摘要
景观生态风险评估是识别生态系统脆弱地区并进行重点治理的必要手段。现有方法多采用土地利用变化数据进行生态风险分析,在多因素综合评估方面尚有欠缺,尤其是难以将气候变化和社会经济发展相结合预测气候变化情景下景观生态风险演变。针对此问题,耦合传统景观生态风险评估模型与深度学习模型,构建多因素影响下生态景观风险的预测模型,并模拟汉江流域景观生态风险变化。结果表明:(1)起点期(2000—2015年)情景下,汉江流域较高生态风险等级主要连片集中在丹江口下游地区;(2)SSP370和SSP585情景下均主要以较高生态风险等级为主,比较连片集中分布在丹江口以下区域;(3)SSP370和SSP585情景下汉江流域内高生态风险等级面积在2042年显著增加,其中SSP370情景下的高生态风险等级的面积平均每10 a增加14.58%。研究提出的多因素景观生态风险预测方法可为气候变化条件下流域的生态风险评估和相关生态补偿政策的制定提供借鉴。
Landscape ecological risk assessment plays a vital role in identifying vulnerable ecosystem areas for targeted management.While current methods primarily rely on land-use change data for ecological risk analysis,they often lack a comprehensive evaluation of multiple factors,especially the prediction of landscape ecological risk dynamics under climate change scenarios integrating climate variations and socio-economic trends.To tackle this issue,we constructed a predictive model for ecological landscape risk influenced by diverse factors by integrating traditional landscape ecological risk assessment models with deep learning technique,and further applied this model to simulating the change in landscape ecological risks of Hanjiang River Basin.Findings reveal that:1) during the baseline period(2000-2015),higher ecological risk levels predominantly clustered in the downstream of Danjiangkou reservoir;2) both SSP370 and SSP585 scenarios exhibited elevated ecological risk levels,particularly concentrated in the downstream of Danjiangkou;3) the high ecological risk area in Hanjiang River basin significantly expanded under the 2042 scenario for SSP370 and SSP585,with an average increase of 14.58% per decade under the SSP370 scenario.The proposed landscape ecological risk prediction approach in consideration of multiple factors serves as a valuable reference for ecological risk assessment in the basin under changing climatic conditions and the formulation of ecological compensation policies.
作者
吴启亮
郑航
刘悦忆
陈进
WU Qi-liang;ZHENG Hang;LIU Yue-yi;CHEN Jin(School of Environment and Civil Engineering,Dongguan University of Technology,Dongguan 523808,China;Changjiang River Scientific Research Institute,Changjiang Water Resources Commission,Wuhan 430010,China)
出处
《长江科学院院报》
CSCD
北大核心
2024年第4期78-88,共11页
Journal of Changjiang River Scientific Research Institute
基金
国家自然科学基金“长江水科学研究联合基金”项目(U2040206)
国家自然科学基金青年项目(51909035)
国家自然科学基金面上项目(52179009)。
