地理科学进展 ›› 2022, Vol. 41 ›› Issue (12): 2327-2341.doi: 10.18306/dlkxjz.2022.12.011
周沛芳1,2,3(), 周涛1,2,3,*(
), 刘霞1,2,3, 张亚杰1,2,3, 徐艺心1,2,3, 罗惠1,2,3, 于佩鑫1,2,3, 张靖宙1,2,3
收稿日期:
2022-03-07
修回日期:
2022-10-25
出版日期:
2022-12-28
发布日期:
2022-12-31
通讯作者:
*周涛(1972— ),男,湖南冷水江人,教授,博士生导师,主要研究方向为全球变化与植被响应、陆地生态系统碳循环。E-mail: tzhou@bnu.edu.cn作者简介:
周沛芳(1997— ),湖南常德人,硕士生,主要研究方向为气候变化及生态环境响应。E-mail: pfzhou@mail.bnu.edu.cn
基金资助:
ZHOU Peifang1,2,3(), ZHOU Tao1,2,3,*(
), LIU Xia1,2,3, ZHANG Yajie1,2,3, XU Yixin1,2,3, LUO Hui1,2,3, YU Peixin1,2,3, ZHANG Jingzhou1,2,3
Received:
2022-03-07
Revised:
2022-10-25
Online:
2022-12-28
Published:
2022-12-31
Supported by:
摘要:
土壤有机碳对区域碳平衡起着关键性的作用,量化其空间格局及动态变化是准确评估生态系统碳汇潜力的基础。然而,不同土壤有机碳估算方法和不同样本得出的结果存在非常大的差异和不确定性,尤其是地形复杂、对气候变化敏感的青藏高原地区。为定量评估不同方法估算的土壤有机碳密度空间分布格局在青藏高原地区的差异,论文以青海省为研究区,收集整理了青海省806个土壤有机碳密度采样点数据,基于气候、植被、地形和土壤等多种解释变量,采用逐步回归、反距离权重插值、普通克里格插值和随机森林模型4种不同的方法,对青海省表层(0~30 cm)土壤有机碳密度空间分布及其影响因素进行了探究。结果表明,归一化植被指数、光合有效辐射、总氮、年均温、海拔、年降水量和净初级生产力是土壤有机碳密度估算的重要变量;尽管4种方法所估算的青海省土壤有机碳密度的均值较为接近,处于5.14~5.62 kg C·m-2之间,但其变化范围存在较大差异,分别为0.17~23.25、0.34~46.61、0.56~35.08和0.62~24.85 kg C·m-2;4种方法模拟结果的均方根误差分别为3.93、3.37、3.48和3.19 kg C·m-2,平均标准差分别为0.12、0.51、0.61和0.27 kg C·m-2,其中随机森林模型的结果较为稳定且精度较高,也更能准确反映青海省土壤有机碳的空间分布格局。比较发现,现有的土壤有机碳产品(SoilGrids250m 2.0和HWSD v1.2)在反映青海省土壤有机碳的分布方面还存在较大差异,相对而言,SoilGrids250m 2.0产品的土壤有机碳和随机森林模拟结果比较接近。
周沛芳, 周涛, 刘霞, 张亚杰, 徐艺心, 罗惠, 于佩鑫, 张靖宙. 青海省土壤有机碳估算及其不确定性分析[J]. 地理科学进展, 2022, 41(12): 2327-2341.
ZHOU Peifang, ZHOU Tao, LIU Xia, ZHANG Yajie, XU Yixin, LUO Hui, YU Peixin, ZHANG Jingzhou. Estimation of soil organic carbon and its uncertainty in Qinghai Province[J]. PROGRESS IN GEOGRAPHY, 2022, 41(12): 2327-2341.
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