杉木北带东区杉木人工林碳储量影响因素源解析

The influencing factors of carbon storage in Chinese fir plantations in the eastern part of the northern extreme of Chinese fir distribution

全球气候变化下碳储量的准确估算是当今世界的焦点问题。本文利用杉木气候敏感的区域——安徽省两大杉木人工林产区(大别山区以及皖南地区)80块受人为干扰较小、不同林龄序列的杉木人工林样地调查数据,采用随机森林算法(Random forest,RF)构建包含候选林分、立地和气候因子的碳储量(地上碳储量(Aboveground carbon storage,C_(a))、地下碳储量(Belowground carbon storage,C_(b))和总碳储量(Total carbon storage,C))模型,并基于最优模型厘清杉木北带东区杉木人工林碳储量(C_(a)、C_(b)和C)估算差异的来源,确定主导因子,量化影响因素对碳储量的影响程度及其影响方向,以了解气候变化对树木生长的影响。结果表明:林分因子是影响杉木北带东区杉木人工林碳储量(C_(a)、C_(b)和C)的主导因子,其相对重要性值均超过76%,其中林分断面积(BA)影响最大,C_(a)、C_(b)和C均随BA的增加而增加;气候因子是影响杉木人工林碳储量的第二大因子,其相对重要性值均不超过17%,其中降水季节性(Bio15)影响最大,C_(a)、C_(b)和C随Bio15的增加而略有降低;而立地因子对杉木人工林碳储量模型的解释能力有限,其相对重要性值均低于3%,C_(a)、C_(b)和C随立地因子的变化极小。

Accurately estimating carbon storage has long been a focus under the context of global climate change.In this study,we collected data from 80 plots in two major Chinese fir plantations production areas in Chinese fir sensitive area to climate change,i.e.Dabie mountainous area and southern Anhui Province,with low human disturbance and different age sequences.Random forest(RF)algorithm was used to construct models that estimate carbon storage aboveground carbon storage(C_(a)),belowground carbon storage(C_(b))and total carbon storage(C)with candidate independent variables such as stand,site,and climate factors.Based on the optimal model,the sources of the estimation variations in carbon storage(C_(a),C_(b) and C)were quantified.The effects and significance of the influencing factors on carbon storage were evaluated to understand the impacts of climate change on tree growth.The results showed that stand factors were the dominant factors affecting carbon storage(C_(a),C_(b) and C)of Chinese fir plantations,and their relative importance value was over 76%.Among the stand factors,stand basal area(BA)had the greatest influence,with C_(a),C_(b),and C increasing with the increases of BA.Climate factors were of secondary importance in affecting the carbon storage of Chinese fir plantation,with the relative importance value being less than 17%.Among the climate factors,Precipitation seasonality(Bio15)exerted the greatest influence,with C_(a),C_(b) and C decreasing slightly with the increase of Bio15.Site factors had limited explanatory power,with their relative importance being less than 3%.There were little changes in C_(a),C_(b) and C with the site factors.