中国生态农业学报（中英文）2023，Vol.31Issue(12)：1943-1952,10.DOI:10.12357/cjea.20230622
基于DPSIR模型的乡村生态景观生物多样性预警
Biodiversity early warning of rural ecological landscape based on DPSIR model
摘要
Abstract
In view of the potential threats to biodiversity in the process of rural revitalization and the needs of conservation and man-agement,this study organically combined the theories and methods of biodiversity with society,economy,population,etc.,and built the early warning index system of biodiversity in rural ecological landscape based on the DPSIR(Driving Force-Pressure-State-Impact-Response)model.Based on the principles of scientificity,relevance,practicality and comparability,the index system reflects the impact of human interference,global change,major disasters,measures and inputs taken by human to maintain the biodiversity of rural ecological landscape,and other factors on rural biodiversity,including 12 factors and 25 indicators of the driving force,pressure,state,impact and response of biodiversity.The mean square deviation method was used to determine the weight value of each index,divide the evaluation level.And the comprehensive index method was used to wam the biodiversity of the rural ecological landscape.The rural biodiversity in this study comprehensively considered the"Ecology,Production,Living"functions of the countryside.Therefore,the species of wild animals and plants,crop species,and rural green plants were all included in the calculation of the biod-iversity index.This research method has been applied in the Paifang Community of Nanjing to give early warning to the high risk area.This study provides a new idea and method for biodiversity protection and evaluation in the revitalization and planning of green livable countryside,and it is of great significance to build a beautiful countryside with green harmony.关键词
乡村景观/生物多样性预警/DPSIR模型/指标体系Key words
Rural landscape/Early warning of biodiversity/DPSIR model/Indicator system分类
农业科技引用本文复制引用
徐文婷,谢宗强,葛结林,徐凯,熊高明,毛江涛..基于DPSIR模型的乡村生态景观生物多样性预警[J].中国生态农业学报（中英文）,2023,31(12):1943-1952,10.基金项目
国家重点研发计划项目(2019YFD1100403)资助 This study was supported by the National Key Research and Development Project of China(2019YFD1100403). （2019YFD1100403）
