the outer edge of the hierarchical spatial structure characteristics.

(3) The overall upward trend of DPC is obvious, showing a pattern of gradual attenuation from dual core to periphery. The average value of DPC in the northwest china is the lowest, which is closely related to the level of regional economic development and related investment, reflecting that economic driving is the key variable to regulate the improvement of defense and protection capacity. The mean value of ARC in the Northwest China is the lowest, the level of ARC in the western region fluctuates greatly, and other regions re-main relatively stable. The OIC shows a significant overall upward trend, forming a multipolar distribution pattern with ' Beijing - Shanghai - Zhejiang - Guangdong - Ganqing - Tibet ' as the core and gradually decreasing outward radiation.

(4) The regional difference of China 's TER is gradually expanding, and the overall difference degree shows a fluctuating upward trend. The regional differences show the characteristics of high coincidence and fluctuation balance, and the fluctuation range is small, which indicates that the TER has strong stability, balance and self-regulation ability. A dynamic balance mechanism has been formed in the development process of each region, which can maintain the development in a relatively stable difference interval. The difference within the region presents a spatial distribution pattern of ' South China > North China > East China > Northwest > Northeast > Southwest > Central China '. The difference between East China and Northwest China is the largest, and the contribution rate of regional differences is the largest. It has been in a dominant position and is the main source of overall differences.

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

congratulations to the authors for improving the manuscript