the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Tree height uncertainty biases aboveground biomass estimation more than wood density in miombo woodlands
Abstract. Accurate and unbiased estimation of tree aboveground biomass (AGB) is essential for large-scale monitoring of forest carbon stocks. But estimating AGB typically requires several data imputation steps that can introduce substantial errors that are hard to quantify and correct for. Two sources of uncertainty that are thought to be particularly important but remain poorly understood are tree height – which is generally estimated using allometric models – and wood density – which is most commonly assigned from databases based on taxonomic matching. Here, we used data from 154 destructively harvested trees in Zambia’s miombo woodlands that span a large range of sizes to develop a framework to partition errors in AGB arising from uncertainty in tree height and wood density. We found that when locally-calibrated allometries are used to estimate missing tree height information and when wood density is imputed from species-specific values derived from public databases, AGB can be estimated with high precision and little or no bias. However, when tree height and wood density are imputed more coarsely using generic information, errors in AGB can be substantial. In particular, estimating tree height using a regional allometric model developed for tropical dry forests led to 35 % underestimation of AGB. Our study provides an intuitive approach for quantifying and partitioning errors in AGB arising from uncertainty in tree height and wood density, paving the way for more robust mapping of forest carbon stocks and fluxes.
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Status: open (until 14 Oct 2025)
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RC1: 'Comment on egusphere-2025-3133', Sybryn Maes, 22 Jul 2025
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See attached file for specific feedback
- Overall feedback:
Well written, relevant topic. Overall, the paper is carefully presented. The method section requires more detail imo, for the manuscript to be more deeply reviewed. Right now, because of a lack of information on some accounts it was not possible to correctly review it imo (therefore I also did not read the discussion in too great detail at this stage). I suggest a major revision.
-Authors should provide recommendations for how to improve agb measurements given the practical implementation and scope of their article, and this agb measurement methodology (e.g. forest carbon projects).
-Authors should clarify and potentially rephrase/concretize their objectives (L103-107)and then link it better to the methodology and data collection that was necessary for reaching their objectives.
-Authors should consider whether the introduction and article in general should speak about a larger context of tropical forests (or even ‘and savannas’ as they mention in first line of intro), or specifically target miombo woodlands as the title suggests. Though I understand that tropical forests in general might be relevant since equations are used in miombo from tropical forests more widely, it is important to clarify in the text the distinction imo, and also clearly introduce miombo as a specific type of dry forest at some point in the intro already. I also think the authors should acknowledge and provide info on the available other destructive tree datasets / equations for miombo systems. Please see my specific feedback on that.
-Authors should provide more information on how they tackled the fact that their data comes from three different sites (statistically / ecologically)?
-Authors should provide more detailed information on the methodology used for the forest inventory data. See specific comments.
-Authors should explain why other allometric equations from miombo (destructive tree harvest datasets) have not been included in the comparison and/or include them throughout the analysist o make it more robust and exhaustive.
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