2001—2020年塔城地区草地健康时空变化特征及其驱动力分析

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Spatiotemporal dynamics and driving forces of grassland health in Tacheng Prefecture from 2001 to 2020

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doi:10.12118/j.issn.1000-6060.2024.392

Abstract:

As an important agricultural and pastoral area, Tacheng Prefecture, Xinjiang, China requires an in-depth study of grassland health to support conservation efforts and grazing management. However, the long-term spatiotemporal dynamics of grassland health and its driving forces across different grassland types remain insufficiently explored. This study constructs a “pressure-state-response” model using 15 indicators and employs spatial principal component analysis, the coefficient of variation, the Hurst index, spatial autocorrelation, and the geographic detector method to evaluate the spatiotemporal dynamics of grassland health and its driving forces inTacheng Prefecture from 2001 to 2020. The results indicate that: (1) Temporally, the grassland health index inTacheng Prefecture exhibits a fluctuating downward trend. The warning and collapse levels show opposite trends, whereas the sub-healthy and healthy levels remain relatively stable. (2) Spatially, the multi-year average grassland health levels transition from sub-healthy to warning and collapse states from west to east. Most grassland types predominantly fall within the sub-healthy category. (3) Regarding future trends, grassland health in Tacheng Prefecture is expected to continue declining, particularly in Tacheng City, southern Emin County, and northern Hoboksar Mongolian Autonomous County. (4) In terms of driving factors, vegetation is the primary determinant of grassland health, and factor interactions enhance its effects more significantly than single factors. Human activities and socio-economic factors also interact with vegetation, further influencing grassland health. These findings provide a theoretical basis and valuable reference for future grassland planning and management in Tacheng Prefecture.

Key words: “pressure-state-response” model, grassland health, Hurst index, geographic detector, Tacheng Prefecture

XING Mengxiang, ZHENG Jianghua, LI Gangyong, PENG Jian, Kaisa MIJITI, LIU Liang, ZHANG Jianli, MA Lisha, LU Jiantao. Spatiotemporal dynamics and driving forces of grassland health in Tacheng Prefecture from 2001 to 2020[J].Arid Land Geography, 2025, 48(4): 673-688.

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[1]	Wang S, Dai E, Jia L, et al. Assessment of multiple factors and interactions affecting grassland degradation on the Tibetan Plateau[J]. Ecological Indicators, 2023, 154: 110509, doi: 10.1016/j.ecolind.2023.110509.
[2]	刘玉佳, 彭建, 李刚勇, 等. 基于GEE的库鲁斯台草原生态环境评价[J]. 生态学杂志, 2023, 42(11): 2776-2785.
	[Liu Yujia, Peng Jian, Li Gangyong, et al. Eeo-environmental assessment of Kurustai grassland based on Google Earth Engine[J]. Chineese Journal of Ecology, 2023, 42(11): 2776-2785.]
[3]	Bengtsson J, Bullock J M, Egon B, et al. Grasslands: More important for ecosystem services than you might think[J]. Ecosphere, 2019, 10(2): e02582, doi: 10.1002/ecs2.2582.
[4]	陈春波, 李刚勇, 彭建, 等. 新疆草地生态健康智能监测网络体系构建[J]. 草业科学, 2023, 40(5): 1420-1434.
	[Chen Chunbo, Li Gangyong, Peng Jian, et al. The systematic construction of a smart network for ecological health observation of grassland in Xinjiang[J]. Pratacultural Science, 2023, 40(5): 1420-1434.]
[5]	郭宏. 新疆塔城地区天然草原退化原因及治理对策[J]. 草食家畜, 2015(3): 55-57.
	[Guo Hong. Causes and countermeasures of natural grassland degradation in Tacheng area of Xinjiang Province[J]. Grass-feeding Livetock, 2015(3): 55-57.]
[6]	董世魁, 张宇豪, 王冠聪. 草地健康与退化评价: 概念、原理及方法[J]. 草业科学, 2023, 40(12): 2971-2981.
	[Dong Shikui, Zhang Yuhao, Wang Guancong. Assessment of grassland health and degradation: Concepts, principles, and methods[J]. Pratacultural Science, 2023, 40(12): 2971-2981.]
[7]	陈春波, 彭建, 李刚勇. 新疆草地生态系统健康评价体系构建[J]. 干旱区研究, 2022, 39(1): 270-281. doi: 10.13866/j.azr.2022.01.26
	[Chen Chunbo, Peng Jian, Li Gangyong. Establishment of grassland ecosystem health evaluation system in Xinjiang[J]. Arid Zone Research, 2022, 39(1): 270-281.] doi: 10.13866/j.azr.2022.01.26
[8]	刘亮, 彭建, 李刚勇, 等. 2010—2021年新疆库鲁斯台草原动态遥感监测变化分析[J]. 新疆农业科学, 2024, 61(1): 230-240. doi: 10.6048/j.issn.1001-4330.2024.01.025
	[Liu Liang, Peng Jian, Li Gangyong, et al. Analysis of dynamic remote sensing monitoring changes in Kulusitai grassland in Xinjiang from 2010 to 2021[J]. Xinjiang Agricultural Science, 2024, 61(1): 230-240.]
[9]	姜佳昌, 孙斌, 潘冬荣, 等. 基于VOR指数的肃南县草地生态系统健康评价[J]. 中国草食动物科学, 2020, 40(4): 39-43.
	[Jiang Jiachang, Sun Bin, Pan Dongrong, et al. Health assessment of grassland ecosystem in Sunan County based on VOR index[J]. China Herbivore Science, 2020, 40(4): 39-43.]
[10]	陆均, 胡玉昆, 岳平, 等. 基于CVOR指数的巴音布鲁克高寒草原健康评价[J]. 干旱区研究, 2017, 34(4): 862-869.
	[Lu Jun, Hu Yukun, Yue Ping, et al. Assessment on the health of alpine steppe in Bayinbuluk based on CVOR index[J]. Arid Zone Research, 2017, 34(4): 862-869.]
[11]	赵玉婷, 李文龙, 陈迪, 等. 高寒牧区草地生态系统健康动态评价—以甘南地区为例[J]. 草业科学, 2017, 34(1): 16-29.
	[Zhao YuTing, Li Wenlong, Chen Di, et al. Dynamic assessment of alpine pasture grassland ecosystem health: A case study from the Gannan region[J]. Pratacultural Science, 2017, 34(1): 16-29.]
[12]	Miller M E. Broad-scale assessment of rangeland health, grand staircase-escalante national monument, USA[J]. Rangeland Ecology & Management, 2008, 61(3): 249-262.
[13]	王玮, 常学礼, 吕世海, 等. 高寒草原湿地自然保护区生态系统健康评价[J]. 生态学杂志, 2013, 32(10): 2780-2787.
	[Wang Wei, Chang Xueli, Lü Shihai, et al. Ecosystem health assessment of alpine grassland wetland nature reserve[J]. Chinese Journal of Ecology, 2013, 32(10): 2780-2787.]
[14]	马春燕, 刘明蕊, 刘世婷, 等. 草地健康评价方法研究综述[J]. 应用生态学报, 2023, 34(12): 3427-3436. doi: 10.13287/j.1001-9332.202312.007
	[Ma Chunyan, Liu Mingrui, Liu Shiting, et al. Research review on methods of grassland health assessment[J]. Chinese Journal of Applied Ecology, 2023, 34(12): 3427-3436.] doi: 10.13287/j.1001-9332.202312.007
[15]	Costanza R, Mangeau M. What is a healthy ecosystem?[J]. Aquatic Ecology, 1999, 33(1): 105-115.
[16]	Tongway D, Hindley N. Landscape function analysis: A system for monitoring rangeland function[J]. African Journal of Range & Forage Science, 2004, 21(2): 109-113.
[17]	孙宇, 刘维忠, 盛洋. 基于PSR模型的新疆水资源经济生态韧性时空差异及影响因素分析[J]. 干旱区地理, 2023, 46(12): 2017-2028. doi: 10.12118/j.issn.1000-6060.2023.155
	[Sun Yu, Liu Weizhong, Sheng Yang. Spatiotemporal differences and influencing factors of economic and ecological resilience of water resources in Xinjiang based on the PSR model[J]. Arid Land Geography, 2023, 46(12): 2017-2028.] doi: 10.12118/j.issn.1000-6060.2023.155
[18]	刘思怡, 丁建丽, 张钧泳, 等. 艾比湖流域草地生态系统环境健康遥感诊断[J]. 草业学报, 2020, 29(10): 1-13. doi: 10.11686/cyxb2019542
	[Liu Siyi, Ding Jianli, Zhang Junyong, et al. Remote sensing diagnosis of grassland ecosystem environmental health in the Ebinur Lake Basin[J]. Acta Prataculturae Sinica, 2020, 29(10): 1-13.] doi: 10.11686/cyxb2019542
[19]	Yi F, Lu Q, Li Y, et al. Ecological vulnerability assessment of natural oasis in arid Areas: Application to Dunhuang, China[J]. Ecological Indicators, 2023, 149: 110139, doi: 10.1016/j.ecolind.2023.110139.
[20]	Kang H, Tao W, Chang Y, et al. A feasible method for the division of ecological vulnerability and its driving forces in southern Shaanxi[J]. Journal of Cleaner Production, 2018, 205: 619-628.
[21]	Kamran M, Yamamoto K. Evolution and use of remote sensing in ecological vulnerability assessment: A review[J]. Ecological Indicators, 2023, 148: 110099, doi: 10.1016/j.ecolind.2023.110099.
[22]	Gong Z, Ge W, Guo J, et al. Satellite remote sensing of vegetation phenology: Progress, challenges, and opportunities[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2024, 217: 149-164.
[23]	高婧, 井立红, 陈静, 等. 塔城地区1961—2020年季节性干旱演变特征[J]. 沙漠与绿洲气象, 2023, 17(5): 109-117.
	[Gao Jing, Jing Lihong, Chen Jing, et al. Evolution characteristics of seasonal drought in Tacheng area of Xinjiang from 1961 to 2020[J]. Desert and Oasis Meteorology, 2023, 17(5): 109-117.]
[24]	许鹏. 新疆草地资源及其利用[M]. 乌鲁木齐: 新疆科技卫生出版社, 1993.
	[Xu Peng. Grassland resources and their utilization in Xinjiang[M]. Urumqi: Xinjiang Science and Technology Health Press, 1993.]
[25]	Hu X, Ma C, Huang P, et al. Ecological vulnerability assessment based on AHP-PSR method and analysis of its single parameter sensitivity and spatial autocorrelation for ecological protection: A case of Weifang City, China[J]. Ecological Indicators, 2021, 125: 107464, doi: 10.1016/j.ecolind.2021.107464.
[26]	赵浩然, 曹生奎, 曹广超, 等. 2000—2020年青海湖流域植被降水利用效率时空变化特征[J]. 生态学报, 2024, 44(8): 1-17.
	[Zhao Haoran, Cao Shengkui, Cao Guangchao, et al. Spatial and temporal characteristics of annual vegetation precipitation use efficiency in the Qinghai Lake Basin from 2000 to 2020[J]. Acta Ecologica Sinica, 2024, 44(8): 1-17.]
[27]	刘亮, 关靖云, 穆晨, 等. 2008—2018年伊犁河流域植被净初级生产力时空分异特征[J]. 生态学报, 2022, 42(12): 4861-4871.
	[Liu Liang, Guan Jingyun, Mu Chen, et al. Spatio-temporal characterstics of vegetation net primary productivity in the Ili River Basin from 2008 to 2018[J]. Acta Ecologica Sinica, 2022, 42(12): 4861-4871.]
[28]	刘如龙, 赵媛媛, 陈国清, 等. 内蒙古黄河流域1990—2020年生境质量评估[J]. 干旱区研究, 2024, 41(4): 674-683. doi: 10.13866/j.azr.2024.04.13
	[Liu Rulong, Zhao Yuanyuan, Chen Guoqing, et al. Assessment of habitat quality in the Yellow River Basin in Inner Mongolia from 1990 to 2020[J]. Arid Zone Research, 2024, 41(4): 674-683.] doi: 10.13866/j.azr.2024.04.13
[29]	Jiang B, Chen W, Dai X, et al. Change of the spatial and temporal pattern of ecological vulnerability: A case study on Cheng-Yu urban agglomeration, southwest China[J]. Ecological Indicators, 2023, 149: 110161, doi: 10.1016/j.ecolind.2023.110161.
[30]	勿吉斯古冷, 那日苏, 丽娜, 等. 2001—2020年呼伦贝尔草原土地沙漠化敏感性时空格局演化[J/OL]. 干旱区地理.[2024-12-20]. https://link.cnki.net/urlid/65.1103.X.20241009.0918.001.
	[Wujisiguleng, Narisu, Li Na, et al. Spatiotemporal pattern evolution of land desertification sensitivity in Hulun Buir grassland from 2001 to 2020[J/OL]. Arid Land Geography.[2024-12-20]. https://link.cnki.net/urlid/65.1103.X.20241009.0918.001.]
[31]	王劲峰, 徐成东. 地理探测器: 原理与展望[J]. 地理学报, 2017, 72(1): 116-134. doi: 10.11821/dlxb201701010
	[Wang Jinfeng, Xu Chengdong. Geodetector: Principle and prospective[J]. Acta Geographica Sinica, 2017, 72(1): 116-134.] doi: 10.11821/dlxb201701010
[32]	和海秀, 付爱红, 王川. 塔城地区西北部低山草甸植被指数变化及其驱动力[J]. 中国沙漠, 2023, 43(1): 187-196. doi: 10.7522/j.issn.1000-694X.2022.00122
	[He Haixiu, Fu Aihong, Wang Chuan. Negetation index change and its driving forces of low mountain meadow vegetation in the northwest of Tacheng Region, Xinjiang, China[J]. Journal of Desert Research, 2023, 43(1): 187-196.] doi: 10.7522/j.issn.1000-694X.2022.00122
[33]	殷桂涛. 退耕还草工程在塔城地区塔尔巴合台山前旱地的生态恢复效果研究[J]. 草食家畜, 2016(5): 70-73.
	[Yin Guitao. Study on ecology restoring farmland to grassland in dryland of Taerbahetaishan in Tacheng[J]. Grass Feeding Livestock, 2016(5): 70-73.]
[34]	范君. 北疆草地覆盖度和净初级生产力的时空变化及退化分析[D]. 乌鲁木齐: 新疆农业大学, 2023.
	[Fan Jun. Spatio-temporal variation and degradation analysis of grassland coverage and net primary productivity in north Xinjiang[D]. Urumqi: Xinjiang Agricultural University, 2023.]
[35]	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. doi: 10.13866/j.azr.2022.01.25
	[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.] doi: 10.13866/j.azr.2022.01.25
[36]	和海秀, 周洪华, 白如霄. 基于土地利用变化的新疆塔城地区碳排放特征分析[J]. 水土保持通报, 2022, 42(3): 373-380.
	[He Haixiu, Zhou Honghua, Bai Ruxiao. Characteristics of carbon emissions based on land use changes in Tacheng Area of Xinjiang Uygur Autonomous Region[J]. Bulletin of Soil and Water Conservation, 2022, 42(3): 373-380.]
[37]	古丽娜尔·沙亚汗, 李佳欢, 谭学周, 等. 新疆塔城不同类型草场生产力动态变化[J]. 草地学报, 2017, 25(1): 49-54.
	[Shayakhan Gulnar, Li Jiahuan, Tan Xuezhou, et al. Dynamic change of grassland productivity in Tacheng, Xinjiang[J]. Acta Agrestia Sinica, 2017, 25(1): 49-54.] doi: 10.11733/j.issn.1007-0435.2017.01.008
[38]	朱大鹏, 何祥博, 李涛, 等. 基于气候变暖和封山禁牧的关山草原生态系统变化研究[J]. 绿色科技, 2022, 24(18): 47-51, 6.
	[Zhu Dapeng, He Xiangbo, Li Tao, et al. Research progress of grassland ecosystem changes in guanshan grassland based on climate warming and grazing prohibition factors[J]. Journal of Green Science and Technology, 2022, 24(18): 47-51, 6.]
[39]	黄兰鹰, 张好, 杨育林, 等. 1998—2020年若尔盖地区植被NDVI变化特征及驱动因子分析[J]. 自然保护地, 2024, 4(3): 74-75.
	[Huang Lanying, Zhang Hao, Yang Yulin, et al. Analysis of driving factors and variation characteristics of vegetation NDVI in Zoige region from 1998 to 2020[J]. Natural Protected Areas, 2024, 4(3): 74-75.]
[40]	Geng X, Wang X, Fang H, et al. Vegetation coverage of desert ecosystems in the Qinghai-Tibet Plateau is underestimated[J]. Ecological Indicators, 2022, 137: 108780, doi: 10.1016/j.ecolind.2022.108780.
[41]	Xue H, Chen Y, Dong G, et al. Quantitative analysis of spatiotemporal changes and driving forces of vegetation net primary productivity (NPP) in the Qimeng region of Inner Mongolia[J]. Ecological Indicators, 2023, 154: 110610, doi: 10.1016/j.ecolind.2023.110610.
[42]	Xi Z, Chen G, Xing Y, et al. Spatial and temporal variation of vegetation NPP and analysis of influencing factors in Heilongjiang Province, China[J]. Ecological Indicators, 2023, 154: 110798, doi: 10.1016/j.ecolind.2023.110798.
[43]	Zhou Q, Chen W, Wang H, et al. Spatiotemporal evolution and driving factors analysis of fractional vegetation coverage in the arid region of northwest China[J]. Science of the Total Environment, 2024, 954: 176271, doi: 10.1016/j.scitotenv.2024.176271.
[44]	张倩, 曹广超, 张乐乐, 等. 祁连山南坡植被绿度时空变化及其对气候变化和人类活动的响应[J]. 干旱区研究, 2024, 41(12): 2143-2153. doi: 10.13866/j.azr.2024.12.15
	[Zhang Qian, Cao Guangchao, Zhang Lele, et al. Spatiotemporal changes in vegetation greenness on the southern slopes of the Qilian Mountains and their responses to climate change and human activities[J]. Arid Zone Research, 2024, 41(12): 2143-2153.] doi: 10.13866/j.azr.2024.12.15

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目标层	准则层	指标层	单位	空间分辨率	数据来源	属性
塔城地区草地健康评价指标	压力层（P）	年均降水量	mm·a^-1	0.0833°	https://data.tpdc.ac.cn/	+
		年均气温	℃·a^-1	0.0833°	https://data.tpdc.ac.cn/	+
		草原载蓄量	羊·km^-2	-	https://tjj.xinjiang.gov.cn/	-
		人均耕地面积	hm²·人^-1	1 km	https://tjj.xinjiang.gov.cn/	-
		人口密度	人·km^-2	-	https://tjj.xinjiang.gov.cn/	-
	状态层（S）	净初级生产力	g C·m^-2·a^-1	500 m	https://urs.earthdata.nasa.gov/home	+
		植被覆盖度	%	250 m	https://urs.earthdata.nasa.gov/home	+
		归一化植被指数	-	250 m	https://urs.earthdata.nasa.gov/home	+
		增强植被指数	-	250 m	https://urs.earthdata.nasa.gov/home	+
		坡度	(°)	90 m	通过高程计算	-
		高程	m	90 m	https://www.resdc.cn/	-
	响应层（R）	耕地面积比重	%	-	https://tjj.xinjiang.gov.cn/	-
		人均GDP	10⁴元	-	https://tjj.xinjiang.gov.cn/	+
		经济密度	元·km^-1	1 km	https://tjj.xinjiang.gov.cn/	+
		城市化水平	%	-	https://tjj.xinjiang.gov.cn/	+

指数取值范围	未来变化趋势
θ_Slope>0，H>0.5	持续增加
θ_Slope<0，H>0.5	持续减小
θ_Slope>0，H<0.5	由增加变为减小
θ_Slope<0，H<0.5	由减少变为增加

交互作用类型	比较
q(X₁∩X₂)<Min[q(X₁), q(X₂)]	非线性减弱
Min[q(X₁), q(X₂)]<q(X₁∩X₂)<Max[q(X₁), q(X₂)]	单因子非线性减弱
q(X₁∩X₂)>Max[q(X₁), q(X₂)]	双因子增强
q(X₁∩X₂)=q(X₁)+q(X₂)	独立
q(X₁∩X₂)>q(X₁)+q(X₂)	非线性增强

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