Allometric Estimates of Aboveground Biomass Using Cover and Height Are Improved by Increasing Specificity of Plant Functional Groups in Eastern Australian Rangelands
Allometric Estimates of Aboveground Biomass Using Cover and Height Are Improved by Increasing Specificity of Plant Functional Groups in Eastern Australian Rangelands
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DOI：
10.1016/j.rama.2020.01.009
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发表时间：
2020-05-01
影响因子：
2.3
通讯作者：
Nielsen, Uffe N.
中科院分区：
文献类型：
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作者：
Chieppa, Jeff;Power, Sally A.;Nielsen, Uffe N.
植物地上生物量(AGB)是评估生态系统功能的一个有用的指标，它对变化的环境条件的敏感性提供了对潜在的全球变化影响的洞察。利用植被特征(如植物复盖度或高度)对AGB进行异速生长估计，为重复测量提供了非破坏性的生物量替代物，但可能会给估计带来不确定性。我们估计了来自6个地点的15种植物的植被盖度与盖度指数和AGB之间的关系，以确定在半干旱的东澳大利亚牧场无损估计生物量的最可靠的方法。通过在四个不同的特异性水平上对物种进行分组来进行估计，以测试普通估计是否比基于生活史和形态特征的物种分组更可靠。然后在每个地点的一块1.5米(2)的地块上对估计进行测试以进行验证。在所有情况下，模型都具有非常显著的意义(P<；0.001)，调整后的R-2值在覆盖模型的0.42%到0.96%之间，覆盖高度指数模型的0.38%到0.98%之间。我们发现，增加身高改进模型适合四组，而减少模型适合两组。基于覆盖高度指数的模型的AGB估计误差在-66.8%到4%之间(绝对平均值为35%)。基于Cover的模型误差在-13.4%到53%之间(绝对平均值为14.2%)。对于验证样地中基于覆盖的AGB估计，根据植物功能类型(PFT)对植物进行分组比使用所有15个物种的数据进行估计(绝对平均误差65.2%)提高了精度(绝对平均误差17.3%)。总体盖度是估算AGB的有用指标(除一个地点外，精确度在-2.3%到11.5%之间)，而高度(被认为是冠层特征的指标)在少数情况下提供了好处。我们建议，未来的研究应该测试更多的基于PFT的非破坏性代理和群体物种，以改进使用异速生长的AGB估计。(C)2020年牧场管理学会。爱思唯尔公司出版，版权所有。
Plant aboveground biomass (AGB) is a useful metric to assess ecosystem functioning, and its sensitivity to changing environmental conditions provides insight into potential global change impacts. Allometric estimates of AGB using vegetation characteristics such as plant cover or height provide nondestructive biomass proxies for repeated measurements but can introduce uncertainty to estimates. We estimated the relationship between both plant cover and a cover.height index and AGB for 15 plant species from six sites to identify the most reliable approach to estimate biomass nondestructively in semiarid eastern Australian rangelands. Estimates were made by grouping species at four different levels of specificity, to test whether generic estimates were more robust than grouping species based on life history and morphological characteristics. Estimates were then tested on a 1.5-m(2) plot at each site for validation. In all cases, models were highly significant (P < 0.001) with adjusted R-2 values ranging from 0.42 to 0.96 for cover models and 0.38 to 0.98 for cover.height index models. We found the addition of height improved model fits in four groups while reducing model fits in two groups. The error around AGB estimates for cover.height index-based models ranged from -66.8 to 4% (absolute mean 35%). Cover-based models had errors between -13.4% and 53% (absolute mean 14.2%). For cover-based estimates of AGB in validation plots, grouping plants by plant functional types (PFTs) increased accuracy (absolute mean error 17.3%) compared with estimates using data from all 15 species (absolute mean of 65.2%). Overall cover was a useful surrogate to estimate AGB (with the exception of one site, accuracy ranged from -2.3% to 11.5%), while height (thought to be a surrogate for canopy characteristics) provided benefit in a few circumstances. We suggest that future research should test additional nondestructive proxies and group species based on PFTs to improve AGB estimates using allometry. (C) 2020 The Society for Range Management. Published by Elsevier Inc. All rights reserved.