首页|基于多源遥感数据的广东省次生林地上生物量影响机制及增碳潜力

基于多源遥感数据的广东省次生林地上生物量影响机制及增碳潜力

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次生林中累积的地上生物量形成的巨大碳库,对于缓解气候变化具有重要作用.广东省空间异质性显著影响着次生林的碳汇速率,但其驱动因素尚不清楚,严重制约了未来碳汇能力的准确估算和预测.基于遥感技术在时空监测方面的优势,本研究利用地上生物量、次生林种植年份及气候等高时空分辨率遥感数据,量化了四大方面驱动因素对广东省次生林地上生物量累积速度和空间模式的影响,并结合情景分析预测了广东省未来的次生林增碳潜力.结果表明:整体上,林龄是影响广东省地上生物量累积的最重要因素,然而其他影响因素的贡献则具有较强的空间异质性.在珠三角地区,气候是第二大主要驱动因素,而在粤北、粤东和粤西地区则是地形地貌.土壤元素含量的影响在四个区域普遍较小.4个情景中,在储量最大情景下至2050年可最大程度增碳62.45±2.55 Tg C.本研究可为森林可持续管理及高质量发展提供科学参考.
Analysis of the Impact Mechanism of Secondary Forest Aboveground Biomass and Estimation of Carbon Sink Potential in Guangdong Province
Mitigating climate change is facilitated by the significant carbon reservoir formed through the accumu-lation of aboveground biomass in secondary forests.The spatial heterogeneity of Guangdong Province signifi-cantly affects the carbon sink rate of secondary forests.However,the driving factors remain unclear,which seri-ously constrains the accurate estimation and prediction of future carbon sink capacity.Based on the advantages of remote sensing technology in spatial and temporal monitoring,this study quantified the impacts of four major drivers on the rate of accumulation and spatial pattern of aboveground biomass in secondary forests in Guang-dong Province,using high spatial and temporal resolution remote sensing data on aboveground biomass,year of planting secondary forests,and climate,and combined with scenario analyses to predict the future potential of secondary forests in Guangdong Province in terms of carbon enhancement.The results showed that,overall,stand age was the most important factor influencing aboveground biomass accumulation in Guangdong Prov-ince,however,the contributions of other influencing factors were highly spatially heterogeneous.In the Pearl River Delta(PRD)region,climate was the second most important driver,while in the northern,eastern and western regions of Guangdong,it was topography and geomorphology.The effect of soil element content is gen-erally small in the four regions.Among the four scenarios,the maximum storage scenario could maximise car-bon gain of 62.45±2.55 Tg C by 2050.This study can provide scientific reference for sustainable forest manage-ment and high-quality development.

High-resolution remote sensingAboveground biomassMechanismsCarbon augmentationSpa-tial heterogeneity

毕崇远、李雪艳、苏泳娴、温兴平、吴建平、张超群

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昆明理工大学 国土资源工程学院,云南 昆明 650093

广东省科学院广州地理研究所,广东 广州 510070

中国科学院广州地球化学研究所,广东 广州 510640

中山大学 大气科学学院,广东珠海 519082

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高分辨率遥感 地上生物量 机制 增碳 空间异质性

2024

遥感技术与应用
中国科学院遥感联合中心

遥感技术与应用

CSTPCD北大核心
影响因子:0.961
ISSN:1004-0323
年,卷(期):2024.39(5)