New insights into large tropical tree mass and structure from direct harvest and terrestrial lidar
New insights into large tropical tree mass and structure from direct harvest and terrestrial lidar
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通过直接收获和地面激光雷达对大型热带树木质量和结构的新见解
DOI：
10.1101/2020.09.29.317198
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发表时间：
2020
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影响因子：
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通讯作者：
Burt A
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作者：
Burt A
陆地植被碳储存的很大一部分储存在热带森林的地上生物量中，但确切数量仍然不确定，部分原因是缺乏测量。到目前为止，亚马逊地区只有10棵大型热带树木的可访问的同行评审数据，这些树木已经收获并完全通过称重直接测量。在东亚马逊原始林中采集了4株树干直径0.6-1.2 m，树高30-46 m，AGB 3960-18 584 kg的热带雨林大树，测定了其地上绿色质量、含水量和木质组织密度。我们首先介绍了这些数据提供的罕见的生态见解，包括不系统的树内密度变化，高度和半径。我们还发现，大多数AGB通常被发现在冠，但从42%到62%不等。然后，我们比较非破坏性的方法来估计这些树木的AGB，使用经典的异速生长和新的激光雷达为基础的方法。地面激光雷达点云收集收获前，我们安装圆柱体模型的木质结构，使体积派生的AGB检索。从这种方法的估计比异速生长的同行（平均树规模的相对误差：3%对15%）更准确，和误差减少时，放大到累积AGB的四棵树（1%对15%）。此外，虽然异速生长误差增加了四倍，树木的直径范围内的大小，激光雷达误差保持不变。这表明这些激光雷达估计的误差是随机和附加的。如果这些结果可以在森林场景中转移，地面激光雷达方法将减少林分规模AGB估计的不确定性，从而促进我们对热带森林在全球碳循环中的作用的理解。
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.