基于DPSIR模型的县域生物多样性综合评估——以江苏省生物多样性本底调查试点县域为例

蔡琨; 彭智奇; 沈明明; 孙长海; 王备新

引用本文:	蔡琨,彭智奇,沈明明,孙长海,王备新.基于DPSIR模型的县域生物多样性综合评估——以江苏省生物多样性本底调查试点县域为例[J].环境监控与预警,2024,16(5):157-165
	CAI Kun,PENG Zhiqi,SHEN Mingming,SUN Changhai,WANG Beixin.Evaluation of Biodiversity at the County Level Using DPSIR Model： A Case Study on Pilot Biodiversity Survey Counties in Jiangsu Province[J].Environmental Monitoring and Forewarning,2024,16(5):157-165

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基于DPSIR模型的县域生物多样性综合评估——以江苏省生物多样性本底调查试点县域为例
蔡琨¹，彭智奇²，沈明明²，孙长海²，王备新^2*
1.江苏省环境监测中心，江苏南京 210019；2.南京农业大学植物保护学院，江苏南京 210095

摘要:

目前考虑生物多样性的多维评估及其变化的多驱动因素和长期动态模拟预测等研究相对缺乏。鉴于系统性和多层次分析等优点，“驱动力—压力—状态—影响—响应”（DPSIR）框架模型是当前国际上重要的生物多样性综合评估方法。然而，由于数据不足，县域层面的指标构建及赋权仍面临挑战。以2017—2019年江苏省21个生物多样性本底调查试点县域的生物、社会、经济发展、环境等数据为研究对象，探讨适合县域生物多样性评估的DPSIR模型的指标构建和赋权。研究记录了4 324个物种（不包括浮游植物和浮游动物），其中陆生维管植物最多（1 817种），两栖动物最少（17种）。宜溧山区、滨海湿地和宁镇山脉的6个区县的DPSIR综合指数值要高于其他县域。模型5个因子的权重值依次为：影响、状态、响应、驱动力和压力。模型识别出的5个高权重指标依次为自然保护区面积比、底栖动物物种数、森林面积比、湿地面积比、城镇化率。上述结果表明，保护森林与湿地生境、控制外来入侵物种和减轻城镇化影响是江苏省生物多样性保护未来工作的重点。研究结果为我国县域生物多样性科学评估、保护和管理工作提供了方法参考。

关键词: 生物多样性公约 DPSIR模型生物多样性综合评价指数县域尺度

DOI：DOI：10.3969/j.issn.1674-6732.2024.05.024

分类号:Q16

基金项目:江苏省环境监测科研基金资助项目（2326）；江苏省生态环境厅科技项目“江苏省生物多样性保护管理与示范研究”（2019002）

Evaluation of Biodiversity at the County Level Using DPSIR Model： A Case Study on Pilot Biodiversity Survey Counties in Jiangsu Province

CAI Kun¹， PENG Zhiqi²， SHEN Mingming²， SUN Changhai²， WANG Beixin^2*

1.Jiangsu Environmental Monitoring Center， Nanjing， Jiangsu 210019， China；2.College of Plant Protection， Nanjing Agricultural University， Nanjing， Jiangsu 210095，China

Abstract:

Currently， there is still a relative lack of research on the multidimensional assessment of biodiversity， the influence of multiple drivers， and long term dynamic simulation and prediction. Given its advantages in systematic and multidimensional analysis， DPSIR （Drive， Pressure， Status， Impact and Response） framework has become an important method for comprehensive international biodiversity assessment. However， the construction and weighting of indicators at the county level still face challenges due to the lack of data. In this paper we examines data from the biodiversity baseline surveys conducted in 21 biodiversity pilot survey counties in Jiangsu province from 2017 to 2019， focusing on biological， socio-economic development， and environmental data， to explore the construction and weighting of DPSIR indicators suitable for county-level biodiversity assessment. The study recorded 4，324 species （excluding phytoplankton and zooplankton）， with terrestrial vascular plants being the most abundant and reptiles the least. The DPSIR comprehensive index values for 6 counties in Yili mountain area， coastal wetlands and Ninzheng mountain area were higher than those of other counties. The weights of the five factors in the model are as follows： Impact， State， Response， Driver and Pressure. The five high-weight indicators identified by the DPSIR model are the percentage of natural reserve area， the ratio of forest， urbanization rate and the number of invasive alien species. Our results suggest that the key future efforts for biodiversity in Jiangsu province should focus on protecting forest and wetland habitats， controlling the invasion of non native species， and mitigating the impacts of urbanization. Our research provides methodological references for scientific assessment， conservation， and management of county-level biodiversity in China.

Key words: Convention on Biological Diversity （CBD） DPSIR model Comprehensive biodiversity evaluation index County scale