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桂西南喀斯特-北部湾海岸带生态环境脆弱性时空分异与驱动机制研究
引用本文:张泽,胡宝清,丘海红,邓雁菲.桂西南喀斯特-北部湾海岸带生态环境脆弱性时空分异与驱动机制研究[J].地球信息科学,2021,23(3):456-466.
作者姓名:张泽  胡宝清  丘海红  邓雁菲
作者单位:1.北部湾环境演变与资源利用教育部重点实验室,南宁 5300012.广西地表过程与智能模拟重点实验室,南宁 5300013.南宁师范大学地理与海洋研究院 南宁 5300014.南宁师范大学地理科学与规划学院,南宁 530001
基金项目:国家自然科学基金项目(42071135、41930537);广西自然科学基金项目(2016GXNSFGA380007);广西科技计划项目(AD19110142)。
摘    要:为揭示生态环境脆弱性的时空分异和驱动因子,本研究在山江海视角下,以桂西南喀斯特-北部湾海岸带为典型研究区,运用空间主成分分析法,地理探测器模型,结合生态环境脆弱性综合指数,系统分析桂西南喀斯特-北部湾海岸带生态环境脆弱性的时空分异特征及驱动机制。结果表明:① 研究区2008、2013、2018年脆弱性指数分别为0.54、0.61、0.69,多年平均值为0.61,整体处于中度脆弱,在空间上,由城市中心向四周逐渐降低的趋势;在时间上,生态环境脆弱等级呈微恶化趋势; ② 在单因子作用中6个驱动因子对生态环境脆弱性的解释力强度为汛期降雨量(0.457)>植被覆盖度(0.384)>高温季节温度(0.311)>废水入海量(0.248)>NPP(0.184)>人口密度(0.036)。在多因子交互中,只有汛期降水量和NPP, NPP和高温季节温度、废水入海量和NPP呈非线性增强,其余的交互作用均为双线性增强,而且汛期降水量和植被覆盖度的单因子影响较强,交互作用后影响也是最强(0.679),说明了汛期降水量和植被覆盖度为该区域的主要驱动因子。

关 键 词:山江海视角  生态环境脆弱性  时空分异  空间主成分分析法  生态环境脆弱性指数  地理探测器  驱动机制  桂西南喀斯特-北部湾海岸带  
收稿时间:2020-06-03

Spatio-temporal Differentiation and Driving Mechanism of Ecological Environment Vulnerability in Southwest Guangxi Karst-Beibu Gulf Coastal Zone
ZHANG Ze,HU Baoqing,QIU Haihong,DENG Yanfei.Spatio-temporal Differentiation and Driving Mechanism of Ecological Environment Vulnerability in Southwest Guangxi Karst-Beibu Gulf Coastal Zone[J].Geo-information Science,2021,23(3):456-466.
Authors:ZHANG Ze  HU Baoqing  QIU Haihong  DENG Yanfei
Institution:1. Key Laboratory of Environment Change and Resources Use in Beibu Gulf, Ministry of Education, Nanning 530001, China2. Guangxi Key Laboratory of Earth Surface Processes and Intelligent Simulation, Nanning 530001, China3 Institute of geography and oceanography, Nanning normal university, Nanning 530001, China4. School of Geography and Planning, Nanning normal university, Nanning 530001, China
Abstract:Characterizing the spatiotemporal changes in ecological vulnerability and reveal its driving factors is important, especially for unique geographical environment that connects mountains, rivers, and sea together, In this study, we chose the Southwest Guangxi karst-Beibu gulf coastal zone as the typical study area. We combined the spatial principal component analysis and geo-detector model to quantify the ecological vulnerability index and further characterizes the spatiotemporal changes in ecological vulnerability and evaluates its driving mechanism. Our results show that:(1) the vulnerability index of the study area was 0.54, 0.61 and 0.69,respectively for 2008, 2013, and 2018, with a multi-year average of 0.61. The general ecological vulnerability level was moderately fragile with a slightly worse trend over time;and(2) the top six explanatory driving factors of ecological vulnerability were rainfall in flood season(0.457), vegetation coverage(0.384), temperature in hot seasons(0.311), waste water input(0.248), NPP(0.184), and population density(0.036). For the interaction between driving factors, only rainfall in flood season and NPP, NPP and temperature in hot seasons, waste water input and NPP showed positive nonlinear relationships, while the rest had linear relationships. Flood season rainfall and vegetation coverage had the strongest effect on ecological vulnerability and a strongest interaction(0.679) with each other. Our study illustrates that flood season rainfall and vegetation coverage are the main driving factors of ecological vulnerability in the study area.
Keywords:view of mountains  rivers and seas  ecological vulnerability  spatial-temporal differentiation  spatial principal component analysis  ecological environment vulnerability index  geographical detector  driving mechanism  Southwest Guangxi karst-Beibu gulf coastal zone
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