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    Author(s): Brian J. Clough; Matthew B. Russell; Grant M. DomkeChristopher W. Woodall; Philip J. Radtke
    Date: 2016
    Source: Ecological Modelling
    Publication Series: Scientific Journal (JRNL)
    Station: Northern Research Station
    PDF: Download Publication  (1.0 MB)


    tEstimation of live tree biomass is an important task for both forest carbon accounting and studies of nutri-ent dynamics in forest ecosystems. In this study, we took advantage of an extensive felled-tree database(with 2885 foliage biomass observations) to compare different models and grouping schemes based onphylogenetic and geographic variation for predicting foliage biomass at the tree scale. We adopted aBayesian hierarchical statistical framework, first to compare linear models that predict foliage biomassdirectly to models that separately estimate a foliage ratio as a component of total aboveground biomass,then to compare species specific models to both 'narrow' and 'broad' general biomass models using thebest fitted functional form. We evaluated models by simulating new datasets from the posterior pre-dictive distribution, using both summary statistics and visual assessments of model performance. Keyfindings of our study were: (1) simple linear models provided a better fit to our data than component ratiomodels, where total biomass and the foliar ratio are estimated separately; (2) species-specific equationsprovided the best predictive performance, and there was no advantage to narrow species groupings rel-ative to broader groups; and (3) all three model schemes (i.e., species-specific models versus narrow orbroad groupings proposed in national-scale biomass equations) tended to over-predict foliage biomassand resulted in predictions with very high uncertainty, particularly for large diameter trees. This analysisrepresents a fundamental shift in carbon accounting by employing felled-tree data to refine our under-standing of uncertainty associated with component biomass estimates, and presents an ideal approach toaccount for tree-scale allometric model error when estimating forest carbon stocks. However, our resultsalso highlight the need for substantial improvements to both available fitting data and models for foliagebiomass before this approach is implemented within the context of greenhouse gas inventories.

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    Clough, Brian J.; Russell, Matthew B.; Domke, Grant M.; Woodall, Christopher W.; Radtke, Philip J. 2016. Comparing tree foliage biomass models fitted to a multispecies, felled-tree biomass dataset for the United States. Ecological Modelling. 333: 79-91.


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    Foliage biomass models, Component ratio models, Bayesian hierarchical models, Posterior predictive checking, Prediction uncertainty

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