Seasonal dynamics and age of stemwood nonstructural carbohydrates in temperate forest trees

Richardson, Andrew D.; Carbone, Mariah S.; Keenan, Trevor F.; Czimczik, C. I.; Hollinger, David Y.; Murakami, Paula F.; Schaberg, Paul G.; Xu, Xiaomei

doi:10.1111/nph.12042

Cited by 356 publications

(406 citation statements)

References 64 publications

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“…They found that leaf phenology, NSC storage and intra-annual growth were clearly different between species, highlighting their contrasting carbon allocation. Very recently, the seasonal dynamics and ages of stemwood NSC in temperate forest trees has been assessed by Richardson et al (2013). These authors found that NSC were both highly dynamic and about a decade old.…”

Section: Does Leaf Production Impact Wood Production?mentioning

confidence: 97%

Asynchronism in leaf and wood production in tropical forests: a study combining satellite and ground-based measurements

Wagner

Rossi²,

Stahl

et al. 2013

Biogeosciences

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Abstract. The fixation of carbon in tropical forests mainly occurs through the production of wood and leaves, both being the principal components of net primary production. Currently field and satellite observations are independently used to describe the forest carbon cycle, but the link between satellite-derived forest phenology and field-derived forest productivity remains opaque. We used a unique combination of a MODIS enhanced vegetation index (EVI) dataset, a wood production model based on climate data and direct litterfall observations at an intra-annual timescale in order to question the synchronism of leaf and wood production in tropical forests. Even though leaf and wood biomass fluxes had the same range (respectively 2.4 ± 1.4 and 2.2 ± 0.4 Mg C ha −1 yr −1 ), they occurred separately in time. EVI increased with leaf renewal at the beginning of the dry season, when solar irradiance was at its maximum. At this time, wood production stopped. At the onset of the rainy season, when new leaves were fully mature and water available again, wood production quickly increased to reach its maximum in less than a month, reflecting a change in carbon allocation from short-lived pools (leaves) to long-lived pools (wood). The time lag between peaks of EVI and wood production (109 days) revealed a substantial decoupling between the leaf renewal assumed to be driven by irradiance and the water-driven wood production. Our work is a first attempt to link EVI data, wood production and leaf phenology at a seasonal timescale in a tropical evergreen rainforest and pave the way to develop more sophisticated global carbon cycle models in tropical forests.

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Section: Does Leaf Production Impact Wood Production?mentioning

confidence: 97%

Asynchronism in leaf and wood production in tropical forests: a study combining satellite and ground-based measurements

Wagner

Rossi²,

Stahl

et al. 2013

Biogeosciences

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“…Similarly, we calculated that the size of the NSC pool in branches + stems were 4.6-and sixfold greater than the C pools in the leaf canopy of larch and ash, respectively. However, the residence time of NSC storage could be several years, and only a small fraction of the NSC pool is likely to be mobilized during a growing season under normal conditions (Würth et al 2005;Vargas et al 2009;Richardson et al 2013). In our study, the NSC mobilized from storage organs from mid-May to mid-June accounted for 20 and 31 % of the whole-tree NSC pool in larch and ash, respectively, which are comparable to values (less than one-third) reported in other studies (Hoch et al 2003;Würth et al 2005;Körner 2003).…”

Section: Seasonal Dynamics Of the Sizes Of Nsc And N Pools In Differementioning

confidence: 99%

Whole-tree dynamics of non-structural carbohydrate and nitrogen pools across different seasons and in response to girdling in two temperate trees

Mei

Xiong

et al. 2014

Oecologia

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mobilized to maintain root activities during the growing season. Tree mortality was observed 1 year after girdling, at which time there was still an abundant NSC pool in the roots. We conclude that (1) different storage organs differ in their contribution to new tissue growth at the beginning of the growing season and that those storage organs holding higher fractions of the NSC or N pool are not necessarily those which mobilize more NSC or N; (2) tree growth may not be limited by carbon (C) availability; (3) C storage in non-absorptive roots plays an important role in maintaining tree survival after the termination of photosynthate flow from aboveground sources.

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“…These strategies differ in the number of storage compartments, Storage: 0, Storage: 1, and Storage: 2. Adapted from (Richardson et al, 2013). The parameters are the rates at which the carbon cycles into and out of the compartments; thus, the fluxes are proportional to the C stocks and the rates.…”

Section: Methodsmentioning

confidence: 99%

“…We implemented three models whose carbon allocation strategies varied depending on the number of storage compartments (0, 1, or 2) (Figure 2), following the hypotheses proposed by Richardson et al (2013). The core structure of the models is a constant photosynthetic input -gross primary production (GPP): u-of 1400 gCm −2 year −1 (Urbanski et al, 2007), which enters the system through the Photoassimilates compartment.…”

Section: Methodsmentioning

confidence: 99%

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

Ceballos-Núñez¹,

Richardson²,

Sierra³

2017

Preprint

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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

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Seasonal dynamics and age of stemwood nonstructural carbohydrates in temperate forest trees

Cited by 356 publications

References 64 publications

Asynchronism in leaf and wood production in tropical forests: a study combining satellite and ground-based measurements

Asynchronism in leaf and wood production in tropical forests: a study combining satellite and ground-based measurements

Whole-tree dynamics of non-structural carbohydrate and nitrogen pools across different seasons and in response to girdling in two temperate trees

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

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