Global patterns of woody residence time and its influence on model simulation of aboveground biomass

Abstract

Running Title: forest woody residence time and biomass modeling Key Points:(1) Woody residence time (τ w , years) is related to forest age, annual temperature and precipitation.(2) Influences of meteorological drivers on τ w are different among various plant functional types.(3) The estimated global forest τ w shows large spatial heterogeneity and this strongly AbstractWoody residence time (τ w ) is an important parameter that expresses the balance between mature forest recruitment/growth and mortality. Using field data collected from the literature, this study explored the global forest τ w and investigated its influence on model simulations of aboveground biomass (AGB) at a global scale. Specifically, τ w was found to be related to forest age, annual temperature and precipitation at a global scale, but its determinants were different among various plant function types. The estimated global forest τ w based on the filed data showed large spatial heterogeneity, which plays an important role in model simulation of AGB by a Dynamic Global Vegetation Model (DGVM). τ w could change the resulting AGB in 10-fold based on a site-level test using the Monte Carlo method. At the global level, different parameterization schemes of the Integrated Biosphere Simulator using the estimated τ w resulted in a two-fold change in the AGB simulation for 2100. Our results highlight the influences of various biotic and abiotic variables on forest τ w . The estimation of τ w in our study may help improve the model simulations and reduce the parameter's uncertainty over the projection of future AGB in the current DGVM or Earth System Models.A clearer understanding of the responses of τ w to climate change and the corresponding sophisticated description of forest growth/mortality in model structure is also needed for the improvement of carbon stock prediction in future studies.

Underestimated ecosystem carbon turnover time and sequestration under the steady state assumption: A perspective from long‐term data assimilation

“…In addition, the vegetation C partition scheme varies with stand age (Zhou, Shi, et al., ). The decisive role of whole‐vegetation turnover time in determining the uncertainty in ecosystem C storage capacity has been supported by recent modeling and experimental research (Friend et al., ; Medlyn et al., ; Xue et al., ). Therefore, our results further highlight the need to focus on the deviation in vegetation C turnover time under the SSA to avoid considerable bias in ecosystem MTT and thus the C sequestration estimation.…”

Variations of carbon allocation and turnover time across tropical forests

“…Most of the current DGVMs use a fixed turnover rate (or mortality rate) for wood biomass and they do not explicitly simulate tree mortality attributable to factors such as fire, competition, insects and pathogens. A few exceptions (e.g., LPJ and LPJ‐GUESS models) do not use a simple fixed value, and they calculate the mortality rate attributable to negative carbon balance, competition, harsh climate and fire (Xue et al., 2017). Our gridded turnover time/rate of carbon pools might help to improve model structure or parameterization schemes.…”

“…Thus, it is useful to compute the carbon allocation and turnover time of individual pools separately. At the plot level, carbon allocation and turnover time within the major carbon pools have been measured (Chen et al., 2013; Keeling & Phillips, 2007; Xue et al., 2017), but information on large‐scale patterns of carbon allocation and turnover is still lacking. Moreover, using tree‐ring data or ground measurements, previous studies found a trade‐off between the growth and the life span of trees (Brienen et al, 2020; Stephenson & van Mantgem, 2005), but it still remains unknown whether the hypothesis of “grow fast, die fast” holds good at the ecosystem scale.…”

The Transferability of Random Forest in Canopy Height Estimation from Multi-Source Remote Sensing Data

“…Moreover, as a carbon sink, forest dynamics are closely related to the global carbon cycle and climate changes [2][3][4]. Canopy height is an important forest structure parameter for understanding the forest ecosystem, and has been used to estimate forest aboveground biomass and therefore model the global carbon stock and carbon dynamics [5][6][7][8].…”