Data from: Closing a gap in tropical forest biomass estimation: taking crown mass variation into account in pantropical allometries

Accurately monitoring tropical forest carbon stocks is an outstanding challenge. Allometric models that consider tree diameter, height and wood density as predictors are currently used in most tropical forest carbon studies. In particular, a pantropical biomass model has been widely used for approximately a decade, and its most recent version will certainly constitute a reference in the coming years. However, this reference model shows a systematic bias for the largest trees. Because large trees are key drivers of forest carbon stocks and dynamics, understanding the origin and the consequences of this bias is of utmost concern. In this study, we compiled a unique tree mass dataset on 673 trees measured in five tropical countries (101 trees > 100 cm in diameter) and an original dataset of 130 forest plots (1 ha) from central Africa to quantify the error of biomass allometric models at the individual and plot levels when explicitly accounting or not accounting for crown mass variations. We first showed that the proportion of crown to total tree aboveground biomass is highly variable among trees, ranging from 3 to 88 %. This proportion was constant on average for trees < 10 Mg (mean of 34 %) but, above this threshold, increased sharply with tree mass and exceeded 50 % on average for trees ≥ 45 Mg. This increase coincided with a progressive deviation between the pantropical biomass model estimations and actual tree mass. Accounting for a crown mass proxy in a newly developed model consistently removed the bias observed for large trees (> 1 Mg) and reduced the range of plot-level error from −23–16 to 0–10 %. The disproportionally higher allocation of large trees to crown mass may thus explain the bias observed recently in the reference pantropical model. This bias leads to far-from-negligible, but often overlooked, systematic errors at the plot level and may be easily corrected by accounting for a crown mass proxy for the largest trees in a stand, thus suggesting that the accuracy of forest carbon estimates can be significantly improved at a minimal cost.

精准监测热带森林碳储量是当前学界面临的重大挑战。以树木胸径、树高和木材密度作为预测因子的异速生长模型（allometric model），目前是绝大多数热带森林碳研究的主流分析工具。具体而言，一款泛热带生物量模型（pantropical biomass model）已被广泛应用近十年，其最新版本无疑将在未来数年成为该领域的参考基准。然而，该参考模型对最大径级树木存在系统性估算偏差。由于大径级树木是森林碳储量与动态变化的核心驱动因子，解析该偏差的成因与影响便成为学界高度关注的核心议题。本研究整合了来自5个热带国家的673株树木的独特生物量实测数据集（其中包含101株胸径＞100cm的个体），以及来自中非地区的130块1公顷森林样地的原始实测数据集，旨在量化在明确考虑冠部生物量变化与未考虑该变化两种场景下，生物量异速生长模型在个体与样地尺度上的误差水平。研究首先发现，树木冠部生物量占地上总生物量的比例存在极高的个体间变异，区间为3%至88%。对于生物量＜10 Mg的树木，该比例的平均值保持稳定（约34%）；但当生物量超过该阈值后，该比例随树木生物量急剧升高，在生物量≥45 Mg的个体中，该比例的平均值更是超过了50%。该变化趋势与泛热带生物量模型估算值与实测树木生物量之间的渐进式偏差高度吻合。在新构建的模型中引入冠部生物量替代指标后，所有生物量＞1 Mg的大径级树木的估算偏差均被消除，同时样地尺度的误差区间从-23%至16%缩减至0%至10%。由此可见，大径级树木对冠部生物量的不成比例分配，正是近期泛热带参考模型出现估算偏差的核心原因。该偏差会在样地尺度上造成不容忽视却常被忽视的系统性误差，但只需通过考虑林分中大径级树木的冠部生物量替代指标即可轻松修正。这意味着仅需极低的成本，便可大幅提升森林碳储量估算的准确性。