浑善达克沙地植被变化定量归因及多情景预测

doi:10.12118/j.issn.1000-6060.2022.302

摘要/Abstract

摘要：

在未来全球变化的背景下，我国干旱和半干旱区域植被更加敏感，平衡经济发展和环境保护仍面临重大挑战，而对干旱和半干旱区的植被进行动态监测和影响评估是一项十分必要的工作。通过分析2000—2020年浑善达克沙地归一化植被指数（Normalized difference vegetation index，NDVI）时空变化特征，识别导致研究区NDVI变化的驱动机制和主要的驱动因子，采用情景分析探讨其植被未来变化的轨迹。结果表明：过去20 a间，浑善达克沙地NDVI呈现波动上升趋势；放牧是影响此地区植被变化的主要因子，但放牧对其NDVI变化的影响力有逐渐减弱的趋势；情景模拟显示，浑善达克沙地虽然向恢复方向发展，但因其脆弱的生态环境，使得其植被仍受到人类活动和气候变化的胁迫。研究结果为浑善达克沙地的生态恢复和生态建设工作提供一定的理论支持，并根据当地的实际情况提出相应的对策与建议。

关键词: 趋势分析, 地理探测器, 多情景预测, NDVI, 浑善达克沙地

Abstract:

In the context of future global warming, the vegetation in arid and semi-arid regions in China is more sensitive, and the balance between economic development and environmental protection remains challenging. Therefore, it is essential to conduct dynamic monitoring and driving factors assessment of vegetation in those areas. In this study, the spatiotemporal variation of NDVI in Otindag Sandy Land from 2000 to 2020 was first analyzed using Theil-Sen median trend analysis; next, the driving mechanism of NDVI change was analyzed using the Geodetector model. Finally, multiscenario analysis was used to reveal the future change trajectories of vegetation in the area. The results showed that the NDVI of Otindag Sandy Land exhibited upward fluctuation trends within 20 years, and grazing is the main factor affecting the changes in NDVI in Otindag Sandy Land; however, the effect of grazing to NDVI dynamics in the Otindag Sandy Land gradually weakened. In addition, the multiscenario prediction results show that, although the vegetation of Otindag Sandy Land is developing toward restoration, its fragile ecological environment and the vegetation status were still threatened by human activities and climate change. This study provides a theoretical basis for the Otindag Sandy Land ecological construction and restoration, as well as relevant countermeasures and suggestions according to the actual situation.

Key words: trend analysis, geodetector, multi-scenario prediction, NDVI, Otindag Sandy Land

罗嘉艳, 张靖, 徐梦冉, 莫宇, 同丽嘎. 浑善达克沙地植被变化定量归因及多情景预测[J]. 干旱区地理, 2023, 46(4): 614-624.

LUO Jiayan, ZHANG Jing, XU Mengran, MO Yu, TONG Liga. Vegetation dynamic and its driving force and multi-scenario prediction in Otindag Sandy Land[J]. Arid Land Geography, 2023, 46(4): 614-624.

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参考文献 49

[1]	Mea. Millennium ecosystem assessment: Ecosystems and human well-being-synthesis[M]. Washington, DC: Island Press, 2005.
[2]	Reynolds J F, Smith D M S, Lambin E F, et al. Global desertification: Building a science for dryland development[J]. Science, 2007, 316(5826): 847-851. doi: 10.1126/science.1131634 pmid: 17495163
[3]	Huang J, Zhai J, Jiang T, et al. Analysis of future drought characteristics in China using the regional climate model CCLM[J]. Climate Dynamics, 2018, 50(1-2): 507-525. doi: 10.1007/s00382-017-3623-z
[4]	Huang J, Yu H, Guan X, et al. Accelerated dryland expansion under climate change[J]. Nature Climate Change, 2016, 6(2): 166-171. doi: 10.1038/NCLIMATE2837
[5]	Zhou D, Zhao X, Hu H, et al. Long-term vegetation changes in the four mega-sandy lands in Inner Mongolia, China[J]. Landscape Ecology, 2015, 30(9): 1613-1626. doi: 10.1007/s10980-015-0151-2
[6]	王牧兰, 包玉海, 银山. 浑善达克沙地动态变化影响因素分析[J]. 干旱区资源与环境, 2004(增刊3): 44-47.
	[Wang Mulan, Bao Yuhai, Yinshan. Dynamic changes of the landscape structure of Hunshandake Sandy Land and analysis on its forming factors[J]. Journal of Arid Land Resources and Environment, 2004(Suppl. 3): 44-47.]
[7]	Wang J, He T, Guo X, et al. Dynamic changes of sandy land in northwest of Beijing, China[J]. Environmental Monitoring and Assessment, 2006, 121(1-3): 109-125. pmid: 16758285
[8]	丁国栋, 蔡京艳, 王贤, 等. 浑善达克沙地沙漠化成因、过程及其防治对策研究——以内蒙古正蓝旗为例[J]. 北京林业大学学报, 2004(4): 15-19.
	[Ding Guodong, Cai Jingyan, Wang Xian, et al. Causes, process and counter measures of desertification in Hunshandake Sand Land: Taking Zhenglan Banner, Inner Mongolia as an example[J]. Journal of Beijing Forestry University, 2004(4): 15-19.]
[9]	Zhao Y, Chi W, Kuang W, et al. Ecological and environmental consequences of ecological projects in the Beijing-Tianjin sand source region[J]. Ecological Indicators, 2020, 112: 106111, doi: 10.1016/j.ecolind.2020.106111. doi: 10.1016/j.ecolind.2020.106111
[10]	Wang H, Yao F, Zhu H, et al. Spatiotemporal variation of vegetation coverage and its response to climate factors and human activities in arid and semi-arid areas: Case study of the Otindag Sandy Land in China[J]. Sustainability, 2020, 12(12): 5214, doi: 10.3390/su12125214. doi: 10.3390/su12125214
[11]	同丽嘎, 宁小莉, 张靖, 等. 近30 a浑善达克沙地沙漠化时空演变特征及驱动机制研究[J]. 干旱区地理, 2021, 44(4): 992-1002.
	[Tong Liga, Ning Xiaoli, Zhang Jing, et al. Spatial-temporal variation and driving mechanism of desertification in Hunshandake (Otindag) Sandy Land in recent 30 years[J]. Arid Land Geography, 2021, 44(4): 992-1002.]
[12]	姚雪玲, 李龙, 王锋, 等. 放牧方式对浑善达克沙地榆树疏林退化的影响[J]. 生态学报, 2020, 40(5): 1663-1671.
	[Yao Xueling, Li Long, Wang Feng, et al. Effects of grazing management on the degradation of Ulmus pumila open forest in Otindag Sandy Land[J]. Acta Ecologica Sinica, 2020, 40(5): 1663-1671.]
[13]	王旭洋, 李玉霖, 连杰, 等. 半干旱典型风沙区植被覆盖度演变与气候变化的关系及其对生态建设的意义[J]. 中国沙漠, 2021, 41(1): 183-194. doi: 10.7522/j.issn.1000-694X.2020.00089
	[Wang Xuyang, Li Yulin, Lian Jie, et al. Relationship between vegetation coverage and climate change in semi-arid sandy land and the significance to ecological construction[J]. Journal of Desert Research, 2021, 41(1): 183-194.] doi: 10.7522/j.issn.1000-694X.2020.00089
[14]	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.
	[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.]
[15]	于娜, 赵媛媛, 丁国栋, 等. 基于生态足迹的中国四大沙地地区可持续评价[J]. 干旱区地理, 2018, 41(6): 1310-1320.
	[Yu Na, Zhao Yuanyuan, Ding Guodong, et al. Sustainability assessment in four sandy lands of China based on the ecological footprint model[J]. Arid Land Geography, 2018, 41(6): 1310-1320.]
[16]	Burrell A L, Evans J P, Liu Y. Detecting dryland degradation using time series segmentation and residual trend analysis (TSS-RESTREND)[J]. Remote Sensing of Environment, 2017, 197: 43-57. doi: 10.1016/j.rse.2017.05.018
[17]	李永利, 张存厚, 王英, 等. 浑善达克沙地地上净初级生产力动态及对气候变化的响应[J]. 草业科学, 2021, 38(1): 1-10.
	[Li Yongli, Zhang Cunhou, Wang Ying, et al. Dynamics of above-ground net primary production and its response to climate change in the Hunshandake sand[J]. Pratacultural Science, 2021, 38(1): 1-10.]
[18]	Gou F, Liang W, Sun S, et al. Analysis of the desertification dynamics of sandy lands in northern China over the period 2000—2017[J]. Geocarto International, 2021, 36(17): 1938-1959. doi: 10.1080/10106049.2019.1678677
[19]	Kang W P, Liu S L, Chen X, et al. Evaluation of ecosystem stability against climate changes via satellite data in the eastern sandy area of northern China[J]. Journal of Environmental Management, 2022, 308: 114596, doi: org/10.1016/j.jenvman.2022.114596. doi: org/10.1016/j.jenvman.2022.114596
[20]	Ma W, Wang X, Zhou N, et al. Relative importance of climate factors and human activities in impacting vegetation dynamics during 2000—2015 in the Otindag Sandy Land, northern China[J]. Journal of Arid Land, 2017, 9(4): 558-567. doi: 10.1007/s40333-017-0062-y
[21]	Zheng Y R, Xie Z X, Robert C, et al. Did climate drive ecosystem change and induce desertification in Otindag Sandy Land, China over the past 40 years?[J]. Journal of Arid Environments, 2006, 64(3): 523-541. doi: 10.1016/j.jaridenv.2005.06.007
[22]	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
[23]	孟琪, 武志涛, 杜自强, 等. 京津风沙源区不同分区植被覆盖度变化及归因分析[J]. 应用生态学报, 2021, 32(8): 2895-2905. doi: 10.13287/j.1001-9332.202108.018
	[Meng Qi, Wu Zhitao, Du Ziqiang, et al. Variation in fractional vegetation cover and its attribution analysis of different regions of Beijing-Tianjin sand source region, China[J]. Chinese Journal of Applied Ecology, 2021, 32(8): 2895-2905.] doi: 10.13287/j.1001-9332.202108.018
[24]	马永桃, 任孝宗, 胡慧芳, 等. 基于地理探测器的浑善达克沙地植被变化定量归因[J]. 中国沙漠, 2021, 41(4): 195-204. doi: 10.7522/j.issn.1000-694X.2021.00066
	[Ma Yongtao, Ren Xiaozong, Hu Huifang, et al. Vegetation dynamics and its driving force in Otindag Sandy Land based on geodetector[J]. Journal of Desert Research, 2021, 41(4): 195-204.] doi: 10.7522/j.issn.1000-694X.2021.00066
[25]	邓腾林, 宋一凡, 王明新, 等. 浑善达克沙地归一化植被指数动态变化及其对标准化降水蒸散发指数的时空响应关系[J]. 中国水利水电科学研究院学报, 2022, 20(3): 221-230.
	[Deng Tenglin, Song Yifan, Wang Mingxin, et al. Dynamic variations of normalized difference vegetation index variations in Otindag SandLand and its spatio-temporal responses to standardized precipitation evapotranspiration index[J]. Journal of China Institute of Water Resources and Hydropower Research, 2022, 20(3): 221-230.]
[26]	Dvorak M T, Armour K C, Frierson D M W, et al. Estimating the timing of geophysical commitment to 1.5 and 2.0 ℃ of global warming[J]. Nature Climate Change, 2022, 312, doi: 10.1038/s41558-022-01372-y. doi: 10.1038/s41558-022-01372-y
[27]	齐丹卉, 杨洪晓, 卢琦, 等. 浑善达克沙地植物群落主要类型与特征[J]. 中国沙漠, 2021, 41(4): 23-33. doi: 10.7522/j.issn.1000-694X.2021.00029
	[Qi Danhui, Yang Hongxiao, Lu Qi, et al. Types and characteristics of plant communities in the Otingdag Sandy Land[J]. Journal of Desert Research, 2021, 41(4): 23-33.] doi: 10.7522/j.issn.1000-694X.2021.00029
[28]	Zhang J, Li X, Buyantuev A, et al. How do trade-offs and synergies between ecosystem services change in the long period? The case study of Uxin, Inner Mongolia, China[J]. Sustainability, 2019, 11(21): 6041, doi: 10.3390/SU11216041. doi: 10.3390/SU11216041
[29]	Wu D, Zhao X, Liang S, et al. Time-lag effects of global vegetation responses to climate change[J]. Global Change Biology, 2015, 21(9): 3520-3531. doi: 10.1111/gcb.12945 pmid: 25858027
[30]	Sun R, Chen S, Su H. Climate dynamics of the spatiotemporal changes of vegetation NDVI in northern China from 1982 to 2015[J]. Remote Sensing, 2021, 13(2): 187, doi: 10.3390/rs13020187. doi: 10.3390/rs13020187
[31]	史娜娜, 肖能文, 王琦, 等. 锡林郭勒植被NDVI时空变化及其驱动力定量分析[J]. 植物生态学报, 2019, 43(4): 331-341. doi: 10.17521/cjpe.2018.0254
	[Shi Na’na, Xiao Nengwen, Wang Qi, et al. Temporal and spatial variation of vegetation NDVI and its driving forces in Xilingol[J]. Chinese Journal of Plant Ecology, 2019, 43(4): 331-341.] doi: 10.17521/cjpe.2018.0254
[32]	Hao R, Yu D, Liu Y, et al. Impacts of changes in climate and landscape pattern on ecosystem services[J]. Science of the Total Environment, 2017, 579: 718-728. doi: 10.1016/j.scitotenv.2016.11.036
[33]	Zheng K Y, Tan L S, Sun Y W, et al. Impacts of climate change and anthropogenic activities on vegetation change: Evidence from typical areas in China[J]. Ecological Indicators, 2021, 126: 107648, doi: org/10.1016/j.ecolind.2021.107648. doi: org/10.1016/j.ecolind.2021.107648
[34]	Wang L, Yu D, Liu Z, et al. Study on NDVI changes in Weihe watershed based on CA-Markov model[J]. Geological Journal, 2018, 53: 435-441. doi: 10.1002/gj.3259
[35]	Masson-Delmotte V, Zhai P, Pirani A, et al. Climate change 2021: The physical science basis[M]. Cambridge, UK and New York, USA: Cambridge University Press, 2021: 32.
[36]	安妮, 宁小莉, 海全胜, 等. 基于MODIS数据的近15年浑善达克沙地植被净初级生产力时空分布研究[J]. 干旱区资源与环境, 2020, 34(4): 168-175.
	[An Ni, Ning Xiaoli, Hai Quansheng, et al. Optical model for estimating the spatial and temporal distribution of vegetation net primary productivity in Hunshandake Sandy Land in recent 15 years[J]. Journal of Arid Land Resources and Environment, 2020, 34(4): 168-175.]
[37]	Xie Y C, Sha Z Y. Quantitative analysis of driving factors of grassland degradation: A case study in Xilin River Basin, Inner Mongolia[J]. Scientific World Journal, 2012, 2012: 169724, doi: 10.1100/2012/169724. doi: 10.1100/2012/169724
[38]	Hao L, Sun G, Liu Y Q, et al. Effects of precipitation on grassland ecosystem restoration under grazing exclusion in Inner Mongolia, China[J]. Landscape Ecology, 2014, 29: 1657-1673. doi: 10.1007/s10980-014-0092-1
[39]	Li A, Wu J, Huang J. Distinguishing between human-induced and climate-driven vegetation changes: A critical application of RESTREND in Inner Mongolia[J]. Landscape Ecology, 2012, 27(7): 969-982. doi: 10.1007/s10980-012-9751-2
[40]	Liu C, Melack J, Tian Y, et al. Detecting land degradation in eastern China grasslands with time series segmentation and residual trend analysis (TSS-RESTREND) and GIMMS NDVI3g data[J]. Remote Sensing, 2019, 11(9): 1014, doi: 10.3390/rs11091014. doi: 10.3390/rs11091014
[41]	陈宸, 井长青, 邢文渊, 等. 近20年新疆荒漠草地动态变化及其对气候变化的响应[J]. 草业学报, 2021, 30(3): 1-14.
	[Jing Changqing, Xing Wenyuan, et al. Desert grassland dynamics in the last 20 years and its response to climate change in Xinjiang[J]. Acta Prataculturae Sinica, 2021, 30(3): 1-14.]
[42]	Gardiner B, Berry P, Moulia B. Wind impacts on plant growth, mechanics and damage[J]. Plant Sciences, 2016, 245: 94-118. doi: 10.1016/j.plantsci.2016.01.006
[43]	Wang X M, Lang L L, Yan P, et al. Aeolian processes and their effect on sandy desertification of the Qinghai-Tibet Plateau: A wind tunnel experiment[J]. Soil and Tillage Research, 2016, 158: 67-75. doi: 10.1016/j.still.2015.12.004
[44]	Zou X Y, Li J F, Cheng H, et al. Spatial variation of topsoil features in soil wind erosion areas of northern China[J]. Catena, 2018, 167: 429-439. doi: 10.1016/j.catena.2018.05.022
[45]	Zhang G, Xu X, Zhou C, et al. Responses of grassland vegetation to climatic variations on different temporal scales in Hulun Buir Grassland in the past 30 years[J]. Journal of Geographical Sciences, 2011, 21(4): 634-650. doi: 10.1007/s11442-011-0869-y
[46]	邵艳莹, 吴秀芹, 张宇清, 等. 内蒙古地区植被覆盖变化及其对水热条件的响应[J]. 北京林业大学学报, 2018, 40(4): 33-42.
	[Shao Yanying, Wu Xiuqin, Zhang Yuqing, et al. Response of vegetation coverage to hydro-thermal change in Inner Mongolia of northern China[J]. Journal of Beijing Forestry University, 2018, 40(4): 33-42.]
[47]	贺军奇, 魏燕, 高万德, 等. 毛乌素沙地东南缘植被NDVI时空变化及其对气候因子的响应[J]. 干旱区地理, 2022, 45(5): 1523-1533.
	[He Junqi, Wei Yan, Gao Wande, et al. Temporal and spatial variation of vegetation NDVI and its response to climatic factors in the southeastern margin of Mu Us Sandy Land[J]. Arid Land Geography, 2022, 45(5): 1523-1533.]
[48]	Dong S K, Gao H W, Xu G C, et al. Farmer and professional attitudes to the large-scale ban on livestock grazing of grasslands in China[J]. Environmental Conservation, 2007, 34(3): 246-254.
[49]	Zhang Y, Wang Q, Wang Z, et al. Impact of human activities and climate change on the grassland dynamics under different regime policies in the Mongolian Plateau[J]. Science of the Total Environment, 2020, 698: 134304, doi: 10.1016/j.scitotenv.2019.134304. doi: 10.1016/j.scitotenv.2019.134304

类型I	类型II	指标	代码
自然因素	气候	年均温/℃	TEM
		年降水量/mm	PRE
		年均风速/m·s^-1	WND
	地形	高程/m	ELEV
		坡度/(°)	SLP
		坡向/(°)	ASP
	土壤	土壤类型	SOIL
	植被	植被类型	VGT
人类活动		土地利用类型	LUC
		人口密度/人·km^-2	POP
		牲畜数量/头	SHEEP

情景	情景名称	情景变化参数
惯性发展情景	惯性发展	驱动因子不做处理，遵循NDVI的惯性发展规律
气候变化情景¹	降水增多	调整降水值，将降水的值总体提升25%，其余因子不做处理
	降水降低	调整降水值，将降水的值总体降低25%，其余因子不做处理
	风速提高	调整风速值，将风速的值总体提升25%，其余因子不做处理
	风速降低	调整风速值，将风速的值总体降低25%，其余因子不做处理
经济优先情景²	放牧压力增加	调整牲畜数量，将牲畜数量的值总体提升50%，其余因子不做处理
生态保护情景²	放牧压力减少	调整牲畜数量，将牲畜数量的值总体降低50%，其余因子不做处理

年份	因子
年份	TEM	PRE	WND	ELEV	SLP	ASP	SOIL	VGT	LUC	POP	SHEEP
2001—2005	0.09	0.54	0.53	0.49	0.08	0.04	0.25	0.08	0.14	0.05	0.74
2006—2010	0.12	0.49	0.50	0.42	0.09	0.04	0.25	0.07	0.14	0.02	0.60
2011—2015	0.16	0.54	0.53	0.47	0.08	0.04	0.24	0.08	0.13	0.04	0.64
2016—2020	0.20	0.57	0.54	0.49	0.09	0.03	0.25	0.08	0.13	0.08	0.62

年份	情景	情景名称	植被覆盖区分级
年份	情景	情景名称	低度	较低	中等	较高	高度
2020	-	-	12034	10105	8531	5607	5469
2030（模拟）	惯性发展情景	惯性发展	10527	9141	9976	6916	5187
	气候变化情景	降水增多	7511	9141	9976	6794	8324
		降水降低	12305	10729	7992	5532	5188
		风速提高	12758	10227	7990	5760	5011
		风速降低	8933	9141	9976	6916	6780
	经济优先情景	放牧压力增加	12750	10267	7927	5499	5303
	生态保护情景	放牧压力减少	7249	9141	9976	6916	8464