基于GAM的喀斯特植被覆盖与驱动因素非线性关系分析

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摘要利用Theil-Sen斜率估计和Mann-Kendall显著性检验对2000~2018年西南五省的归一化植被指数(NDVI)进行研究,探究植被覆盖的时空变化特征.用MK(Mann-Kendall)突变检验寻找NDVI与夜间灯光数据的突变时间点.借助广义可加模型(GAM)对社会经济驱动因素,自然驱动因素分别拟合植被覆盖的响应曲线,探究喀斯特地区与非喀斯特地区的非线性响应关系的差异.结果表明:研究区中部、东部的植被恢复效果整体比西部地区好;利用夜间灯光数据作为表征城镇化的替代变量,城镇化与植被覆盖都在2009~2010年之间发生了突变,城镇化的突变时间早于植被覆盖的突变;喀斯特地区有88.54%的植被覆盖增加,其中有48.15%显著增加;非喀斯特地区有80.08%的植被覆盖增加,其中显著增加的占32.34%.喀斯特地区的植被恢复整体要比非喀斯特地区好.植被指数与国内生产总值(GDP)、路网密度、建成区面积等人类影响因素呈现不同的非线性响应关系.整体而言,非喀斯特地区受到的气温影响要比喀斯特地区的大,降雨、土层厚度对喀斯特地区植被恢复的影响更大一些.对比评价喀斯特与非喀斯特地区的植被恢复效果,分区探索植被覆盖变化背后驱动机制的非线性关系,对生态恢复规划等具有启示意义.

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关键词 ：喀斯特, 植被指数, 驱动因子, 突变检验, 非线性, 广义可加模型(GAM)

Abstract：This study explored the spatial and temporal variation characteristics of vegetation cover, using Theil-Sen slope estimation with the Mann-Kendall (MK) significance test for determining the normalized vegetation index (NDVI) of five Southwestern provinces in China from 2000~2018. The MK mutation test was used to determine the mutation time points of NDVI and nighttime light data. The generalized additive model (GAM) was used to fit the response curve of vegetation cover with socio-economic and natural driving factors, and the difference in the nonlinear response relationship between karst and non-karst areas was studied. The results showed that the overall effect of vegetation restoration in the Central and Eastern areas of the study was greater than that in the Western areas. Night light data were used as proxy variables to characterize urbanization. The results showed that both urbanization and vegetation cover underwent abrupt changes between 2009 and 2010, with the abrupt change in urbanization occurring earlier than that in vegetation cover. There was an 88.54% increase in vegetation index in karst regions, with a 48.15% significant increase. In non-karst regions, 80.08% of the vegetation cover increased, with 32.34% of a considerable increase. Generally, vegetation restoration in karst regions is better than in non-karst regions. There were different nonlinear responses between the vegetation index and human influencing factors such as gross domestic product, road network density, and built-up areas. Overall, non-karst regions are more affected by temperature than karst regions. However, precipitation and soil thickness exert a slightly more significant impact on vegetation restoration in karst regions than in non-karst regions. The comparative evaluation of vegetation restoration effects in karst and non-karst regions and exploration of the nonlinear relationships of the leading causes behind vegetation cover changes exert an influential impact on ecological restoration planning.

Key words： Karst vegetation index driver factors mutation testing nonlinearity generalized additive model (GAM)

收稿日期: 2022-09-07

PACS:	X171
	Q948

基金资助:国家重点研发计划项目(2022YFF1300701);国家自然科学基金资助项目(42001090);四川省天府青城计划(ZX20220027)

通讯作者: 彭立,研究员,pengli@imde.ac.cn E-mail: pengli@imde.ac.cn

作者简介: 黄琪(1999-),女,宁夏银川人,四川师范大学硕士研究生,主要从事区域生态系统管理方面研究.20211101021@stu.sicnu.edu.cn.

引用本文:

黄琪, 彭立, 李赛男, 黄紫燕, 邓伟. 基于GAM的喀斯特植被覆盖与驱动因素非线性关系分析[J]. 中国环境科学, 2023, 43(5): 2489-2496. HUANG Qi, PENG Li, LI Sai-nan, HUANG Zi-yan, DENG Wei. Analysis of the nonlinear relationship between karst vegetation cover and driving factors based on GAM. CHINA ENVIRONMENTAL SCIENCECE, 2023, 43(5): 2489-2496.

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http://www.zghjkx.com.cn/CN/ 或 http://www.zghjkx.com.cn/CN/Y2023/V43/I5/2489

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