详细信息
The Effect of Stand Density, Biodiversity, and Spatial Structure on Stand Basal Area Increment in Natural Spruce-Fir-Broadleaf Mixed Forests ( SCI-EXPANDED收录 EI收录) 被引量:10
文献类型:期刊文献
英文题名:The Effect of Stand Density, Biodiversity, and Spatial Structure on Stand Basal Area Increment in Natural Spruce-Fir-Broadleaf Mixed Forests
作者:Liu, Di[1,2] Zhou, Chaofan[1,2] He, Xiao[1,2] Zhang, Xiaohong[1,2] Feng, Linyan[1,2] Zhang, Huiru[2,3]
第一作者:刘丹;Liu, Di
通信作者:Zhang, HR[1];Zhang, HR[2]
机构:[1]Chinese Acad Forestry, Res Inst Forest Resource Informat Tech, Beijing 100091, Peoples R China;[2]Natl Forestry & Grassland Adm, Key Lab Forest Management & Growth Modeling, Beijing 100091, Peoples R China;[3]Chinese Acad Forestry, Expt Ctr Forestry North China, 1 Shuizha West Rd, Beijing 102300, Peoples R China
年份:2022
卷号:13
期号:2
外文期刊名:FORESTS
收录:;EI(收录号:20220511575951);Scopus(收录号:2-s2.0-85123783793);WOS:【SCI-EXPANDED(收录号:WOS:000762798400001)】;
基金:FundingThis research was funded by Thirteenth Five-year Plan Pioneering project of the High Technology Plan of the National Department of Technology (No.2017YFC0504101).
语种:英文
外文关键词:spatial structure parameters; stand density; biodiversity; random forests; BAI model
摘要:Forest trees exhibit a large variation in the basal area increment (BAI), and the variation is attributed to the stand density, biodiversity, and stand spatial structure. Studying and quantifying the effect of these above variables on tree growth is vital for future forest management. However, the stand spatial structure based on neighboring trees has rarely been considered, especially in the mixed forests. This study adopted the random-forest (RF) algorithm to model and interpret BAI based on stand density, biodiversity, and spatial structure. Fourteen independent variables, including two stand density predictors, four biodiversity predictors, and eight spatial structure predictors, were evaluated. The RF model was trained for the whole stand, three tree species groups (gap, neutral, and shade_tolerant), and two tree species (spruce and fir). A 10-fold blocked cross-validation was then used to optimize the hyper-parameters and evaluate the models. The squared correlation coefficients (R-2) for the six groups were 0.233 for the whole stand, 0.575 for fir, 0.609 for shade_tolerant, 0.622 for neutral, 0.722 for gap, and 0.730 for spruce. The Stand Density Index (SDI) was the most-important predictor, suggesting that BAI is primarily restricted by competition. BAI and species biodiversity were positively correlated for the whole stand. The stands were expected to be randomly distributed based on the relationship between the uniform angle index (W) and growth. The relationship between dominance (U) and BAI indicated that small trees should be planted around the light-demanding tree species and vice versa. Of note, these findings emphasize the need to consider the three types of variables in mixed forests, especially the spatial structure factors. This study may help make significant advances in species composition, spatial arrangement, and the sustainable development of mixed forests.
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