Ages and transit times as important diagnostics of model performance for predicting carbon dynamics in terrestrial vegetation models

Abstract

Abstract. The global carbon cycle is strongly controlled by the source/sink strength of vegetation as well as the capacity of terrestrial ecosystems to retain this carbon. These dynamics, as well as processes such as the mixing of old and newly fixed carbon, have been studied using ecosystem models, but different assumptions regarding the carbon allocation strategies and other model structures may result in highly divergent model predictions. We modeled three systems of vegetation compartments and assessed their performance by calculating the age of the carbon in vegetation system and within each compartment, and 5 the overall transit time of C in the system. We used these diagnostics to assess the influence of three different carbon allocation schemes on the rates of C cycling in vegetation. First, we used published measurements of ecosystem C compartments from the Harvard Forest Environmental Measurement Site to find the best set of parameters for the different model structures. Second, we calculated C stocks, release fluxes, radiocarbon values based on the bomb spike, ages, and transit times. We found a good fit of the three model structures to the available data, but the time series of C in foliage and wood need to be complemented 10 with other ecosystem compartments in order to reduce the high parameter collinearity that we observed, and reduce model equifinality. Differences in model structures had a small impact on predicting C stocks in ecosystem compartments, but overall they resulted in very different predictions of age and transit time distributions. In particular, the inclusion of two storage compartments resulted in the prediction of a system mean age that was 10-20 years older than in the models with one or no storage compartments. The age of carbon in the wood compartment of this model was also distributed towards older ages, 15 whereas fast cycling compartments had an age distribution that did not exceed 5 years. As expected, models with C distributed towards older ages also had longer transit times. These results suggest that ages and transit times, which can be indirectly measured using isotope tracers, serve as important diagnostics of model structure and could largely help to reduce uncertainties in model predictions. Furthermore, by considering age and transit times of C in vegetation compartments as distributions, not only their mean values, we obtain additional insights on the temporal dynamics of carbon use, storage, and allocation to plant 20 parts, which not only depends on the rate at which this C is transferred in and out of the compartments, but also on the stochastic nature of the process itself. 1Biogeosciences Discuss., https://doi

Probability distributions of nonstructural carbon ages and transit times provide insights into carbon allocation dynamics of mature trees

“…To represent and understand these dynamics, compartmental models have been proposed where NSC is allocated to both organ‐specific compartments (e.g. leaves, stems and roots) and compound‐specific compartments (Richardson et al , 2012; Klein & Hoch, 2015; Ceballos‐Núñez et al , 2018).…”

“…In trees, NSC dynamics determine the age and transit time distributions of the C in the different organ‐specific and compound‐specific pools (Ceballos‐Núñez et al , 2018). Carbon age is defined as the time elapsed after a C atom enters the system until the time of observation (Bolin & Rodhe, 1973), that is, an age of zero represents the moment of C fixation from the atmosphere.…”

“…Carbon age is defined as the time elapsed after a C atom enters the system until the time of observation (Bolin & Rodhe, 1973), that is, an age of zero represents the moment of C fixation from the atmosphere. Transit time is defined as the time that a C atom remains in the system until it exits (Ceballos‐Núñez et al , 2018). To give an example: when defining our observed system as all the NSC in a tree, C atoms would enter through photosynthesis (with age equal to zero) and leave when being allocated to the formation of structural tissue (growth) or to catabolic requirements (e.g.…”

“…Here, we define NSC transit time as the time elapsed between these two points. These definitions allow us to estimate the distributions of the NSC ages and NSC transit times across all C pools using models (Ceballos‐Núñez et al , 2018; Metzler et al , 2018). This offers a useful alternative to evaluate NSC dynamics in trees.…”

“…For healthy, unstressed trees not experiencing C limitation, NSC in respiration and growth consists mainly of C from the current growth year (< 1 yr old) (Richardson et al , 2015; Muhr et al , 2018). However, previous studies have shown that trees under C supply limitation start mobilizing stored C, resulting in an increase in the mean age of the C used for new growth or metabolism (Vargas et al , 2009; Carbone et al , 2013; Trumbore et al , 2015; Ceballos‐Núñez et al , 2018; Muhr et al , 2018). How the quantity and mobility of stored C vary with tree species and/or between organs in the same tree will result in different age and transit time distributions.…”