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首页> 外文期刊>Australian Journal of Botany >Allometry for estimating aboveground tree biomass in tropical and subtropical eucalypt woodlands: towards general predictive equations.
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Allometry for estimating aboveground tree biomass in tropical and subtropical eucalypt woodlands: towards general predictive equations.

机译:估计热带和亚热带桉树林地上地上树生物量的异速生长法:朝向一般预测方程式。

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摘要

A fundamental tool in carbon accounting is tree-based allometry, whereby easily measured variables can be used to estimate aboveground biomass (AGB). To explore the potential of general allometry we combined raw datasets from 14 different woodland species, mainly eucalypts, from 11 sites across the Northern Territory, Queensland and New South Wales. Access to the raw data allowed two predictor variables, tree diameter (at 1.3-m height; D) and tree height (H), to be used singly or in various combinations to produce eight candidate models. Following natural log (ln) transformation, the data, consisting of 220 individual trees, were re-analysed in two steps: first as 20 species-site-specific AGB equations and, second, as a single general AGB equation. For each of the eight models, a comparison of the species-site-specific with the general equations was made with the Akaike information criterion (AIC). Further model evaluation was undertaken by a leave-one-out cross-validation technique. For each of the model forms, the species-site-specific equations performed better than the general equation. However, the best performing general equation, ln(AGB)=-2.0596+2.1561 ln(D)+0.1362 (ln(H))2, was only marginally inferior to the species-site-specific equations. For the best general equation, back-transformed predicted v. observed values (on a linear scale) were highly concordant, with a slope of 0.99. The only major deviation from this relationship was due to seven large, hollow trees (more than 35% loss of cross-sectional stem area at 1.3 m) at a single species-site combination. Our best-performing general model exhibited remarkable stability across species and sites, when compared with the species-site equations. We conclude that there is encouraging evidence that general predictive equations can be developed across sites and species for Australia's woodlands. This simplifies the conversion of long-term inventory measurements into AGB estimates and allows more resources to be focused on the extension of such inventories..
机译:碳核算的基本工具是基于树的异速测量法,通过这种方法,可以轻松测量变量来估算地上生物量(AGB)。为了探索一般异体异形的潜力,我们结合了来自北领地,昆士兰州和新南威尔士州的11个站点的14种不同林地物种(主要是桉树)的原始数据集。通过访问原始数据,可以单独或以各种组合使用两个预测变量,即树木直径(1.3米高; D)和树木高度(H),以生成八个候选模型。经过自然对数(ln)转换后,分两步重新分析了由220棵单独的树木组成的数据:首先是20种针对特定物种的AGB方程,其次是单个通用AGB方程。对于这八个模型中的每一个,都使用Akaike信息标准(AIC)对特定物种物种与一般方程进行了比较。通过留一法交叉验证技术进行了进一步的模型评估。对于每种模型形式,特定物种物种方程式的性能均优于一般方程式。但是,性能最佳的通用方程ln(AGB)=-2.0596 + 2.1561 ln(D)+0.1362(ln(H))2仅次于特定物种位置的方程。对于最佳通用方程式,经过反变换的预测v。观测值(在线性范围内)高度一致,斜率为0.99。与这种关系的唯一主要偏差是由于在单个物种-地点组合处有七棵大的空心树(1.3 m处的茎横断面积损失超过35%)。与物种-地点方程相比,我们性能最好的通用模型在物种和地点之间表现出显着的稳定性。我们得出结论,有令人鼓舞的证据表明,可以针对澳大利亚林地的各个地点和物种建立通用的预测方程。这简化了将长期库存测量值转换为AGB估算值的过程,并使更多资源集中于此类库存的扩展。

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