生态与环境

陕北黄土高原生态脆弱性时空变异及驱动因素分析

  • 卓静 ,
  • 胡皓 ,
  • 何慧娟 ,
  • 王智 ,
  • 杨承睿
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  • 1.陕西省突发事件预警信息发布中心,陕西 西安 710015
    2.陕西省气象局秦岭和黄土高原生态环境气象重点实验室,陕西 西安 710015
    3.陕西省农业遥感与经济作物气象服务中心,陕西 西安 710015
卓静(1978-),女,硕士,正高级工程师,主要从事生态气象与气象灾害预警传播研究. E-mail: 79506610@qq.com

收稿日期: 2023-01-13

  修回日期: 2023-03-13

  网络出版日期: 2023-12-05

基金资助

陕西省重点研发计划(2022SF-432);陕西省自然科学基础研究计划(2022JQ-232)

Spatiotemporal variation and driving factors of ecological vulnerability in the Loess Plateau of northern Shaanxi

  • Jing ZHUO ,
  • Hao HU ,
  • Huijuan HE ,
  • Zhi WANG ,
  • Chengrui YANG
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  • 1. Shaanxi Early Warning Center, Xi’an 710015, Shaanxi, China
    2. Key Laboratory of Eco-Environment and Meteorology for The Qinling Mountains and Loess Plateau, Shaanxi Meteorological Bureau, Xi’an 710015, Shaanxi, China
    3. Shaanxi Meteorological Service Center of Agricultural Remote Sensing and Economic Crop, Xi’an 710015, Shaanxi, China

Received date: 2023-01-13

  Revised date: 2023-03-13

  Online published: 2023-12-05

摘要

在多源数据的支撑下,基于敏感性-恢复力-压力模型构建评估指标体系,分析生态恢复工程实施前后(1997年和2021年)陕北黄土高原不同行政区、不同生态功能区和不同坡度的生态脆弱性时空分异规律及驱动机制。结果表明:(1) 陕北黄土高原生态脆弱性明显改善,生态脆弱性指数均值从41.74下降至32.96,减幅21.0%;生态脆弱性等级也整体下降,已由中脆弱和低脆弱性占主导转化为低脆弱性占主导的格局。生态脆弱性存在明显地带性分布特征,从南到北生态脆弱性等级逐步提高。(2) 1997—2021年,51.2%的区域生态脆弱性有所改善,以中脆弱改善到低脆弱为主;4.6%的区域生态脆弱性有所增加,以一般脆弱增加至低脆弱、低脆弱增加至中脆弱为主。铜川市、延安市和榆林市辖区内生态脆弱性指数和等级均在下降,其中铜川市生态脆弱性最低,榆林市最高。3个生态功能区生态脆弱性指数和等级均在显著下降,降幅表现为:退耕还林区>风沙区>黄桥林区。(3) 符合退耕条件的区域,高等级脆弱性大幅转化为低等级脆弱性,生态脆弱性得到明显改善,工程取得了较为显著的成效。(4) 剖析驱动机制可以发现,人为因素和自然因素的驱动力各占83.1%和16.9%,说明生态恢复工程是区域生态脆弱性显著改善的主要驱动力。研究结果可为该区域生态恢复工程成效评估和生态可持续性修复提供科学的参考数据。

本文引用格式

卓静 , 胡皓 , 何慧娟 , 王智 , 杨承睿 . 陕北黄土高原生态脆弱性时空变异及驱动因素分析[J]. 干旱区地理, 2023 , 46(11) : 1768 -1777 . DOI: 10.12118/j.issn.1000-6060.2023.027

Abstract

Studying spatiotemporal changes in ecological vulnerability in the Loess Plateau region of northern Shaanxi before and after the implementation of an ecological restoration project helps to understand the impact of the project implementation on regional ecological vulnerability and provides a scientific reference for the sustainable restoration of regional ecology. This study aims to provide a scientific foundation for the sustainable restoration of the ecology in this region by leveraging multisource data and an evaluation index system built around the sensitivity-resilience-stress model. The analysis encompasses the spatiotemporal variation of ecological vulnerability in different administrative regions, diverse ecological function areas, and varying slopes in the region before and after the implementation of the project (1997 and 2021) is analyzed with the driving mechanism. The results show the following key insights: (1) The ecological vulnerability in the Loess Plateau, China, was improved substantially. The mean regional ecological vulnerability index decreases from 41.74 to 32.96, a decrease of 21.0%. This shift transforms from medium and low vulnerability to a predominantly low vulnerability pattern. (2) Ecological vulnerability in the study area exhibits a zonal distribution, and the ecological vulnerability in the south is better than that in the north. From 1997 to 2021, 51.2% of the regional ecological vulnerability in the study area was improved, mainly from medium to low vulnerability, accounting for 75.3% of the total area improved, predominantly concentrated in farmland to forest and sandstorm areas. The second notable improvement involves the shift from low to general vulnerability, accounting for 16.9% of the improved areas, mainly within the Huangqiao forest area. Conversely, 4.6% of the regional ecological vulnerability increases in the study area, with general vulnerability rising to low and low vulnerability rising to medium, accounting for 52.9% and 45.6% of the increased area of ecological vulnerability, respectively. These increases are scattered in the sandstorm areas and Huangqiao forest areas. Among the administrative units, Tongchuan City is the lowest ecologically fragile, while Yulin City is the highest, with the most vulnerable areas concentrated in Yulin City. However, the ecological vulnerability index and grade declined in the three municipal districts. Similarly, the ecological vulnerability index and grade of the three ecofunctional areas considerably decreased, with the largest decrease in the area of returning farmland to forest, followed by the wind-sand areas, and finally, the Huangqiao forest area. (3) In designated cropland-to-forest conversion zones, high-grade vulnerability largely transforms into low-grade vulnerability, leading to noticeable regional ecological improvement. (4) Analysis of the driving mechanism reveals that the driving forces of human and natural factors account for 83.1% and 16.9%, respectively. This result shows that ecological restoration projects are the main driving force for the profound improvement of regional ecological vulnerability.

参考文献

[1] 雷波, 焦峰, 王志杰, 等. 黄土丘陵区不同植被带典型小流域生态脆弱性评价[J]. 自然灾害学报, 2013, 22(5): 149-159.
[1] [ Lei Bo, Jiao Feng, Wang Zhijie, et al. Eco-environment vulnerability assessment of typical small watersheds in different vegetation zones of loess hilly area[J]. Journal of Natural Disasters, 2013, 22(5): 149-159. ]
[2] 魏晓旭, 赵军, 魏伟, 等. 中国县域单元生态脆弱性时空变化研究[J]. 环境科学学报, 2016, 36(2): 726-739.
[2] [ Wei Xiaoxu, Zhaojun, et al. Spatial and temporal changes of ecological vulnerability per county unit in China[J]. Acta Scientiae Circumstantiae, 2016, 36(2): 726-739. ]
[3] 赵桂久, 刘燕华, 赵名茶. 生态环境综合整治与恢复技术研究[M]. 北京: 科学技术出版社, 1995: 47-80.
[3] [ Zhao Guijiu, Liu Yanhua, Zhao Mingcha. Study on the technology of comprehensive regulation and restoration of ecological environment[M]. Beijing: Science and Technology Press, 1995: 47-80. ]
[4] 贾晶晶, 赵军, 王建邦, 等. 基于SRP模型的石羊河流域生态脆弱性评价[J]. 干旱区资源与环境, 2020, 34(1): 34-41.
[4] [ Jia Jingjing, Zhao Jun, Wang Jianbang, et al. Ecological vulnerability assessment of Shiyang River Basin based on SRP model[J]. Journal of Arid Land Resources and Environment, 2020, 34(1): 34-41. ]
[5] 安芬, 李旭东, 程东亚. 贵州省乌江流域生态脆弱性评价及其空间变化特征[J]. 水土保持通报, 2019, 39(4): 261-269.
[5] [ An Fen, Li Xudong, Cheng Dongya. Ecological vulnerability assessment and spatial variation characteristics of Wujiang River Basin in Guizhou Province[J]. Bulletin of Soil and Water Conservation, 2019, 39(4): 261-269. ]
[6] 霍童, 张序, 周云, 等. 基于暴露-敏感-适应性模型的生态脆弱性时空变化评价及相关分析——以中国大运河苏州段为例[J]. 生态学报, 2022, 42(6): 2281-2293.
[6] [ Huo Tong, Zhang Xu, Zhou Yun, et al. Identification of the critical ecological spaces in the Dongjiang River Basin based on ecosystem service function[J]. Acta Ecologica Sinica, 2022, 42(6): 2281-2293. ]
[7] 杨雯娜, 周亮, 孙东琪. 基于分区-集成的黄河流域生态脆弱性评价[J]. 自然资源遥感, 2021, 33(3): 211-218.
[7] [ Yang Wenna, Zhou Liang, Sun Dongqi. Ecological vulnerability assessment of the Yellow River Basin based on partition-integration concept[J]. Remote Sensing for Natural Resources, 2021, 33(3): 211-218. ]
[8] 乌宁巴特, 刘新平, 马相平. 叶尔羌河流域土地生态脆弱性差异评价[J]. 干旱区地理, 2020, 43(3): 849-858.
[8] [ Wu Ningbart, Liu Xinping, Ma Xiangping. Evaluation on the difference of land ecological vulnerability in the Yarkant River Basin[J]. Arid Land Geography, 2020, 43(3): 849-858. ]
[9] 马子惠, 马书明, 张树深. 大连市生态脆弱性评价及其不确定性分析[J]. 水土保持通报, 2019, 39(3): 237-242, 262, 313-314.
[9] [ Ma Zihui, Ma Shuming, Zhang Shushen. Ecological vulnerability assessment and its uncertainty analysis of Dalian City[J]. Bulletin of Soil and Water Conservation, 2019, 39(3): 237-242, 262, 313-314. ]
[10] 王鹏, 赵微, 柯新利. 基于SRP模型的潜江市生态脆弱性评价及时空演变[J]. 水土保持研究, 2021, 28(5): 347-354.
[10] [ Wang Peng, Zhao Wei, Ke Xinli. Evaluation and spatiotemporal evolution of ecological vulnerability of Qianjiang based on SRP model[J]. Research of Soil and Water Conservation, 2021, 28(5): 347-354. ]
[11] 钟祺康, 王志一, 王娜, 等. 陕北干旱区景观生态风险空间分异特征及驱动因素分析[J]. 测绘通报, 2022, 544(7): 100-106.
[11] [ Zhong Qikang, Wang Zhiyi, Wang Na, et al. Spatial differentiation characteristics and driving factors of landscape ecological risk in arid area of northern Shaanxi[J]. Bulletin of Surveying and Mapping, 2022, 544(7): 100-106. ]
[12] 张佳辰, 高鹏, 董学德, 等. 基于景观格局分析的青岛市海岸带生态脆弱性评价[J]. 生态与农村环境学报, 2021, 37(8): 1022-1030.
[12] [ Zhang Jiachen, Gao Peng, Dong Xuede, et al. Ecological vulnerability assessment of Qingdao coastal zone based on landscape pattern analysis[J]. Journal of Ecology and Rural Environment, 2021, 37(8): 1022-1030. ]
[13] 李路, 孙桂丽, 陆海燕, 等. 喀什地区生态脆弱性时空变化及驱动力分析[J]. 干旱区地理, 2021, 44(1): 277-288.
[13] [ Li Lu, Sun Guili, Lu Haiyan, et al. Spatial-temporal variation and driving forces of ecological vulnerability in Kashi Prefecture[J]. Arid Land Geography, 2021, 44(1): 277-288. ]
[14] 徐超璇, 鲁春霞, 黄绍琳. 张家口地区生态脆弱性及其影响因素[J]. 自然资源学报, 2020, 35(6): 1288-1300.
[14] [ Xu Chaoxuan, Lu Chunxia, Huang Shaolin. Study on ecological vulnerability and its influencing factors in Zhangjiakou area[J]. Journal of Natural Resources, 2020, 35(6): 1288-1300. ]
[15] 张行, 陈海, 史琴琴, 等. 陕西省景观生态脆弱性时空演变及其影响因素[J]. 干旱区研究, 2020, 37(2): 496-505.
[15] [ Zhang Xing, Chen Hai, Shi Qinqin, et al. Spatiotemporal evolution and driving factors of landscape ecological vulnerability in Shaanxi Province[J]. Arid Zone Research, 2020, 37(2): 496-505. ]
[16] 孙桂丽, 陆海燕, 郑佳翔, 等. 新疆生态脆弱性时空演变及驱动力分析[J]. 干旱区研究, 2022, 39(1): 258-269.
[16] [ Sun Guili, Lu Haiyan, Zheng Jiaxiang, et al. Spatio-temporal variation of ecological vulnerability in Xinjiang and driving force analysis[J]. Arid Zone Research, 2022, 39(1): 258-269. ]
[17] 朱琪, 周旺明, 贾翔, 等. 长白山国家自然保护区及其周边地区生态脆弱性评估[J]. 应用生态学报, 2019, 30(5): 1633-1641.
[17] [ Zhu Qi, Zhou Wangming, Jiaxiang, et al. Ecological vulnerability assessment on Changbai Mountain National Nature Reserve and its surrounding areas, northeast China[J]. Chinese Journal of Applied Ecology, 2019, 30(5): 1633-1641. ]
[18] 朱琪, 王亚楠, 周旺明, 等. 东北森林带生态脆弱性时空变化及其驱动因素[J]. 生态学杂志, 2021, 40(11): 3474-3482.
[18] [ Zhu Qi, Wang Ya’nan, Zhou Wangming, et al. Spatiotemporal changes and driving factors of ecological vulnerability in northeast China forest belt[J]. Chinese Journal of Ecology, 2021, 40(11): 3474-3482. ]
[19] 刘佳茹, 赵军, 沈思民, 等. 基于SRP概念模型的祁连山地区生态脆弱性评价[J]. 干旱区地理, 2020, 43(6): 1573-1582.
[19] [ Liu Jiaru, Zhao Jun, Shen Simin, et al. Ecological vulnerability assessment of Qilian Mountains region based on SRP conceptual model[J]. Arid Land Geography, 2020, 43(6): 1573-1582. ]
[20] 李芮芝, 胡希军, 杜心宇, 等. 基于SRP模型的南雄丹霞梧桐自然保护区生态脆弱性评价[J]. 西北林学院学报, 2021, 36(5): 152-160.
[20] [ Li Ruizhi, Hu Xijun, Du Xinyu, et al. Ecological vulnerability assessment based on SPR model in Nanxiong Danxia Indus Nature Reservation Area[J]. Journal of Northwest Forestry University, 2021, 36(5): 152-160. ]
[21] 王茜, 赵筱青, 普军伟, 等. 滇东南喀斯特区域生态脆弱性的时空演变及其影响因素[J]. 应用生态学报, 2021, 32(6): 2180-2190.
[21] [ Wang Qian, Zhao Xiaoqing, Pu Junwei, et al. Spatial-temporal variations and influencing factors of eco-environment vulnerability in the karst region of southeast Yunnan, China[J]. Chinese Journal of Applied Ecology, 2021, 32(6): 2180-2190. ]
[22] 陈臻琦, 张靖, 张贻龙, 等. 基于VSD的近20 a来浑善达克沙地生态脆弱性变化研究[J]. 干旱区研究, 2021, 38(5): 1464-1473.
[22] [ Chen Zhenqi, Zhang Jing, Zhang Yilong, et al. Spatio-temporal patterns variation of ecological vulnerability in Otindag Sandy Land based on a vulnerability scoping diagram[J]. Arid Zone Research, 2021, 38(5): 1464-1473. ]
[23] 陈枫, 李泽红, 董锁成, 等. 基于VSD模型的黄土高原丘陵沟壑区县域生态脆弱性评价——以甘肃省临洮县为例[J]. 干旱区资源与环境, 2018, 32(11): 74-80.
[23] [ Chen Feng, Li Zehong, Dong Suocheng, et al. Evaluation of ecological vulnerability in gully-hilly region of Loess Plateau based on VSD model: A case of Lintao County[J]. Journal of Arid Land Resources and Environment, 2018, 32(11): 74-80. ]
[24] 张学渊, 魏伟, 周亮, 等. 西北干旱区生态脆弱性时空演变分析[J]. 生态学报, 2021, 41(12): 4707-4719.
[24] [ Zhang Xueyuan, Zhou Liang, et al. Analysis on spatio-temporal evolution of ecological vulnerability in arid areas of northwest China[J]. Acta Ecologica Sinica, 2021, 41(12): 4707-4719. ]
[25] 黄越, 程静, 王鹏. 中国北方农牧交错区生态脆弱性时空演变格局与驱动因素——以盐池县为例[J]. 干旱区地理, 2021, 44(4): 1175-1185.
[25] [ Huang Yue, Cheng Jing, Wang Peng. Spatiotemporal evolution pattern and driving factors of ecological vulnerability in agro-pastoral region in northern China: A case of Yanchi County in Ningxia[J]. Arid Land Geography, 2021, 44(4): 1175-1185. ]
[26] 郭婧, 魏珍, 任君, 等. 基于熵权灰色关联法的高寒贫困山区生态脆弱性分析——以青海省海东市为例[J]. 水土保持通报, 2019, 39(3): 191-199.
[26] [ Guo Jing, Wei Zhen, Ren Jun, et al. Analysis on ecological vulnerability in high-cold and poverty-stricken mountainous areas based on entropy and gray correlation methods: A case study in Haidong City, Qinghai Province[J]. Bulletin of Soil and Water Conservation, 2019, 39(3): 191-199. ]
[27] 卓静, 朱延年, 何慧娟, 等. 生态恢复工程对陕北地区生态系统格局的影响[J]. 生态学报, 2020, 40(23): 8627-8637.
[27] [ Zhuo Jing, Zhu Yannian, He Huijuan, et al. Impacts of ecological restoration projects on the ecosystem in the Loess Plateau[J]. Acta Ecologica Sinica, 2020, 40(23): 8627-8637. ]
[28] 傅伯杰. 退耕还林工程是黄土实现了生态环境保护和社会经济发展“双赢”[N]. 延安日报, 2019-08-13(04).
[28] [ Fu Bojie. The project of returning farmland to forest has realized the “win-win” of ecological environment protection and social and economic development of loess[N]. Yanan Daily, 2019-08-13(04). ]
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