摘要
以江苏省常州市作为研究区域,基于2000—2020年的遥感影像,综合运用FLUS模型及生态系统服务价值(ESV)评估方法,系统模拟研究在自然发展、耕地保护和生态保护3种不同情景下2035年常州市土地利用变化对ESV的影响。结果表明,2000—2020年常州市土地利用动态度呈下降趋势,其中转出量最高的是耕地,转入量最高的是建设用地;受土地利用变化的影响,2000—2020年常州市ESV整体呈先增加后减少的趋势,水域是影响生态系统服务价值变化的主要土地利用类型,调节服务和支持服务是常州市主要的两大生态系统服务功能。常州市ESV在不同情景模拟下差异较大,其中,自然发展情景下ESV最低,生态保护情景下ESV最高。最后提出生态保护情景是优化区域土地利用结构、维持生态系统服务价值的最佳发展模式,应作为常州市未来土地利用的长期发展战略。
Taking Changzhou City of Jiangsu Province as the study area,based on remote sensing images from 2000 to 2020,the FLUS model and the ecosystem service value(ESV)assessment method were used to systematically study the impacts of land use changes on ESV in Changzhou City in 2035 under three different scenarios of natural development,cultivated land preservation and ecological protection.The results showed that the dynamic degree of land use in Changzhou City showed a downward trend from 2000 to 2020.Among them,the highest amount of transferred out was cultivated land,and the highest amount of transferred in was construction land.The ESV in Changzhou City from 2000 to 2020 demonstrated a trend of initially increasing and then decreasing,owing to the impact of land use changes.The water area exerted the primary impact on the change of ESV,and regulatory and support services were the two main ecosystem service functions in Changzhou City.The ESV of Changzhou City exhibited significant variations under different scenario simulations,with the natural development scenario resulting in the lowest ESV and the ecological protection scenario resulting in the highest ESV.Finally,it was recommended that the ecological protection scenario was the best development model to optimize the regional land use structure and maintain the value of ecosystem services,which should be used as a long-term development strategy for future land use in Changzhou City.
作者
何宇辰
景晓栋
孙媛媛
HE Yu-chen;JING Xiao-dong;SUN Yuan-yuan(Business School,Hohai University,Nanjing 211100,China;Yangtze Institute for Conservation and Development,Nanjing 210098,China)
出处
《湖北农业科学》
2024年第11期47-56,78,共11页
Hubei Agricultural Sciences
基金
江苏省研究生科研与实践创新计划项目(KYCX22_0688)。