西江流域生态脆弱性时空分异及其驱动机制研究

doi:10.12082/dqxxkx.2018.170633

地球信息科学学报 ›› 2018, Vol. 20 ›› Issue (7): 947-956.doi: 10.12082/dqxxkx.2018.170633

• 地理空间分析综合应用 • 上一篇下一篇

西江流域生态脆弱性时空分异及其驱动机制研究

王钰(), 胡宝清^*()

1. 广西师范学院北部湾环境演变与资源利用教育部重点实验室南宁 530001
2. 广西地表过程与智能模拟重点实验室,南宁530001
3. 广西师范学院地理科学与规划学院南宁 530001

收稿日期:2017-12-26 修回日期:2018-02-06 出版日期:2018-07-20 发布日期:2018-07-13
通讯作者: 胡宝清 E-mail:wangyu175@163.com;hbq1230@gxtc.edu.cn
作者简介:
作者简介:王钰(1993-),女,广西北海人,硕士生,研究方向为脆弱性环境演变与生态安全。 E-mail: wangyu175@163.com
基金资助:
国家自然科学基金项目（41661021、41361022）;广西自然基金创新团队项目(2016JJF15001);广西科技开发项目（14125008-2-24）

Spatial and Temporal Differentiation of Ecological Vulnerability of Xijiang River in Guangxi and Its Driving Mechanism

WANG Yu(), HU Baoqing^*()

1. Key Laboratory of Environment Change and Resources Use in Beibu Gulf (Guangxi Teachers Education University), Ministry of Education, Nanning 530001, China
2. Guangxi Key Laboratory of Earth Surface Processes and Intelligent Simulation, Nanning 530001, China
3. School of Geography and Planning, Guangxi Teachers Education University, Nanning 530001, China;

Received:2017-12-26 Revised:2018-02-06 Online:2018-07-20 Published:2018-07-13
Contact: HU Baoqing E-mail:wangyu175@163.com;hbq1230@gxtc.edu.cn
Supported by:
National Natural Science Foundation of China, No.41661021, 41361022;Guangxi Natural Fund Innovative Team Project, No.2016JJF15001;Guangxi Science and Technology Development Project, No.14125008-2-24

摘要/Abstract

摘要：

流域作为人口、资源、资本都相对集中的水文单元,其生态系统结构的稳定性是区域社会经济发展的基础。流域在生态系统演变及人类频繁活动的共同胁迫下,生境敏感性增强,脆弱易损。本文以广西西江流域为例,通过对其生态脆弱性成因机制分析,依循“敏感性-压力度-恢复力”评估框架,选取11个指标构建完成流域生态脆弱性评价指标体系,以GIS技术为支撑,采用空间主成分分析法和差值法对生态脆弱性指数进行计算与分析,探究2000-2010年广西西江流域生态脆弱性时空变化特征。基于地理探测器的因子探测和交互探测模块分析各影响因子对流域生态脆弱性结果的解释力及因子交互作用对流域生境脆弱性变化的驱动机制。结果表明:① 2000-2010年,广西西江流域生态脆弱性指数多年平均值为0.69,整体处于中度脆弱状态。空间上,流域生态脆弱性表现为中部高于四周,由城市核心区往外逐步减弱的格局特征,研究时段内流域生态脆弱性综合指数多年平均值最大的为贵港市（3.40）,最小的为百色市（2.23）;时间上,10年间,流域整体生态脆弱性呈现轻微恶化的趋势,2005年流域中部及东部地区受高温影响,导致2005年流域生态脆弱性指数整体高于其他两年;② 6个因子对流域生态脆弱性的解释力强度为生物丰度指数（0.475）>高温季节温度（0.340）>植被覆盖度（0.211）>NPP（0.183）>降雨侵蚀力（0.098）>汛期降雨量（0.030）,因子交互协同作用后对结果解释力增强。

关键词: 生态脆弱性, 地理探测器, 时空分异, 驱动机制, 广西西江流域

Abstract:

As a hydrologic unit with dense population, abundant resource and intensive capital, the stability of ecosystem structure of a basin lays the foundation of regional economy's development. Influenced by ecosystem's evolution together with human being's activities, the basin environment becomes more and more sensitive and vulnerable. In case of Xijiang River in Guangxi, the thesis is to make an analysis on the cause of its ecological vulnerability and construct evaluation indexes system with eleven indices under the framework of sensitivity-pressure-recovery. Supported by GIS technology, the ecological vulnerability index（EVI）was calculated and analyzed by Principal Component Analysis and difference method, which probes into the spatial and temporal characteristics of ecological vulnerability change from 2000 to 2010. Based on the factor and the interaction detect modules of geographical detector, it aims to analyze the explanatory power of impact factors on ecological vulnerability and the driving forces of factor interaction to the changes of ecological vulnerability in the basin. The results are as following: from 2000 to 2010, the ecological vulnerability index means kept at 0.69 for years, which was at moderate vulnerability. Spatially, the central basin is more sensitive than the surround area showing a declining trend from center to suburbs. The maximum of the average ecological vulnerability composite index of the whole basin for 2000-2010, is 3.40 at Guigang City. The minimum is 2.23 at Baise City. During the past ten years, the ecological fragility of the basin showed a slight deterioration. In year 2005, central and eastern parts of the basin were influenced by high temperature, which led to the higher ecological vulnerability comprehensive index in 2005 than other years. The order of the explanatory power intensity of the six factors on the ecological vulnerability is as follows: biological abundance index (0.475)>temperature at high temperature season (0.340)>vegetation coverage (0.211)>NPP (0.183)>rainfall erosivity (0.098)>Rainfall in flood season (0.030), and the explanatory power on results will be strengthened by factors cooperative interaction.

Key words: ecological vulnerability, geographical detector, spatial and temporal differentiation, driving mechanism, Xijiang River in Guangxi

王钰, 胡宝清. 西江流域生态脆弱性时空分异及其驱动机制研究[J]. 地球信息科学学报, 2018, 20(7): 947-956.

WANG Yu,HU Baoqing. Spatial and Temporal Differentiation of Ecological Vulnerability of Xijiang River in Guangxi and Its Driving Mechanism[J]. Journal of Geo-information Science, 2018, 20(7): 947-956.

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目标层	要素层	指标层	指标性质
生态脆弱性	生态敏感性	高程	正向
		地形起伏度	正向
		植被覆盖度	负向
		汛期降雨量	正向
		高温季节温度	正向
		降雨侵蚀力	正向
		景观干扰度	正向
	生态压力度	人口密度	正向
	生态恢复力	植被净初级生产力	负向
		生物丰度指数	负向
		经济密度	负向

脆弱性等级	生态脆弱性指数标准化值	脆弱程度	生态特征
Ⅰ	< 0.2	潜在脆弱	生态系统功能完整,对各类干扰敏感性弱,承受生态压力小,自我恢复能力强,无生态异常出现
Ⅱ	0.2-0.4	微度脆弱	生态系统功能较为完善,对各类干扰敏感性较弱,承受生态压力较小,自我恢复能力强,存在潜在的生态异常
Ⅲ	0.4-0.6	轻度脆弱	生态系统功能尚可维持,对各类干扰敏感性中等,承受生态压力接近阈值,自我恢复力较弱,出现少量生态异常
Ⅳ	0.6-0.8	中度脆弱	生态系统功能部分退化,对各类干扰敏感性较强,承受生态压力较大,受损后恢复难度较大,生态异常较多
Ⅴ	> 0.8	重度脆弱	生态系统功能退化严重,对各类干扰敏感性强,承受生态压力大,受损后恢复难度极大,生态异常集中连片出现

判断依据	交互作用
P(X1∩X2)<min(P(X1),P(X2))	非线性减弱
min(P(X1),P(X2))<P(X1∩X2)<max(P(X1),P(X2))	单线性减弱
P(X1∩X2)>max(P(X1),P(X2))	双线性增强
P(X1∩X2)= P(X1)+P(X2)	相互独立
P(X1∩X2)>P(X1)+P(X2)	非线性增强

年份	主成分系数	主成分
年份	主成分系数	PC1	PC2	PC3	PC4	PC5
2000	特征值 λ	0.0390	0.0219	0.0155	0.0095	0.0073
	贡献率/%	37.4154	21.0766	14.8903	9.1736	7.0614
	累计贡献率/%	37.4154	58.4920	73.3823	82.5559	89.6173
2005	特征值 λ	0.0362	0.0198	0.0105	0.0087	0.0079
	贡献率/%	38.4644	20.9905	11.2189	9.2838	8.4047
	累计贡献率/%	38.4644	59.4549	70.6738	79.9575	88.3623
2010	特征值 λ	0.0377	0.0224	0.0100	0.0089	0.0080
	贡献率/%	37.1375	22.0626	9.8852	8.7832	7.8885
	累计贡献率/%	37.1375	59.2001	69.0854	77.8686	85.7570

X1∩X2	P(X1∩X2)	判断	交互作用
生物丰度指数（0.475）∩高温季节温度（0.340）	0.676	P(X1∩X2)>max(P(X1),P(X2))	双线性增强
生物丰度指数（0.475）∩汛期降雨量（0.030）	0.505	P(X1∩X2)>max(P(X1),P(X2))	双线性增强
生物丰度指数（0.475）∩NPP（0.183）	0.518	P(X1∩X2)>max(P(X1),P(X2))	双线性增强
生物丰度指数（0.475）∩降雨侵蚀力（0.098）	0.530	P(X1∩X2)>max(P(X1),P(X2))	双线性增强
生物丰度指数（0.475）∩植被覆盖度（0.211）	0.529	P(X1∩X2)>max(P(X1),P(X2))	双线性增强
高温季节温度（0.340）∩汛期降雨量（0.030）	0.351	P(X1∩X2)>max(P(X1),P(X2))	双线性增强
高温季节温度（0.340）∩NPP（0.183）	0.533	P(X1∩X2)>P(X1)+P(X2)	非线性增强
高温季节温度（0.340）∩降雨侵蚀力（0.098）	0.368	P(X1∩X2)>max(P(X1),P(X2))	双线性增强
高温季节温度（0.340）∩植被覆盖度（0.211）	0.475	P(X1∩X2)>max(P(X1),P(X2))	双线性增强
汛期降雨量（0.030）∩NPP（0.183）	0.230	P(X1∩X2)>P(X1)+P(X2)	非线性增强
汛期降雨量（0.030）∩降雨侵蚀力（0.098）	0.125	P(X1∩X2)>max(P(X1),P(X2))	双线性增强
汛期降雨量（0.030）∩植被覆盖度（0.211）	0.234	P(X1∩X2)>max(P(X1),P(X2))	双线性增强
NPP（0.183）∩降雨侵蚀力（0.098）	0.286	P(X1∩X2)>P(X1)+P(X2)	非线性增强
NPP（0.183）∩植被覆盖度（0.211）	0.314	P(X1∩X2)>max(P(X1),P(X2))	双线性增强
降雨侵蚀力（0.098）∩植被覆盖度（0.211）	0.281	P(X1∩X2)>max(P(X1),P(X2))	双线性增强

西江流域生态脆弱性时空分异及其驱动机制研究

Spatial and Temporal Differentiation of Ecological Vulnerability of Xijiang River in Guangxi and Its Driving Mechanism

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