基于地理探测器的宁夏草地植被覆被时空分异及驱动因子

doi:10.13866/j.azr.2023.08.13

Abstract

Abstract:

This study aims to examine the spatiotemporal variation characteristics of grassland vegetation cover at the regional scale and analyze its driving factors. The findings will provide a scientific reference and decision-making basis for the scientific formulation of protection and restoration models, treatment measures, and the sustainable management of the grassland ecosystem in Ningxia, which are crucial for maintaining the balance of the regional grassland ecosystem and promoting ecological protection and high-quality development in the Yellow River Basin. In this study, the NDVI time series dataset of SPOT/VEGETATION (2000-2019) was used as the data source. The annual mean method, Theil-Sen Median trend analysis, and Mann-Kendall test were employed to study the spatiotemporal distribution and variation characteristics of grassland vegetation cover in Ningxia. Furthermore, the Hurst index method was used to analyze the sustainability characteristics and future development trends of grassland vegetation cover. Simultaneously, the influence of 13 factors, such as average precipitation, altitude, and gross domestic product, on the spatiotemporal distribution was quantified based on the geographical detectors approach. The results show that from 2000 to 2019, the average annual NDVI of vegetation in Ningxia grassland showed a fluctuating growth trend, with a growth rate of 0.005 per year. The regional fluctuation was quite different, with extremely high and high vegetation cover areas concentrated in the Liupan Mountains and the irrigation area along the Yellow River. Overall, the NDVI change showed a low to medium fluctuation trend, and the regional fluctuation was quite different. The vegetation cover condition improved significantly over the 20-year period, with a small degradation area and a favorable overall change trend. However, 59.341% of the grasslands are projected to face potential risks of continuous degradation or transformation from improvement to degradation in the future. The most sensitive environmental factor influencing grassland vegetation distribution response was precipitation, and climate and soil had the strongest interaction explanatory power overall. The relationship between the factors affecting the distribution and variation characteristics of grassland vegetation primarily manifested as mutual reinforcement or nonlinear enhancement, with no independent relationship between the factors. This study provides a scientific reference and decision-making basis for the sustainable management of the grassland ecosystem in Ningxia.

Key words: NDVI, trend analysis, spatiotemporal variation, driving factor, grassland, Ningxia

WEN Miaoxia, HE Xuegao, LIU Huan, ZHANG Jing, LUO Chen, JIA Fengming, WANG Yigui, HU Yunyun. Analysis of the spatiotemporal variation characteristics and driving factors of grassland vegetation cover in Ningxia based on geographical detectors[J].Arid Zone Research, 2023, 40(8): 1322-1332.

Figures/Tables 15

Fig. 1

Tab. 1

Tab. 2

Tab. 3

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Tab. 4

Fig. 6

Tab. 5

Tab. 6

Fig. 7

Fig. 8

Tab. 7

References 31

[1]	Gibson D J. Grasses and Grassland Ecology[M]. New York: Oxford University Press, 2009:1-320.
[2]	Dixon A P, Faber-Langendoen D, Josse C, et al. Distribution mapping of world grassland types[J]. Journal of Biogeography, 2014, 41(11): 2003-2019. doi: 10.1111/jbi.12381
[3]	Conant R T. Challenges and opportunities for carbon sequestration in grassland systems[J]. Integrated Crop Management, 2010, 9: 3-5.
[4]	赵同谦, 欧阳志云, 贾良清, 等. 中国草地生态系统服务功能间接价值评价[J]. 生态学报, 2004, 24(6): 1101-1110.
	[ Zhao Tongqian, Ouyang Zhiyun, Jia Liangqing, et al. Ecosystem services and their valuation of China grassland[J]. Acta Ecologica Sinica, 2004, 24(6): 1101-1110. ]
[5]	郭艳菊, 马晓静, 许爱云, 等. 宁夏东部风沙区沙化草地土壤水分和植被的空间特征[J]. 生态学报, 2022, 42(4): 1571-1581.
	[ Guo Yanju, Ma Xiaojing, Xu Aiyun, et al. Spatial characteristics of soil moisture and vegetation in desertification grassland in eastern Ningxia sand-wind area, China[J]. Acta Ecologica Sinica, 2022, 42(4): 1571-1581. ]
[6]	Carlson T N, Ripley D A. On the relation between NDVI, fractional vegetation cover, and leaf area index[J]. Remote Sensing of Environment, 1997, 62(3): 241-252. doi: 10.1016/S0034-4257(97)00104-1
[7]	Zhao L, Dai A, Dong B. Changes in global vegetation activity and its driving factors during 1982-2013[J]. Agricultural and Forest Meteorology, 2018, 249: 198-209. doi: 10.1016/j.agrformet.2017.11.013
[8]	李茂林, 闫庆武, 仲晓雅, 等. 干旱半干旱地区植被覆盖度变化及主导因素分析: 以锡林郭勒为例[J]. 生态与农村环境学报, 2021, 37(12): 1548-1558.
	[ Li Maolin, Yan Qingwu, Zhong Xiaoya, et al. Analysis on evolution and dominant factors of factional vegetation coverage in arid and semi-arid regions: A case of Xilingol[J]. Journal of Ecology and Rural Environment, 2021, 37(12): 1548-1558. ]
[9]	张起鹏, 王建, 张志刚, 等. 高寒草甸草原景观格局动态演变及其驱动机制[J]. 生态学报, 2019, 39(17): 6510-6521.
	[ Zhang Qipeng, Wang Jian, Zhang Zhigang, et al. Dynamic change of landscape patterns and its driving mechanism in the Qinghai-Tibetan alpine meadow[J]. Acta Ecologica Sinica, 2019, 39(17): 6510-6521. ]
[10]	李鑫磊, 李瑞平, 王秀青, 等. 基于地理探测器的河套灌区林草植被覆盖度时空变化与驱动力分析[J]. 干旱区研究, 2023, 40(4): 623-635.
	[ Li Xinlei, Li Ruiping, Wang Xiuqing, et al. Spatiotemporal change and analysis of factors driving forest-grass vegetation coverage in Hetao Irrigation District based on geographical detector[J]. Arid Zone Research, 2023, 40(4): 623-635. ]
[11]	林妍敏, 李文慧, 南雄雄, 等. 基于地理探测器的宁夏贺兰山植被覆盖度时空分异及驱动因子[J]. 应用生态学报, 2022, 33(12): 3321-3327. doi: 10.13287/j.1001-9332.202212.025
	[ Lin Yanmin, Li Wenhui, Nan Xingxiong, et al. Spatial-temporal differentiation and driving factors of vegetation coverage in Ningxia Helan Mountain based on geodetector[J]. Chinese Journal of Applied Ecology, 2022, 33(12): 3321-3327. ] doi: 10.13287/j.1001-9332.202212.025
[12]	李梦华, 韩颖娟, 赵慧, 等. 基于地理探测器的宁夏植被覆盖度时空变化特征及其驱动因子分析[J]. 生态环境学报, 2022, 31(7): 1317-1325. doi: 10.16258/j.cnki.1674-5906.2022.07.004
	[ Li Menghua, Han Yingjuan, Zhao Hui, et al. Analysis on spatial-temporal variation characteristics and driving factors of fractional vegetation cover in Ningxia based on geographical detector[J]. Ecology and Environmental Sciences, 2022, 31(7): 1317-1325. ] doi: 10.16258/j.cnki.1674-5906.2022.07.004
[13]	付含培, 王让虎, 王晓军. 1999—2018年黄河流域NDVI时空变化及驱动力分析[J]. 水土保持研究, 2022, 28(2): 146-162.
	[ Fu Hanpei, Wang Ranghu, Wang Xiaojun. Analysis of spatiotemporal variations and driving forces of NDVI in the Yellow River Basin during1999-2018[J]. Research of Soil and Water Conservation, 2022, 28(2): 146-162. ]
[14]	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 Jingfeng, Xu Chengdong. Geodetector: Principle and prospective[J]. Acta Geographica Sinica, 2017, 72(1):116-134. ] doi: 10.11821/dlxb201701010
[15]	《中国地图集》编辑部. 中国地图集[M]. 北京: 地质出版社, 2010: 250-253.
	[ Editorial Board of Atlas of China. Atlas of China[M]. Beijing: Geology Press, 2010: 250-253. ]
[16]	Theil H. A rank-invariant method of linear and polynomial regression analysis. I, II and III[J]. Proceedings of Koninklijke Nederlandse Akademie van Wetenschappen, 1950, 53: 386-392.
[17]	Sen K P. Estimates of the regression coefficient based on Kendall’s tau[J]. Journal of the American Statistical Association, 1968, 63(324): 1379-1389. doi: 10.1080/01621459.1968.10480934
[18]	Ali R, Kuriqi A, Abubaker S, et al. Long-term trends and seasonality detection of the observed flow in Yangtze river using Mann-Kendall and Sen’s innovative trend method[J]. Water, 2019, 11: 1855. doi: 10.3390/w11091855
[19]	Hurst H E. Long-term storage capacity of reservoirs[J]. Transactions of the American Society of Civil Engineers, 1951, 116(1): 770-799. doi: 10.1061/TACEAT.0006518
[20]	任丽雯, 王兴涛, 刘明春, 等. 石羊河流域植被净初级生产力时空变化及驱动因素[J]. 干旱区研究, 2023, 40(5): 818-828.
	[ Ren Liwen, Wang Xingtao, Liu Mingchun, et al. Temporal and spatial changes and the driving factors of vegetation NPP in Shiyang River Basin[J]. Arid Zone Research, 2023, 40(5): 818-828. ]
[21]	郝家田, 胡云云, 杜一尘, 等. 基于NDVI的2009—2018年黄河流域林草植被覆盖变化[J]. 林业科学, 2022, 58(3): 10-19.
	[ Hao Jiatian, Hu Yunyun, Du Yichen, et al. NDVI-based coverage changes of forest and grass vegetation in Yellow River Basin during 2009 to 2018[J]. Scientia Silvae Sinicae, 2022, 58(3): 10-19. ]
[22]	杜灵通, 宋乃平, 王磊, 等. 近30 a气候变暖对宁夏植被的影响[J]. 自然资源学报, 2015, 30(12): 2095-2106. doi: 10.11849/zrzyxb.2015.12.011
	[ Du Lingtong, Song Naiping, Wang Lei, et al. Impact of global warming on vegetation activity in Ningxia Province from 1982 to 2013[J]. Journal of Natural Resources, 2015, 30(12): 2095-2106. ] doi: 10.11849/zrzyxb.2015.12.011
[23]	裴志方, 杨武年, 吴彬, 等. 2000—2016年宁夏植被覆盖景观格局遥感动态分析[J]. 水土保持研究, 2018, 25(1): 215-219.
	[ Pei Zhifang, Yang Wunian, Wu Bin, et al. Analysis of dynamic vegetation cover landscape pattern in Ningxia Hui Autonomous Region from 2000 to 2016 using remote sensing[J]. Research of Soil and Water Conservation, 2018, 25(1): 215-219. ]
[24]	王文晓, 黄文广, 杨君珑, 等. 宁夏草原物种丰富度分布格局及其水热解释[J]. 干旱区资源与环境, 2019, 33(5): 158-163.
	[ Wang Wenxiao, Huang Wenguang, Yang Junlong, et al. Distribution patterns and climate explanation of plant species richness in Ningxia grasslands[J]. Journal of Arid Land Resources and Environment, 2019, 33(5): 158-163. ]
[25]	查同刚, 孙向阳, 于卫平, 等. 宁夏段黄河护岸林体系结构的研究[J]. 北京林业大学学报, 2004, 26(3): 93-96.
	[ Zha Tonggang, Sun Xiangyang, Yu Weiping, et al. Search on the construction of the Yellow River protection forest system in Ningxia Autonomous Region[J] Journal of Beijing Forestry University, 2004, 26(3): 93-96. ]
[26]	叶培龙, 张强, 王莺, 等. 1980—2018年黄河上游气候变化及其对生态植被和径流量的影响[J]. 大气科学学报, 2020, 43(6): 967-979.
	[ Ye Peilong, Zhang Qiang, Wang Ying, et al. Climate change in the upper Yellow River Basin and its impact on ecological vegetation and runoff from 1980 to 2018[J]. Transactions of Atmospheric Sciences, 2020, 43(6): 967-979. ]
[27]	李玉武, 徐友宁, 张江华. 宁夏“三区两线”露天矿山复绿对策[J]. 宁夏工程技术, 2015, 14(4): 380-383.
	[ Li Yuwu, Xu Youning, Zhang Jianghua. Countermeasures on vegetation restoration for opencast of Three Districts and Two Lines in Ningxia[J]. Ningxia Engineering Technology, 2015, 14(4): 380-383. ]
[28]	秦格霞, 吴静, 李纯斌, 等. 中国北方草地植被物候变化及其对气候变化的响应[J]. 应用生态学报, 2019, 30(12): 4099-4107. doi: 10.13287/j.1001-9332.201912.015
	[ Qin Gexia, Wu Jing, Li Chunbin, et al. Grassland vegetation phenology change and its response to climate changes in North China[J]. Chinese Journal of Applied Ecology, 2019, 30(12): 4099-4107. ] doi: 10.13287/j.1001-9332.201912.015
[29]	王吉智. 宁夏土壤[M]. 银川: 宁夏人民出版社, 1990: 49.
	[ Wang Jizhi. Ningxia Soil[M]. Yinchuan: Ningxia people’s Publishing House, 1990: 49. ]
[30]	王贵贤. 国土工作手册[M]. 济南: 山东人民出版社, 1988: 281.
	[ Wang Guixian. Homeland Work Manual[M]. Jinan: Shandong people’s Publishing House, 1988: 281. ]
[31]	刘宪锋, 朱秀芳, 潘耀忠, 等. 1982—2012年中国植被覆盖时空变化特征[J]. 生态学报, 2015, 35(16): 5331-5342.
	[ Liu Xianfeng, Zhu Xiufang, Pan Yaozhong, et al. Spatiotemporal changes in vegetation coverage in China during 1982-2012[J]. Acta Ecologica Sinica, 2015, 35(16): 5331-5342. ]

数据集	数据来源	空间分辨率	数据预处理
NDVI数据集	中国科学院资源环境科学数据中心(https://www.resdc.cn/)	1 km	-
中国气象背景数据集		500 m	-
中国1∶1000000地貌类型空间分布数据		1 km	-
中国土壤类型空间分布数据		1 km	-
（数字高程模型）DEM		90 m	利用ArcGIS 10.8获取坡度和坡向数据，统一范围大小和空间分辨率
GDP密度	宁夏数据网站 (http://nxdata.com.cn/)	县域尺度	在ArcGIS 10.8中，插值到县域尺度
人口密度	宁夏数据网站 (http://nxdata.com.cn/)	县域尺度	在ArcGIS 10.8中，插值到县域尺度
草地矢量数据	2021年宁夏林草资源数据库	-	按细化地类提取宁夏回族自治区范围内的草地图斑，融合生成草地范围矢量数据

气候因素	地表因素	人类活动因素
平均降水量（X₁）	海拔（X₇）	GDP（X₁₂）
湿润指数(X₂)	土壤类型（X₈）	人口密度（X₁₃）
干燥度(X₃)	地貌（X₉）
年均温（X₄）	坡度（X₁₀）
≥0 ℃积温（X₅）	坡向（X₁₁）
≥10 ℃积温（X₆）

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

	植被类型	2000年
	植被类型	极低植被覆被	低植被覆被	中植被覆被	高植被覆被	极高植被覆被	合计
2019年	极低植被覆被	15.746	0.040	0.007	0.010		15.803
	低植被覆被	29.591	0.297	0.008			29.896
	中植被覆被	28.450	1.291	0.071		0.022	29.834
	高植被覆被	9.923	4.493	0.692	0.086	0.021	15.215
	极高植被覆被	0.304	3.093	3.477	1.735	0.643	9.252
合计		84.014	9.214	4.255	1.831	0.686	100.000

发展方向	结果	面积/km²	占比/%
良性方向	持续性&轻微改善	1554.343	7.560
	持续性&显著改善	5694.847	27.699
	反持续性&轻微退化	1009.142	4.909
	反持续性&显著退化	17.953	0.087
恶性方向	持续性&轻微退化	565.989	2.753
	持续性&显著退化	32.126	0.161
	反持续性&轻微改善	3562.232	17.326
	反持续性&显著改善	8039.117	39.101
不确定	反持续性&不变	51.024	0.248
稳定	持续性&不变	33.071	0.156

Analysis of the spatiotemporal variation characteristics and driving factors of grassland vegetation cover in Ningxia based on geographical detectors

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 15

References 31

Related Articles 15

Metrics

Comments

Recommended 0

因子	q值	P值
年平均降水量（X₁）	0.800	0.036
湿润度（X₂）	0.794	0.023
干燥度（X₃）	0.770	0.008
年均温（X₄）	0.620	0.020
≥0 ℃积温（X₅）	0.615	0.014
海拔（X₇）	0.591	0.031
土壤类型（X₈）	0.499	0.564
地貌（X₉）	0.392	0.870
人口密度（X₁₃）	0.258	0.387
坡度（X₁₀）	0.179	0.576
坡向（X₁₁）	0.170	0.868
≥10 ℃积温（X₆）	0.137	0.880
GDP（X₁₂）	0.071	0.908

因子	草地NDVI适宜类型或范围	NDVI均值
年平均降水量	545~623 mm	0.596
湿润度	80~200	0.596
干燥度	0~62	0.542
年均温	2.8~3.7 ℃	0.472
≥0 ℃积温	2165~2416 ℃	0.472
≥10 ℃积温	1905~2087 ℃	0.402
海拔	2303~2502 m	0.436
土壤类型	半水成土	0.403
地貌	中起伏山脉	0.596
坡度	24.73°~28.73°	0.365
坡向	349.69°~0.84°	0.385
GDP	5×10⁴~6×10⁴元·km^-2	0.475
人口密度	62~72人·km^-2	0.587

[1]	LI Xiaofeng, HUI Tingting, LI Yaoming, MAO Jiefei, WANG Guangyu, FAN Lianlian. Effects of different grazing management strategies on plant diversity in the mountain grassland of Xinjiang, China [J]. Arid Zone Research, 2024, 41(1): 124-134.
[2]	LIU Yidan, YAO Xiaojun, LI Zongxing, HU Jiayu. Impacts of climate change and land use/cover change on the net primary productivity of vegetation in Hexi Region, Northwest China [J]. Arid Zone Research, 2024, 41(1): 169-180.
[3]	ZHOU Jing,SUN Yongfeng,DING Jieping,BAI Haojiang,MA Xiang,WANG Xuyang,Luo Yongqing. Changes in vegetation biomass and its relationship with soil carbon during restoration processes in degraded sandy grasslands [J]. Arid Zone Research, 2023, 40(9): 1457-1464.
[4]	CHEN Chunbo,LI Junli,ZHAO Yan,XIA Jiang,TIAN Weitao,LI Chaofeng. Spatiotemporal dynamics of grassland vegetation and its responses to climate change in Changji Hui Autonomous Prefecture, Xinjiang [J]. Arid Zone Research, 2023, 40(9): 1484-1497.
[5]	ZHAO Zhuoyi, HAO Xingming. Actual evapotranspiration characteristics and attribution in arid Central Asia based on the Priestley-Taylor method [J]. Arid Zone Research, 2023, 40(7): 1085-1093.
[6]	CUI Yang,WANG Dai,GAO Ruina,AN Xingqin. Atmospheric environmental capacity characteristics and influencing factors of Ningxia over the past 60 years [J]. Arid Zone Research, 2023, 40(6): 885-895.
[7]	YANG Jianling,ZHANG Suzhao,MA Junbin,WANG Dai,Huang Yin. The impact of the North Atlantic sea surface temperature anomaly on precipitation anomaly in Ningxia from late spring to early summer and associated mechanisms [J]. Arid Zone Research, 2023, 40(5): 703-714.
[8]	CHEN Jiawei, CHU Jianmin, GAN Honghao, XU Lei, GONG Shuai, LIU Hao, WANG Yingxin, YANG Hongxiao, XU Xiaoqing, QI Danhui. Asociation characteristics of Amygdalus pedunculata and the environmental factors driving them in Otindag Sandy Land [J]. Arid Zone Research, 2023, 40(5): 777-784.
[9]	REN Liwen, WANG Xingtao, LIU Mingchun, WANG Dawei. Temporal and Spatial changes and the driving factors of vegetation NPP in Shiyang River Basin [J]. Arid Zone Research, 2023, 40(5): 818-828.
[10]	TA Fuyuan, ZHANG Hongyang, GOU Wenshan, MA Weixin, HU Guixin. Survey of species diversity of darkling beetles in the Minqin temperate desert steppe [J]. Arid Zone Research, 2023, 40(5): 840-848.
[11]	DUAN Yujia, HE Yi, ZHAO Jie, WU Qiong. Analysis of impact of human activities on runoff changes in Yue River Basin of the Qinling Mountains [J]. Arid Zone Research, 2023, 40(4): 605-614.
[12]	LI Xinlei, LI Ruiping, WANG Xiuqing, WANG Sinan, WANG Chengkun. Spatiotemporal change and analysis of factors driving forest-grass vegetation coverage in Hetao Irrigation District based on geographical detector [J]. Arid Zone Research, 2023, 40(4): 623-635.
[13]	ZHAO Jian, DENG Chengjun, LI Wenli, ZHAO Jin, GONG Yanming, LI Kaihui. Evaluation of the degree of degradation of Xinjiang Tianshan Bayinbuluk grassland in 35 years [J]. Arid Zone Research, 2023, 40(4): 636-646.
[14]	MA Haowen, WANG Yongfang, GUO Enliang. Remote sensing monitoring of aeolian desertification in Ongniud Banner based on GEE [J]. Arid Zone Research, 2023, 40(3): 504-516.
[15]	SHAO Jian,ZHANG Suzhao,CHEN Min,LI Qiang,ZHENG Youjiong,CHENG Yao,MA Ning. Application of FY-4A satellite data in short-time severe precipitation of Ningxia [J]. Arid Zone Research, 2023, 40(2): 163-172.