黄土高原2000—2020年生态网络演变及关键修复区识别

doi:10.13474/j.cnki.11-2246.2023.0225

测绘通报 ›› 2023, Vol. 0 ›› Issue (8): 19-23,77.doi: 10.13474/j.cnki.11-2246.2023.0225

黄土高原2000—2020年生态网络演变及关键修复区识别

赵菊花¹, 杨永崇¹, 王涛², 杨梅焕¹, 谢艳玲³, 郭志炜¹, 陈佳旺⁴

1. 西安科技大学测绘科学与技术学院, 陕西西安 710054;
2. 西安科技大学国土空间研究所, 陕西西安 710054;
3. 贵州省第一测绘院, 贵州贵阳 550025;
4. 中冶武勘智诚(武汉)工程技术有限公司, 湖北武汉 430074

收稿日期:2022-12-28 修回日期:2023-03-06 发布日期:2023-09-01
通讯作者: 谢艳玲。E-mail:48041545@qq.com
作者简介:赵菊花(1997-),女,硕士生,研究方向为地理空间信息技术与应用。E-mail:1844764309@qq.com
基金资助:
国家自然科学基金(41977059；42271309)；陕西省软科学研究计划(2022KRM034)

Evolution of ecological network and identification of key restoration areas in the Loess Plateau during 2000-2020

ZHAO Juhua¹, YANG Yongchong¹, WANG Tao², YANG Meihuan¹, XIE Yanling³, GUO Zhiwei¹, CHEN Jiawang⁴

1. College of Geomatics, Xi'an University of Science and Technology, Xi'an 710054, China;
2. Institute of Territorial Space, Xi'an University of Science and Technology, Xi'an 710054, China;
3. First Surveying and Mapping Institute of Guizhou Provence, Guiyang 550025, China;
4. WSGRI Smart City(Wuhan) Engineering Technology Co., Ltd., Wuhan 430074, China

Received:2022-12-28 Revised:2023-03-06 Published:2023-09-01

摘要/Abstract

摘要： 生态修复工程对国家生态保护具有重要促进作用,生态质量评价及构建生态网络是识别生态修复区域的重要途径。本文利用遥感生态指数(RSEI)、最小累积阻力模型、重力模型构建2000、2010、2020年黄土高原生态网络,并分析其演变特征,识别不同时期生态关键修复区。结果表明: ① 2000-2020年,黄土高原生态质量整体处于中等偏低水平,空间上呈西北差东南优的分布特征。2000-2010年,生态质量改善趋势明显,占总面积的53.55%。② 2000-2020年黄土高原生态廊道数量增加,总长度减少。生态廊道主要景观类型为草地、林地、耕地。重要廊道多分布于研究区东南部生态源地附近,数量占比逐年增加;西北部廊道数量少、距离远、重要性低、连通性较差。③ 黄土高原生态关键修复区中,生态夹点集中分布在西南部和东部,障碍点分散在东部和南部,主要土地利用类型为草地和耕地,面积均呈增加趋势。生态断裂点分布广泛,在黄土高原东部省会城市周边较集聚。本研究可为黄土高原国土空间生态修复工程实施提供科学参考。

关键词: 生态修复, 遥感生态指数, 电路理论, 生态夹点, 黄土高原

Abstract: Ecological restoration projects play an important role in promoting national ecological protection. Ecological quality assessment and ecological network construction are important ways to identify ecological restoration areas. In this paper, remote sensing ecological index (RSEI), minimum cumulative resistance model and gravity model are used to construct the Loess Plateau ecological network in 2000, 2010 and 2020, and its evolution characteristics is analyzed, ecological key restoration areas in different periods are identified. The results show that: ① From 2000 to 2020, the overall ecological quality of the Loess Plateau was at a moderate and low level, with a spatial distribution feature of poor ecological quality in the northwest and better ecological quality in the southeast. From 2000 to 2010, the ecological quality improved significantly, accounting for 53.55% of the total area. ② From 2000 to 2020, the number of ecological corridors on the Loess Plateau increased, while the total length decreased. The main landscape types of ecological corridor are grassland, woodland and cultivated land. Most important corridors were distributed near the ecological source area in the southeast of the study area, and the number proportion increased year by year. The northwest corridor is small in number, long in distance, low in importance and poor in connectivity. ③ In the key ecological restoration areas of the Loess Plateau, the ecological pinch points were concentrated in the southwest and the east, and the obstacle points were scattered in the east and the south. The main land use types were grassland and cultivated land, and the area showed an increasing trend. Ecological fracture points are widely distributed and clustered around provincial capitals in the east of the Loess Plateau. This study can provide scientific reference for the implementation of territorial ecological restoration projects on the Loess Plateau.

Key words: ecological restoration, remote sensing ecological index, circuit theory, ecological pinch point, Loess Plateau

中图分类号:

P237

赵菊花, 杨永崇, 王涛, 杨梅焕, 谢艳玲, 郭志炜, 陈佳旺. 黄土高原2000—2020年生态网络演变及关键修复区识别[J]. 测绘通报, 2023, 0(8): 19-23,77.

ZHAO Juhua, YANG Yongchong, WANG Tao, YANG Meihuan, XIE Yanling, GUO Zhiwei, CHEN Jiawang. Evolution of ecological network and identification of key restoration areas in the Loess Plateau during 2000-2020[J]. Bulletin of Surveying and Mapping, 2023, 0(8): 19-23,77.

参考文献

[1] 彭建,赵会娟,刘焱序,等. 区域生态安全格局构建研究进展与展望[J]. 地理研究,2017,36(3):407-419.
[2] 方莹,王静,黄隆杨,等. 基于生态安全格局的国土空间生态保护修复关键区域诊断与识别:以烟台市为例[J]. 自然资源学报,2020,35(1):190-203.
[3] PENG Jian,PAN Yajing,LIU Yanxu,et al. Linking ecological degradation risk to identify ecological security patterns in a rapidly urbanizing landscape[J]. Habitat International,2018,71:110-124.
[4] 袁少雄,宫清华,陈军,等. 广东省自然保护区生态网络评价及其生态修复建议[J]. 热带地理,2021,41(2):431-440.
[5] 王浩,马星,杜勇. 基于生态系统服务重要性和生态敏感性的广东省生态安全格局构建[J]. 生态学报,2021,41(5):1705-1715.
[6] TANG Feng,ZHOU Xu,WANG Li,et al. Linking ecosystem service and MSPA to construct landscape ecological network of the Huaiyang section of the grand canal[J]. Land,2021,10(9):919.
[7] 周浪,李明慧,周启刚,等. 基于电路理论的特大山地城市生态安全格局构建:以重庆市都市区为例[J]. 水土保持研究,2021,28(2):319-325.
[8] 戴璐,刘耀彬,黄开忠. 基于MCR模型和DO指数的九江滨水城市生态安全网络构建[J]. 地理学报,2020,75(11):2459-2474.
[9] 陆禹,佘济云,罗改改,等. 基于粒度反推法和GIS空间分析的景观格局优化[J]. 生态学杂志,2018,37(2):534-545.
[10] ZHANG Haitao,LI Jialin,TIAN Peng,et al. Construction of ecological security patterns and ecological restoration zones in the city of Ningbo,China[J]. Journal of Geographical Sciences,2022,32(4):663-681.
[11] 倪庆琳,侯湖平,丁忠义,等. 基于生态安全格局识别的国土空间生态修复分区:以徐州市贾汪区为例[J]. 自然资源学报,2020,35(1):204-216.
[12] 于成龙,刘丹,冯锐,等. 基于最小累积阻力模型的东北地区生态安全格局构建[J]. 生态学报,2021,41(1):290-301.
[13] 徐涵秋. 城市遥感生态指数的创建及其应用[J]. 生态学报,2013,33(24):7853-7862.
[14] 徐涵秋. 利用改进的归一化差异水体指数(MNDWI)提取水体信息的研究[J]. 遥感学报,2005,9(5):589-595.
[15] 吴茂全,胡蒙蒙,汪涛,等. 基于生态安全格局与多尺度景观连通性的城市生态源地识别[J]. 生态学报,2019,39(13):4720-4731.
[16] 张晓琳,金晓斌,韩博,等. 长江下游平原区生态网络识别与优化:以常州市金坛区为例[J]. 生态学报,2021,41(9):3449-3461.
[17] 汉瑞英,赵志平,肖能文,等. 基于最小累积阻力差值模型的北京市生态安全格局构建[J]. 水土保持通报,2022,42(3):95-102.
[18] YU Haoran,WANG Yongzheng,CHAN Eme,et al. Construction of ecological network based on multi-scale conversion and nesting[J]. Water,2021,13(9):1278.
[19] 许峰,尹海伟,孔繁花,等. 基于MSPA与最小路径方法的巴中西部新城生态网络构建[J]. 生态学报,2015,35(19):6425-6434.
[20] CARROLL C,MCRAE B H,BROOKES A. Use of linkage mapping and centrality analysis across habitat gradients to conserve connectivity of gray wolf populations in western North America[J]. Conservation Biology,2012,26(1):78-87.
[21] MCRAE B H,DICKSON B G,KEITT T H,et al. Using circuit theory to model connectivity in ecology,evolution,and conservation[J]. Ecology,2008,89(10):2712-2724.
[22] 周圆,张青年. 道路网络对物种迁移及景观连通性的影响[J]. 生态学杂志,2014,33(2):440-446.
[23] 韦宝婧,苏杰,胡希军,等. 基于"HY-LM"的生态廊道与生态节点综合识别研究[J]. 生态学报,2022,42(7):2995-3009.

黄土高原2000—2020年生态网络演变及关键修复区识别

Evolution of ecological network and identification of key restoration areas in the Loess Plateau during 2000-2020

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