As tropical deforestation and forest degradation accelerate, carbon-credit trading could provide a financial incentive to preserve and regenerate forests. Since carbon trading relies on the accurate quantification of carbon stocks, allometric equations are urgently needed to derive above-ground dry biomass (AGB) from easily measured variables. Few allometric equations have been published for regenerating secondary forests in Southeast Asia. This study established new allometric equations, to determine AGB and carbon in regenerating secondary forests on shifting cultivation fallows in northern Thailand. To develop the equations, data were collected from 78 trees (136 felled individual stems, including coppices) ranging in size from 1 to 32.9 cm diameter at breast height (D). The dependent variable was AGB. The independent variables were D, tree height (H) and wood density (WD). Wood density varied significantly among species (p < 0.05). Consequently, including WD in the function D²H × WD predicted AGB most accurately, compared with other functions that excluded it. Mean carbon concentration in stems, branches, and leaves was 44.84% ± 1.63 of dry mass, but it varied significantly among tree species (p < 0.05). The new allometric equation revealed that tree ABG was highest in secondary forest, followed by the 7-year-fallow and the 4-year-fallow: 105.3, 38.3 and 10.3 Mg ha⁻¹, respectively, while above-ground carbon was 47.7, 17.4, and 4.6 Mg C ha⁻¹, respectively. Natural regeneration accumulated carbon slower than reported for active restoration, suggesting that managed restoration is preferable to passive regeneration on fallows in northern Thailand. The allometric equations, derived from this study, can be used to accurately determine tree ABG and carbon storage in regenerating secondary forest, with higher precision than has hitherto been possible, thus satisfying the monitoring requirements of REDD+ and other carbon-trading schemes.

随着热带森林砍伐和森林退化的加剧，碳信用交易可以提供财政诱因来保护和更新森林。由于碳交易依赖于碳储量的准确量化，因此迫切需要异速方程来从易于测量的变量中得出地上干生物量（AGB）。很少有异速生长方程被出版来再生东南亚的次生林。这项研究建立了新的异速方程，以确定泰国北部轮流种植休耕地再生次生林中的AGB和碳。为了发展这些方程式，从乳房高度（D）处直径从1到32.9 cm的78棵树（136个砍倒的单个茎，包括coppepes）中收集了数据。因变量是AGB。自变量为D，树高（H）和木材密度（WD）。物种之间的木材密度差异很大（p  ＜0.05）。因此，与将DWD排除在函数之外的其他函数相比，将WD包括在函数D ² H×WD中可以最准确地预测AGB。茎，枝和叶中的平均碳浓度为干重的44.84％±1.63，但在树种之间差异显着（p  <0.05）。新的测长方程表明，次生林中ABG树最高，其次是7年休耕和4年休耕：分别为105.3、38.3和10.3 Mg ha ^-1，而地上碳为47.7， 17.4和4.6 Mg C ha ^-1， 分别。自然再生积累的碳比主动恢复所报告的碳要慢，这表明在泰国北部休耕时，有管理的恢复优于被动再生。这项研究得出的异速方程可以用来准确确定再生次生林中的树木ABG和碳储量，其精度要高于迄今为止的精度，从而满足了REDD +和其他碳交易方案的监测要求。