关键词: 细根, 生物量估算模型, 喀斯特, 热带季雨林

Abstract: Abstract Aim Fine root biomass is the basis for quantifying fine root dynamic characteristics, such as fine root turnover and nutrient return. The especial karst habitat with high-rock outcrops and gravel soil determines that the traditional root drilling method for measuring fine root biomass is time-consuming, labor-intensive, destructive and difficult to achieve site-specific sampling, and the sample heterogeneity is large. Therefore, it is necessary to establish the fine root biomass estimation models based on morphological character, to accurately estimate fine root biomass and its fine root turnover rate. Methods Five dominant tree species, Vitex kwangsiensis, Garcinia paucinervis, Streblus tonkinensis, Diospyros siderophylla and Excentrodendron tonkinense in Nonggang National Nature Reserve, Guangxi, were selected to establish the fine root biomass estimation models. Two kinds of classification of fine root were defined as 1–3 orders and diameter ≤2 mm. We sampled the fine root of different diameter at breast height (DBH) levels and soil layers to construct the correlation equations between length and diameter, or root surface area and fine root biomass. We tested the robustness and accuracy of different model, and picked out the optimal fine root biomass estimation models. Important findings The results showed that: (1) Fine root diameter, length and surface area were significantly positive correlated with fine root biomass, thus the fine root morphological characters can be used to construct the correlation equation with fine root biomass. (2) The bivariate fine root biomass estimation model based on diameter and length is more accurate than the univariate model based on fine root surface area. It may be due to the bivariate model incorporates the changes of fine root tissue density and specific root length with root order or diameter, and can better reflect the changes of fine root biomass per unit volume or length. (3) The optimal estimation models of fine root biomass are different among tree species, due to the differences of fine root diameter, specific root length and root tissue density among tree species. The buildup of fine root biomass estimation model based on the fine root morphological indicators is beneficial for converting the fine root morphological data which are sampled using visualization technology such as micro root canal in the fixed location into fine root biomass data. This are contributed to more accurately estimate the fine root turnover rate and nutrients return of special rock mountain habitat. Keywords? fine root; biomass estimation model; karst; tropical seasonal forest

Key words: fine root, biomass estimation model, karst, tropical seasonal forest