文献类型：期刊文献

英文题名：Effects of Urban Forest Types and Traits on Soil Organic Carbon Stock in Beijing

作者：Xu, Xinhui[1,2] Sun, Zhenkai[1,2] Hao, Zezhou[1,2] Bian, Qi[1,2] Wei, Kaiyue[1,2] Wang, Cheng[1,2]

第一作者：Xu, Xinhui

通信作者：Sun, ZK[1];Sun, ZK[2]

机构：[1]Chinese Acad Forestry, Res Inst Forestry, Beijing 100091, Peoples R China;[2]Natl Forestry & Grassland Adm, Key Lab Tree Breeding & Cultivat & Urban Forest R, Beijing 100091, Peoples R China

年份：2021

卷号：12

期号：4

外文期刊名：FORESTS

收录：;EI(收录号：20211510206525);Scopus(收录号：2-s2.0-85103907571);WOS:【SCI-EXPANDED(收录号:WOS:000643011500001)】；

基金：This work was funded by National Non-Profit Research Institutions of the Chinese Academy of Forestry (grant numbers: CAFYBB2020ZB008) and by the China Scholarship Council (CSC) (grant numbers: 201903270038).

语种：英文

外文关键词：forest types; forest traits; partial least squares regression; soil organic carbon; urban forest

摘要：Forests can affect soil organic carbon (SOC) quality and distribution through forest types and traits. However, much less is known about the influence of urban forests on SOC, especially in the effects of different forest types, such as coniferous and broadleaved forests. Our objectives were to assess the effects of urban forest types on the variability of SOC content (SOC concentration (SOCC) and SOC density (SOCD)) and determine the key forest traits influencing SOC. Data from 168 urban forest plots of coniferous or broadleaved forests located in the Beijing urban area were used to predict the effects of forest types and traits on SOC in three different soil layers, 0-10 cm, 10-20 cm, and 20-30 cm. The analysis of variance and multiple comparisons were used to test the differences in SOC between forest types or layers. Partial least squares regression (PLSR) was used to explain the influence of forest traits on SOC and select the significant predictors. Our results showed that in urban forests, the SOCC and SOCD values of the coniferous forest group were both significantly higher than those of the broadleaved group. The SOCC of the surface soil was significantly higher than those of the following two deep layers. In PLSR models, 42.07% of the SOCC variance and 35.83% of the SOCD variance were explained by forest traits. Diameter at breast height was selected as the best predictor variable by comparing variable importance in projection (VIP) scores in the models. The results suggest that forest types and traits could be used as an optional approach to assess the organic carbon stock in urban forest soils. This study found substantial effects of urban forest types and traits on soil organic carbon sequestration, which provides important data support for urban forest planning and management.