Propagating uncertainty to estimates of above-ground biomass for Kenyan mangroves: A scaling procedure from tree to landscape level
Propagating uncertainty to estimates of above-ground biomass for Kenyan mangroves: A scaling procedure from tree to landscape level
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DOI：
10.1016/j.foreco.2013.09.047
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发表时间：
2013-12-15
影响因子：
3.7
通讯作者：
Mencuccini, M.
中科院分区：
文献类型：
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作者：
Cohen, R.;Kaino, J.;Mencuccini, M.
红树林是全球重要的碳储存库，因此有可能被纳入未来基于森林的气候变化缓解战略，例如减少森林砍伐和退化造成的排放（REDD+）。参与REDD+将要求发展中国家对森林地上生物量（AGB）进行可靠的估计，并辅以适当的不确定性衡量标准。 AGB 的最终估计应考虑已知的不确定性来源（测量和预测），特别是在大空间尺度估计 AGB 时。在这项研究中，使用混合效应模型来解释肯尼亚红树林由于物种和地点效应而异速生长关系的变异性。除了一组特定于物种的方程外，还生成了肯尼亚红树林的通用生物量方程。该通用方程具有广泛应用的潜力，因为它可以用于预测新树木的 AGB，其中没有特定物种-位点异速生长关系的预先存在的知识：实际生物量研究中最常见的情况。使用混合效应模型对 AGB 的预测显示与 AGB 的原始观测值具有良好的对应性，尽管在较高的 AGB 值下显示出较差的拟合度，这表明在外推时要谨慎。使用来自莫桑比克赞比西河三角洲的独立验证数据集发现 AGB 的观测值和预测值之间存在很强的关系（R-2 = 0.96，p =
Mangroves are globally important carbon stores and as such have potential for inclusion in future forest-based climate change mitigation strategies such as Reduced Emissions from Deforestation and Degradation (REDD+). Participation in REDD+ will require developing countries to produce robust estimates of forest above-ground biomass (AGB) accompanied by an appropriate measure of uncertainty. Final estimates of AGB should account for known sources of uncertainty (measurement and predictive) particularly when estimating AGB at large spatial scales. In this study, mixed-effects models were used to account for variability in the allometric relationship of Kenyan mangroves due to species and site effects. A generic biomass equation for Kenyan mangroves was produced in addition to a set of species-site specific equations. The generic equation has potential for broad application as it can be used to predict the AGB of new trees where there is no pre-existing knowledge of the specific species-site allometric relationship: the most commonly encountered scenario in practical biomass studies. Predictions of AGB using the mixed-effects model showed good correspondence with the original observed values of AGB although displayed a poorer fit at higher AGB values, suggesting caution in extrapolation. A strong relationship was found between the observed and predicted values of AGB using an independent validation dataset from the Zambezi Delta, Mozambique (R-2 = 0.96, p =