| 长三角地区土地利用与生态系统服务时空变化多情景模拟 |
| 摘要点击 474 全文点击 7 投稿时间：2025-05-31 修订日期：2025-09-24 |
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| 中文关键词 InVEST模型 生态系统服务功能（ES） PLUS模型 长三角地区 未来情景预测 |
| 英文关键词 InVEST model ecosystem services（ES） PLUS model Yangtze River Delta future scenario prediction |
| DOI 10.13227/j.hjkx.202505359 |
| 作者 | 单位 | E-mail | | 张维栋 | 安徽农业大学资源与环境学院, 合肥 230036
安徽农业大学林学与园林学院, 合肥 230036 | 2768147016@qq.com | | 董斌 | 安徽农业大学资源与环境学院, 合肥 230036 | dongbin@ahau.edu.cn | | 朱培桢 | 安徽农业大学资源与环境学院, 合肥 230036
安徽农业大学经济管理学院, 合肥 230036 | | | 彭聪阁 | 安徽农业大学资源与环境学院, 合肥 230036
安徽农业大学林学与园林学院, 合肥 230036 | | | 王昊 | 安徽农业大学资源与环境学院, 合肥 230036
安徽农业大学林学与园林学院, 合肥 230036 | | | 屈建伸 | 安徽农业大学资源与环境学院, 合肥 230036
安徽农业大学林学与园林学院, 合肥 230036 | | | 韩月侠 | 安徽农业大学资源与环境学院, 合肥 230036
安徽农业大学经济管理学院, 合肥 230036 | |
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| 中文摘要 |
| 生态系统服务功能在新时代高质量生态发展背景下具有重要的研究意义. 以长三角地区为研究区域，基于PLUS-InVEST模型评估1990~2020年研究区内5项生态系统服务功能，利用地理探测器模型识别其主导其空间分异的驱动因子. 在土地利用预测的基础上模拟了在不同情景下研究区2030年生态系统服务功能的空间分布. 结果表明：①1990~2020年间，长三角地区的碳储量、生境质量和土壤保持表现为南高北低，粮食生产功能呈现南部和西南部较高，北部较低的分布. 产水量则主要集中分布在南部山区. ②高程与坡度是碳储量、生境质量、土壤保持和粮食生产变化的主导驱动因素. 产水量功能方面，气候因素起主导作用，年降水量的空间分布能够解释产水量的空间分异. ③与2020年相比，自然发展情景下，研究区的产水量、粮食生产和生境质量增加，碳储量和土壤保持量下降；在生态保护情景下，5项生态系统服务功能均有所提升；而在耕地保护情景下，碳储量、粮食生产和土壤保持量有所增加，产水量和生境质量下降. 研究结果可为长三角地区生态保护及管理提供科学参考. |
| 英文摘要 |
| Ecosystem services（ES） play a critical role in the context of high-quality ecological development in the new era. This study focuses on the Yangtze River Delta Region as the study area， employing the InVEST model to assess four key ecosystem services from 1990 to 2020， analyzing their spatiotemporal evolution patterns. Using the geographical detector model， we identify the dominant driving factors behind the spatial heterogeneity of these services. Additionally， GeoDa software is applied to conduct an in-depth analysis of the trade-offs and synergies among different ecosystem services. Finally， the PLUS model is utilized to simulate and predict the spatial distribution patterns of ecosystem services in 2030 under various development scenarios. The results showed： ① From 1990 to 2020， in the Yangtze River Delta Region， carbon storage and habitat quality were generally higher in the south and lower in the north and central areas. Food production， conversely， was higher in the north and lower in the south. Both habitat quality and soil conservation exhibited a distribution pattern with higher values in the south and southwest and lower values in the north. Water yield was primarily concentrated in the mountainous areas of Zhejiang and southern Anhui. ② Topography and elevation were the key factors influencing changes in carbon storage and soil conservation function， and population density was the key factor influencing changes in habitat quality， while annual precipitation was the primary driver influencing changes in water yield. Apart from topographic factors， precipitation and population density were the key factors influencing grain production. ③ Compared to the baseline year of 2020， the study area exhibited the following changes in ecosystem services under different scenarios： Under the natural development scenario， water yield and habitat quality increased， while carbon storage and soil retention decreased. Under the ecological protection scenario， carbon storage， water yield， and habitat quality all showed improvement. Finally， under the cropland protection scenario， carbon storage and soil retention increased， whereas water yield and habitat quality declined. This study provides valuable insights into the complex dynamics of ecosystem services in rapidly urbanizing regions， offering a scientific basis for regional ecological planning and sustainable development strategies. |
