基于InVEST-PLUS模型的碳储量空间关联性及预测——以广东省为例

林彤; 杨木壮; 吴大放; 刘锋; 杨金海; 王颖佳

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中国环境科学 ›› 2022, Vol. 42 ›› Issue (10) : 4827-4839.

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基于InVEST-PLUS模型的碳储量空间关联性及预测——以广东省为例

林彤, 杨木壮, 吴大放, 刘锋, 杨金海, 王颖佳

作者信息 +

Spatial correlation and prediction of land use carbon storage based on the InVEST-PLUS model- A case study in Guangdong Province

LIN Tong, YANG Mu-zhuang, WU Da-fang, LIU Feng, YANG Jin-hai, WANG Ying-jia

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摘要

构建土地利用碳储量数据库，基于InVEST模型Carbon模块，得到广东省1990~2020年碳储量时空分布情况.用Moran’s I指数和Getis-Ord Gi^*分析格网尺度下碳储量时空分布特征，用Anselin Local Moran’s I得到LISA集聚图.然后运用PLUS模型和14个土地利用驱动因子预测2050年土地利用及其碳储量分布.结果表明，土地利用变化直接影响区域碳储量高低，林地、草地等具有生态服务功能地类碳密度最高，分别是188.44，329.34Mg/hm².碳储量空间格局整体呈现出中部低、北部高、东西中等的特点.碳储量空间分布特征与土地利用特征一致，碳储量显著高值集聚区域分布在建设用地少、生态用地多且连片的粤北地区，显著低值区域分布在国土开发强度和生态用地破碎化程度高的珠三角地带.在自然发展情景下，到2050年广东省土地利用碳储量将减少4327.21万Mg，随着国土空间进一步开发，环珠江口沿岸城市碳储量持续下降.增加植被生态系统碳储量，是实现碳中和的重要手段之一.要继续维持粤北山区生态保护屏障的重要地位，减缓珠三角城市土地开发强度，提高建设用地集约节约能力，形成平衡协调的土地利用和碳储量格局.

Abstract

This paper calculated the spatial and temporal distribution of carbon storage in Guangdong Province from 1990 to 2020 based on the land use carbon storage database and the Carbon module of the InVEST model. Morans' I index and Getis-Ord Gi^* were used to analyze the spatial and temporal distribution characteristics of carbon storage at the grid scale. Then, the LISA agglomeration maps were obtained by calculating Anselin Local Moran's I. Finally, the PLUS model and 14 land use drivers are applied to predict the land use and its carbon storage distribution in 2050. The results showed that land use changes significantly affected the regional carbon storage and the highest carbon density was found in forest land and grassland, 188.44 and 329.34Mg/hm², respectively.. The spatial pattern of carbon stocks is characterized by "low in the central part, high in the north, and medium in the east and west". The spatial distribution of carbon storage is consistent with the distribution of land use. The areas with significantly high values of carbon storage were located in the northern part of Guangdong Province, where there were few construction land and more concentrated ecological land. The areas with significantly low values were located in the Pearl River Delta region where the intensity of land development and ecological land fragmentation were higher. Under the natural development scenario, the carbon storage of land use in Guangdong Province will be reduced by 43.2721 million Mg by 2050. With the further development of land space, the carbon stock of coastal cities around the Pearl River Estuary will continue to decline. Therefore, increasing carbon storage in vegetation ecosystem is one of the most important ways to achieve carbon neutrality. We should continue to maintain the important position of the ecological protection barrier in the mountainous areas of northern Guangdong, slow down the intensity of urban land development in the Pearl River Delta, improve the ability to conserve land for construction, and form a balanced and coordinated pattern of land use and carbon storage.

导出引用

林彤, 杨木壮, 吴大放, 刘锋, 杨金海, 王颖佳. 基于InVEST-PLUS模型的碳储量空间关联性及预测——以广东省为例[J]. 中国环境科学. 2022, 42(10): 4827-4839

LIN Tong, YANG Mu-zhuang, WU Da-fang, LIU Feng, YANG Jin-hai, WANG Ying-jia. Spatial correlation and prediction of land use carbon storage based on the InVEST-PLUS model- A case study in Guangdong Province[J]. China Environmental Science. 2022, 42(10): 4827-4839

中图分类号： X321

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基金

广东省自然科学资金资助项目（2017A030313240）；2020年广东省研究生教育创新计划项目（2020JGXM085）；教育部人文社科研究规划项目（14YJA630083）；广东省哲学社会科学“十三五”规划2020年度学科共建项目（GD20XYJ32）；广东省教育科学“十三五”规划2020年度研究项目（2020GXJK199）；广东省高等学校教学管理学会2021年度课程思政建设项目（X-KCSZ2021158）