• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

[基于PLUS-InVEST耦合模型的京津风沙源区碳储量变化及多情景预测]

[Changes in Carbon Storage and Multi-Scenario Prediction in the Beijing-Tianjin Sandstorm Source Region Using a Coupled PLUS-InVEST Model].

作者信息

Huang Yan, Liu Xiao-Man, Gao Bing-Bing, Hou Peng, Zhou Hai-Li

机构信息

Satellite Application Center for Ecology and Environment, MEE, Beijing 100094, China.

Chinese Research Academy of Environmental Sciences, Beijing 100012, China.

出版信息

Huan Jing Ke Xue. 2025 Sep 8;46(9):5741-5751. doi: 10.13227/j.hjkx.202408114.

DOI:10.13227/j.hjkx.202408114
PMID:40962765
Abstract

Quantitative assessment and prediction of the impacts of regional land use changes on ecosystem carbon storage have profound practical significance for achieving sustainable regional development. Focusing on the Beijing-Tianjin Sandstorm Source Region (BTRSSR), a key target area of the Grain for Green Program, this study leveraged land use data extending from 2000 to 2020. We first analyzed the spatiotemporal patterns of land use changes within this period. Subsequently, the InVEST model was employed to discern the spatiotemporal distribution and dynamics of carbon storage. Furthermore, the Markov-PLUS model was applied to forecast the land use patterns and corresponding changes in carbon storage for the year 2040 under the three scenarios of natural development, urban development, and ecological conservation. The key findings are as follows: ① Land Use Dynamics (2000-2020): The BTRSSR showed an expansion of forestland, grassland, shrubland, and construction land, accompanied by a contraction in water bodies, cultivated land, and unused land. Notably, cultivated land primarily transitioned to grassland, forestland, and construction land, while unused land primarily converted to grassland. ② Carbon Storage Trends (2000-2020): Overall, the region's carbon storage exhibited an upward trend, with a total increase of 7.92 Tg. Spatially, a gradual decrease in carbon storage was observed from southeast to northwest. The augmentation of forestland and grassland emerged as the primary driver behind this increase in regional carbon storage. ③ Future Projections (2040): With the exception of the urban development scenario, both the natural development and ecological conservation scenarios project further increases in future carbon storage in the BTRSSR. Notably, under the ecological conservation scenario, the projected total carbon storage reaches 4 243.65 Tg, surpassing that of the natural development scenario by 8.04 Tg. This underscores the assertion that the Grain for Green Program effectively enhances ecosystem carbon storage, with the ecological conservation scenario identified as the optimal development pathway for the study area. These findings highlight the critical role of land use management policies, particularly those promoting ecological restoration, in enhancing regional carbon sequestration and fostering sustainable development.

摘要

定量评估和预测区域土地利用变化对生态系统碳储量的影响,对于实现区域可持续发展具有深远的现实意义。本研究聚焦于京津风沙源治理工程的重点目标区域——京津风沙源治理区(BTRSSR),利用了2000年至2020年的土地利用数据。我们首先分析了该时期内土地利用变化的时空格局。随后,运用InVEST模型来识别碳储量的时空分布和动态变化。此外,应用马尔可夫- PLUS模型预测了在自然发展、城市发展和生态保护三种情景下2040年的土地利用格局及相应的碳储量变化。主要研究结果如下:①土地利用动态(2000 - 2020年):京津风沙源治理区林地、草地、灌木林地和建设用地面积扩大,水体、耕地和未利用地面积减少。值得注意的是,耕地主要转变为草地、林地和建设用地,而未利用地主要转变为草地。②碳储量趋势(2000 - 2020年):总体而言,该区域碳储量呈上升趋势,共增加了7.92太克。在空间上,从东南向西北碳储量逐渐减少。林地和草地面积的增加是区域碳储量增加的主要驱动因素。③未来预测(2040年):除城市发展情景外,自然发展和生态保护情景均预测京津风沙源治理区未来碳储量将进一步增加。值得注意的是,在生态保护情景下,预计总碳储量将达到4243.65太克,比自然发展情景高出8.04太克。这强调了退耕还林还草工程有效增加了生态系统碳储量,生态保护情景被确定为研究区域的最优发展路径。这些研究结果突出了土地利用管理政策,特别是那些促进生态恢复的政策,在增强区域碳固存和促进可持续发展方面的关键作用。

相似文献

1
[Changes in Carbon Storage and Multi-Scenario Prediction in the Beijing-Tianjin Sandstorm Source Region Using a Coupled PLUS-InVEST Model].[基于PLUS-InVEST耦合模型的京津风沙源区碳储量变化及多情景预测]
Huan Jing Ke Xue. 2025 Sep 8;46(9):5741-5751. doi: 10.13227/j.hjkx.202408114.
2
[Spatial and Temporal Evolution and Prediction of Carbon Storage in Dali County Based on InVEST-PLUS Model].基于InVEST-PLUS模型的大荔县碳储量时空演变与预测
Huan Jing Ke Xue. 2025 Sep 8;46(9):5765-5776. doi: 10.13227/j.hjkx.202405321.
3
Using PLUS-InVEST-OPGD model to explore spatiotemporal variation of ecosystem carbon storage and its drivers in Jinsha river basin, China.利用PLUS-InVEST-OPGD模型探究中国金沙江流域生态系统碳储量的时空变化及其驱动因素。
PeerJ. 2025 Jul 28;13:e19681. doi: 10.7717/peerj.19681. eCollection 2025.
4
[Exploring the Impact of Future Multi-scenario Land Use Change on Henan Province Regional Carbon Storage].[探索未来多情景土地利用变化对河南省区域碳储量的影响]
Huan Jing Ke Xue. 2025 Jun 8;46(6):3830-3845. doi: 10.13227/j.hjkx.202405168.
5
The impact of the Grain-for-Green Programme on carbon storage in the Upper Yangtze River Basin based on the PLUS-InVEST model.基于PLUS-InVEST模型的长江上游流域退耕还林工程对碳储量的影响
Carbon Balance Manag. 2025 Jul 30;20(1):24. doi: 10.1186/s13021-025-00315-2.
6
[Ecosystem Services Assessment and Network Optimization Under Multiple Scenario Simulations in the Karst Area of Southeast Yunnan].滇东南喀斯特地区多情景模拟下的生态系统服务评估与网络优化
Huan Jing Ke Xue. 2025 Jul 8;46(7):4615-4627. doi: 10.13227/j.hjkx.202406123.
7
[Assessing the Economic Value of Carbon Storage and Land Use Changes in Wuhan Based on the FLUS and InVEST Model].基于FLUS和InVEST模型评估武汉碳储量与土地利用变化的经济价值
Huan Jing Ke Xue. 2025 Sep 8;46(9):5777-5787. doi: 10.13227/j.hjkx.202409345.
8
[Estimation of Carbon Storage and Economic Value of Ningdong Energy and Chemical Base Based on InVEST and CA-Markov Model].基于InVEST和CA-Markov模型的宁东能源化工基地碳储量及经济价值估算
Huan Jing Ke Xue. 2025 Jul 8;46(7):4416-4427. doi: 10.13227/j.hjkx.202406102.
9
[Multi-Scenario Simulation of Land Use Change in Chengyu Economic Zone and Its Influence on Carbon Reserves].成渝经济区土地利用变化的多情景模拟及其对碳储量的影响
Huan Jing Ke Xue. 2025 Sep 8;46(9):5718-5728. doi: 10.13227/j.hjkx.202407242.
10
[Spatial-temporal Evolution and Prediction of Carbon Reserves in Wanjiang River Basin with the InVEST-PLUS Model].基于InVEST-PLUS模型的皖江流域碳储量时空演变及预测
Huan Jing Ke Xue. 2025 Jun 8;46(6):3818-3829. doi: 10.13227/j.hjkx.202406063.