基于电路理论的浙江省生态保护修复关键区域识别

doi:10.16258/j.cnki.1674-5906.2024.09.015

生态环境学报 ›› 2024, Vol. 33 ›› Issue (9): 1482-1494.DOI: 10.16258/j.cnki.1674-5906.2024.09.015

• 研究论文【环境科学】 • 上一篇

基于电路理论的浙江省生态保护修复关键区域识别

张雯¹^,²(), 郑天¹, 刘永超¹, 钟捷¹, 苏杰³, 李加林¹^,²^,^*()

1.宁波大学土木工程与地理环境学院，浙江宁波 315211
2.浙江省陆海国土空间利用与治理协同创新中心，浙江宁波 315211
3.南京大学建筑与城市规划学院，江苏南京 210093

收稿日期:2024-04-18 出版日期:2024-09-18 发布日期:2024-10-18
通讯作者: ^*李加林。E-mail: lijialin@nbu.edu.cn
作者简介:张雯（1989年生），女，工程师，硕士研究生，主要从事自然地理研究。E-mail: 2311110033@nbu.edu.cn
基金资助:
国家自然科学基金项目(42276234);国家自然科学基金项目(41976209);宁波市科技局重大项目(2022Z181);宁波市社科基金项目(N0.G2023-2-59)

Identification of Key Areas for Ecological Protection and Restoration in Zhejiang Province Based on Circuit Theory

ZHANG Wen¹^,²(), ZHENG Tian¹, LIU Yongchao¹, ZHONG Jie¹, SU Jie³, LI Jialin¹^,²^,^*()

1. School of Civil & Environmental Engineering and Geography Science, Ningbo University, Ningbo 315211, P. R. China
2. Zhejiang Collaborative Innovation Center for Land and Marine Spatial Utilization and Governance Research, Ningbo 315211, P. R. China
3. School of Architecture and Urban Planning, Nanjing University, Nanjing 210093, P. R. China

Received:2024-04-18 Online:2024-09-18 Published:2024-10-18

摘要/Abstract

摘要：

科学识别生态保护修复关键区域，因地制宜推进生态管治，可为区域生态安全提供保障。以浙江省为研究区，运用InVEST模型、水量平衡方程、修正通用土壤流失方程、层次分析等方法，以生态系统服务重要性、生态敏感性为评价指标提取生态源地；考虑未来土地格局空间变化的可能性，设置多因素驱动因子，利用PLUS模型的LEAS模块计算每种土地利用类型未来增长的潜在变化概率，并结合多项阻力因子构建综合生态阻力面；最终借助可以有效预测生物种群迁移和扩散过程的电路理论识别生态保护修复关键区域。结果表明，1）浙江省生态源地共65个，面积3.49×10⁴km²，占研究区总面积的33.1%，其中最大源地面积为1.84×10⁴ km²，最小源地面积为20.1 km²。源地类型以林地为主，主要分布于浙西南和浙西北地区。2）生态阻力面高值区主要分布于浙东北平原、浙中盆地、浙东南沿海建成区以及周围耕地，土壤侵蚀度是各类用地发展的主要驱动因子，研究区整体用地发展受制于自然条件。3）提取147条生态廊道，总长度1906 km，平均长度13.0 km，累积成本加权距离4869 km，平均加权距离33.1 km，其中25条高阻廊道和59条低阻廊道是需重点修复、保护的关键廊道，廊道空间异质性特征显著，浙东北地区生态连通性明显较差。4）识别441处生态夹点和90处生态障碍点为需进行生态保护修复的关键节点，面积分别为246、206 km²，其中杭州、绍兴、金华3市夹点占夹点总面积的64.5%，杭州、绍兴、金华、湖州4市障碍点占障碍点总面积的82.4%。综合研究区地形特征和用地现状，提出分区保护修复建议，以期为浙江省生态管治工作提供参考。

关键词: 生态保护修复, 电路理论, InVEST模型, PLUS模型, 浙江省

Abstract:

Scientifically identifying key areas for ecological protection and restoration and promoting ecological management according to local conditions can ensure regional ecological security. This study focused on Zhejiang Province, where the importance of ecosystem services and ecological sensitivity were used as evaluation indicators to extract ecological source areas using the InVEST model, the water balance equation, the modified universal soil loss equation, and hierarchical analysis. Considering the potential spatial changes in land patterns, multi-factor driving factors were incorporated. The LEAS module of the PLUS model was employed to calculate the potential future growth probabilities of different land use types, and a comprehensive ecological resistance surface was constructed by integrating multiple resistance factors. Circuit theory was then applied to predict the migration and diffusion processes of biological populations effectively, ultimately identifying key areas for ecological conservation and restoration. The results were as follows: 1) 65 ecological source areas were identified in Zhejiang Province, covering 3.49×10⁴ km², accounting for 33.1% of the total study area, among which the largest source area was 1.84×10⁴ km², and the smallest was 20.1 km². The source areas were mainly woodlands, which were distributed in the southwest and northwest Zhejiang province. 2) High ecological resistance surface values were mainly found in the northeast Zhejiang Plain, central Zhejiang Basin, coastal built-up areas of southeast Zhejiang, and the surrounding cultivated land. Soil erosion is the main driving factor for land-use development, and the overall land-use development in the study area is subject to natural conditions. 3) 147 ecological corridors were extracted, with a total length of 1906 km, an average length of 13.0 km, a cumulative cost-weighted distance of 4869 km, and an average weighted distance of 33.1 km. Among them, 25 high-resistance corridors and 59 low-resistance corridors were key corridors requiring key restoration and protection. The spatial heterogeneity of the corridors was significant, and the ecological connectivity in northeast Zhejiang was poor. 4) A total of 441 ecological pinch points and 90 ecological barrier points were identified as key nodes in need of ecological protection and restoration, with areas of 246 km² and 206 km², respectively. Pinch points in Hangzhou, Shaoxing, and Jinhua accounted for 64.5% of the total pinch points, whereas barrier points in Hangzhou, Shaoxing, Jinhua, and Huzhou accounted for 82.4% of the total area of the obstacle points. The topographic characteristics and land use status of the area were comprehensively studied, and recommendations for regional protection and restoration were proposed to guide ecological governance in Zhejiang Province.

Key words: ecological protection and restoration, circuit theory, InVEST model, PLUS model, Zhejiang Province

中图分类号:

X171.1
X37

张雯, 郑天, 刘永超, 钟捷, 苏杰, 李加林. 基于电路理论的浙江省生态保护修复关键区域识别[J]. 生态环境学报, 2024, 33(9): 1482-1494.

ZHANG Wen, ZHENG Tian, LIU Yongchao, ZHONG Jie, SU Jie, LI Jialin. Identification of Key Areas for Ecological Protection and Restoration in Zhejiang Province Based on Circuit Theory[J]. Ecology and Environment, 2024, 33(9): 1482-1494.

图/表 14

参考文献 41

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评价因子	敏感性等级					权重
评价因子	低	较低	一般	较高	高	权重
高程/m	<138	138−348	348−592	592−902	>902	0.111
坡度/(°)	<7	7−16	16−25	25−34	>34	0.222
土地利用类型	建设用地	未利用地	耕地、草地	水域	林地	0.167
植被覆盖度	<0.280	0.280−0.530	0.530−0.710	0.710−0.850	>0.850	0.167
土壤侵蚀强度	微侵蚀	轻度侵蚀	中度侵蚀	强烈侵蚀	极强烈侵蚀	0.333

评价因子	敏感性等级					权重
评价因子	低	较低	一般	较高	高	权重
高程/m	<138	138−348	348−592	592−902	>902	0.111
坡度/(°)	<7	7−16	16−25	25−34	>34	0.222
土地利用类型	建设用地	未利用地	耕地、草地	水域	林地	0.167
植被覆盖度	<0.280	0.280−0.530	0.530−0.710	0.710−0.850	>0.850	0.167
土壤侵蚀强度	微侵蚀	轻度侵蚀	中度侵蚀	强烈侵蚀	极强烈侵蚀	0.333

阻力因子	相对阻力值					权重
阻力因子	1	3	5	7	9	权重
土地利用修正阻力值	由公式 (5) 计算并按自然断点法分类得出					0.445
高程/m	<138	138−348	348−592	592−902	>902	0.052
坡度/(°)	<7	7−16	16−25	25−34	>34	0.105
植被覆盖度	>0.850	0.710−0.850	0.530−0.710	0.280−0.530	<0.280	0.148
距铁路、高速距离/km	>10	5−10	2−5	1−2	<1	0.125
距国道、省道距离/km	>5	2−5	1−2	0.5−1	<0.5	0.125

阻力因子	相对阻力值					权重
阻力因子	1	3	5	7	9	权重
土地利用修正阻力值	由公式 (5) 计算并按自然断点法分类得出					0.445
高程/m	<138	138−348	348−592	592−902	>902	0.052
坡度/(°)	<7	7−16	16−25	25−34	>34	0.105
植被覆盖度	>0.850	0.710−0.850	0.530−0.710	0.280−0.530	<0.280	0.148
距铁路、高速距离/km	>10	5−10	2−5	1−2	<1	0.125
距国道、省道距离/km	>5	2−5	1−2	0.5−1	<0.5	0.125

重要性等级	杭州	宁波	温州	嘉兴	湖州	绍兴	金华	衢州	舟山	台州	丽水
低	1.70×10³	1.77×10³	1.01×10³	1.49×10³	832	1.08×10³	1.10×10³	479	235	874	552
中	3.88×10³	3.45×10³	3.13×10³	2.56×10³	2.73×10³	3.20×10³	3.74×10³	2.31×10³	278	3.23×10³	1.89×10³
较高	3.58×10³	3.11×10³	3.47×10³	14.7	1.24×10³	2.76×10³	2.74×10³	1.55×10³	504	3.32×10³	3.52×10³
高	7.87×10³	600	3.92×10³	0.570	1.09×10³	1.28×10³	3.54×10³	4.61×10³	96.3	2.08×10³	1.16×10⁴

基于电路理论的浙江省生态保护修复关键区域识别

Identification of Key Areas for Ecological Protection and Restoration in Zhejiang Province Based on Circuit Theory

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敏感性等级	杭州	宁波	温州	嘉兴	湖州	绍兴	金华	衢州	舟山	台州	丽水
低	4.13×10³	4.02×10³	2.10×10³	4.01×10³	3.03×10³	2.78×10³	3.16 ×10³	1.60 ×10³	400	2.59×10³	661
中	3.05×10³	2.03×10³	2.44×10³	53.2	1.36×10³	2.34×10³	2.49 ×10³	2.12 ×10³	496	2.21×10³	2.28 ×10³
较高	5.39×10³	1.86×10³	3.47 ×10³	6.45	970	2.09×10³	2.93×10³	2.61×10³	198	2.45×10³	5.10×10³
高	4.49×10³	1.04×10³	3.52×10³	0.070	539	1.12×10³	2.57×10³	2.62×10³	23.9	2.26×10³	9.49×10³

生态保护修复区域	杭州	宁波	温州	湖州	绍兴	金华	衢州	台州	丽水
生态源地	7.15×10³	517	3.67×10³	775	1.08×10³	3.38×10³	4.23×10³	2.03×10³	1.20×10⁴
低阻廊道	17.0	29.9	9.00	44.4	51.0	17.2	0.18	12.3	2.88
中阻廊道	83.5	26.5	21.8	19.3	80.1	89.0	15.6	52.5	4.59
高阻廊道	20.2	0.00	1.35	1.53	0.00	29.7	15.3	11.8	0.00
生态夹点	64.3	3.06	26.5	9.72	47.1	47.3	27.1	20.4	0.630
生态障碍点	59.6	7.47	11.4	30.8	44.8	34.8	9.99	7.56	0.00

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