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Wiley, Global Change Biology, 12(22), p. 3996-4013, 2016

DOI: 10.1111/gcb.13315

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Variation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models

Journal article published in 2016 by Michelle O. Johnson, David Galbraith ORCID, Manuel Gloor, Hannes De Deurwaerder, Matthieu Guimberteau ORCID, Anja Rammig, Kirsten Thonicke ORCID, Hans Verbeeck, Celso von Randow, Abel Monteagudo, Celso Randow, Oliver L. Phillips, Roel J. W. Brienen, Ted R. Feldpausch, Gabriela Lopez Gonzalez and other authors.
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Understanding the processes that determine aboveground biomass (AGB) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models (DGVMs). AGB is determined by inputs from woody productivity (woody NPP) and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP, control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVMs. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB, which is consistent with the importance of stand size-structure for determining spatial variation in AGB. The relationship between stem mortality rates and AGB varies among different regions of Amazonia, indicating that variation in wood density and height/diameter relationships also influence AGB. In contrast to previous findings, we find that woody NPP is not correlated with stem mortality rates, and is weakly positively correlated with AGB. Across the four models, basin-wide average AGB is similar to the mean of the observations. However, the models consistently overestimate woody NPP, and poorly represent the spatial patterns of both AGB and woody NPP estimated using plot data. In marked contrast to the observations, DGVMs typically show strong positive relationships between woody NPP and AGB. Resolving these differences will require incorporating forest size structure, mechanistic models of stem mortality and variation in functional composition in DGVMs. This article is protected by copyright. All rights reserved.