Burt Andrew, Boni Vicari Matheus, da Costa Antonio C L, Coughlin Ingrid, Meir Patrick, Rowland Lucy, Disney Mathias
Department of Geography, University College London, London, UK.
Instituto de Geosciências, Universidade Federal do Pará, Belém, Brazil.
R Soc Open Sci. 2021 Feb 10;8(2):201458. doi: 10.1098/rsos.201458.
A large portion of the terrestrial vegetation carbon stock is stored in the above-ground biomass (AGB) of tropical forests, but the exact amount remains uncertain, partly owing to the lack of measurements. To date, accessible peer-reviewed data are available for just 10 large tropical trees in the Amazon that have been harvested and directly measured entirely via weighing. Here, we harvested four large tropical rainforest trees (stem diameter: 0.6-1.2 m, height: 30-46 m, AGB: 3960-18 584 kg) in intact old-growth forest in East Amazonia, and measured above-ground green mass, moisture content and woody tissue density. We first present rare ecological insights provided by these data, including unsystematic intra-tree variations in density, with both height and radius. We also found the majority of AGB was usually found in the crown, but varied from 42 to 62%. We then compare non-destructive approaches for estimating the AGB of these trees, using both classical allometry and new lidar-based methods. Terrestrial lidar point clouds were collected pre-harvest, on which we fitted cylinders to model woody structure, enabling retrieval of volume-derived AGB. Estimates from this approach were more accurate than allometric counterparts (mean tree-scale relative error: 3% versus 15%), and error decreased when up-scaling to the cumulative AGB of the four trees (1% versus 15%). Furthermore, while allometric error increased fourfold with tree size over the diameter range, lidar error remained constant. This suggests error in these lidar-derived estimates is random and additive. Were these results transferable across forest scenes, terrestrial lidar methods would reduce uncertainty in stand-scale AGB estimates, and therefore advance our understanding of the role of tropical forests in the global carbon cycle.
陆地植被碳储量的很大一部分储存在热带森林的地上生物量（AGB）中，但具体数量仍不确定，部分原因是缺乏相关测量数据。迄今为止，可获取的经同行评审的数据仅来自亚马逊地区10棵已砍伐并通过称重进行全面直接测量的大型热带树木。在此，我们在东亚马逊地区完整的原始森林中砍伐了4棵大型热带雨林树木（树干直径：0.6 - 1.2米，树高：30 - 46米，AGB：3960 - 18584千克），并测量了地上绿色物质、水分含量和木质组织密度。我们首先展示了这些数据所提供的罕见生态见解，包括树木内部密度随高度和半径的非系统性变化。我们还发现，大部分AGB通常存在于树冠中，但占比在42%至62%之间变化。然后，我们使用经典异速生长法和基于激光雷达的新方法，比较了估算这些树木AGB的非破坏性方法。在砍伐前收集了地面激光雷达点云数据，我们在这些点云上拟合圆柱体以模拟木质结构，从而能够获取基于体积的AGB。这种方法的估算结果比异速生长法更准确（平均树木尺度相对误差：3%对15%），并且在按比例扩大到这4棵树的累计AGB时误差减小（1%对15%）。此外，虽然在直径范围内异速生长法的误差随树木大小增加了四倍，但激光雷达法的误差保持不变。这表明这些基于激光雷达的估算误差是随机且可累加的。如果这些结果能够在不同森林场景中通用，地面激光雷达方法将减少林分尺度AGB估算的不确定性，从而增进我们对热带森林在全球碳循环中作用的理解。
