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Journal of Resources and Ecology >

2025 , Vol. 16 >Issue 5: 1515 - 1527

DOI: https://doi.org/10.5814/j.issn.1674-764x.2025.05.022

Agro-ecosystem and Rural Revitalization

Ethnic Minority Villages in the Upper Yangtze River Basin: Spatial Patterns, Formation Mechanisms, and Implications for Rural Revitalization

  • MA Taijia , 1 ,
  • CHEN Guolei , 1, * ,
  • LUO Jing 2 ,
  • SUN Jianwei 1 ,
  • LI Lianlian 1
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  • 1. School of Geographical and Environmental Sciences, Guizhou Normal University, Guiyang 550025, China
  • 2. Hubei Provincial Key Laboratory for Geographical Process Analysis and Simulation, Central China Normal University, Wuhan 430079, China
* CHEN Guolei, E-mail:

MA Taijia, E-mail:

Received date: 2025-04-02

  Accepted date: 2025-07-01

  Online published: 2025-10-14

Supported by

The National Natural Science Foundation of China(42271228)

The National Natural Science Foundation of China(41871176)

The National Natural Science Foundation of China(42361028)

The Guizhou Science and Technology Foundation(ZK[2021] General 186)

The Natural Science Research Fund of Guizhou Provincial Department of Education(Guizhou Jiaohe KY Zi [2022] 156)

The Guizhou Normal University Doctoral Research Project(GZNUD [2019] 5)

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Abstract

Minority characteristic villages are an important carrier of Chinese cultural heritage and key locations for the implementation of the rural revitalization strategy. This study takes 683 villages with national minority characteristics in the upper reaches of the Yangtze River Basin as the research object. It uses spatial analysis and geographic exploration technology to explore the spatial distribution characteristics of minority characteristic villages in the upper reaches of the Yangtze River Basin, the formation mechanism, and potential for rural revitalization. The results show that: (1) The spatial distribution of ethnic minority villages in the upper reaches of the Yangtze River Basin is not balanced, with an overall distribution pattern of “dense in the south and sparse in the north”. (2) The spatial distribution of ethnic villages is of the aggregation type, and the overall spatial distribution is characterized by “one nucleus with multiple points” and “cold in the north and hot in the east”. (3) The main factors affecting the spatial distribution of ethnic villages are the economy, population, ecology, transportation, and natural environment. (4) The spatial differentiation of ethnic villages in the upper reaches of the Yangtze River Basin is the result of a combination of factors. In the context of future rural revitalization, we should anchor the revitalization and protection of ethnic villages, focus on the construction of inter-regional cooperation mechanisms, refine the spatial layout and optimal integration, and sincerely devote ourselves to the excavation and inheritance of the unique culture of ethnic groups to comprehensively, profoundly, and systematically promote the efficient practice of the rural revitalization strategy.

Key words： ethnic minority villages; spatial distribution; influence mechanism; geographic exploration; rural revitalization

Cite this article

MA Taijia , CHEN Guolei , LUO Jing , SUN Jianwei , LI Lianlian . Ethnic Minority Villages in the Upper Yangtze River Basin: Spatial Patterns, Formation Mechanisms, and Implications for Rural Revitalization[J]. Journal of Resources and Ecology, 2025 , 16(5) : 1515 -1527 . DOI: 10.5814/j.issn.1674-764x.2025.05.022

1 Introduction

Minority characteristic villages (hereinafter referred to as ethnic villages) are natural or administrative villages with a relatively high concentration and proportion of ethnic minority populations, perfect production and living functions, and distinctive ethnic characteristics (Liu and Li, 2015). As the core and key entry point for coordinating human-land relations, ethnic villages play a crucial role in rural revitalization (Li et al., 2021). However, rapid industrialization and urbanization have disturbed these traditional settlements, leading to problems such as the fading of ethnic cultures, depopulation, population aging, and hollowing out of villages (Chen et al., 2018; Zou et al., 2022). Therefore, promoting the sustainable development of ethnic villages is urgently needed. Since 1982, China's policy framework regarding ethnic villages has evolved. Landmark regulations, such as the 1982 Law of the People's Republic of China on the Protection of Cultural Relics, the 2008 Regulations on the Protection of Famous Historical and Cultural Towns and Villages, and the Outline of the Plan for the Protection and Development of Villages with Ethnic Minority Characteristics (2011-2015), aimed to address the issues of architectural homogenization, over-commercialization of development, and cultural preservation. Between 2014 and 2020, the State Ethnic Affairs Commission recognized 1652 national-level ethnic villages in three batches, setting a benchmark for conservation work. In 2021, the Outline of the National Fourteenth Five-Year Plan and Vision 2035 further established the conservation of ethnic villages as a strategic priority for cultural heritage protection and rural modernization. Therefore, studying the spatial patterns of ethnic villages and their driving mechanisms in the context of rural revitalization is crucial for enhancing cultural resilience and promoting sustainable development.
The research on ethnic villages has become increasingly abundant worldwide. Foreign research mainly focuses on ethnic communities, and the research content primarily focuses on ethnic community tourism development (Yang et al., 2020), ethnic village tourism resilience (Wang et al., 2025), industrial development (Li et al., 2016a), operational management (Mbaiwa, 2011), and cultural preservation (Nichols, 2004). On the other hand, domestic research on ethnic villages covers multidisciplinary perspectives such as architecture, sociology, geography, and economics, and the topics include ethnic culture and industrial resilience (Xie et al., 2024; Yan et al., 2024), tourism development and management (Xu et al., 2012), cultural and ecological protection and development (Chen et al., 2024), spatial reconfiguration and morphological evolution (Zhang et al., 2016; Tao et al., 2023), landscape characterization and evaluation systems (Li et al., 2016b), and spatial distribution and influencing factors (Zhang et al., 2025). In studies on the spatial distribution and influencing factors of ethnic villages, the research scales involve different levels such as national, provincial, and municipal (Wang et al., 2025). The influencing factors are mainly classified into two categories: natural and humanistic, covering factors such as topography and geomorphology, the distribution of water systems, transportation networks and economic conditions (Chen et al., 2018). The research methods mostly use GIS spatial analysis and probes (Wang et al., 2025), such as the closest neighbor index, kernel density analysis, buffer zone analysis and other techniques (Yang et al., 2022). In general, the research on ethnic villages by scholars at home and abroad has produced fruitful results, which serves as a good reference for the theoretical framework of this study, but there are still some aspects for further improvement. For example, the attention to small- and medium-scale ethnic villages in specific watersheds is limited, and research on the contribution of ethnic villages to rural revitalization from the perspective of geography needs to be enriched. Therefore, research on ethnic villages in specific watersheds at small and medium scales is of great theoretical and practical significance.
The upper reaches of the Yangtze River Basin are an important ecological barrier area and ethnic culture-rich area in China, and the three provinces of Yunnan, Guizhou, and Sichuan have an irreplaceable strategic position in the maintenance of ecological security and ethnic culture inheritance. As the core area of the ecological security barrier in the upper reaches of the Yangtze River, these three provinces are the key areas for consolidating the results of poverty alleviation and realizing common prosperity in the ethnic regions. Their 683 national-level ethnic villages account for 41.3% of the country's total, making them an important carrier of Chinese cultural diversity and a key node for rural revitalization. The Chinese leader emphasized that “ethnic minority culture is an important part of Chinese culture, and we should protect and develop ethnic minority villages so that people of all ethnic groups can share the fruits of development” and pointed out that “we should adhere to ecological priority and green development, and organically combine the protection of ethnic cultures with ecological protection”. Taking the three provinces in the upper reaches of the Yangtze River Basin as the study area, this study adopted a spatial analysis method to systematically explore the spatial distribution characteristics of ethnic villages and their influencing mechanisms. Then based on those results, it also explored in-depth the inspiration of ethnic villages in helping rural revitalization. This study provides a scientific basis for optimizing the spatial development pattern of the upper reaches of the Yangtze River Basin and building a solid ecological barrier, and at the same time, it provides theoretical support and practical paths for ethnic villages to contribute to rural revitalization and promote regional high-quality development.

2 Data and methods

2.1 Data sources

(1) Ethnic village data
A total of 683 ethnic villages in three provinces in the upper reaches of the Yangtze River Basin were selected as the research samples. The sample information came from the list of three batches of national-level ethnic villages published by the State Ethnic Affairs Commission of the People's Republic of China from 2014 to 2020 (https://www.neac.gov.cn/seac/xwzx/201409/1002845.shtml). Using the Baidu coordinate picking system for place name searching, the geographic coordinates of the 683 ethnic villages in the three provinces in the upper reaches of the Yangtze River Basin were determined. The coordinates were imported into the ArcGIS 10.2 software, and an indicator database was established. Visual mapping was performed to obtain the spatial distribution map of the three batches of ethnic villages in the upper reaches of the Yangtze River Basin (Figure 1).
Figure 1 Spatial distribution of ethnic villages in the study area
(2) Geographic data
The administrative district map of the upper reaches of the Yangtze River Basin, DEM map with 30 m resolution, and river network data were extracted from the Resource and Environment Science Data Center of the Chinese Academy of Sciences (https://www.resdc.cn/Default.aspx).
(3) Natural and socioeconomic data
Using ArcGIS 10.2 software, the DEM elevation data of the three provinces were projected and cropped for the extraction and calculation of topographic relief data. The distances between villages and river systems were calculated using “superposition analysis” and “multi-ring buffer analysis” in ArcGIS 10.2 software. Population data, GDP per capita, rural disposable income per capita, and other socioeconomic data of cities and prefectures were obtained from the 2021 Statistical Yearbook of Cities (prefectures) and the National Economic and Social Development Statistical Bulletin for the corresponding years.

2.2 Research methods

2.2.1 Nearest neighbor index method

The nearest neighbor index is often used to express the degree of mutual proximity of point elements in space, and it can be calculated to analyze the spatial distribution of ethnic villages (Wang et al., 2023). The point elements can be divided into three types of spatial distribution: uniform, cohesive, and random distribution (Liu et al., 2023), and the calculation formula is:
R$\text{=}\frac{{{{\bar{r}}}_{\text{1}}}}{{{{\bar{r}}}_{\text{2}}}}\text{=}\frac{{{{\bar{r}}}_{\text{1}}}}{\text{1}/\text{2}\sqrt{\frac{n}{A}}}\text{=}\frac{{{{\bar{r}}}_{\text{1}}}}{\text{1}/\text{2}\sqrt{D}}$
where R is the nearest neighbor index; ${{\bar{r}}_{\text{1}}}$ is the actual closest neighborhood distance; ${{\bar{r}}_{\text{2}}}$ is the theoretical closest distance; n is the number of ethnic villages; A is the area of the study area; and D represents the density of points in the study area. A value of R>1 means that the distribution of villages in the study area is uniform; when R<1, it indicates that the distribution of villages is cohesive; and when R=1, it suggests that the distribution of villages is random.

2.2.2 Kernel density estimation method

The kernel density can reveal the spatial distribution density of ethnic villages and their characteristics (Shi, 2010), and the calculation formula is:
$f\text{(}x\text{)=}\frac{\text{1}}{n}\underset{i\text{=1}}{\overset{n}{\mathop \sum }}\,\frac{\text{1}}{h}k\left( \frac{x-{{x}_{i}}}{h} \right)$
where $f(x) $ is the kernel density function; n is the number of points in the neighborhood; h is the bandwidth; $k\left( \frac{x-{{x}_{i}}}{h} \right)$ is the kernel function; and (x–xi) is used to measure the distance between two points. The kernel densities of the three batches of national and ethnic villages were analyzed separately with the kernel density analysis tool in ArcGIS 10.2 software.

2.2.3 Spatial autocorrelation analysis

Spatial autocorrelation analysis can be used to determine whether there is a spatial correlation between the values of point elements and the neighboring elements (Sridharan et al., 2007). The Moran index (Moran's I) reflects the global autocorrelation, which can reveal the existence of spatial aggregation characteristics of villages, and the value range Moran's I is between (–1, 1). A positive value indicates that the spatial correlation between elements is positive; a negative value indicates that the spatial correlation between elements is negative; and a value of 0 indicates that the spatial distribution is uncorrelated. Local autocorrelation can be characterized by $\text{Getis-Ord}\ G_{i}^{\text{*}}$, which can reflect the degree of spatial agglomeration of villages in different units, and its standardized formula is:
$Z\left( G_{i}^{\text{*}} \right)\text{=}G_{i}^{\text{*}}-\frac{E\text{(}G_{i}^{\text{*}}\text{)}}{\sqrt{\text{Var(}G_{i}^{\text{*}}\text{)}}}$
where $E\text{(}G_{i}^{\text{*}}\text{)}$ is the expected value and $\text{Var}\ \text{(}G_{i}^{\text{*}}\text{)}$ is the coefficient of variation. If the value of $Z\left( G_{i}^{*} \right)$ is positive, then the ethnic villages around region i are in a high-value spatial agglomeration, or hot spot; and if the value of $Z\left( G_{\text{i}}^{\text{*}} \right)$ is negative, then the ethnic villages around region i are in a low-value spatial agglomeration, or cold spot.

2.2.4 Geodetector

Geodetector is often used to measure the spatial dissimilarity of elements and detect the interactions between explanatory factors and the driving factors behind them (Wang and Xu, 2017). In this study, the detector was used to analyze the spatial dissimilarity of the factors influencing the spatial distribution of ethnic villages, and its formula is:
$q\text{=1}-\frac{\text{1}}{N{{\sigma }^{\text{2}}}}\underset{j\text{=1}}{\overset{L}{\mathop \sum }}\,{{N}_{j}}{{\sigma }_{j}}^{\text{2}}$
where $q$ reflects the value of factors influencing the spatial distribution of ethnic villages in the upper reaches of the Yangtze River Basin; L is the type of factor influencing the spatial distribution of ethnic villages; j represents the stratum classification of a variable Y or detecting factor, and Nj and σj2 represent the sample size and variance of stratum j of the research object, respectively. q ranges from 0 to 1, and the larger the value, the stronger the effect of detection factors on the spatial distribution of ethnic villages in the upper reaches of the Yangtze River Basin.

3 Results and analysis

3.1 Spatial pattern of ethnic villages in the upper Yangtze River Basin

3.1.1 Spatial quantitative characteristics of ethnic villages

The ethnic villages in the upper reaches of the Yangtze River Basin are unevenly distributed among the different regions. Overall, the spatial distribution of ethnic villages is characterized as “dense in the south and sparse in the north,” and the villages are mainly distributed in the central part of Guizhou, the western part of Yunnan, and the northwestern part of the Sichuan Basin (Figure 2). At the provincial level, Guizhou Province has the largest number of ethnic villages, followed by Yunnan Province and then Sichuan Province, accounting for 45.68%, 36.16%, and 18.15% in that order. At the municipal level, the distribution of ethnic villages within different municipalities is quite uneven (Table 1). Among the 46 towns, only five prefectural-level cities and states (Qiandongnan, Aba, Qiannan, Dali, and Tongren) account for 40.5% of the total number of ethnic villages, of which Qiandongnan has the largest number of villages at 126, followed by Aba, Qiannan, Dali, Tongren, Qiuxinan, and Honghe Prefecture, with 25-40 villages each. Meanwhile, there are no ethnic villages in 12 cities in Sichuan, including Guang’an, Zigong, and Deyang. The probable reason for this is that these areas are located in the central and eastern parts of Sichuan Province, with relatively small minority populations which account for only 12.1% of the province, and this province has a fusion of traditional ethnic characteristics with modern culture, so it lacks the conditions for the formation of national-level ethnic villages.
Figure 2 Gradient distribution of ethnic villages in the upper Yangtze River Basin
Table 1 Ethnic villages at the city/prefecture level in the upper Yangtze River Basin
Region Number Percentage (%) Region Number Percentage (%)
Qiandongnan 126 18.45 Leshan 11 1.61
Aba 40 5.86 Wenshan 9 1.32
Qiannan 38 5.56 Zhaotong 9 1.32
Dali 38 5.56 Lijiang 7 1.02
Tongren 35 5.12 Guangyuan 7 1.02
Qianxinan 28 4.10 Diqing 6 0.88
Honghe 25 3.66 Panzhihua 5 0.73
Pu’er 24 3.51 Kunming 5 0.73
Ganzi 24 3.51 Yibin 4 0.59
Anshun 23 3.37 Qujing 2 0.29
Chuxiong 21 3.07 Ya’an 1 0.15
Lincang 20 2.93 Guang’an 0 0.00
Yuxi 19 2.78 Zigong 0 0.00
Liangshan 18 2.64 Deyang 0 0.00
Bijie 18 2.64 Dazhou 0 0.00
Dehong 17 2.49 Luzhou 0 0.00
Nujiang 17 2.49 Meishan 0 0.00
Zunyi 16 2.34 Nanchong 0 0.00
Guiyang 15 2.20 Chengdu 0 0.00
Xishuangbanna 15 2.20 Neijiang 0 0.00
Mianyang 14 2.05 Ziyang 0 0.00
Liupanshui 13 1.90 Bazhong 0 0.00
Baoshan 13 1.90 Suining 0 0.00

3.1.2 Spatial distribution types of ethnic villages

To analyze the degree of mutual proximity of ethnic villages and determine their spatial distribution types, the nearest neighbor index values of the three batches of ethnic villages in the upper reaches of the Yangtze River Basin were calculated using ArcGIS 10.2 software. The results (Table 2) show that the nearest neighbor index of all villages, and the first, the second, and the third batches of ethnic villages are 0.635, 0.733, 0.649, and 0.658, respectively, with R<1 and P<0.01, which passes the reliability test. This indicates that the ethnic villages of the three batches have a concentrated spatial distribution in the geographical area, and show a significantly aggregated distribution pattern. Further analysis reveals that the degrees of aggregation of the three batches of ethnic villages differ, in the order of the first batch>the third batch>the second batch. Before the State Ethnic Affairs Commission named the first and third batches of ethnic villages, the government issued documents such as the “Twelfth Five-Year Plan for Ethnic Minorities” and the “Opinions on the Implementation of the Strategy of Rural Revitalization”, which put forward the official opinions on the protection and inheritance of ethnic cultures, the implementation of the rural revitalization strategy, and the enhancement of cultural relic protection and utilization, indicating that the development of ethnic villages cannot be achieved without a high degree of support from the state. A series of policies have provided carriers and directions for the protection and development of ethnic villages and laid an important foundation for the inheritance and promotion of the excellent Chinese ethnic culture.
Table 2 Nearest neighbor index values and spatial distribution patterns of ethnic villages in the upper Yangtze River Basin
Batch R Z P Distribution pattern
First batch 0.733 -5.31 <0.001 Aggregation
Second batch 0.649 -11.89 <0.001 Aggregation
Third batch 0.658 -10.56 <0.001 Aggregation
Total 0.635 -18.27 <0.001 Aggregation

3.1.3 Spatial density characteristics of ethnic villages

To reveal the spatial agglomeration characteristics of ethnic villages in the upper reaches of the Yangtze River Basin, mapping was conducted using the “Kernel Density Analysis” tool in ArcGIS 10.2 software. The kernel density values were categorized into five levels using the natural breakpoint method, and the results are shown in Figure 3. 1) The spatial agglomeration of ethnic villages in the upper reaches of the Yangtze River Basin is remarkable, and the overall spatial distribution is characterized by “one nucleus and many points”. The “one core” is the area of high nuclear density, located in Qiandongnan and Qiannan Prefectures, and the “multiple points” is the area of high nuclear density, located in the Qianzhong area of Guizhou and Ganzi Prefecture of Sichuan (Figure 3a). 2) For the different batches, the first batch of ethnic villages formed several agglomerations characterized by “multi-core” distribution. The areas with high kernel density are mainly located in Tongren, Qiandongnan, Guiyang, Qiannan, Anshun, and Qianxinan, while the areas with higher kernel density are mainly located in Honghe, Pu’er, Lincang, Dehong, Dali, Lijiang and Nujiang (Figure 3b). The degree of concentration of ethnic villages in the second batch is less than that of the first batch, showing a spatial distribution characterized by a “single core” in Guizhou's Qiandongnan Prefecture. The area of lower-value zones has increased extensively, with obvious spatial differences, and the distribution of ethnic villages in cities and states other than Qiandongnan Prefecture is characterized by low aggregation (Figure 3c). The third batch of ethnic villages has achieved a certain degree of development compared with the second batch. Higher-value areas in western Yunnan and the northwestern Sichuan Basin are distributed in a “sporadic” manner, with greater concentration (Figure 3d).
Figure 3 Kernel density map of ethnic villages in the upper Yangtze River Basin

3.1.4 Spatial association characteristics of ethnic villages

The data in Table 3 show that the Moran's I for the spatial distribution of all ethnic villages is estimated to be 0.2495, which is greater than 0. The Moran's I values of the first, second, and third batches are estimated to be 0.5248, 0.1291, and 0.1919, respectively, which are all greater than the expected index of -0.0222, indicating that the spatial distribution of ethnic villages exhibits significant spatial positive correlation in areas of similar quantity and scale. The cold spot/hot spot map of the spatial distribution of ethnic villages was produced using the hotspot analysis tool in ArcGIS (Figure 4), and it shows that the spatial distribution of ethnic villages is characterized by “cold in the north and hot in the east”. Generally, the northeastern and southern areas of Sichuan Province, western Guizhou, and northern and eastern Yunnan Province are cold spots and insignificant areas with the most sparse distribution of ethnic villages. Ethnic villages are mainly concentrated in the hotspot and sub-hotspot areas such as Qiandongnan, Qiannan, Pu’er, Yuxi, Ganzi, and others, which show significant differences in spatial distribution.
Table 3 Moran's I values of the overall situation of ethnic villages in the upper Yangtze River Basin
Batch Global
Moran's I		 Expected index value Variance Z value P value
First batch 0.5248 -0.0222 0.0043 8.2819 <0.0001
Second batch 0.1291 -0.0222 0.0017 3.6292 0.0003
Third batch 0.1919 -0.0222 0.0042 3.2778 0.0010
Total 0.2495 -0.0222 0.0027 5.1971 <0.0001
Figure 4 Cold and hot spot analysis of ethnic villages in the upper Yangtze River Basin

3.2 Factors influencing the spatial distribution of ethnic villages in the upper reaches of the Yangtze River Basin

3.2.1 Influencing factor selection

Compared with villages in general, minority characteristic villages in the upper reaches of the Yangtze River Basin have distinctive ethnic cultural and ecological composite characteristics, and their spatial differentiation patterns are affected by multiple factors such as natural geographic conditions and socioeconomic development. Based on the evaluation index system of ethnic minority characteristic villages (Li et al., 2015; Li et al., 2016b), this study referred to the research ideas of Wang and Liu (2019), Kong et al. (2023), and Zou et al. (2023). Then, considering the scientific nature of the indexes the availability of data, and the location of the upper reaches of Yangtze River Basin, the spatial differentiation pattern of ethnic villages was constructed from the five dimensions of economic development level, population distribution, ecological environmental quality, transportation capacity, and natural environmental conditions, and then compared to that of villages in general. The indicator system of factors influencing the spatial differentiation of ethnic villages in the upper reaches of the Yangtze River Basin is shown in Table 4 and includes the following specific indicators. 1) The regional economic development level is an important factor affecting the development, protection, and inheritance of ethnic villages, and the three indicators of per capita GDP, per capita disposable income of rural residents, and urbanization rate were selected for analysis (Sun et al., 2017). 2) Population distribution directly impacts the development of ethnic villages, and two indicators were selected, namely, the number of ethnic minority populations and population density (Yang et al., 2021). 3) Ecological environmental quality is an important guarantee and material basis for the economic development of ethnic villages, and the total amount of water resources and forest coverage were selected (Zou et al., 2023). 4) Transportation conditions are important support for the external communication and contact of characteristic villages, and the two indicators of highway mileage and density were adopted (Wu et al., 2025). 5) Natural environmental conditions are the basic factors restricting human agricultural production and the layout of villages, and the two indicators of topography and river water system were selected (Zhou et al., 2020). All these indicators were imported into ArcGIS, and their correlations were analyzed comprehensively with the help of overlay, buffer, detector, and other methods.
Table 4 Detection results of factors influencing ethnic villages in the upper Yangtze River Basin
Dimension Indicator Unit q value P value
Population distribution characteristics Population of ethnic minority groups (X1) persons 0.451 <0.001
Population density (X2) persons km-2 0.321 <0.001
Economic development level Urbanization rate (X3) % 0.233 <0.001
Rural disposable income per capita (X4) yuan 0.329 <0.001
GDP per capita (X5) yuan 0.116 <0.001
Ecological environmental quality Total water resources (X6) 108 m3 0.325 <0.001
Forest coverage rate (X7) % 0.263 <0.001
Transportation capacity Highway mileage (X8) km 0.118 <0.001
Highway density (X9) km (104 persons)-1 0.299 <0.001

3.2.2 Influence factor detection and analysis

By using the detector to measure the q-value of the driving force of the factors influencing ethnic villages, the results (Table 4) show that there are significant differences in the driving forces influencing the spatial distribution of ethnic villages. Their q-values are ranked as the number of ethnic minority populations (0.451)>disposable income per capita in rural areas (0.329)>total water resources (0.325)>population density (0.321)>road density (0.299)>Forest cover (0.263)>Urbanization rate (0.233)>Highway mileage (0.118)> GDP per capita (0.116). Clearly the number of ethnic minority populations, rural per capita disposable income, and total water resources are the main influencing factors controlling the spatial differentiation of ethnic villages. In contrast, GDP per capita and road mileage have weaker influences on the distribution of ethnic villages.
Interaction detection was carried out to further explore whether a synergistic effect among the factors affecting the spatial layout of ethnic villages enhances the explanatory efficacy of the spatial differentiation (Figure 5). The results show that the interactive effect between different influencing factors is greater than the independent effect of a single factor. The interaction type is two-factor and nonlinear enhancement. Therefore, the independent factors do not influence the spatial distribution of ethnic villages, but the distribution is the result of the interaction of economic development, population distribution, transportation, the natural environment, and other factors. Among them, population density, rural per capita disposable income, and forest coverage have the strongest interactions with other factors, all exceeding 0.400, indicating that these three factors play a dominant role in the interaction. The interaction between the total amount of water resources and the number of ethnic minorities is the greatest, with an interactive effect of 0.842, followed by the interaction between forest coverage and the number of ethnic minorities, with an interactive effect of 0.834. This indicates that the distribution of ethnic villages is greatest in areas with abundant water resources, extensive forest coverage and a large number of ethnic minorities.
Figure 5 Factor interaction detection results

3.2.3 Exploring the causes of differentiation patterns

(1) Population distribution. Population distribution has an important influence on the inheritance and development of ethnic culture. In the detection results of influencing factors, the number of minority populations and population density have significant explanatory powers of 0.451 and 0.321, respectively. They also frequently interact with other factors, showing interaction values greater than 0.500, indicating that the population size and density have a stronger effect on the overall spatial distribution of ethnic villages. As the main body of agricultural production and the primary element of regional economic development, population drives the continuation and growth of villages with different regional characteristics. In addition, the migration and mobility of ethnic minority populations and their aggregation and reproduction promote the evolution and development of the spatial structure of ethnic villages to a deeper extent.
(2) Level of economic development. Regional economic development is an important pillar for the protection and inheritance of ethnic villages. In the influencing factor detection results, the effect of economic development level on the spatial distribution of ethnic villages is weak; and its indicator layers of urbanization rate, rural per capita disposable income, and per capita GDP have explanatory powers of 0.233, 0.329, and 0.116, respectively. Combined with the kernel density analysis map (Figure 3), this study found that some regions with lower levels of economic development have more ethnic villages. For example, Qiandongnan of Guizhou, Dali of Yunnan, and Aba of Sichuan are the cities and states with the highest distribution of ethnic villages in their respective provinces, but their per capita GDPs are only 70.7%, 89.4%, and 96.3% of the provincial averages; their per capita disposable incomes are 86.8%, 104%, and 87.2%, respectively; and their urbanization rates are 88.5%, 93.7%, and 81.9%, respectively. Except for Dali, where the per capita disposable income was higher than the provincial average, in the three regions where the number of ethnic villages ranked first among the provinces, the average values of these three key indicators were lower than the provincial averages. This is mainly due to the relatively weak economic development of the region, which is constrained by the terrain. As a result, the agricultural industry accounts for a large proportion of the way of life, the living habits tend to retain the traditional style, and the authenticity of the ethnic villages has been better protected.
(3) Transportation capacity. Transportation is an important condition for a region's external links. However, the influencing factor results show that transportation capacity has the lowest explanatory power for the spatial distribution of ethnic villages. The explanatory powers of road mileage and highway density among the secondary indicators are only 0.118 and 0.299, respectively. Still, the factor interaction results show that the explanatory power of the interaction between transportation conditions and other influencing factors is significantly enhanced, with the maximum interactive effect value reaching 0.831 and the minimum value being 0.377. Regional transportation conditions do not substantially affect the spatial differentiation of ethnic villages in the short term. However, strengthening the construction of transportation in ethnic areas is still necessary to promote the development and integration of tourism resources, facilitate the circulation of agricultural products, activate the ethnic culture, and promote the synergistic development of the economy, society, and culture in ethnic areas.
(4) Ecological environmental quality. The ecological environment has a direct impact on the spatial differentiation of ethnic villages. The explanatory powers of total water resources and forest cover are 0.325 and 0.263, respectively, so they have a more prominent influence on the distribution of ethnic villages. They also have stronger interactions with other factors, among which the interactions with the number of ethnic minority populations are as high as 0.842 and 0.834 respectively, indicating that the distribution of ethnic villages in regions with a better ecological environment is higher. The upper reaches of the Yangtze River Basin, such as Qiandongnan, Pu’er, Nujiang, Qiannan, Tongren, and others, have abundant natural resources and a good ecological environment, which are favorable for allowing ethnic groups to gather and flourish. These areas not only carry rich ecological functions but also meet the preferences of ethnic groups for an ideal living environment, and they provide sufficient material protection for the survival and development of the groups, thus becoming the areas where ethnic villages thrive.
(5) Natural geographic elements. The natural geographic environment is the basis for human production and life and the layout of villages. The relationship between the spatial distribution of ethnic villages and the topography and rivers was explored through superposition analysis and buffer zone analysis methods. As shown in Table 5, the number of ethnic villages shows a decreasing trend with an increase in elevation. The ethnic villages are concentrated at 74-1768 m above sea level, accounting for 72% of the total villages. The three batches of ethnic villages are all demarcated by 2775 m, showing a distribution pattern of “ladder-like” decline. This is because lower terrain is more convenient for the living and working of residents, which attracts the population to gather and form many villages with special characteristics, and also indicates that the spatial differentiation of ethnic villages in the upper reaches of the Yangtze River Basin is greatly influenced by regional topographic conditions.
Table 5 Relationship between ethnic villages and elevation
Elevation (m) [74, 992] [993, 1768] [1769, 2775] [2776, 3867] [3868, 7433]
First batch 41 43 20 3 1
Proportion (%) 38 39.8 18.5 2.8 0.9
Second batch 120 118 59 15 2
Proportion (%) 38.2 37.6 18.8 4.8 0.6
Third batch 84 86 74 17 0
Proportion (%) 32.2 33 28.3 6.5 0
Total 245 247 153 35 3
Proportion (%) 35.9 36.2 22.4 5.1 0.4
The river water system is a key resource that affects agricultural production and the survival of ethnic characteristics. With the help of the multi-ring buffer method, the influence of the major rivers in the three provinces in the upper reaches of the Yangtze River Basin on the ethnic villages was analyzed and they were divided into five grades with an equal spacing of 2 km to explore the spatial distances between the towns and the rivers. The results (Table 6) show that with an increase in the buffer radius, the number of villages gradually decreases, presenting a distribution characteristic of “near the water”. Ethnic villages are mostly distributed within the range of less than 2 km from water, with 203 villages accounting for 29.7%. Within the range of the five levels, the number of ethnic villages in the three batches decreases with an increasing distance from the river. This is because a closer distance to the river is more favorable for the settlement's agricultural irrigation and domestic water use; and the relatively flat terrain around the river valleys is conducive to the development of the settlement's agriculture. In addition, the river's shipping and transportation conditions also make material exchange and cultural dissemination more convenient.
Table 6 Relationship between ethnic villages and distance to a river
Distance (km) (0, 2] (2, 4] (4, 6] (6, 8] (8, 10]
First batch 34 11 7 13 6
Proportion (%) 31.5 10.2 6.5 12.0 5.5
Second batch 96 31 37 33 23
Proportion (%) 30.6 9.9 11.8 10.5 7.3
Third batch 73 30 27 17 26
Proportion (%) 28.0 11.5 10.3 6.5 9.7
Total 203 72 71 63 55
Proportion (%) 29.7 10.5 10.4 9.2 8.0
The diagram in Figure 6 shows that the spatial distribution characteristics of ethnic villages in the upper reaches of the Yangtze River Basin result from the combined effects of natural and human factors, such as population size, per capita disposable income, transportation capacity, and forest coverage. As a carrier, population distribution is the key to the spread of ethnic culture, which drives the dynamic evolution of the spatial aggregation pattern of villages, while the economy provides material support for the survival of villages and promotes the further expansion of the spatial pattern of villages. High transportation costs not only restrict the economy but also preserve the original appearance of the village to a certain extent. The ecological environment serves as a catalyst, complementing the development of the village. The geographic environment is the natural foundation for the spatial pattern of the village, providing a suitable site for the production and living of ethnic communities under the spatial structure.
Figure 6 Mechanisms influencing the spatial distribution of ethnic villages in the upper Yangtze River Basin

4 Conclusions and implications

4.1 Conclusions

This study took 683 national ethnic villages in the upper reaches of the Yangtze River Basin as the research object and adopted the methods of nearest neighbor index, kernel density estimation, and spatial autocorrelation analysis to reveal the spatial distribution pattern of ethnic villages in the upper reaches of the Yangtze River Basin. It also analyzed the mechanisms influencing the spatial differentiation of ethnic villages with the help of geographic probes, spatial superposition and buffer analysis. Three main conclusions can be drawn from these analyses. 1) In terms of spatial distribution, the distribution pattern is “dense in the south and sparse in the north”. The distribution type is aggregation, and the overall spatial distribution is characterized by “one nucleus and multiple points” and “cold in the north and hot in the east”. 2) The results show that the spatial distribution of ethnic villages is mainly affected by the dual role of natural and human factors. The most significant impact among the human factors is from population distribution, followed by the economic level, while the weakest impact is from the transportation capacity. In the natural geographic environment, with an increase in elevation, and as the distance from the river increases, the number of ethnic villages shows a decreasing trend, and the ethnic villages are mostly located in the lower terrain area and “near water”. 3) The results of the interaction detection of factors show that the interactive effect between different influencing factors is greater than the independent effect of a single factor, indicating that the spatial differentiation of ethnic villages results from the joint action of multiple factors. Specifically, population density, rural per capita disposable income, forest coverage and other factors have the strongest interactions. The total water resources and the number of ethnic minorities have the largest interaction.

4.2 Implications for rural revitalization

From the perspective of rural revitalization, based on this study on the spatial differentiation pattern and influence mechanism of ethnic villages in three provinces in the upper Yangtze River Basin several policy implications can be proposed.
(1) Establish a cross-provincial cultural and ecological reserve based on the spatial distribution characteristics. Given the spatial distribution pattern of ethnic villages in the upper reaches of the Yangtze River Basin, regional delineation should be optimized and development patterns should be identified to improve policy implementation precision. The three major ethnic village agglomerations of Qianzhong, western Yunnan, and northwestern Sichuan are rich in traditional culture and history, and their unique cultural and ecological resources are the core for establishing cross-provincial cultural and ecological reserves. The government should delineate the scope of the cultural and ecological reserves and formulate and implement targeted protection plans based on local development patterns, architectural styles, and cultural characteristics. In the scattered distribution areas such as Qujing, Yibin, and Zunyi, which are close to the borderlines between the three provinces, attention should be paid to excavating the cultures of characteristic villages and combining traditional ethnic culture with modern elements to ensure the living transmission of culture and expand regional influence. In addition, it is necessary to break through the administrative barriers across provinces and ensure continuous policy guarantees and financial support to realize the overall protection of the cultural ecosystem.
(2) Combine the mechanism of spatial distribution and promote the revitalization system of ethnic villages at different levels. The spatial distribution of ethnic villages in the upper reaches of the Yangtze River Basin is affected by a combination of factors, and the promotion of ethnic village revitalization should be considered from three aspects. First, promote the exchange and blending of the cultures of various ethnic groups. Through folklore sharing, inter-ethnic intermarriage, joint schooling, and other initiatives a platform for ethnic cultural exchanges should be created to inject lasting vitality into revitalizing the ethnic villages. Second, convert resources into productivity by making full use of the endowed resources of the watershed to create ethnic industries, such as rural leisure and agricultural tourism, which will drive employment and promote economic development. Third, develop differentiated infrastructure construction standards. For high-altitude regions, river valleys along the river, ecological protection, and other regions, the ecological toughness standards for transportation, energy, water conservancy, and other facilities need to be established. Through cultural integration to coalesce development consensus, industrial empowerment to stimulate endogenous power, and facility upgrading to build a solid foundation for development, we can create a revitalization system for ethnic villages that synergizes cultural inheritance and economic growth.
(3) Improve the graded training path of non-genetic inheritance bearers to stimulate the vitality of rural revitalization. For the inheritance crisis faced by the non-heritage industry of ethnic villages in the process of industrialization, systematic measures should be taken. First, establish a four-level inheritance system of “national-provincial-city- county” and formulate corresponding recognition standards and support policies to form a hierarchical talent structure. Second, according to the degree of endangerment of inheritance projects and the age structure of the inheritors, adopt key protection, regular cultivation and innovative cultivation measures to improve the cultural inheritance and economic growth. At the same time, a dynamic evaluation and withdrawal system for inheritors needs to be established, and safeguarding policies such as subsidies for inheritance activities should be improved. Finally, given the current problems such as small audiences in the non-heritage industry, insufficient inheritance motivation, and difficulty in training young inheritors, we need to increase the digitalization of the non-heritage industry, cultivate subdivided audience groups with the help of live broadcasting and other new media to satisfy the diversified cultural needs, broaden the living space of non-heritage, and realize the simultaneous development of non-heritage living inheritance and rural cultural revitalization.
(4) Promote the point-axis gradual expansion mode and build a community of ethnic villages. First, select the model village as the core of development and drive the development of the surrounding villages along the transportation arteries, economic corridors, and cultural ties. Second, cultivate characteristic advantageous industries in the model villages, incorporate the neighboring villages’ local characteristics and folklore experience projects into the development routes, and promote regional participation in the industrial division of labor and resource sharing. Once again, the model villages should be taken as the core nodes of cultural dissemination, and the exchange and integration of national cultures within the point-axis region should be promoted. Finally, the construction of high-speed information networks and interconnected infrastructure will promote information exchange and resource sharing among “people”, “places” and “industries”, thereby providing strong support for the comprehensive revitalization of the ethnic village community.

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