Genetic Characteristics of Spatial Network Structures in Traditional Bouyei Village Architecture in Central Guizhou

Abstract

Traditional villages are irreplaceable cultural heritage sites, and studying their architectural spatial networks is key to preserving both the villages and their culture. This research focuses on four Bouyei villages in Central Guizhou, using social network analysis, spatial gene theory, and diversity analysis to explore their architectural spatial network characteristics. Findings include the following: (1) Zhenshan Village has the best network condition, while that or the others is average; (2) all the villages show low vulnerability Cp-1 genes; (3) Bouyei architectural networks are stable and continuous; and (4) the network is influenced by military culture, feng shui, agricultural culture, Buyi ethnic spiritual beliefs (Mo Belief Culture), topographical conditions, and modern planning interventions. The study aims to deepen the understanding of the cultural values and spatial layout characteristics of traditional villages, while preserving the cultural heritage of traditional settlements and ethnic minorities.

1. Introduction

Traditional Chinese villages are ancient settlements with historical, cultural, scientific, artistic, social, and economic value [1]. While China has implemented strategies to promote the sustainable development of villages, such as the evaluation process for the Chinese Traditional Villages List [2], rapid urban expansion has often overlooked the unique regional characteristics of these villages during planning and renovation. This has led to dramatic changes in architectural styles and spatial patterns, resulting in the marginalization of traditional villages in modern society [3]. Bryan Lawson emphasized in The Language of Space that “space not only creates the environment but also organizes human behavior and social relationships”. Recent studies further demonstrate that changes in the external environment can influence the cohesion of social relationships [4,5]. Therefore, studying the architectural space of traditional villages is critical for their sustainable development and preservation.

In recent years, research on traditional village spaces has primarily focused on landscape spaces [6,7], public spaces [8,9], and spatial morphology [10,11]. The concept of “space syntax”, introduced comprehensively in the 1970 book Space is the Machine [12,13], established a systematic research framework for studying spatial physical forms and structural sequences, and offered new directions for contemporary architectural space studies. However, space syntax is commonly applied in urban planning, where social relationships are relatively weak [14,15,16], and proves less effective in rural areas, where strong interactions exist between social relationships and architectural distribution. To address this gap, some scholars have applied social network analysis to the study of architectural spatial networks in traditional villages [17,18]. This method, also utilized in urban planning [19,20], explores the intrinsic connections within architectural spaces by analyzing spatial network characteristics and proposing strategies for conservation and renewal.

In 1976, Richard Dawkins introduced the concept of the meme in The Selfish Gene, likening it to a gene and identifying it as the fundamental unit of cultural inheritance [21]. In 1996, the theory of “gene–culture coevolution” was proposed, introducing “culturgen” as the basic unit of cultural inheritance [22]. In 1990, Chinese scholar Liu Changlin offered a comprehensive definition of cultural genes in China’s Systems Thinking: A Perspective on Cultural Genes [23]. Since the beginning of the 21st century, research on cultural genes has expanded, focusing on the transmission of traditional culture [24,25]. Building on the idea of cultural genes, scholars have applied the gene concept to historical landscapes and spatial layouts of towns and settlements, coining the term “landscape genes” to describe inherited cultural elements in settlement landscapes that feature distinctive prototypical characteristics passed down through generations [26]. The cultural elements of settlement landscapes that have been passed down through generations and exhibit significant primitive characteristics are referred to as landscape genes, such as the Drum tower and songs of the Dong ethnic group [27]. Current research on landscape genes primarily focuses on the identification of landscape genes in traditional villages [27,28] and the construction of landscape gene maps [29,30]. The emerging concept of spatial genes is defined as “the smallest unit of genetic information about intrinsic laws or principles of nature, society, and art, inherited both innately and experientially, representing the fundamental unit of spatial trait inheritance” [31]. Research on spatial genes can be summarized into two main areas: the identification and diversity of spatial genes [32,33,34] and the inheritance and renewal of spatial genes [35,36]. Notable examples include studies on the diversity of spatial genes in traditional villages of the Dong ethnic group [32] and the Bai ethnic group [33], which examine the spatial gene characteristics and inherent structural connections within ethnic minority villages.

Overall, research on the architectural spatial network characteristics and spatial genes of traditional Bouyei villages remains limited. Considering the close relationship between social connections and village architectural layouts [3], this study employs social network analysis and spatial gene theory to examine the spatial network characteristics and spatial network genes of traditional village architecture. Spatial gene studies typically examine “spatial relationships”, “spatial attributes”, or “spatial entities”, and encompass structural, functional, or morphological genes [2]. This study focuses on spatial structure genes, analyzing the organizational patterns and inherent logic of nodes and connections in spatial networks. This quantitative approach uncovers underlying structural rules while addressing surface characteristics.

Four traditional Bouyei villages in Central Guizhou—Awai, Gaodang, Zhenshan, and Matou—were selected for this study. First, the architectural spatial network characteristics were analyzed, and this was followed by the identification of architectural spatial network genes. Finally, the importance values and diversity indices were used for a quantitative analysis of the spatial network genes. This study aimed to deeply explore the spatial characteristics and architectural wisdom of traditional Bouyei villages, with the hope of contributing to the protection and sustainable development of traditional villages.

2. Study Areas and Objects

2.1. Study Area

The study area is located in central Guizhou, China (22°25′ N–28°20′ N, 105°47′ E–108°41′ E), a region characterized by typical karst landforms [37]. The terrain is predominantly mountainous and hilly, with a warm and humid climate. Guizhou Province accounts for 87.94% of the Bouyei population in China and 20% of the minority population in the province. A total of 757 villages in Guizhou have been included in the List of Chinese Traditional Villages (from https://www.gov.cn/ accessed on 12 April 2024. For non-Chinese readers, please visit https://www.dmctv.cn/villages.aspx?lx=cl (accessed on 20 January 2025), and use the translation feature to access the list of traditional villages). The unique natural environment of central Guizhou has constrained transportation and economic development, preserving many original characteristics of the villages, which offer significant research value. However, in recent years, traditional villages in central Guizhou have faced challenges such as the disruption of spatial patterns and threats to cultural heritage due to rapid urbanization. Therefore, selecting this region as the study area holds substantial theoretical and practical significance. Figure 1 illustrates the study area.

2.2. Research Objects

This study selected four traditional Bouyei villages in central Guizhou as the research subjects: Awai Zhai, Gaodang Village, Zhenshan Village, and Matou Village. These villages all exhibit typical Bouyei cultural characteristics and hold significant research value in terms of their historical culture and architectural spatial layout (Table 1).

3. Research Methods

3.1. Building Space Network Analysis Method

The study employed ArcGIS 10.8, Matlab 2021b, and UCINET 6 to construct architectural space networks through three steps (Figure 2): first, ArcGIS was used for preliminary spatial data analysis and processing (The base data consist of maps containing building and road layout information, sourced from https://www.tianditu.gov.cn/, accessed on 20 December 2023, and field surveys conducted in April 2024); second, Matlab was utilized to create a 2-mode binary matrix representing the relationships between buildings and roads; and finally, the matrix data were imported into UCINET for network feature analysis. This process allows for effective analysis of spatial connectivity and provides foundational data for subsequent spatial analysis, optimization, or simulation.

Figure 3 shows the results of spatial connectivity processing for the sample village using ArcGIS, highlighting the relationships and connections between buildings and roads within the study area. It provides a visual representation of spatial patterns and connectivity.

In the 1-mode binary matrix of the architectural spatial network, a “1” indicates a road connection between buildings, while a “0” signifies no connection (see Figure 4).

Based on social network analysis methods [2], Table 2 presents the characteristics, definitions, formulas, and functions of the five indicators applied in this study for architectural space network analysis: network density, Lambda difference, cutpoints, degree centrality, and betweenness centrality.

3.2. Spatial Network Gene Identification System for Bouyei Architecture in Central Guizhou

Inspired by the hierarchical structure of plant communities [38] and previous studies on spatial genes [31,32], the architectural space network genes are divided into four gene fragments, five genetic units, and ten genotypes (network characteristic attributes). Figure 5 illustrates the hierarchical classification of architectural space network genes. Each gene unit (e.g., density or cutpoint) corresponds to a specific gene segment (e.g., completeness or vulnerability), collectively defining the spatial network genes of traditional Bouyei villages.

Gene types are named and coded systematically based on the initials of the gene segments and units (e.g., architectural space network–vulnerability–cutpoint: AsnVCp-1 and AsnVCp-2. For simplicity, these will be referred to as Cp-1 and Cp-2 in subsequent sections.) The breakpoint values for gene trait expression were derived from the standardized average values of architectural space network indicators from four sample villages. The identification results are shown in Table 3.

3.3. Determination of Importance Values and Diversity in Building Spatial Networks

To analyze the architectural spatial network data for the four traditional villages, statistical analysis of importance and diversity was conducted using Excel2021 software.

A. Measurement of gene importance in Bouyei architectural spatial networks in Central Guizhou.

To further investigate the characteristics of the architectural spatial network genes of Bouyei traditional villages in Guizhou, the importance of the gene values was measured to determine the significance and role of each gene. The calculation formula is as follows [38]:

Importance Value = (Relative Abundance + Relative Significance + Relative Frequency)/3

where:

Relative Abundance (RA) is the number of individuals of a specific spatial network gene divided by the total number of spatial network gene individuals, multiplied by 100%.

Relative Significance (RD) is the significance of a specific spatial network gene divided by the total significance of all spatial network genes, multiplied by 100%.

Relative Frequency (RF) is the frequency of a specific spatial network gene divided by the total frequency of all spatial network genes, multiplied by 100%.

B. Measurement of gene diversity in Bouyei architectural spatial networks in Central Guizhou.

This study employs a combination of richness and evenness indices to measure the diversity of spatial network genes. Drawing from biodiversity research [24], specifically, two richness indices—Margalef’s index and Simpson’s index, and one evenness index—Pielou’s index is applied. If a spatial network contains a variety of spatial network genes with even distribution, it is considered to have high diversity. The calculation formulas are as follows:

(1) Margalef index:

The Margalef index is calculated as follows:

(1)$\mathrm{Margalef}\mathrm{Index}={\displaystyle \frac{\left(\mathrm{S}-1\right)}{\mathrm{InN}}}$

where S represents the number of different types of spatial network genes in the network and N is the total number of spatial network genes in the network.

(2) Simpson index:

The Simpson index measures the probability that two randomly chosen individuals belong to the same gene type. It is calculated as follows:

(2)$\mathrm{Simpson}\mathrm{Index}=1-{{\displaystyle \sum }}_{\mathrm{i}=1}^{\mathrm{k}}{\left({\displaystyle \frac{{\mathrm{n}}_{\mathrm{i}}}{\mathrm{N}}}\right)}^2$

where n_i is the number of individuals of gene type i and N is the total number of spatial network genes.

(3) Pielou index:

The Pielou index, which measures the evenness of gene distribution, is calculated as follows:

(3)$\mathrm{Pielou}\mathrm{Index}={\displaystyle \frac{{\mathrm{H}}^{\prime }}{\mathrm{InS}}}$

where H′ is the Shannon–Wiener diversity index and InS is the natural logarithm of the number of different gene types S. The Shannon–Wiener diversity index is calculated as follows:

(4)${\mathrm{H}}^{\prime }={{\displaystyle \sum }}_{\mathrm{i}=1}^{\mathrm{k}}\left({\displaystyle \frac{{\mathrm{n}}_{\mathrm{i}}}{\mathrm{N}}}\right)\mathrm{In}\left({\displaystyle \frac{{\mathrm{n}}_{\mathrm{i}}}{\mathrm{N}}}\right)$

where n_i is the number of individuals of gene type i and N is the total number of spatial network genes.

Note: For Pielou’s index, Pi represents the importance ratio of the i-th gene type in the Bouyei traditional village spatial network, calculated as follows:

(5)$\mathrm{Pi}={\displaystyle \frac{{\mathrm{n}}_{\mathrm{i}}}{\mathrm{N}}}$

where n_i is the number of individuals of the i-th gene type and N is the total number of spatial network genes in the sample.

4. Results

4.1. Analysis of Architectural Spatial Network Characteristics in Bouyei Traditional Villages of Central Guizhou

Table 4 shows that the architectural spatial network of Zhenshan Village is in better condition compared to that of the other three villages.

Zhenshan Village exhibits the highest network density, while Matou, Gaodang, and Awai villages show similar densities, with Awai having the lowest. Network density reflects the connectivity level of village roads. Zhenshan Village, influenced by its military garrison culture and defensive terrain, features densely built structures and grid-like road connections. Matou and Gaodang, as first- and second-batch traditional villages, respectively, have undergone earlier planning and protection efforts, with many roads being reconstructed. Awai Village, characterized by hilly terrain and dispersed buildings, has relatively fewer roads.

The proportion of cutpoints across all four villages is 0.00%, indicating no disconnections within their architectural spatial networks. This suggests that Bouyei traditional villages in central Guizhou exhibit low vulnerability, good neighborhood relations, and minimal building isolation.

The Lambda difference of Gaodang Village is close to that of Awai and Zhenshan villages, with Zhenshan Village having the lowest value, indicating the highest network stability. Matou Village, however, has a higher Lambda difference, reflecting lower stability. Influenced by agrarian culture and abundant land resources, buildings in Matou Village are primarily distributed along water bodies and scattered across fields, forming numerous dispersed clusters. Connections between these clusters are at greater risk.

Zhenshan Village has the highest degree centralization due to its hierarchical influences, showing a pronounced centripetal trend with less impact from modern planning and better preservation of architectural spaces. Gaodang Village and Matou Village display moderate degree centralization, indicating a weaker centripetal trend in these river valley-type villages centered around an agricultural culture. Awai Village, which has the lowest degree centralization, exhibits a weaker centripetal force. Awai Village was historically a semi-military settlement, but it has recently undergone rapid tourism development, leading to the construction of numerous new buildings and roads, with many old houses now left uninhabited.

Gaodang Village has the highest betweenness centralization, with there being relatively little variation in betweenness centralization among Awai Village, Zhenshan Village, and Matou Village. This indicates that Gaodang Village has preserved architecturally significant structures central to Bouyei culture, with relatively rational planning.

4.2. Architectural Spatial Network Gene Characteristics of Traditional Bouyei Villages in Central Guizhou

4.2.1. Identification Results of Architectural Spatial Network Genes in Bouyei Traditional Villages of Central Guizhou

Table 5 presents the architectural spatial network gene types identified in Bouyei traditional villages of Central Guizhou, revealing a total of nine distinct gene types.

Zhenshan Village displays the gene types Nd-1, Cp-1, Lc-1, Dc-1, and Bc-2, indicating that its architectural spatial network is characterized by “high density, low vulnerability, high stability, high centripetal force, and the absence of influential core buildings”.

Matou Village is associated with gene types Nd-2, Cp-1, Lc-2, Dc-2, and Bc-2. This pattern suggests that the architectural spatial network of Matou Village exhibits “low density, low vulnerability, low stability, low centripetal force, and a lack of influential core buildings”.

Gaodang Village shows gene types Nd-2, Cp-1, Lc-1, Dc-2, and Bc-1, reflecting that its architectural spatial network features “low density, low vulnerability, high stability, low centripetal force, and the presence of influential core buildings”.

Awai Village corresponds to gene types Nd-2, Cp-1, Lc-1, Dc-2, and Bc-2. This indicates that the architectural spatial network of Awai Village demonstrates “low density, low vulnerability, high stability, low centripetal force, and the absence of influential core buildings”.

4.2.2. Importance Characteristics of Architectural Spatial Network Genes in Bouyei Villages of Central Guizhou

Table 6 highlights that among the architectural spatial network genes of Bouyei traditional villages in central Guizhou, gene Cp-1 has the highest importance value of 0.1556, suggesting that “low vulnerability” is the most prominent feature of these villages’ architectural spatial networks. Genes Nd-2, Lc-1, Dc-2, and Bc-2, with slightly lower importance values of 0.1306, indicate that traits such as “low density, high stability, low centripetal force, and the absence of dominant core buildings” are also significant characteristics of these networks.

Although genes Nd-1, Lc-2, Dc-1, and Bc-1 have lower importance values of 0.0806, their presence in various Bouyei traditional villages reflects the impact of diverse geographical environments and cultural backgrounds. Gene Cp-2, with the lowest importance value of 0.0000, indicates that “high vulnerability” is rarely seen in the architectural spatial networks of Bouyei traditional villages.

4.2.3. Diversity Characteristics of Architectural Spatial Network Genes in Bouyei Villages of Central Guizhou

Table 7 shows that the Margalef, Simpson, and Pielou indices are consistent across Zhenshan, Matou, Gaodang, and Awai villages. This uniformity suggests strong and stable diversity in the architectural spatial network genes of the Bouyei villages in central Guizhou. The consistent values of these indices highlight the stability and continuity of genetic heritage, reflecting a high degree of uniformity in Bouyei architectural culture.

5. Discussion

5.1. Factors Influencing the Architectural Space Network Genes of Traditional Bouyei Villages in Central Guizhou

This study demonstrates that the architectural space network genes of the Bouyei ethnic villages in central Guizhou are influenced by multiple factors, specifically historical and cultural background, topographical conditions, and modern planning interventions.

5.1.1. Historical and Cultural Background

Military culture and feng shui principles: Zhenshan Village developed a dense building layout and a highly connected and centralized architectural space network due to historical military needs and traditional feng shui principles (e.g., the “mountain box” principle) [39].

Agricultural culture: the network gene characteristics of Matou and Gaodang villages, such as “low density and moderate centrality”, reflect their agricultural culture-based village attributes [40,41]. The interplay between farmland and buildings highlights the role of agricultural culture in shaping the spatial networks of these villages.

Bouyei spiritual beliefs: the Bouyei people’s emphasis on natural harmony and their Mo Belief Culture have profoundly influenced village spatial networks. The prominence of the Cp-1 gene (low vulnerability) illustrates the Bouyei’s focus on neighborly harmony and environmental conservation [42], which is indirectly reflected in the architectural space layout.

5.1.2. Topographical Conditions

Differences between mountainous and flat terrain: the mountainous terrain of Zhenshan Village, characterized by its defensibility, fostered a compact building layout. In contrast, the relatively flat terrains of Awai and Matou villages led to more dispersed building distributions and fewer roads.

Impact of waterbody distribution: Matou Village’s dispersed building layout along waterbodies demonstrates the constraints of topography on the stability of village spatial networks. The large spacing between buildings makes these dispersed clusters more susceptible to external disturbances, increasing the network’s instability and vulnerability.

5.1.3. Modern Planning Interventions

Positive and negative impacts of planning: reasonable planning in Gaodang Village has avoided excessive demolition [41], achieving a balanced relationship between tradition and development. This has resulted in a network with higher stability and intermediate centrality. Conversely, Awai Village has undergone large-scale tourism development in recent years, with the construction of hotels, flower cake factories, and other facilities [43]. While these changes have boosted economic income, they have weakened the characteristics of the traditional architectural space network, reduced centrality, and left many old buildings uninhabited.

Destructive effects of improper development: Matou Village, historically an important garrison settlement, has become more dispersed and unstable due to modern planning interventions [1]. This highlights that excessive reconstruction or neglect of traditional layouts during modern development can negatively impact village networks.

5.2. Strategies for Conservation and Sustainable Development

• 1.. Preserving the Architectural Space Network of Traditional Villages

The architectural space network’s connectivity and cultural characteristics should be preserved when protecting Bouyei traditional villages. The case of Zhenshan Village demonstrates that moderate conservation measures can maintain the network’s stability and traditional appearance, while excessive interventions may disrupt the original layout. The dispersed layout and low network stability of Matou Village suggest the need for differentiated strategies tailored to each village’s unique characteristics. For example, efforts should focus on enhancing connectivity between buildings while avoiding significant alterations to the original spatial layout.

• 2.. Balancing Rapid Development and Cultural Heritage

Rapid tourism development in Awai Village has brought new economic opportunities. However, the newly constructed roads and buildings, while improving convenience, have weakened the integrity of the traditional spatial network. In contrast, the balanced planning in Gaodang Village provides a valuable reference, where the preservation of core buildings has helped safeguard the village’s cultural identity.

To achieve sustainable development, planning should fully respect the traditional culture and geographical features of the Bouyei people. For instance, efforts should prioritize the preservation of the “low vulnerability” trait of the Cp-1 gene to maintain the stability of the Bouyei architectural space network. Simultaneously, cultural hub buildings should be adequately protected to prevent their disappearance due to tourism development or modern construction. Additionally, policymakers and planners should deepen their understanding of local culture and integrate elements of indigenous spiritual beliefs into development initiatives to foster cultural identity.

In summary, the architectural space network characteristics of traditional Bouyei villages in central Guizhou are intricately linked to their geographical environment, historical culture, and local spiritual beliefs. Conservation and development should be guided by the architectural space network characteristics and their underlying genes, ensuring scientific planning and moderate protection. This approach can achieve a balance between cultural preservation and economic development, contributing not only to the continuation of Bouyei culture but also providing valuable insights for the conservation and development of other traditional villages.

5.3. Limitations of the Study

This study focuses on traditional Buyi villages, attempting to apply the concept of architectural spatial network genes to the study of traditional village spaces and reveal their inherent patterns. However, the research has certain limitations, as outlined below:

1. This study selected only four Buyi villages as case studies, which may not comprehensively represent all Buyi or other ethnic traditional villages. This limitation may affect the generalizability and applicability of the research findings. In the future, we plan to expand the sample size, covering more ethnicities and regions for a broader comparative study.

2. The theoretical system of traditional village spatial genes is still in its exploratory phase, and the introduction and quantification methods of spatial genes are relatively simple. Therefore, future research will continue to deepen the development of spatial gene theory and further improve research methods.

3. This study focuses solely on the “architectural spatial network gene”, while the broader category of spatial network genes also includes “waterbody spatial network genes”, “green space spatial network genes”, and “three-life spatial network genes”, among others. In the future, we will expand the scope of the study to analyze different types of spatial network genes and conduct comparative analyses.

In conclusion, the analysis and conclusions of this study have certain limitations. Subsequent research will increase the sample size and types, deepen the research methods for spatial genes, and explore the long-term effects of time and social changes on the architectural spatial networks of traditional villages.

6. Conclusions

This study focuses on four traditional Bouyei villages in Central Guizhou, analyzing their architectural spatial network characteristics and spatial genes using social network analysis, spatial gene theory, and diversity analysis. The conclusions are as follows:

• Zhenshan Village has the best architectural spatial network condition, while that of the other three villages is relatively average;

• Four gene fragments, five gene units, and nine gene types were identified in the architectural spatial networks of the Bouyei villages;

• All villages express the low vulnerability Cp-1 gene, with Cp-1 having the highest importance value. Its typical traits include “low density, high stability, low vulnerability, weak centripetal force, and a lack of highly influential core buildings”;

• Diversity indices indicate that the architectural spatial network genes of the Bouyei villages have strong stability and continuity, reflecting a highly unified architectural culture.

The architectural space network genes of the sample villages are primarily influenced by military culture, feng shui principles, agricultural culture, Bouyei spiritual beliefs (Mo Belief Culture), topographical conditions, and modern planning interventions. When conserving traditional villages, efforts should focus on preserving their architectural space networks while seeking a balance between rapid development and cultural heritage preservation. This study further deepens the understanding of the cultural values and spatial layout characteristics of the Buyi ethnic group’s traditional villages, offering a Chinese case for the protection and sustainable development of rural settlements worldwide.

Author Contributions

Writing—original draft preparation, Y.Z. and writing—review and editing, Z.H. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Not applicable.

Data Availability Statement

Data are contained within the article.

Acknowledgments

The authors are thankful to reviewers and editors for their insightful comments and suggestions in an earlier edition of this article.

Conflicts of Interest

The authors declare no conflicts of interest.

Footnotes

Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Figures and Tables

Figure 1. Location map of the study area. (a) Location of Guizhou Province in China; (b) location of Guiyang and Anshun in Hunan Province; (c) location of Kaiyang and Huaxi County, Guiyang City: the location of the study sample villages in Guiyang City; and (d) location of Xixiu and Zhenning County, Anshun City: the location of the study sample villages in Anshun City.

Figure 2. The process of constructing the building spatial network.

Figure 3. Spatial connectivity analysis map of Awai, Gaodang, Zhenshan, and Matou villages (building: solid gray surface and road: hollow surface).

Figure 4. Diagram of binary matrix construction (Note: JZ1, JZ2, … JZ11 represent building identifiers.).

Figure 5. Hierarchical classification of architectural space network genes.

Table 1

Basic information about the sample villages.

Traditional Villages	Administrative Region	Geographical Position	Altitude (m)	Topography	Cultural Characteristics	Architectural Features	Conservation Status
Awai Village	Economic and Technological Development Zone, Anshun City	26°17′ N, 105°85′ E	1280	Karst plain	Military Settlement Culture and Vine Weaving Culture	The village is distributed along the highway in a belt-like pattern, with buildings constructed in stone slab house.	Included in the fourth batch of the “Chinese Traditional Village Directory”, it is the only village with Vine Weaving culture in the country, and it boasts well-preserved ancient military sites and various clan genealogies.
Gaodang Village	Zhenning County, Anshun City	26°07′ N, 105°69′ E	1186	Karst valley	Agricultural Culture, Tunpu Culture and Mo Belief Culture	The village is concentrated in the valley, with a clustered layout, and the buildings are constructed in stone slab house.	Included in the second batch of the “Chinese Traditional Village Directory”, this millennium-old Bouyei village has been awarded the title of “National Ecological Civilization Village” and is among the first batch of “Chinese Villages with Ethnic Minority Characteristics”.
Zhenshan Village	Huaxi District, Guiyang City	26.44° N, 106.61° E	1200	Karst hillside	Military Settlement Culture and Feng shui Culture	The village is clustered on the hillside, with a compact layout, and the buildings are constructed in stone slab house.	Included in the first batch of the “Chinese Traditional Village Directory”, recognized as an Ethnic Ecology Museum, and designated as a National Historical and Cultural Village in the seventh batch.
Matou Village	Kaiyang County, Guiyang City	26.55° N, 106.53° E	1180	Karst valley	Tusi chieftain Culture and Agricultural Culture	The village is distributed along the riverbank in a star-shaped pattern, with buildings constructed in a combination of wood and stone, featuring pitched roofs.	Included in the first batch of the “Chinese Traditional Village Directory”, Matou Village’s Bouyei ancient architecture group has been designated as a National Key Cultural Relic Protection Unit in the sixth batch by the State Council.

Table 2

Network Indicators and Specific Interpretation.

Network Characteristics	Metric	Definitions	Formula	Function
Completeness	Network Density	The ratio of actual connections to all possible connections in a network, ranging from 0 to 1.	$D={\displaystyle \frac{2L}{N\left(N-1\right)}}$, where L is the number of actual connections, and N is the total number of nodes.	It reflects the overall closeness of the network. A higher density indicates stronger relationships between nodes, helping to assess their connectivity and interaction.
Stability	Lambda Difference	Measures the impact on network connectivity when a specific node or edge is removed. It is calculated by comparing the connectivity before and after removal.	$\mathsf{\Delta }\mathsf{\lambda }={\mathsf{\lambda }}_{\mathrm{before}}-{\mathsf{\lambda }}_{\mathrm{after}}$, where λ represents network connectivity.	It measures the stability of the network and evaluates its resilience to disturbances. A high difference indicates greater dependence on certain nodes or edges, making the network less stable, while a lower value suggests a more stable layout of buildings and roads.
Vulnerability	Proportion Of Cutpoint	The proportion of cutpoints (nodes whose removal disconnects the network) to the total number of nodes, expressed as a percentage.	$C={\displaystyle \frac{N_{\mathrm{cat}}}{N}}\times 100\%$, where Ncut is the number of cutpoints, and N is the total number of nodes.	To assess the network’s dependence on key nodes, a higher proportion of cutpoints indicates greater vulnerability, while a lower proportion suggests a more robust network structure.
Centrality And Influence	Degree Centralization(CD)	The normalized value of the degree centrality difference between the node with the highest degree centrality and other nodes in the network.	$C_D={\displaystyle \frac{{\sum }_{i=1}^N\left(\max \left(d_i\right)-d_i\right)}{\left(N-1\right)\left(N-2\right)}}$, where di is the degree of the i-th node.	It assesses the network’s reliance on key nodes. Issues with buildings located at cutpoints can disrupt the architectural network. A higher cutpoint ratio indicates greater vulnerability, while a lower ratio suggests a more robust network structure.
	Betweenness Centralization(CB)	The normalized value of the difference in betweenness centrality between the node with the highest betweenness centrality and other nodes in the network.	$C_B={\displaystyle \frac{{\sum }_{i=1}^N\left(\max \left(b_i\right)-b_i\right)}{\left(\mathrm{N}-1\right)\left(\mathrm{N}-2\right)}}$, where bi is the betweenness centrality of the i-th node.	A high betweenness centrality indicates that certain nodes act as bridges in the network, playing a crucial role in connectivity efficiency.

Table 3

Spatial Network Gene Identification System for Bouyei Architecture in Central Guizhou.

Gene Fragment	Gene Unit	Genotype Name	Simplified Code	Character Expression	Attribute Property
Completeness	Network Density	AsnCNd-1	Nd-1	Density ≥ 0.191	High density.
		AsnCNd-2	Nd-2	Density < 0.191	Low density.
Stability	Lambda Difference	AsnSLc-1	Lc-1	Stability difference ≤ 9.78%	Good stability.
		AsnSLc-2	Lc-2	Stability difference > 9.78%	Poor stability.
Vulnerability	Proportion Of Cutpoint	AsnVCp-1	Cp-1	Cutpoint ratio ≤ 0.00%	The cutpoint ratio is small.
		AsnVCp-2	Cp-2	Cutpoint ratio > 0.00%	The cutpoint ratio is large.
Centrality And Influence	Degree Centralization	AsnCiDc-1	Dc-1	Degree Centralization ≥ 34.71%	Degree Centralization is large.
		AsnCiDc-2	Dc-2	Degree Centralization < 34.71%	Degree Centralization is small.
	Betweenness Centralization	AsnCiBc-1	Bc-1	Betweenness Centralization ≥ 14.53%	Betweenness Centralization is large.
		AsnCiBc-2	Bc-2	Betweenness Centralization < 14.53%	Betweenness Centralization is small.

Table 4

Architectural Spatial Network Characteristics of Traditional Bouyei Villages in Central Guizhou.

Traditional Villages	Network Density	Lambda Difference	Proportion of Cutpoint	Degree Centralization	Betweenness Centralization
Zhenshan Village	0.365	8.78%	0.00%	66.92%	13.17%
Matou Village	0.139	11.59%	0.00%	24.98%	11.72%
Gaodang Village	0.148	9.38%	0.00%	28.78%	19.31%
Awai Village	0.111	9.38%	0.00%	18.17%	13.91%

Table 5

Identification Results of Architectural Spatial Network Genes in Traditional Bouyei Villages of Central Guizhou.

Traditional Villages	Network Density	LambdaDifference	Cutpoint	Degree Centralization	Betweenness Centralization
Zhenshan Village	Nd-1	Lc-1	Cp-1	Dc-1	Bc-2
Matou Village	Nd-2	Lc-2	Cp-1	Dc-2	Bc-2
Gaodang Village	Nd-2	Lc-1	Cp-1	Dc-2	Bc-1
Awai Village	Nd-2	Lc-1	Cp-1	Dc-2	Bc-2

Table 6

Importance Indicators of Architectural Spatial Network Genes in Traditional Bouyei Villages of Central Guizhou.

Genotype	Nd-1	Nd-2	Cp-1	Cp-2	Lc-1	Lc-2	Dc-1	Dc-2	Bc-1	Bc-2
Important Value	0.0806	0.1306	0.1556	0.0000	0.1306	0.0806	0.0806	0.1306	0.0806	0.1306

Table 7

Diversity Indicators of Architectural Spatial Network Genes in Traditional Bouyei Villages of Central Guizhou.

Traditional Villages	Margalef Index (R)	Simpson Index (D)	Pielou Index (J)
Zhenshan Village	2.4853	0.8000	0.4343
Matou Village	2.4853	0.8000	0.4343
Gaodang Village	2.4853	0.8000	0.4343
Awai Village	2.4853	0.8000	0.4343

References

1. Zhang, G. Research on the Protection Strategy of Tusi Architectural Heritage in Guiyang. Master’s Thesis; Guizhou University: Guiyang, China, 2021.

2. Fang, Y. Genetic Characteristics and Maintenance Mechanism of Spatial Social Network and Building Network in Tunpu Settlement, Guizhou Province. Master’s Thesis; Guizhou University: Guiyang, China, 2023.

3. Wang, H.-F.; Chiou, S.-C. Study on the sustainable development of human settlement space environment in traditional villages. Sustainability; 2019; 11, 4186. [DOI: https://dx.doi.org/10.3390/su11154186]

4. Bruijn, E.; Whiteman, G. That which doesn’t break us: Identity work by local indigenous ‘stakeholders’. J. Bus. Ethics; 2010; 96, pp. 479-495. [DOI: https://dx.doi.org/10.1007/s10551-010-0479-0]

5. Maher, R.; Loncopán, S. Repoliticizing spirituality: A collaborative autoethnography on Indigenous identity dynamics during an environmental conflict in a Mapuche community in Chile. Hum. Relations; 2024; 77, pp. 906-936. [DOI: https://dx.doi.org/10.1177/00187267241248582]

6. Jiang, Y.; Li, N.; Wang, Z. Parametric Reconstruction of Traditional Village Morphology Based on the Space Gene Perspective—The Case Study of Xiaoxi Village in Western Hunan, China. Sustainability; 2023; 15, 2088. [DOI: https://dx.doi.org/10.3390/su15032088]

7. Dragan, A.; Creţan, R.; Jucu, I.S.; Oancea, O.A. Rural Landscapes as Cultural Heritage and Identity along a Romanian River. Heritage; 2024; 7, pp. 4354-4373. [DOI: https://dx.doi.org/10.3390/heritage7080205]

8. Cordero Ampuero, A.; Gil Manso, M.; Muñoz, M. A Townscape in Evolution: Caño Roto Modern Heritage, 1957–2023. Heritage; 2024; 7, pp. 2348-2369. [DOI: https://dx.doi.org/10.3390/heritage7050111]

9. Xing, Y.; Leng, J. Evaluation of Public Space in Traditional Villages Based on Eye Tracking Technology. J. Asian Arch. Build. Eng.; 2024; 23, pp. 125-139. [DOI: https://dx.doi.org/10.1080/13467581.2023.2229410]

10. Aydin, S.; Çelebioğlu, B.; Aytug, A. Morphological Analysis of Historical Urban Landscape Through Heritage Transect: A Computational Model. J. Digit. Landsc. Archit.; 2024; pp. 354-364. [DOI: https://dx.doi.org/10.14627/537752032]

11. Terada, S.; Boda, S.; Nishimura, S.-Y. A study on the spatial configuration and collective system of street space in Tsutsuishi fishing village in relation to the service wet spaces. J. Asian Arch. Build. Eng.; 2024; 23, pp. 111-124. [DOI: https://dx.doi.org/10.1080/13467581.2023.2229403]

12. Hillier, B.; Leaman, A.; Stansall, P.; Bedford, M. Space syntax. Environ. Plan. B Plan. Des.; 1976; 3, pp. 147-185. [DOI: https://dx.doi.org/10.1068/b030147]

13. Yamu, C.; van Nes, A.; Garau, C. Bill Hillier’s legacy: Space syntax—A synopsis of basic concepts, measures, and empirical application. Sustainability; 2021; 13, 3394. [DOI: https://dx.doi.org/10.3390/su13063394]

14. Günaydın, A.S.; Selçuk, E.B. How urban growth influences the spatial characteristics of cities: Empirical research in Malatya/Türkiye based on space syntax. GeoJournal; 2024; 89, 81. [DOI: https://dx.doi.org/10.1007/s10708-024-11080-z]

15. Askarizad, R.; Daudén, P.J.L.; Garau, C. The application of space syntax to enhance sociability in public urban spaces: A systematic review. ISPRS Int. J. Geo-Inf.; 2024; 13, 227. [DOI: https://dx.doi.org/10.3390/ijgi13070227]

16. Wang, L.; Han, X.; He, J.; Jung, T. Measuring residents’ perceptions of city streets to inform better street planning through deep learning and space syntax. ISPRS J. Photogramm. Remote Sens.; 2022; 190, pp. 215-230. [DOI: https://dx.doi.org/10.1016/j.isprsjprs.2022.06.011]

17. Xie, M.; Xiang, H. Research on the Spatial Context Inheritance Strategy of Traditional Miao-Dong Settlements in Southwest Hunan Province Based on Social Network Analysis. J. Hunan Univ.; 2023; 05, pp. 154-160.

18. Xiang, H.; Xie, M.; Fang, Y. Study on the architecture space-social network characteristics based on social network analysis: A case study of Anshun Tunpu settlement. Ain Shams Eng. J.; 2024; 15, 102333. [DOI: https://dx.doi.org/10.1016/j.asej.2023.102333]

19. Sha, S.; Cheng, Q.; Lu, M. Building a “reservoir of social resilience”: A strategy for social infrastructure regeneration in shrinking cities based on social network analysis. Habitat Int.; 2024; 143, 102991. [DOI: https://dx.doi.org/10.1016/j.habitatint.2023.102991]

20. Song, J.; Chen, J.; Yang, X.; Zhu, Y. Research on Adaptive Reuse Strategy of Industrial Heritage Based on the Method of Social Network. Land; 2024; 13, 383. [DOI: https://dx.doi.org/10.3390/land13030383]

21. Dawkins, R. The Selfish Gene; Oxford University Press: Oxford, UK, 2016.

22. Feldman, M.W.; Laland, K.N. Gene-culture coevolutionary theory. Trends Ecol. Evol.; 1996; 11, pp. 453-457. [DOI: https://dx.doi.org/10.1016/0169-5347(96)10052-5]

23. Lin, C. Chinese System Thinking: A Cultural Gene Perspective; China Social Sciences Press: Beijing, China, 1990.

24. Jiang, W.; Zhang, H. Traditional Chinese culture and the construction of ecological civilization: From cultural genes to practical behaviors—Case studies in confucianism, buddhism and taoism. Chin. J. Urban Environ. Stud.; 2020; 8, 2050011. [DOI: https://dx.doi.org/10.1142/S2345748120500116]

25. Causadias, J.M.; Korous, K.M. How are genes related to culture? An introduction to the field of cultural genomics. The Handbook of Culture and Biology; John Wiley & Sons: Hoboken, NJ, USA, 2017; pp. 151-177.

26. Zui, H.; Chun, L.; Yun, D.; Li, Y. Traditional settlement landscape genes and their research progress. Prog. Geogr.; 2012; 31, pp. 1620-1627.

27. Yang, G.; Hu, L.; Wu, F.; Hu, J. Cultural landscape gene production process and mechanism of Dong traditional village: A case study of Huangdu village. J. Nat. Resour.; 2023; 38, pp. 1164-1177. [DOI: https://dx.doi.org/10.31497/zrzyxb.20230504]

28. Wang, W.; Shi, Q.; Wang, G. Analysis of Performance and Genetic Characteristics of Cultural Landscapes in Traditional Villages along the Jinzhong Section of the Wanli Tea Road from a Landscape Gene Information Chain Perspective: A Case Study of Xiamen Village. Sustainability; 2024; 16, 8131. [DOI: https://dx.doi.org/10.3390/su16188131]

29. Wang, L.; Sun, C.; Wang, M.; Xiao, X. Construction and Characterization of Traditional Village Landscape Cultural Genome Atlases: A Case Study in Xupu County, Hunan, China. Sustainability; 2024; 16, 9524. [DOI: https://dx.doi.org/10.3390/su16219524]

30. Liu, X.; Li, Y.; Wu, Y.; Li, C. the spatial pedigree in traditional villages under the perspective of urban regeneration—Taking 728 villages in Jiangnan region, China as CASES. Land; 2022; 11, 1561. [DOI: https://dx.doi.org/10.3390/land11091561]

31. Huang, Z.; Wang, Z.; Gong, L.; Xiang, H.; Zhao, M.; Liu, Y.; Zhang, R.; Xiang, X.; Fu, D. The connotation and prospect of the concept of spatial gene. Huazhong Archit.; 2020; 10, pp. 19-21.

32. Xiang, H.; Qin, Y.; Xie, M.; Zhou, B. Study on the “space gene” diversity of traditional dong villages in the southwest Hunan province of China. Sustainability; 2022; 14, 14306. [DOI: https://dx.doi.org/10.3390/su142114306]

33. Zhao, H.; Huang, Z.; Deng, C.; Ren, Y. The Decorative Auspicious Elements of Traditional Bai Architecture in Shaxi Ancient Town, China. Sustainability; 2023; 15, 1918. [DOI: https://dx.doi.org/10.3390/su15031918]

34. Nie, Z.; Li, N.; Pan, W.; Yang, Y.; Chen, W.; Hong, C. Quantitative research on the form of traditional villages based on the space gene—A case study of Shibadong village in Western Hunan, China. Sustainability; 2022; 14, 8965. [DOI: https://dx.doi.org/10.3390/su14148965]

35. Zhang, X.; Zhou, L.; Zhou, T. Quantitative analysis of spatial gene in traditional villages: A case study of Korean traditional villages in Northeast China. J. Asian Arch. Build. Eng.; 2024; 2380832. [DOI: https://dx.doi.org/10.1080/13467581.2024.2380832]

36. Lin, J.; He, C.; Shi, S.; Song, J. Heterogeneous isomorphism—Spatial Gene Transcreation Design for Traditional Villages in Hunan. SHS Web Conf.; 2023; 167, 02016. [DOI: https://dx.doi.org/10.1051/shsconf/202316702016]

37. Lu, Q.; Zhao, C.; Huang, H. Comparative study on the temporal and spatial evolution of the ecosystem service value of different karst landform types: A case study in Guizhou province, China. Appl. Sci.; 2022; 12, 12801. [DOI: https://dx.doi.org/10.3390/app122412801]

38. Xiang, X.X.; Huang, Z.S.; Wang, Z.T. The coupling relationship between the spatial morphological structure of karst mountainous cities and the species diversity of plant communities: A case study of Anshun City. Acta Ecol. Sin.; 2021; 2, pp. 575-587.

39. Zhou, Z.; Zheng, X. A study on the spatial morphology of traditional villages in central Guizhou from the perspective of geosexuality. Archit. Cult.; 2023; 8, pp. 70-72.

40. Wang, X.; Qian, L.; Sun, Y.; Qian, Y. A Study on the Spatial Collective Memory of Traditional Settlements in Guizhou: A Case Study of Baojiatun and Gaodang Villages. Archicreation; 2020; 1, pp. 18-25.

41. Du, J.; Wang, J. The construction of Buyi settlements from the perspective of survival and adaptation: A case study of Ninggaodang Village, Anshun Town, Guizhou Province. Archit. Cult.; 2017; 11, pp. 93-95.

42. Yan, Q. On the culture of Zhenning Buyi from the perspective of environmental anthropology. J. Zunyi Norm. Univ.; 2021; 3, pp. 43-46.

43. Yang, H.; Yu, S.; Zhu, L.; Jiang, B. Practical analysis of grassroots party building leading the collective economic development of the village in Awai Village. Rural. Econ. Sci. Technol.; 2023; 22, pp. 93-96.