甘肃南部7种高寒杜鹃生物量模拟

精确测定与模拟高山-亚高山灌丛生物量是了解陆地生态系统碳功能的重要基础工作。以甘肃南部高山-亚高山地区常见的7种高寒杜鹃（Rhododendron spp.）灌木为对象，通过标准植株收获法，建立易测因子与各器官生物量及总生物量的方程并检验拟合精度，筛选最优拟合方程。结果表明：（1）自变量和函数的类型对杜鹃生物量的模拟效果影响较大，700组方程中以D和D²H为自变量和以幂函数为模型拟合的R²相对集中、中位数都较高。（2）遴选出的35组单物种最优生物量模型的R²介于0.66-0.99之间、中位数为0.92，除山光杜鹃（Rh.oreodoxa）的茎、叶生物量和地上生物量模型为线性函数、麻花杜鹃（Rh.maculiferum）的所有模型为指数函数外，其余的生物量模型均为幂函数；D和D²H是单物种生物量模型的最佳预测变量，H仅是黄毛杜鹃（Rh.rufum）除根外、美容杜鹃（Rh.calophytum）叶生物量的最佳预测变量。（3）混合物种最优模型是以D²H为自变量的幂函数，除对叶生物量的模拟精度相对较低外，对其它生物量的模拟均较好。甘肃南部7种高寒杜鹃灌木生物量模型的建立为高寒地区灌丛生态系统碳汇功能的研究提供了支撑。

Biomass simulation of seven alpine Rhododendrons species in the south of Gansu Province

Rhododendron species are broad-leaved evergreen woody shrubs belonging to Ericaceae, and are an important constituent of alpine and subalpine ecosystems. Rh. species are endemic to Tibetan Plateau and surrounding areas. Unlike for trees, biomass estimation models are virtually lacking for Rh. species in natural communities. Therefore, accurate measurement and modeling of biomass for alpine-subalpine Rh. species is a fundamental work for quantifying carbon functions of terrestrial ecosystems. This study aimed to develop allometric models for the estimation of biomass storage of seven Rh. species'' in the alpine-subalpine region of southern Gansu Province. Investigated species included Rh. rufum, Rh. przewalskii, Rh. alophytum, Rh. oreodoxa, Rh. taibaiense, Rh. capitatum and Rh. maculiferum. A total of 312 individuals were harvested for the measurements of above- and belowground biomass. Commonly used models, such as linear, logarithmic, power-law and exponential functions were used for estimating biomass, and basal diameter (D), height (H), canopy (C), crown volume (V) and square of basal diameter×plant height (D²H) from field measurements were used as independent variables, and leaf biomass, stem biomass, aboveground biomass, root biomass and total biomass were treated as dependent variables. Among a total number of 700 models tested, significant relationships were detected between biomass components and field measurements of predictors for the seven studied woody species (all P<0.01). Using D and D²H as independent variables and the power function resulted in a relatively narrow distribution and a high median of R² values. The R² values of the selected 35 optimal models for individual species from the 700 sets varied between 0.66 and 0.99, with a median of 0.92.The models for stem biomass, leaf biomass and aboveground biomass of Rh. oreodoxa were linear functions, for each of these biomass of Rh. maculiferum were exponential functions, while the rest of the biomass models were power functions. The plant height (H) was the best independent variable for the estimation of stem biomass, leaf biomass and aboveground biomass of Rh. rufum and leaf biomass of Rh. calophytum. The results also showed that the power function with D²H as the independent variable was the best model for mixed species, but the predictive power for leaf biomass was relatively low using the mixed-species'' model. The establishment of seven alpine rhododendron shrub biomass models in southern Gansu Provide can serve as an important tool for the study of the carbon sink function of shrub ecosystems in alpine regions. In addition, these models may be applied to Rh. woodland elsewhere in eastern Tibetan Plateau.