Characterizing the effects of climate change on short-term post-disturbance forest recovery in southern China from Landsat time-series observations(1988-2016)
作者机构：College of ForestryNanjing Forestry UniversityNanjing210037China Co-Innovation Center for Sustainable Forestry in Southern ChinaNanjing Forestry UniversityNanjing210037China
出 版 物：《Frontiers of Earth Science》 (地球科学前沿（英文版）)
年 卷 期：2020年第14卷第4期
页 面：816-827页
核心收录：
学科分类：07[理学] 070601[理学-气象学] 0708[理学-地球物理学] 0706[理学-大气科学] 0704[理学-天文学]
基 金：This work was jointly supported by the National Natural Science Foundation of China(Grant Nos.31971577 and 31670552) the Biodiversity Investigation,Observation and Assessment Program sponsored by the Ministry of Ecology and Environment of China(2019-2023) the China Postdoctoral Science Foundation(No.2019M651842) the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)
主 题：climate change forest disturbance forest recovery vegetation change tracker
摘 要：Climate change,a recognized critical environmental issue,plays an important role in regulating the structure and function of forest ecosystems by altering forest disturbance and recovery *** research focused on exploring the statistical relationships between meteorological and topographic variables and the recovery characteristics following disturbance of plantation forests in southern *** used long-term Landsat images and the vegetation change tracker algorithm to map forest disturbance and recovery events in the study area from 1988 to *** multiple linear regression(MLR),random forest(RF)regression,and support vector machine(SVM)regression were used in conjunction with climate variables and topographic factors to model short-term forest recovery using the normalized difference vegetation index(NDVI).The results demonstrated that the regenerating forests were sensitive to the variation in *** fitted results suggested that the relationship between the NDVI values of the forest areas and the post-disturbance climatic and topographic factors differed in regression *** RF regression yielded the best performance with an R2 value of 0.7348 for the validation *** indicated that slope and temperature,especially high temperatures,had substantial effects on post-disturbance vegetation recovery in southern *** other mid-subtropical monsoon regions with intense light and heat and abundant rainfall,the information will also contribute to appropriate decisions for forest managers on forest recovery ***,it is essential to explore the relationships between forest recovery and climate change of different vegetation types or species for more accurate and targeted forest recovery strategies.
维普期刊数据库