Dynamic Modeling of Carbon Metabolism During the Dormant Period Accurately Predicts the Changes in Frost Hardiness in Walnut Trees Juglans regia L.

The leafless period is often considered as inactive, although trees have to actively modulate their metabolism through the cold acclimation/deacclimation processes, to cope with frost exposure during winter and to restore growth ability in spring. Carbon metabolism is a key component of these processes through the osmotic control of extracellular ice formation and the trophic control of bud growth. The influence of temperature on the inter-conversion between starch and soluble carbohydrate has been evidenced for years, but we are currently missing an operational tool to predict starch vs. soluble carbohydrate contents during this period, which should allow to better predict frost hardiness. For this purpose, we exposed 1-year-old branches of Juglans regia to constant temperature for one to 3 weeks and measured the changes in carbohydrate composition at three periods (autumn, winter, and spring). As expected, the temperature significantly affected the changes in carbohydrate composition, but the water content and the sampling period were also relevant. Higher starch hydrolysis was observed at low temperature (<5°C) for all sampling periods. Starch hydrolysis was also observed at warm temperature, but in autumn only. These data were used to compare three modeling approaches simulating the changes in carbohydrate composition through enzymatic analogy. The most empirical and the most mechanistic approach did not succeed to simulate external observations (Root Mean Standard Error of Prediction (RMSEP) > 30 mg.g DM−1, Efficiency (Eff) <0), whereas the intermediate model was more efficient (RMSEP = 15.19 mg.g DM−1, Eff = 0.205 and 16.61 mg.g DM−1, Eff = 0.366, for GFS (Glucose + Fructose + Sucrose) and starch, respectively). The accuracy of the model was further improved when using field data for calibration (RMSEP = 5.86 mg.g DM−1, Eff = 0.962; RMSEP = 10.56 mg.g DM−1, Eff = 0.752, for GFS and starch, respectively). This study provided an operative tool to simulate carbohydrate dynamics over leafless period that could predict frost hardiness with approx. 3.4°C accuracy with temperature, water content and initial starch and soluble carbohydrate measurements. It should now be tested under various meteorological conditions and biological systems

A model for simulating structure-function relationships in walnut tree growth processes.

An ecophysiological growth process model, called INCA, for simulating the growth and development of a young walnut tree (Juglans regia L.) during three or four years, is presented. This tool, currently under development, aims at integrating architectural and physiological knowledge of the processes involved, in order to give a more rational understanding of the pruning operation. The model describes a simple three-dimensional representation of tree crown, solar radiation interception, photosynthesis, respiration, growth and partitioning of assimilates to leaves, stems, branches and roots. It supports the hypothesis that the tree grows as a collection of semiautonomous, interacting organs that compete for resources, based on daily sink strengths and proximity to sources. The actual growth rate of organs is not predetermined by empirical data, but reflects the pattern of available resources. The major driving variables are solar radiation, temperature, topological, geometrical and physiological factors. Outputs are hourly and daily photosynthate production and respiration, daily dimensional growth, starch storage, biomass production and total number of different types of organ. The user can interact or override any or all of the input variables to examine the effects of such changes on photosynthate production and growth. Within INCA, the tree entities and the surrounding environment are structured in a frame-based representation whereas the processes are coded in a rule-based language. The simulation mechanism is primarily based on the rule chaining capabilities of an inference engine

Age, allocation and availability of nonstructural carbon in mature red maple trees

The allocation of nonstructural carbon (NSC) to growth, metabolism and storage remains poorly understood, but is critical for the prediction of stress tolerance and mortality. We used the radiocarbon (14C) ‘bomb spike’ as a tracer of substrate and age of carbon in stemwood NSC, CO2 emitted by stems, tree ring cellulose and stump sprouts regenerated following harvesting in mature red maple trees. We addressed the following questions: which factors influence the age of stemwood NSC?; to what extent is stored vs new NSC used for metabolism and growth?; and, is older, stored NSC available for use? The mean age of extracted stemwood NSC was 10 yr. More vigorous trees had both larger and younger stemwood NSC pools. NSC used to support metabolism (stem CO2) was 1–2 yr old in spring before leaves emerged, but reflected current-year photosynthetic products in late summer. The tree ring cellulose 14C age was 0.9 yr older than direct ring counts. Stump sprouts were formed from NSC up to 17 yr old. Thus, younger NSC is preferentially used for growth and day-to-day metabolic demands. More recently stored NSC contributes to annual ring growth and metabolism in the dormant season, yet decade-old and older NSC is accessible for regrowth

Physiological controls of the isotopic time lag between leaf assimilation and soil CO2 efflux

EA EcolDur CT3International audienceEnvironmental factors and physiological controls on photosynthesis influence the carbon isotopic signature of ecosystem respiration. Many ecosystem studies have used stable carbon isotopes to investigate environmental controls on plant carbon transfer from above- to belowground. However, a clear understanding of the internal mechanisms underlying time-lagged responses of carbon isotopic signatures in ecosystem respiration to environmental changes is still lacking. This study addressed plant physiological controls on the transfer time of recently assimilated carbon from assimilation to respiration. We produced a set of six wheat plants with varying physiological characteristics, by growing them under a wide range of nitrogen supply and soil water content levels under standardised conditions. The plants were pulse-labelled with 13C-CO2, and the isotopic signature of CO2 respired in the dark by plants and soil was monitored continuously over two days. Stomatal conductance (gs) was strongly related to the rate of transfer of recently assimilated carbon belowground. The higher gs, the faster newly assimilated carbon was allocated belowground and the faster it was respired in the soil. Our results suggest that carbon sink strength of plant tissues may be a major driver of transfer velocity of recently assimilated carbon to plant respiratory tissues and soil respiration

Non-structural carbohydrates in woody plants compared among laboratories

Non-structural carbohydrates (NSC) in plant tissue are frequently quantified to make inferences about plant responses to environmental conditions. Laboratories publishing estimates of NSC of woody plants use many different methods to evaluate NSC. We asked whether NSC estimates in the recent literature could be quantitatively compared among studies. We also asked whether any differences among laboratories were related to the extraction and quantification methods used to determine starch and sugar concentrations. These questions were addressed by sending sub-samples collected from five woody plant tissues, which varied in NSC content and chemical composition, to 29 laboratories. Each laboratory analyzed the samples with their laboratory-specific protocols, based on recent publications, to determine concentrations of soluble sugars, starch and their sum, total NSC. Laboratory estimates differed substantially for all samples. For example, estimates for Eucalyptus globulus leaves (EGL) varied from 23 to 116 (mean = 56) mg g⁻¹ for soluble sugars, 6–533 (mean = 94) mg g⁻¹ for starch and 53–649 (mean = 153) mg g⁻¹ for total NSC. Mixed model analysis of variance showed that much of the variability among laboratories was unrelated to the categories we used for extraction and quantification methods (method category R² = 0.05–0.12 for soluble sugars, 0.10–0.33 for starch and 0.01–0.09 for total NSC). For EGL, the difference between the highest and lowest least squares means for categories in the mixed model analysis was 33 mg g⁻¹ for total NSC, compared with the range of laboratory estimates of 596 mg g⁻¹. Laboratories were reasonably consistent in their ranks of estimates among tissues for starch (r = 0.41–0.91), but less so for total NSC (r = 0.45–0.84) and soluble sugars (r = 0.11–0.83). Our results show that NSC estimates for woody plant tissues cannot be compared among laboratories. The relative changes in NSC between treatments measured within a laboratory may be comparable within and between laboratories, especially for starch. To obtain comparable NSC estimates, we suggest that users can either adopt the reference method given in this publication, or report estimates for a portion of samples using the reference method, and report estimates for a standard reference material. Researchers interested in NSC estimates should work to identify and adopt standard methods.This is the publisher’s final pdf. The published article is copyrighted by the author(s) and published by Oxford University Press. The published article can be found at: http://treephys.oxfordjournals.org/Keywords: soluble sugars, starch, particle size, reference method, standardization, non-structural carbohydrate chemical analysis, extraction and quantification consistenc