Spatial Differentiation Characteristics, Driving Mechanisms, and Governance Strategies of Rural Poverty in Eastern Tibet
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsThanks for the review invitation, the research focus of East Tibet region’s rural poverty phenomenon and spatial heterogeneity is of scientific significance and academic value.
Please receive my attached comments to enhance and improve the paper quality before consideration for publication.
1. Section 1. The aim of this research should be rewritten, current version is too tardy. The research aim should be a clear one sentence, and then put forward several research objectives. Do not wrap all these into a very long sentence.
2. Section 2: Figure 1 is too blur, the note inside the figure is difficult to recognise.
3. Section 2 Line 119: What do you mean by “lack of natural resources and environmental pollution”?
4. Section 4: Table 2, the author should clearly provide note upon the abbreviation of factors, otherwise it is very confusing for the readers to follow and understand. This problem happens across the paper, check through the manuscript to provide necessary full name of some confusing short-terms/abbreviations (especially the method terms, the independent factor names, and those appearing in figures and tables)
5. The Discussion seems superficial and can be enhanced. Better taking several representative countries from both Global South and Global North to generate some insightful comparative discussion. This is research work so should not only report statistics results, rather, critical discussion and policy implications are important.
6. Following empirical analysis results, policy implications should be enhanced. Particularly for the three categories of poverty-dominated villages defined in your research. This part should be enhanced as it is important to highlight your research contribution.
7. Careful proofreading should be conducted to enhance the writing quality and readability.
8. Conclusion: very (much too) similar to Abstract, the Conclusion Section should be revised to include research contribution, both theoretically and practically; and the recommendations for future research.
9. Below literature is recommended to enhance the theoretical soundness and empirical discussion centred with rural development, spatial analysis and social-ecological perspective based investigation:
“Rural China staggering towards the digital era: evolution and restructuring” (on Land) "Multifaceted land use change and varied responses of ecological carrying capacity: A case study of Chongqing, China" (on Applied Geography)
Comments on the Quality of English Language
Careful proofreading should be conducted to enhance the writing quality and readability.
Author Response
Response to Reviewer 1 Comments
Many thanks for the valuable comments of the reviewer! These comments are very helpful in improving the quality of this article. We have made targeted changes according to these opinions. We also have done a careful polishing of the English expression in the full text. Now, let's make a detailed description of the changes.
Point 1: Section 1. The aim of this research should be rewritten, current version is too tardy. The research aim should be a clear one sentence, and then put forward several research objectives. Do not wrap all these into a very long sentence.
Response 1: Thank you very much for your advice. Therefore, in response to your suggestion, we have simplified the description of the purpose of the study by summarizing it into a clear sentence and then presenting the 3 research objectives in the form of a short questionnaire formulation.See lines 108 to 118 for details.
Point 2: Section 2: Figure 1 is too blur, the note inside the figure is difficult to recognise.
Response 2: Thank you very much for your advice. We have replaced it with a clear figure, see details at Figure 1.
Point 3: Section 2 Line 119: What do you mean by “lack of natural resources and environmental pollution”?.
Response 3: Thank you very much for your advice. Let's rephrase that statement，“Owing to the menace of geological hazards, paucity or maldistribution of natural resources, and environmental contamination arising from both residential and productive activities, leads to a high poverty risk in localized rural areas.”Specifically, some rural areas have limited natural resources, such as infertile land and water scarcity, which limits the potential and sustainability of agricultural production, which in turn affects the standard of living of farmers. Environmental pollution mainly consists of the destruction or contamination of human habitats, such as the deterioration of the quality of soil or river water sources, which leads to a decrease in crop yields or even results in the inability of crops to grow. In addition, environmental pollution affects the health of the local population and increases health-care expenditures, thereby contributing to poverty.
Point 4: Section 4: Table 2, the author should clearly provide note upon the abbreviation of factors, otherwise it is very confusing for the readers to follow and understand. This problem happens across the paper, check through the manuscript to provide necessary full name of some confusing short-terms/abbreviations (especially the method terms, the independent factor names, and those appearing in figures and tables).
Response 4: Thank you very much for your advice. The full names of some of the poverty impact factors are lengthy and their use may lead to confusion in sentence structure. Therefore, the full name of the impact factor is used only for the first occurrence of the description of the impact factor in paragraph 4.2.1 of the original manuscript, and the abbreviated acronyms of the impact factor are successively marked in parentheses to provide explanatory descriptions of the impact factor provided in the subsequent text. Therefore, the abbreviations of the impact factors are used in Table 2 of the subsequent paragraphs. In addition, in order to provide the reader with a clearer understanding of the meaning of the abbreviations, the abbreviated descriptions are added to the original full names in the column of impact factors in Table 1.
Point 5: The Discussion seems superficial and can be enhanced. Better taking several representative countries from both Global South and Global North to generate some insightful comparative discussion. This is research work so should not only report statistics results, rather, critical discussion and policy implications are important.
Response 5: Thank you very much for your advice.We considered it important to select global cases that are comparable to the study area of this paper, and therefore chose typical globally impoverished areas, such as mountainous regions or river basins for comparative discussion, with typical poverty risks in Africa and Asia. Therefore, Asia (Nepal and India), African countries (Nigeria, Tanzania, Ethiopia, and the Democratic Republic of the Congo), and the Nile Basin were selected, subject to socio-ecological system factors such as complex topography, lack of resources, and weak facilities, which are similarly exposed to marginal, recurrent, and latent poverty risks. For details, see lines 640 to 667 of the manuscript, as follow:
From the perspective of global poverty areas, particularly those in mountainous and watershed areas of Asia and Africa, are significantly impacted by socio-ecological system factors. These include the complexity of the terrain, scarcity of resources, and inadequate infrastructure, which contribute to the risk of marginal, recurrent, and Potential poverty, as well as spatial differentiation. For instance, in Nepal, the current trend of population migration from mountainous regions to urban areas has left behind a trapped poor population, leading to a spatial concentration of poverty and the emergence of marginal poverty[63]. In African nations such as Nigeria, Tanzania, Ethiopia, and the Democratic Republic of Congo, there is an imbalance in regional energy distribution due to energy scarcity and an unequal spatial and temporal allocation of electricity usage. This has triggered multidimensional poverty among marginalized communities[64]. The Purulia region, located in the arid eastern part of India, is at risk of latent or recurrent poverty. This risk is due to underdeveloped social, economic, and infrastructural facilities, along with a limited water supply, which hampers the region's capacity for social development[65]. In the Nile Basin countries, poverty and inequality are widespread. The spatial and temporal patterns of GPI (Growth-Poverty-Inequality) evolution differ based on geographic positions upstream and downstream, with high inequality levels further aggravating poverty conditions[66]. Thus, globally typical impoverished areas are constrained by factors such as topographical location, infrastructure, and ecological resources, and also face the three major risks of poverty: potentiality, recurrence, and marginality. This scenario bears resemblance to the spatial differentiation of rural poverty and its driving factors in Eastern Tibet, where on one hand, there are communities with complex terrain and limited transportation, exhibiting a trend of migration towards towns with better accessibility or their surrounding areas, thereby revealing risks of marginal poverty. On the other hand, these areas are also confronted with inadequate infrastructure provision or a deficiency in ecological resources, which indicates risks of recurrent or potential poverty.
Point 6: Following empirical analysis results, policy implications should be enhanced. Particularly for the three categories of poverty-dominated villages defined in your research. This part should be enhanced as it is important to highlight your research contribution.
Response 6:Thank you very much for your advice. In the original draft, specific measures to address the three main poverty risks were summarized in the summary section of part 5. The policy guidance is now further strengthened in line with the comments on the review., we explore in sections 4.3.1, 4.3.2, and 4.3.3 of the text paragraph how to mitigate the three types of villages at risk of poverty, namely, latent, marginal, and recurrent, in terms of policy formulation. See below for details:
For potential poverty-stricken villages, a government-led 'county-town-village' normalization control model should be established. The local government should establish a disaster and ecological early warning and prevention department, which undertakes the main tasks of monitoring and prevention, emergency management, and guiding and encouraging social forces. Through emergency training, transfer payments, and transfer resettlement, a rapid relief mechanism should be constructed to prepare for risk prevention in advance and to build a strong defense against poverty caused by disasters.
For villages characterized by marginal poverty, it is essential to develop location-specific policies[46]. In areas where there is a concentration of population and economic activities or where population growth is observed, the focus should be on enhancing the supply and preemptive planning of land use and related services. For underdeveloped regions or rural areas with sparse or declining populations, the emphasis should be on ensuring basic public services, providing employment assistance, and facilitating income growth. These measures should be aligned with the demographic trends of the countryside to promote village development and minimize the waste of investment during the rural revitalization process.
For villages experiencing recurrent poverty, policies should be designed to facilitate an orderly and gradual exit, while coordinating with other policies to fill any gaps, thereby reducing or preventing regional poverty resurgence due to policy withdrawal. For instance: initially, by fostering collaboration between banks and insurance companies, a variety of agricultural insurance types should be introduced to provide basic development security for farmers. Subsequently, the state should formulate or optimize talent supply channels for impoverished areas, enabling the empowerment of rural revitalization through diversified industrial development. Lastly, a robust evaluation mechanism should be established during the poverty reduction phase, with government departments at all levels summarizing experiences in poverty alleviation and governance. A normalized, top-down and bottom-up information sharing channel should be established to facilitate the summarization of effective countermeasures and to modify or adjust ineffective response strategies.
Point 7: Careful proofreading should be conducted to enhance the writing quality and readability.
Response 7:Thank you very much for your advice.We are well aware that clear and precise language is crucial to the quality and readability of our work. We have engaged the English language editing services of a professional organization to address linguistic issues, ensuring that the language quality of the manuscript meets academic writing standards.
Point 8: Conclusion: very (much too) similar to Abstract, the Conclusion Section should be revised to include research contribution, both theoretically and practically; and the recommendations for future research.
Response 8:Thank you very much for your advice.On the basis of the summary in Part 6, we further elaborate on the innovations of this study in terms of theoretical approaches and practical applications, The shortcomings and future endeavors of this study are also noted. Details are shown below:
In response to the global reality of diverse regional types, multifaceted risks of poverty recurrence, and the pursuit of high-quality governance objectives, This study leverages spatial poverty theory to analyze the mechanisms behind the formation of potential, recurrent, and marginal poverty risks from a socio-ecological systems perspective. Employing advanced multi-intelligence analysis techniques, it discerns the spatial differentiation and driving factors of these three major types of poverty risks. The research proposes targeted governance measures and policy recommendations, thereby enabling the precise implementation of rural poverty risk management strategies and the transformation of planning techniques. This has significant practical implications for advancing poverty alleviation in vulnerable and less resilient rural areas globally. However, current research on the spatiotemporal dynamics of rural poverty risk necessitates further in-depth investigation. The significant challenges in acquiring regional data have impeded systematic longitudinal studies on the evolution of poverty risk within villages. Moving forward, we aim to leverage predictive methods such as the random forest algorithm and neural network models to address the issue of data scarcity. Additionally, we will employ Geographically and Temporally Weighted Regression to forecast the future trajectory of rural poverty risk and to devise effective long-term strategic planning.
Point 9: Below literature is recommended to enhance the theoretical soundness and empirical discussion centred with rural development, spatial analysis and social-ecological perspective based investigation:“Rural China staggering towards the digital era: evolution and restructuring” (on Land) "Multifaceted land use change and varied responses of ecological carrying capacity: A case study of Chongqing, China" (on Applied Geography).
Response 9:Thank you very much for your advice.We analyze in-depth the two high-quality references provided by the reviewers, and make additions at lines 576-586 and 668-685 in Chapter 5 of the original manuscript to strengthen the theoretical plausibility and empirical discussion centered on rural development, spatial analysis, and socio-ecological perspectives. Details are given below:
Additionally, the dynamics of the social-ecological system behind land use change affect the spatial distribution of rural poverty. Specifically, in areas with complex terrain, the changes in the ecosystem are minimal, and the conversion of farmland back to forest shows a significant positive impact. However, for villages on the edge of cities, the negative impact of converting forest and grassland to arable land is evident. Urban expansion encroaches on forest and farmland, causing farmers to lose their land or be forced to change the way land is used. Moreover, different landscape pattern indices have a significant heterogeneity in their impact on ecological carrying capacity. This also proves that the impact of social-ecological systems on poverty risk presents significant spatial heterogeneity. It is very necessary to explore the patterns and driving mechanisms of the spatial distribution of poverty risk.
From the perspective of rural development in China, the evolution of Chinese rural areas has transformed from a top-down, policy-driven system before the digital era to a system in the digital era that is driven by both top-down and bottom-up approaches, with technology and policy working together. Currently, the development of rural areas in China in the digital age is facing the challenge of the "digital divide," especially in remote areas where insufficient infrastructure and high service costs lead to poverty risks that are diverse and spatially heterogeneous. Utilizing diverse smart analysis technologies to explore the spatial differentiation characteristics of rural poverty risks, identifying the three main types of poverty risks—"potential, recurrent, and marginal"—and proposing targeted measures and policy recommendations is needed for the shift from post-event management to pre-event prevention of rural poverty in China. In addition, digitalization also provides opportunities to alleviate relative poverty. Through policy drive and technological innovation, it is possible to achieve urbanization in place in rural areas and restructure the socio-economic structure, promote the construction and application of information and communication technology infrastructure, and narrow the urban-rural digital gap. This can effectively alleviate the current complex and diverse poverty risks, especially those related to marginal poverty risks.
Thanks again for the valuable comments of the reviewer! These comments are very helpful in improving the quality of this article. We will try our best to improve the quality of the articles. At the same time, we also thank the editorial department for their hard work.
With best wishes！
Author Response File: 
Author Response.docx
Reviewer 2 Report
Comments and Suggestions for AuthorsBased on the socio-ecological perspective and spatial poverty theory, this paper explores the causes and spatial differentiation mechanism of three different types of rural poverty. Specifically, this paper takes the rural areas of eastern Tibet, a typical poverty agglomeration area, as an example, and uses RF, geographic detector and MGWR models and technologies to explore the spatial differentiation characteristics of rural areas in eastern Tibet and diagnose the key factors of differentiation formation. Most of the existing studies focus on vulnerability and resilience assessment in poor areas, which is innovative and novel to some extent.
Here's what I think should be improved:
1. In the screening and classification of factors causing poverty, the Moran index of the normalized vegetation index (NDVI) is incorrectly written, which should be − 0.17 (the original article is written as 0.217).
2. I think MGWR can write a specific model form and add some model explanation, which can better help readers understand the author's intention. The article only has descriptive statistics of intercept terms and explanatory variables.
3. The superposition effect of interaction factors can be introduced in more detail.
Comments on the Quality of English LanguageModerate editing of English language required
Author Response
Response to Reviewer 2 Comments
Many thanks for the valuable comments of the reviewer! These comments are very helpful in improving the quality of this article. We have made targeted changes according to these opinions. We also have done a careful polishing of the English expression in the full text. Now, let's make a detailed description of the changes.
Point 1: In the screening and classification of factors causing poverty, the Moran index of the normalized vegetation index (NDVI) is incorrectly written, which should be − 0.17 (the original article is written as 0.217).
Response 1: Thank you very much for your advice. We have corrected the Moran's I of the Normalized Difference Vegetation Index (NDVI) to -0.17 in the selection and classification of poverty-causing factors, as stated in line 354 of the manuscript.
Point 2: I think MGWR can write a specific model form and add some model explanation, which can better help readers understand the author's intention. The article only has descriptive statistics of intercept terms and explanatory variables.
Response 2: Thank you very much for your advice.This is extremely important to improve the quality and clarity of our papers. We have added an explanation of the multi-scale weighted regression model application scenarios and research selection of this this technical method in the 3.3.3 part of the manuscript, and provide the software download channel (including specific operation methods) for readers to understand in detail more detailed. The specific content is shown below:
The Multiscale Geographically Weighted Regression (MGWR) model is a new version of software applications based on Microsoft Windows and MacOS (https://sgsup.asu.edu/sparc/multiscale-gwr), designed for calibrating multiscale geographically weighted regression (GWR) models. It is gradually being widely used to explore the geographically varying relationships between the dependent variable/response variable and the independent variables/explanatory variables. Incorporating widely used methods for modeling spatial heterogeneity, it relaxes the assumption that all modeled processes operate at the same spatial scale. When considering the degree to which the influence of different independent variables on the dependent variable changes with the spatial scale, the main advantage of the MGWR model is that it not only allows for spatially varying parameter estimation but also generates a unique optimal bandwidth for the relationship between the dependent variable and each independent variable[42].
In this study, the administrative villages in the municipal area are the basic unit, and the study area has a complex topography, and the different independent variables are affected by the spatial scale. Thus, the MGWR model was used to detect spatial heterogeneity affecting rural spatial poverty drivers. It is possible to more precisely analyze and identify the magnitude of the effects of different poverty-causing influences in different geographic locations.
Point 3:The superposition effect of interaction factors can be introduced in more detail.
Response 3: Thank you very much for your advice.According to your suggestion, we have introduced and analyzed the "superimposed effect of interacting factors" in more detail in section 4.2.2 of the manuscript. The following is the revised version of the paper:
Spatial poverty incidence in rural areas of eastern Tibet was affected by a combination of factors. As shown in Fig. 10, in terms of ecological environment and geographical location, the interaction between CLSI and NDVI or LST was the most pronounced, reflecting the challenges faced by steep-slope areas between ecological conservation and economic development. For instance, the undertaking of construction and reclamation on more substantial gradients incurred not only significant costs but also engendered soil erosion and a diminution in vegetative cover,, exacerbating the ecological fragility of steep-slope areas, making them more sensitive to climate change and anthropogenic disturbances. which increased the risk of potential poverty and marginal poverty in the countryside.
In terms of ecological environment and social resources, the interaction between DSI and ESL was the most pronounced, with geological disaster-sensitive areas causing difficulties in siting facilities, leading to an uneven distribution of educational resources and posing the risk of recurrent and potential poverty. Not only does this limit access to quality education for the local population and exacerbate educational inequalities, but since education is a key pathway to enhancing the ability of individuals to lift themselves out of poverty and to reduce poverty in a sustainable manner, uneven access to education further increases the risk of marginalization and recurrent poverty in rural areas, creating a negative cycle.
In terms of geographical location and social resources, the interaction between CLSI and CPCI, ESL and MSL was the most obvious. Highlighting the deep-seated contradictions and challenges in rural areas across multiple dimensions such as geographical environment, land resources, social services, and economic development, the risk of persistent poverty in rural regions is exacerbated. Initially, this is manifested in the limitations of land use, where steep slopes restrict the area of arable land, directly impacting the scale and output of agricultural production, thereby weakening the self-sufficiency of the rural economy. Secondly, the reduction of land resources and the challenges posed by terrain intensify the dispersion of public service facilities, leading to an uneven distribution of educational and medical resources in rural areas, increasing the difficulty and cost for residents to access these essential services, and thereby aggravating social inequality and economic disparity. Moreover, the inequitable access to education and healthcare not only affects the quality of life and health standards of the residents but also limits talent cultivation and social mobility, making it difficult for rural areas to break free from the shackles of poverty.
Author Response File: Author Response.docx
