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bioRxiv · 10.1101/2023.08.10.552736

Plant allometry derived from Metabolic Scaling Theory and segregated by tissue functionality

Abstract

Plant allometry is key for determining the role of forests in global carbon cycles, through the calculation of tree biomass using proxy measurements such as tree diameters or heights. Metabolic Scaling Theory (MST) considers the general principles that underpin allometry, but MST scaling relationships have been challenged on their lack of fit to empirical data and global applicability. Many authors have thus optimised their model forms for statistical performance over theory based approaches. We postulated that MST scaling is applicable only to the proportion of plant tissue with supportive functionality, meaning that as plants evolved tissues of specialized conductive functionality (e.g vessels) their allometry progressed into more complex relationships. Our generalised MST (gMST) models were thus created by considering conductive lumen as unsupportive area, and consequentially removing it from the original MST 2/3 scaling. According to this principle, we deducted generalized gMST relationships with mechanistically deducted coefficients. We found that the gMST height-diameter scaling outperformed current state of the art equations that are widely used within the tropics and that the model performed well across all tested ecoregions. Furthermore, the proposed aboveground biomass models performed similarly to widely used models in the literature within the tropics. The results presented indicate that the further development of generalised allo-metric models remains a research priority given the importance of assessing and monitoring global forest carbon fluxes. The height-diameter models presented can thus be of much use to the wider community in further refining carbon stock estimates globally, providing a universally applicable theoretical framework.

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BibTeXRIS

Sopp, S., Valbuena, R.. 2023-08-11. Plant allometry derived from Metabolic Scaling Theory and segregated by tissue functionality. https://doi.org/10.1101/2023.08.10.552736

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