摘要
了解生态环境质量(EEQ)的时空演变对于理解气候变化与人类活动对生态环境的综合影响至关重要。深入分析湖北省EEQ的时空演变特征及其驱动因素,可为区域生态保护和植被恢复策略提供科学依据。该研究聚焦于海拔、气候条件及人类足迹的协同效应对EEQ演变的影响,利用2001-2020年的EEQ与土地利用数据,结合Theil-Sen Median和Mann-Kendall分析,揭示了EEQ的演变特征并预测了其未来趋势。同时,结合海拔、气候及人类足迹等多元数据,采用线性相关分析和结构方程模型,深入分析了自然与人为因素对EEQ演变的作用机制,并针对EEQ下降提出了应对措施。结果表明,EEQ指数随海拔升高而先增后减,拐点在2000-2200 m之间,这与气温条件及人类活动强度的海拔差异紧密相关。过去20年间,湖北省EEQ整体呈先升后降的趋势,区域差异显著,西部山区EEQ上升,中南部江汉平原则下降。结构方程模型进一步指出,西部山区EEQ受气温正向影响,而江汉平原EEQ则受人类足迹的负向影响与太阳辐射的正向影响的共同作用,模型解释度分别高达98%和82%。基于2011-2020年EEQ趋势与Hurst指数分析,预测西部山区EEQ将持续上升,江汉平原则可能继续下降。为此,提出加强生态环境保护,推动植被恢复,以应对EEQ下降的潜在风险。该研究不仅丰富了EEQ演变机制的理论研究,也为湖北省及类似区域的生态保护和经济可持续发展提供了实践指导和决策依据。其创新在于综合多源数据与多种分析方法,全面剖析EEQ演变的复杂成因,为生态环境研究提供了方法论参考。
Understanding the spatiotemporal evolution of eco-environmental quality(EEQ)is essential for evaluating the combined impacts of climate change and human activities on ecosystems.A thorough analysis of the spatiotemporal characteristics and driving factors of EEQ in Hubei province can offer valuable insights for developing regional ecological protection and vegetation restoration strategies.This study focuses on the synergistic effects of altitude,climate,and human footprint on EEQ evolution.Using EEQ and land use data from 2001 to 2020,along with Theil-Sen Median and Mann-Kendall analyses,the study identifies EEQ evolution patterns and forecasts future trends.Furthermore,by integrating multidimensional data—including altitude,climate,and human footprint—and employing linear correlation analysis and structural equation modeling,the research investigates how natural and anthropogenic factors influence EEQ and suggests strategies to address its decline.The findings revealed that EEQ index increases with altitude until it reaches a turning point between 2000 and 2200 m,after which it declines.This pattern was strongly linked to variations in temperature and the intensity of human activities at different altitudes.Over the past 20 years,EEQ in Hubei province has generally followed a trend of initial improvement followed by decline,with significant regional differences.Specifically,EEQ has increased in the western mountainous areas but has decreased in the central-southern Jianghan plain.The structural equation model further showed that temperature positively influences EEQ in the western mountainous areas,while in the Jianghan plain,EEQ is negatively impacted by human footprint and positively influenced by solar radiation,with the model explaining 98%and 82%of the variance in these regions,respectively.An analysis of EEQ trends from 2011 to 2020,combined with the Hurst index,suggests that EEQ in the western mountainous areas will continue to improve,while it may continue to decline in the Jianghan plain.In response,the study recommends enhancing ecological protection and promoting vegetation restoration to mitigate the risks associated with declining EEQ.This research not only advances the theoretical understanding of EEQ evolution mechanisms but also provides practical guidance and decision-making support for ecological conservation and sustainable economic development in Hubei province and similar regions.The study's innovation lies in its comprehensive integration of multi-source data and diverse analytical methods to thoroughly analyze the complex factors driving EEQ evolution.This approach provides a valuable methodological reference for future research on ecological environments.
作者
梁茂厂
郭晓华
张影
马雨萌
陈弈铭
龚复俊
LIANG Maochang;GUO Xiaohua;ZHANG Ying;MA Yumeng;CHEN Yiming;GONG Fujun(College of Horticulture and Gardening,Yangtze University,Jingzhou 434025,P.R.China;Engineering Research Center of Ecology and Agricultural Use of Wetland,Ministry of Education/Hubei Key Laboratory of Waterlogging Disaster and Agricultural Use of Wetland(Yangtze University),Jingzhou 434025,P.R.China;Wuhan Botanical Garden,Chinese Academy of Sciences,Wuhan 430074,P.R.China)
出处
《生态环境学报》
CSCD
北大核心
2024年第10期1634-1647,共14页
Ecology and Environmental Sciences
基金
国家自然科学基金青年项目(51908063)
长江中下游湿地生态与农业利用教育部工程研究中心开放基金项目(KF202110)。
关键词
生态环境质量
时间序列趋势
结构方程模型
植被覆盖
海拔
人类活动
气候条件
eco-environmental quality
time-series trend
structural equation model
vegetation cover
altitude
human activities
climatic conditions
