Bayesian model predicts the aboveground biomass of Caragana microphylla in sandy lands better than OLS regression models

回归模型可用于预测森林生态系统地上生物量,其中最为常用的是最小二乘回归模型。在预测灌木,尤其是多茎灌木的地上生物量 时,最小二乘法与贝叶斯方法的比较很少被研究。我们开发了小叶锦鸡儿(Caragana microphylla Lam.)生物量预测模型。小叶锦鸡儿是科尔 沁沙地广泛分布的多茎灌木,对减少风蚀、固定沙丘具有重要作用。本研究建立6种表征生物量的异速增长模型,并基于统计标准选择 在预测生物量方面表现最佳的1种,然后分别用最小二乘法与贝叶斯方法对模型中的参数进行估计。参数估计过程中用自助法考察样本量大 小的影响,同时区分测试集与训练集。最后,我们比较了最小二乘法与贝叶斯方法在小叶锦鸡儿地上生物量预测中的表现。异速增长的6个 模型均达到显著水平,其中幂指数为1的模型表现最佳。研究结果表明,采用无先验信息与有先验信息的贝叶斯方法进行估计,得到的均 方误差在测试集上低于最小二乘法。另外,基径作为预测变量在最小二乘法与贝叶斯方法中均不显著,表明在生物量预测模型中应谨慎选 择合适变量。本研究强调贝叶斯方法、自助法和异速增长模型相结合能够提升沙地灌木生物量预测模型的准确度。     

Improved allometric models to estimate the aboveground biomass of tropical trees

Terrestrial carbon stock mapping is important for the successful implementation of climate change mitigation policies. Its accuracy depends on the availability of reliable allometric models to infer oven‐dry aboveground biomass of trees from census data. The degree of uncertainty associated with previously published pantropical aboveground biomass allometries is large. We analyzed a global database of directly harvested trees at 58 sites, spanning a wide range of climatic conditions and vegetation types (4004 trees ≥ 5 cm trunk diameter). When trunk diameter, total tree height, and wood specific gravity were included in the aboveground biomass model as covariates, a single model was found to hold across tropical vegetation types, with no detectable effect of region or environmental factors. The mean percent bias and variance of this model was only slightly higher than that of locally fitted models. Wood specific gravity was an important predictor of aboveground biomass, especially when including a much broader range of vegetation types than previous studies. The generic tree diameter–height relationship depended linearly on a bioclimatic stress variable E, which compounds indices of temperature variability, precipitation variability, and drought intensity. For cases in which total tree height is unavailable for aboveground biomass estimation, a pantropical model incorporating wood density, trunk diameter, and the variable E outperformed previously published models without height. However, to minimize bias, the development of locally derived diameter–height relationships is advised whenever possible. Both new allometric models should contribute to improve the accuracy of biomass assessment protocols in tropical vegetation types, and to advancing our understanding of architectural and evolutionary constraints on woody plant development.     

天然云杉相容性生物量估算模型

基于150株天然云杉实测材积和生物量数据,利用非线性度量误差方法,建立相容性立木材积与生物量方程,并采用总量直接控制方案和分级联合控制方案研建了地上总生物量与4个分项(干材、干皮、树枝、树叶)的相容性方程系统,其中又采取了独立估计和联合估计两种处理方法进行地上生物量的估计.结果表明: 所建一元、二元相容性立木材积和地上生物量模型的材积和生物量决定系数均在0.85以上,最高达0.99,在胸径基础上增加树高变量能显著提高材积的预估效果,但对生物量的预估效果改进不大.就总量与分量相容性模型而言,分级联合控制方案所建的一元模型好于总量直接控制所建的一元模型,两种方案所建的二元模型效果相当.对一元、二元相容性生物量模型的拟合效果进行对比,结果显示,解释变量的增加明显提高了树枝和树叶生物量的拟合效果,对其他几个分量的拟合效果改善不大.对独立估计和联合估计的对比分析显示,两种估计方法几乎没有差异.     

白桦和水曲柳树干温度日变化的空间变异及其影响因子

植物温度是森林生态系统能量平衡和植被呼吸估算的重要参数.采用T型热电偶监测树皮和木材特性各异的2个阔叶树种(白桦和水曲柳)不同深度、高度和方位的树干温度(T_s),探索T_s日变化的空间变异及其影响因素.结果表明: T_s月平均日变化格局与空气温度呈相似的正弦曲线,但T_s变化滞后于空气温度,时滞从树皮表面处的0 h增加到6 cm深度处的4 h.随测定深度的增加和高度的降低,T_s日变化的峰值和日较差均逐渐减小.T_s周向差异不大,休眠季节白天南向、西向T_s日峰值略高.两树种树皮和木材的热学特性(比热容和导热系数)的差异,会通过影响树干表面与外界的热交换和树干内部热扩散而造成T_s径向变化的种间差异.白桦树皮较高的反射率削弱了太阳辐射对T_s的影响.多元逐步回归分析表明,环境因子可以很好地估测T_s日动态(R²>0.85),影响程度依次为空气温度>水汽压>净辐射>风速.估算生物量热储和树干表面CO₂通量时应考虑T_s径向、纵向和种间差异.     

基于物候相机归一化植被指数估算高寒草地植物地上生物量的季节动态

准确评估地上生物量对优化草地资源管理和理解草地碳、水和能量平衡具有重要意义。该文通过近地遥感归一化植被指数(NDVI)构建最优经验模型, 对青藏高原高寒草地地上生物量进行估算。该文利用2018-2019年5-9月野外实测的地上生物量和植物冠层光谱仪(RapidSCAN)测定的NDVI_RS数据, 构建了生长季不同时期地上生物量的估算模型; 并结合2018年NetCam物候相机测定的NDVI_Cam时间序列数据, 实现地上生物量季节动态的模拟。主要结果: (1) NDVI_Cam、NDVI_RS与地上生物量具有相似的单峰型季节变化格局, 但NDVI峰值出现的时间(7月)较地上生物量(8月)更早; (2)基于NDVI的生物量估算最优经验模型在5、7和9月是幂函数, 在6和8月是二次多项式, 估算精度为0.29-0.77; (3)基于NDVI_Cam时间序列数据, 生长季不同时期建模(R² = 0.91)较单一时期(9月)建模(R² = 0.49)对地上生物量季节动态的估算更为准确。这些结果表明, 近地遥感是估算高寒草地植物地上生物量的有效手段, 开展季节性植物生长调查将有助于准确评估草地资源。     

遥感在森林地上生物量估算中的应用

生物量是地表C循环研究的重要组成部分,生物量研究有助于深入认识区域乃至全球的C平衡。森林作为地球最重要的陆地生态系统,区域乃至全球尺度的森林地上生物量估算一直是生态学研究的难点之一。在大的空间尺度上,遥感技术是估算森林地上生物量的有效手段。TM、AVHRR、SAR等数据以及多源数据的融合在森林生物量估算方面广泛应用,并取得了显著效果。运用遥感技术进行森林生物量估算时,所采用的数据源不同,分析方法也不相同,主要分析方法有:相关分析、多元回归分析、神经网络和数学模型模拟等。随着测定不同空间、时间和波谱分辨率的各种传感器的广泛使用,以及生物量遥感估算模型的进一步发展和完善,大尺度森林生物量的遥感估算研究必将向前迈进一大步。     

黄土高原典型草原地上生物量估测模型

为了寻求有效的草地地上生物量估测方法和精确估测黄土高原典型草原草原地上生物量。于2014年8月中旬,在黄土高原典型草原草原地上生物量达到最大值,分别从单株水平和种群水平进行野外调查。以株高(H)和盖度(C)的复合因子(C×H)为自变量,通过回归分析,建立地上生物量估测模型,采用留一法对其精确性进行评估;并通过校正系数以及群落总生物量估测值和实测值比较单株水平和种群水平所建模型的精确性。结果表明:黄土高原典型草原草地,无论在单株水平还是种群水平,线性和幂函数对该区域生物量的拟合效果更好。估测模型检验结果表明,在单株水平各个物种的生物量估测值与实测值相关性较好,均达到了显著水平(P0.05),其r值均大于0.6,总相对误差RS均小于10%,平均相对误差绝对值RMA(average absolute value of relative error)均小于30%,总生物量的实测值与估测值比较接近,校正系数均接近1;而在种群水平上,虽然各物种的生物量估测值与实测值相关性均达到了显著水平(P0.05),但多数物种平均相对误差绝对值RMA大于30%,总相对误差RS(total relative error)均大于10%,总生物量的估测值均大于实测值,校正系数均偏离了1,说明在黄土高原典型草原通过单株水平建立的物种生物量估测模型的精度优于种群水平建立的物种生物量估测模型的精度。     

Allometric Models for Tree Volume and Total Aboveground Biomass in a Tropical Humid Forest in Costa Rica1

Allometric equations for the estimation of tree volume and aboveground biomass in a tropical humid forest were developed based on direct measurements of 19 individuals of seven tree species in Northern Costa Rica. The volume and the biomass of the stems represented about two‐thirds of the total volume and total aboveground biomass, respectively. The average stem volume varied between 4 and 11 Mg/tree and the average total aboveground biomass ranged from 4 to 10 mg/tree. The mean specific gravity of the sampled trees was 0.62 ± 0.06 (g/cm³). The average biomass expansion factor was 1.6 ± 0.2. The best‐fit equations for stem and total volume were of logarithmic form, with diameter at breast height (R²= 0.66 ? 0.81) as an independent variable. The best‐fit equations for total aboveground biomass that were based on combinations of diameter at breast height, and total and commercial height as independent variables had R² values between 0.77 and 0.87. Models recommended for estimating total aboveground biomass are based on diameter at breast height, because the simplicity of these models is advantageous. This variable is easy to measure accurately in the field and is the most common variable recorded in forest inventories. Two widely used models in literature tend to underestimate aboveground biomass in large trees. In contrast, the models developed in this study accurately estimate the total aboveground biomass in these trees.     

Biomass estimation models and allocation patterns of 14 shrub species in Mountain Luya,Shanxi, China

Aims Shrub species have evolved specific strategies to regulate biomass allocation among various organs or between above- and belowground biomass and shrub biomass model is an important approach to estimate biomass allocation among different shrub species. This study was designed to establish the optimal estimation models for each organ (leaf, stem, and root), aboveground and total biomass of 14 common shrub species in Mountain Luya, Shanxi Province, China. Furthermore, we explored biomass allocation characteristics of these shrub species by using the index of leaf biomass fraction (leaf to total biomass), stem biomass fraction (stem to total biomass), root biomass fraction (root to total biomass), and root to shoot mass ratio (R/S) (belowground to aboveground biomass).
Methods We used plant height, basal diameter, canopy diameter and their combination as variables to establish the optimal biomass estimation models for each shrub species. In addition, we used the ratios of leaf, stem, root to total biomass, and belowground to aboveground biomass to explore the difference of biomass allocation patterns of 14 shrub species.
Important findings Most of biomass estimation models could be well expressed by the exponential and linear functions. Biomass for shorter shrub species with more stems could be better estimated by canopy area; biomass for taller shrub species with less stems could be better estimated by the sum of the square of total base diameter multiply stem height; and biomass for the rest shrub species could be better estimated by canopy volume. The averaged value for these shrub species was 0.61, 0.17, 0.48, and 0.35 for R/S, leaf biomass fraction, stem biomass fraction, and root biomass fraction, respectively. Except for leaf biomass fraction, R/S, stem biomass fraction, and root biomass fraction for shrubs with thorn was significantly greater than that for shrubs without thorn.     

基于GF-2的油松人工林地上生物量反演

油松是黄土高原地区重要的造林树种.快速准确地估测其地上生物量,对开展该地区森林资源动态监测等具有重要作用.本研究选取陕西省黄龙山林区石堡林场的油松人工林为对象,结合国产卫星高分二号(GF-2)的多光谱遥感影像与野外同时段实测样地数据,对其地上生物量进行了估算.提取了5种植被指数和8种纹理信息,基于普通回归、逐步回归、岭回归、拉索回归与主成分回归5种方法在4种纹理窗口(3×3、5×5、7×7和9×9)下建模,使用留一法交叉验证测试了每个模型的估算精度.结果表明: 提取的遥感因子之间存在着较为严重的多重共线性关系,大部分遥感因子与油松人工林地上生物量有较为显著的相关性;GF-2数据在石堡林场油松人工林地上生物量的反演中可以实现较高精度,其中估算效果最好的是使用了9×9纹理窗口的主成分回归模型,估算效果最差的是使用了3×3纹理窗口的普通回归模型.利用国产高分辨率卫星影像对油松人工林地上生物量进行反演研究,可以为西北地区林业部门进行森林生物量监测、资源管理与可持续经营提供科学依据.     

Fusion of airborne LiDAR data and hyperspectral imagery for aboveground and belowground forest biomass estimation

Vegetation biomass is a key biophysical parameter for many ecological and environmental models. The accurate estimation of biomass is essential for improving the accuracy and applicability of these models. Light Detection and Ranging (LiDAR) data have been extensively used to estimate forest biomass. Recently, there has been an increasing interest in fusing LiDAR with other data sources for directly measuring or estimating vegetation characteristics. In this study, the potential of fused LiDAR and hyperspectral data for biomass estimation was tested in the middle Heihe River Basin, northwest China. A series of LiDAR and hyperspectral metrics were calculated to obtain the optimal biomass estimation model. To assess the prediction ability of the fused data, single and fused LiDAR and hyperspectral metrics were regressed against field-observed belowground biomass (BGB), aboveground biomass (AGB) and total forest biomass (TB). The partial least squares (PLS) regression method was used to reduce the multicollinearity problem associated with the input metrics. It was found that the estimation accuracy of forest biomass was affected by LiDAR plot size, and the optimal plot size in this study had a radius of 22 m. The results showed that LiDAR data alone could estimate biomass with a relative high accuracy, and hyperspectral data had lower prediction ability for forest biomass estimation than LiDAR data. The best estimation model was using a fusion of LiDAR and hyperspectral metrics (R² = 0.785, 0.893 and 0.882 for BGB, AGB and TB, respectively, with p < 0.0001). Compared with LiDAR metrics alone, the fused LiDAR and hyperspectral data improved R² by 5.8%, 2.2% and 2.6%, decreased AIC value by 1.9%, 1.1% and 1.2%, and reduced RMSE by 8.6%, 7.9% and 8.3% for BGB, AGB and TB, respectively. These results demonstrated that biomass accuracies could be improved by the use of fused LiDAR and hyperspectral data, although the improvement was slight when compared with LiDAR data alone. This slight improvement could be attributed to the complementary information contained in LiDAR and hyperspectral data. In conclusion, fusion of LiDAR and other remotely sensed data has great potential for improving biomass estimation accuracy.     

人工神经网络与相容性生物量模型预测单木地上生物量的比较

森林生物量是林业生产经营和森林资源监测的重要指标,为探索高效低偏的单木生物量估测方法,引入人工神经网络.本研究采用黑龙江省东折棱河林场的101株长白落叶松地上生物量数据,基于不同变量(胸径、树高、冠幅)组合建立了4个聚合模型体系(AMS),采用加权回归消除模型的异方差.然后,基于最优的变量组合建立人工神经网络(ANN)...     

不同载畜率对荒漠草原群落结构和功能群生产力的影响

采用随机区组试验研究了内蒙古高原荒漠草原亚带短花针茅(S tip a brev if lora)草原群落不同载畜率对草原群落结构和功能群生产力的影响。结果表明:随着载畜率的增加,群落的植物种数逐渐减少,在每个载畜率水平下,冷蒿(A rtem isia f rig id a)占有绝对优势地位,优势度为35.66%~41.95%;群落的地上生物量随载畜率的增加而降低,各功能群地上生物量组成中,灌木类处于主体地位,分别占据了群落68%(CK)、77.40%(LG)、73.25%(M G)、76.91%(HG)的生物量;在植物生活型功能组成中,灌木类和杂类草、多年生丛生禾草和杂类草功能群,在生物量上具有生态互补效应(n iche com p lem en tary effect)。     

基于高分一号 WFV 卫星影像的黄河口湿地草本植被生物量估算模型研究

基于高分一号 WFV 卫星数据,通过计算 NDVI、SRI、SAVI、MSAVI、GBNDVI 和 DVI 6种植被指数,结合黄河口湿地现场草本植被地上干生物量样本,进行一元线性、指数、对数和幂4种模型的回归分析,从中选出生物量最佳估算模型。结果表明：（1）指数模型是 NDVI 和 GBNDVI 的最佳生物量回归模型,幂模型是其它植被指数的最佳回归模型（P ＜0．001）;（2）6种植被指数干生物量最佳回归模型的决定系数（R2）都大于0．7,最大为0．77,由大到小排序为 MSAVI ＞SAVI ＞NDVI ＞DVI ＞SRI ＞GBNDVI;（3）各最佳回归模型的平均相对误差（MRE）都小于54％,最小为23．9％,由小到大排序为 NDVI ＜GBNDVI ＜SRI ＜DVI ＝SAVI ＜MSAVI。     

Estimation of stem and tree level biomass models for Prosopis juliflora/pallida applicable to multi-stemmed tree species

The aim of this paper is to develop biomass models for commonly multi-stemmed Prosopis juliflora/pallida trees. The data were collected on three of the Cape Verde islands (Maio, Santiago and Santo Antao). The dataset covers 240 trees containing 1,882 stems with stem diameter at breast height over 2 cm; of that 255 individual tree stems were sampled destructively. These calibration data were used to construct stem and tree-level models for estimation of total aboveground biomass and its fine and course fractions with diameter threshold of 5 cm. A set of parameterized biomass models for multi-stemmed Prosopis spp. trees suited for biomass estimation at tree and stem levels using appropriate set of independent variables, commonly available in forest inventory programs, was created. The effect of site (island) on tree allometry was not detected. The two-phase construction of tree biomass models based on destructive sampling limited to individual stems combined with a routine field measurement of entire multi-stemmed tree specimen represents a practicable approach leading to biomass and carbon assessment that may be generally suited for tree species with complex multi-stemmed growth form similar to that of Prosopis spp.     

臭冷杉生物量分配格局及异速生长模型

摘 要：臭冷杉是长白山阔叶红松林中重要针叶树种,采用整株收获法分析21株臭冷杉地上地下生物量分配格局。在枝条水平上采用样枝直径（BD）、样枝长度（BL）、样枝所在轮生枝位置（WP）建立活枝、针叶生物量异速生长模型,在植株水平上采用胸径（DBH）、树高（H）、年龄（Age）、树冠长度（CL）、树冠比率（CR）、南北向冠幅（CW1）、东西向冠幅（CW2）等变量建立树干木质、树皮、活枝、针叶、粗根及整株生物量模型。并利用逐步线性回归法获得不同器官生物量最优模型。结果表明：（1）活枝生物量主要集中在树冠中下层,针叶生物量集中在树冠中层。树冠中层和下层枝叶生物量无显著差异（p>0.05）;（2）21株臭冷杉地上生物量和地下生物量变动范围分别为1.026–506.047 kg/株和0.241–112.000 kg/株。粗根、活枝、针叶、树干木质、树皮及枯枝生物量占整株生物量的相对比例分别为18.68%、18.39%、12.02%、39.29%、8.70%和2.92%;（3）地上生物量与地下生物量呈显著线性相关（p<0.001）,拟合线性方程斜率为0.23;（4）枝条水平上,活枝生物量模型解释量超过95%,平均预测误差小于30%。与单变量（BD）活枝生物量模型相比,2变量（BD、BL）和3变量（BD、BL、WP）模型解释量分别提高1.2%和2.0%,平均预测误差分别下降6.26%和9.27%。针叶生物量相对较难预测,模型解释量仅为82.7%,平均预测误差接近50%,模型中增加BL 和WP变量并未提高针叶生物量的预测精度。活枝生物量与BD、BL、WP正相关,针叶生物量与BD正相关,与BL、WP负相关;（5）植株水平上,基于胸径的单变量模型可解释量大于90%,增加树高变量未能显著提高生物量模型的预测精度。年龄决定了臭冷杉的树干生物量,忽视年龄变量将会产生生物量预测误差。树冠特征是影响枝叶生物量预测精度的重要变量。综合考虑模型的可解释量及回归系数显著性可知,胸径是预测臭冷杉不同器官生物量的可靠变量。     

利用简易测量板估测白三叶群落地上生物量

地上生物量是草地群落的一个重要指标,而直接收割法对生态系统较脆弱的地区有极大的破坏.为了更有效地估测白三叶群落地上生物量而又不破坏草地,采用自制测量板对陕西省杨凌区大寨镇杜寨村的白三叶群落高度和地上生物量进行了研究.采用铝塑板和高分子板不同规格的17种测量板,将各测量板分别置于白三叶群落上方,记录测量板下方到地面的植物群落高度,重复20次,然后将测量板下方对应面积内的植物齐地面刈割,烘干后,称量得到地上生物量,最后进行数学模型建立、相关性分析,并对模型进行验证.结果表明: 以测量板下方群落高度为自变量,对应面积内群落地上生物量为因变量,建立多种回归方程,群落高度和地上生物量之间呈正相关,R²为0.37～0.76;铝塑板与高分子板相比,其测量得到的生物量变异系数和建立的回归方程决定系数均表现较好,精度较高;最佳测量板为直径35 cm的圆形铝塑板,其最优估测模型为: y=1.6460x-3.3462 (R²=0.76),预测精度达到92.1%.     

Allometric regression equations to determine aerial biomasses of Mediterranean shrubs

One of the difficult problems arising in many ecological models of development of plant communities and populations is how to estimate the aerial biomass in a non destructive way. This paper presents a nondestructive estimation of the aboveground biomass of plants of several species of Mediterranean shrubs. The method used combines the length-based measurements of a number of plants of each of several taxon with measured biomasses of those same plants fitting allometric nonlinear regression equations to yield parameterized models of plant biomass as a function of plant apparent volume. Two methods of estimating the apparent volume are developed and compared with a well known one in literature.     

植株密度和氮素互作对垂穗披碱草生物量分配的影响

垂穗披碱草（Elymus nutans）是高寒地区建植和改良栽培草地的首选草种。虽然合理植株密度和氮素添加量是垂穗披碱草栽培草地稳产的关键因子,但两者之间是否存在最佳互作组合仍不清楚。采用盆栽试验,通过分析不同植株密度（58、102、146株/m²）和氮素添加量（0、200、400 mg/kg）组合状态下垂穗披碱草株高、单株分蘖数、地上生物量、地下生物量、根系体积和地上地下生物量比,以确定理论上是否存在植株密度和氮素添加量的最佳组合。结果表明：随植株密度增加,垂穗披碱草株高、地上生物量和地上地下生物量比值均先增加后降低,而单株分蘖数逐渐减小,根系体积和地下生物量先增加后保持相对稳定;随氮素添加量增加,垂穗披碱草单株分蘖数、地上生物量和地上地下生物量比值均表现为先增加后降低,地下生物量逐渐降低。植株密度与氮素添加量互作虽然对垂穗披碱草的根系体积和单株分蘖数没有显著影响,但两者互作显著影响了垂穗披碱草株高、地上生物量、地下生物量、地上地下生物量比（P<0.01）,这些指标与植株密度和氮素添加量的关系均表现为一个开口向下的抛物面。当植株密度为102株/m²和氮素添加量为200 mg/kg时,垂穗披碱草栽培草地产量最大,生物量分配最优。垂穗披碱草植株密度和氮素添加互作时理论上存在最佳组合,这为垂穗披碱草栽培草地的田间管理提供了理论依据。     

Plant leaf traits,height and biomass partitioning in typical ephemerals under different levels of snow cover thickness in an alpine meadow

Aims In the cold life zones, snow cover is a comprehensive environmental factor that directly influences soil temperature, soil water content, light and nutrient availability. Plants in these zones develop a series of unique mechanisms involving phenological characteristics, reproductive strategies, physiology and morphology to adapt to environmental changes. This paper is focused on the responses of plant leaf traits, height and biomass partitioning to variations in snow cover thickness, in order to better understand the responses of plant functional traits and specific adaptation strategies under global climate change scenarios. Methods Three transects were established along a gradient of snow cover in an alpine meadow of Mt. Kaka, in the eastern Qinghai-Xizang Plateau. Primula purdomii, Pedicularis kansuensis and Ranunculus tanguticus, which are three widely distributed and dominant ephemerals, were sampled and studied, particularly at their blooming stages. Plant height, specific leaf area (SLA) and biomass partitioning were measured accordingly. Important findings The values of SLA in Pedicularis kansuensis and R. tanguticus were relatively greater under better soil conditions; it was smaller in Primula purdomii with thick snow cover. The relationship between aboveground biomass and belowground biomass in Primula purdomii was allometric at sites with both thick and thin snow cover. No significant relationships were found between aboveground biomass and belowground biomass in Pedicularis kansuensis and R. tanguticus at some individual sites. However, when samples of the three species were pooled, the relationships between aboveground biomass and belowground biomass were allometric at all sites, which did not support isometric scaling hypothesis. In addition, on sites with either thick or thin snow cover, aboveground biomass had greater rate of accumulation than belowground biomass; whereas on sites with medium snow cover, the rate of biomass accumulation was greater for belowground component than aboveground component. Functional traits and biomass variables were better correlated in Primula purdomii and Pedicularis kansuensis than in R. tanguticus.