Evolution of ecological spatial network structure in Inner Mongolia sand-prevention belt of northern China
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摘要:
目的 生态空间网络具有保障生态过程、维护生态安全、提升生态系统服务的作用，当前有关研究多针对潜在生态空间网络展开，对现状生态空间网络的研究较少。基于长时间序列土地利用数据，提取现状生态空间网络，分析其结构的演变特征，为优化网络结构、构建区域生态安全格局、提升区域生态服务功能提供重要依据。 方法 以内蒙古防沙带为研究区，首先以空间形态学分析方法分析研究区1990、1995、2000、2005、2010、2015和2020年多种景观组分的空间分布特征，进而以核心区为节点，以连接桥为边构建了研究区实际生态空间网络，利用复杂网络分析中的度、度分布、直径、平均路径长度、聚类系数等多种拓扑结构指标研究了实际生态空间网络的结构演变特征。 结果 研究区景观组分以核心区和连接桥为主，30年间分别占研究区面积的32.13%和28.72%，其次为边缘、孤岛和环，其中核心区在不断减少，孤岛逐渐增多。30年间研究区生态空间网络平均度在20.01至39.98范围内波动，度分布幂律特征明显，幂函数指数呈上升趋势。网络直径从1990年的24下降到2020年的17，平均路径长度从1990年的4.20上升到2020年的5.14。30年间连通子图平均数量为61个，且呈现增加趋势，连通子图规模平均为33.35，呈下降趋势。网络具有极强的度度相关性，度与聚类系数之间没有明显的数量关系。 结论 30年间各指标的变化趋势表明，研究区生态空间网络为无标度非层次同配小世界网络。网络不均匀性较强但有降低趋势，网络局部连接紧密，社团结构明显，但跨社区的长距离连接正在减少，网络正逐渐分裂为互相孤立的多个子图，网络整体连通性有所下降。研究区景观格局的优化可通过建设跨区域的生态廊道、增加各个社团间的连接等措施进行。 Abstract:Objective Ecological spatial networks play an important role in safeguarding ecological processes, maintaining ecological security, and enhancing ecosystem services. Currently, most of the research on ecological spatial networks focuses on potential networks, with relatively little attention paid to the study of existing ecological spatial networks. Based on long-term land use data, the extraction of existing ecological spatial networks and analysis of their structural evolution characteristics provides an important basis for optimizing network structure, constructing regional ecological security patterns, and enhancing regional ecosystem service functions. Method Taking the Inner Mongolia sand-prevention belt as the research area, this study first used spatial morphological analysis method to analyze the spatial distribution characteristics of multiple landscape components in 1990, 1995, 2000, 2005, 2010, 2015, and 2020. Then, using the core area as the node and bridges as edges, the existing ecological spatial network of the research area was constructed. The structural evolution characteristics of the existing ecological spatial network were studied using various topological structure indicators, such as degree, degree distribution, diameter, average path length, and clustering coefficient in complex network analysis. Result The landscape components in the research area were mainly core areas and connecting bridges, which accounted for 32.13% and 28.72% of the research area, respectively, followed by edges, islands and rings. The core area had been decreasing continuously, while the number of islands had been gradually increasing. The average degree of the ecological spatial network in the research area fluctuated between 20.01 and 39.98 over the past 30 years, and the power-law characteristics of degree distribution were obvious, with the power-law index showing an upward trend. The network diameter decreased from 24 in 1990 to 17 in 2020, and the average path length increased from 4.2 in 1990 to 5.14 in 2020. The average number of connected subgraphs was 61 over the past 30 years, showing an increasing trend, while the average size of connected subgraphs was 33.35, showing a decreasing trend. The network had a strong degree-degree correlation, and there was no obvious quantitative relationship between degree and clustering coefficient. Conclusion The trend of various indicators over the past 30 years indicates that the ecological spatial network in the research area is a scale-free, non-hierarchical, assortative small-world network. The network has strong heterogeneity but shows a decreasing trend, with local connections being dense and community structure being obvious. However, long-distance connections across communities are decreasing, and the network is gradually splitting into multiple isolated subgraphs, resulting in a decrease in overall connectivity. Optimization of the landscape pattern in the research area can be achieved through measures such as building cross-regional ecological corridors and increasing connections between different communities. -
图 3 各年份生态空间网络拓扑结构
Figure 3. Topological structure of ecological space network in each year
图 4 各年份生态空间网络度分布
Figure 4. Distribution of ecological spatial network degree in different years
图 7 各年份聚类系数分布及平均聚类系数
Figure 7. Distribution of clustering coefficients and average clustering coefficients in each year
图 8 各年份子图数量与平均子图规模
Figure 8. Number of sub graphs and average sub graph size in each year
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[1] 卢杰, 王戈, 马骏, 等. 基于复杂网络理论的西藏巴宜区森林景观空间结构研究[J]. 农业机械学报, 2021, 52(4): 152−158. doi: 10.6041/j.issn.1000-1298.2021.04.016Lu J, Wang G, Ma J, et al. Forest ecological network construction and structure evaluation based on complex network theory in Bayi District of Tibet[J]. Transactions of the Chinese Society of Agricultural Machinery, 2021, 52(4): 152−158. doi: 10.6041/j.issn.1000-1298.2021.04.016 [2] 牛腾, 岳德鹏, 张启斌, 等. 潜在生态网络空间结构与特性研究[J]. 农业机械学报, 2019, 50(8): 166−175. doi: 10.6041/j.issn.1000-1298.2019.08.019Niu T, Yue D P, Zhang Q B, et al. Spatial structure and characteristics of potential ecological networks[J]. Transactions of the Chinese Society of Agricultural Machinery, 2019, 50(8): 166−175. doi: 10.6041/j.issn.1000-1298.2019.08.019 [3] 于强. 基于复杂网络理论的荒漠绿洲区生态网络研究[D]. 北京: 北京林业大学, 2018.Yu Q. Research on ecological network of desert oasis based on complex network theory[D]. Beijing: Beijing Forestry University, 2018. [4] Weber T, Sloan A, Wolf J. Maryland’s green infrastructure assessment: development of a comprehensive approach to land conservation[J]. Landscape and Urban Planning, 2006, 77(1−2): 94−110. doi: 10.1016/j.landurbplan.2005.02.002 [5] 于强, 张启斌, 牛腾, 等. 绿色生态空间网络研究进展[J]. 农业机械学报, 2021, 52(12): 1−15. doi: 10.6041/j.issn.1000-1298.2021.12.001Yu Q, Zhang Q B, Niu T, et al. Research progress and prospect of green ecological space network[J]. Transactions of the Chinese Society of Agricultural Machinery, 2021, 52(12): 1−15. doi: 10.6041/j.issn.1000-1298.2021.12.001 [6] Yu Q , Yue D P, Wang Y H, et al. Optimization of ecological node layout and stability analysis of ecological network in desert oasis: a typical case study of ecological fragile zone located at Deng Kou County (Inner Mongolia)[J]. Ecological Indicators, 2018: 84: 304−318. doi: 10.1016/j.ecolind.2017.09.002 [7] Kong F H, Yin H W, Nobukazu N, et al. Urban green space network development for biodiversity conservation: Identification based on graph theory and gravity modeling[J]. Landscape and Urban Planning, 2009, 95(1): 16−27. [8] Yin Y J, Liu S L, Sun Y X, et al. Identifying multispecies dispersal corridor priorities based on circuit theory: a case study in Xishuangbanna, Southwest China[J]. Journal of Geographical Sciences, 2019, 29(7): 1228−1245. doi: 10.1007/s11442-019-1655-5 [9] Peng J , Yang Y , Liu Y X, et al. Linking ecosystem services and circuit theory to identify ecological security patterns[J]. Science of the Total Environment, 2018: 644: 781−790. doi: 10.1016/j.scitotenv.2018.06.292 [10] Fang M Z, Si G X, Yu Q, et al. Study on the relationship between topological characteristics of vegetation ecospatial network and carbon sequestration capacity in the Yellow River Basin, China[J/OL]. Remote Sens, 2021, 13(23): 4926[2022−04−10]. https://doi.org/10.3390/rs13234926. [11] 王晓峰, 勒斯木初, 张明明. “两屏三带”生态系统格局变化及其影响因素[J]. 生态学杂志, 2019, 38(7): 2138−2148. doi: 10.13292/j.1000-4890.201907.024Wang X F, Lesimuchu, Zhang M M. Ecosystem pattern change and its influencing factors of “two barriers and three belts”[J]. Chinese Journal of Ecology, 2019, 38(7): 2138−2148. doi: 10.13292/j.1000-4890.201907.024 [12] 刘利民, 王婷婷, 李秀芬, 等. 近15年内蒙古防沙带防风固沙功能时空变化特征[J]. 生态学杂志, 2021, 40(11): 3436−3447. doi: 10.13292/j.1000-4890.202111.007Liu L M, Wang T T, Li X F, et al. Ecosystem pattern change and its influencing factors of “two barriers and three belts”[J]. Chinese Journal of Ecology, 2021, 40(11): 3436−3447. doi: 10.13292/j.1000-4890.202111.007 [13] 刘江, 谢遵博, 王千慧, 等. 北方防沙带东部区生态安全格局构建及优化[J]. 生态学杂志, 2021, 40(11): 3412−3423. doi: 10.13292/j.1000-4890.202111.018Liu J, Xie Z B, Wang Q H, et al. The construction and optimization of ecological security pattern in the eastern part of the sand prevention belt in Northern China[J]. Chinese Journal of Ecology, 2021, 40(11): 3412−3423. doi: 10.13292/j.1000-4890.202111.018 [14] 孔繁花, 尹海伟. 济南城市绿地生态网络构建[J]. 生态学报, 2008, 28(4): 1711−1719. doi: 10.3321/j.issn:1000-0933.2008.04.042Kong F H, Yin H W. Developing green space ecological networks in Jinan City[J]. Acta Ecologica Sinica, 2008, 28(4): 1711−1719. doi: 10.3321/j.issn:1000-0933.2008.04.042 [15] Wang Y J, Qu Z Y, Zhong Q C, et al. Delimitation of ecological corridors in a highly urbanizing region based on circuit theory and MSPA[J/OL]. Ecological Indicators, 2022, 142: 109258[2022−08−10]. https://doi.org/10.1016/j.ecolind.2022.109258. [16] 张燕婷. 北方防沙带土地利用格局演变特征及防风固沙功能变化评估研究[D]. 南昌: 江西财经大学, 2014.Zhang Y T. The research on land use pattern evolution characteristics of northern sand belt, along with windbreak and sand fixation function change assessment[D]. Nanchang: Jiangxi University of Finance and Economics, 2014. [17] 王晓峰, 尹礼唱, 张园. 关于生态屏障若干问题的探讨[J]. 生态环境学报, 2016, 25(12): 2035−2040. doi: 10.16258/j.cnki.1674-5906.2016.12.020Wang X F, Yin L C, Zhang Y. Discussion on some issues of ecological barrier[J]. Ecology and Environmental Sciences, 2016, 25(12): 2035−2040. doi: 10.16258/j.cnki.1674-5906.2016.12.020 [18] Vogt P, Riitters K H, Estreguil C, et al. Mapping spatial patterns with morphological image processing[J]. Landscape Ecology, 2007, 22(2): 171−177. doi: 10.1007/s10980-006-9013-2 [19] 邱瑶, 常青, 王静. 基于MSPA的城市绿色基础设施网络规划——以深圳市为例[J]. 中国园林, 2013, 29(5): 104−108.Qiu Y, Chang Q, Wang J. A MSPA-based planning of urban green infrastructure network:a case of Shenzhen[J]. Chinese Landscape Architecture, 2013, 29(5): 104−108. [20] Soille P, Vogt P. Morphological segmentation of binary patterns[J]. Pattern Recognition Letters, 2009, 30(4): 456−459. doi: 10.1016/j.patrec.2008.10.015 [21] Lada A A. Bernardo H. Power-law distribution of the World Wide Web[J/OL]. Science, 2000, 287: 2115[2009−03−01]. https://doi.org/10.1016/j.patrec.2008.10.015. [22] Chen B, Zhu W, Liu Y. Algorithm for complex network diameter based on distance matrix[J]. Journal of Systems Engineering and Electronics, 2018, 29(2): 336−342. [23] Réka A, Albert-Làszlò B. Statistical mechanics of complex networks[J]. Reviews of Modern Physics, 2002, 74(1): 47−97. doi: 10.1103/RevModPhys.74.47 [24] Wang X C, Wang R R, Yu Q, et al. Study on the structural properties of an ecospatial network in Inner Mongolia and its relationship with NPP[J/OL]. Applied Sciences, 2022, 12(10): 4872. [2022−04−11]. https://doi.org/10.3390/app12104872. [25] 杨景峰, 朱大鹏, 赵瑞琳. 城轨网络站点重要度评估与级联失效抗毁性分析[J]. 中国安全科学学报, 2022, 32(8): 161−167. doi: 10.16265/j.cnki.issn1003-3033.2022.08.1148Yang J F, Zhu D P, Zhao R L. Evaluation of station importance and cascading failure resistance analysis of urban rail transit network[J]. China Safety Science Journal, 2022, 32(8): 161−167. doi: 10.16265/j.cnki.issn1003-3033.2022.08.1148 [26] Arruda G F D, Cozzo E, Moreno Y, et al. On degree-degree correlations in multilayer networks[J]. Physica D: Nonlinear Phenomena, 2016, 323−324: 5−11. [27] Josep L, Garcia D, David J, et al. Degree correlations in growing networks with deletion of nodes[J]. Physica D: Nonlinear Phenomena, 2008, 237(5): 640−651. doi: 10.1016/j.physd.2007.10.012 [28] Tatsuya F, Norrikazu T. Graphs that locally maximize clustering coefficient in the space of graphs with a fixed degree sequence[J]. Discrete Applied Mathematics, 2017, 217: 525−535. doi: 10.1016/j.dam.2016.10.002 [29] 张启斌. 乌兰布和沙漠东北缘生态网络构建与优化研究[D]. 北京: 北京林业大学, 2019.Zhang Q B. Study on the construction and optimization of ecological network in the northeastern margin of Ulanbuhe Desert[D]. Beijing: Beijing Forestry University, 2019. [30] Fruchterman T M J, Reingold E M. Graph drawing by force-directed placement[J]. Software- Practice and Experience, 1991, 21(11): 1129–1164 doi: 10.1002/spe.4380211102 [31] 裴燕如, 孙炎浩, 于强, 等. 黄河流域典型矿区生态空间网络优化——以鄂榆地区为例[J]. 煤炭学报, 2021, 46(5): 1541−1554. doi: 10.13225/j.cnki.jccs.ST21.8218Pei Y R, Sun Y H, Yu Q, et al. Optimization of ecological spatial network in typical mining areas of the Yellow River Basin: take Ordos and Yulin areas of the Yellow River Basin as examples[J]. Journal of China Coal Society, 2021, 46(5): 1541−1554. doi: 10.13225/j.cnki.jccs.ST21.8218 -
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