Although temperature is an important driver of seasonal changes in photosynthetic physiology, photoperiod also regulates leaf activity. Climate change will extend growing seasons if temperature cues predominate, but photoperiod-controlled species will show limited responsiveness to warming. We show that photoperiod explains more seasonal variation in photosynthetic activity across 23 tree species than temperature. Although leaves remain green, photosynthetic capacity peaks just after summer solstice and declines with decreasing photoperiod, before air temperatures peak. In support of these findings, saplings grown at constant temperature but exposed to an extended photoperiod maintained high photosynthetic capacity, but photosynthetic activity declined in saplings experiencing a naturally shortening photoperiod; leaves remained equally green in both treatments. Incorporating a photoperiodic correction of photosynthetic physiology into a global-scale terrestrial carbon-cycle model significantly improves predictions of seasonal atmospheric CO 2 cycling, demonstrating the benefit of such a function in coupled climate system models. Accounting for photoperiod-induced seasonality in photosynthetic parameters reduces modeled global gross primary production 2.5% (∼4 PgC y −1 ), resulting in a >3% (∼2 PgC y −1 ) decrease of net primary production. Such a correction is also needed in models estimating current carbon uptake based on remotely sensed greenness. Photoperiod-associated declines in photosynthetic capacity could limit autumn carbon gain in forests, even if warming delays leaf senescence.day length | gross primary productivity | carbon sequestration | leaf area index | evapotranspiration W arming over the past 50 y has lengthened temperate growing seasons by 3.6 d per decade (1, 2). Longer growing seasons may increase net ecosystem productivity (2, 3), but increased spring carbon uptake has been accompanied by reduced autumn carbon uptake (2, 4). In extratropical ecosystems, where spring temperature is a major control on bud break, increased carbon sink strength has been linked to warmer April and May temperatures (3, 4), although drought can offset the increase in carbon uptake (5). The autumn switch from being a carbon sink to a carbon source in these ecosystems has been attributed to higher autumn temperatures, which are assumed to maintain high photosynthetic rates but even higher respiration rates (6). However, it is well known that leaf phenology responds to photoperiod, as well as temperature (7). Seasonal fluctuations in photosynthetic parameters are often modeled with temperature (8). However, photosynthetic physiology has also been shown to respond to photoperiod in controlled studies; instituting a short-day treatment in the fall, but maintaining high summer growth temperatures, inhibited the photosynthetic capacity of Pinus banksiana seedlings (9, 10). Seasonal measurements of photosynthetic capacity in trees under naturally changing photoperiod and air temperature signals are needed to ascertain whe...

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Leaf gas exchange and temperature response were measured to assess temperature acclimation within a tree canopy in climatically contrasting genotypes of Acer rubrum L. Over the course of two 50 d continuous periods, growth temperature was controlled within tree crowns and the steady-state rate of leaf gas exchange was measured. Data were then modelled to calculate the influence of genotype variation and vertical distribution of physiological activity on carbon uptake. The maximal rate of Rubisco carboxylation (V(cmax)), the maximum rate of electron transport (J(max)), leaf dark respiration rate (R(d)), maximum photosynthesis (A(max)), and the CO(2) compensation point (Gamma) increased with temperature during both (i) a constant long-term (50 d) daytime temperature or (ii) ambient daytime temperature with short-term temperature control (25-38 degrees C). In addition, within-crown variation in the temperature response of photosynthesis and R(d) was influenced by acclimation to local microclimate temperature gradients. Results indicated that carbon uptake estimates could be overestimated by 22-25% if the vertical distribution of temperature gradients is disregarded. Temperature is a major factor driving photosynthetic acclimation and within-crown gas exchange variation. Thus, this study established the importance of including spatial acclimation to temperature- and provenance-, ecotype-, and/or genotype-specific parameter sets into carbon uptake models.

We investigated which parameters required by the MAESTRA model were most important in predicting leaf-area-based transpiration in 5-year-old trees of five deciduous hardwood species-yoshino cherry (Prunus x yedoensis Matsum.), red maple (Acer rubrum L. 'Autumn Flame'), trident maple (Acer buergeranum Miq.), Japanese flowering cherry (Prunus serrulata Lindl. 'Kwanzan') and London plane-tree (Platanus x acerifolia (Ait.) Willd.). Transpiration estimated from sap flow measured by the heat balance method in branches and trunks was compared with estimates predicted by the three-dimensional transpiration, photosynthesis and absorbed radiation model, MAESTRA. MAESTRA predicted species-specific transpiration from the interactions of leaf-level physiology and spatially explicit micro-scale weather patterns in a mixed deciduous hardwood plantation on a 15-min time step. The monthly differences between modeled mean daily transpiration estimates and measured mean daily sap flow ranged from a 35% underestimation for Acer buergeranum in June to a 25% overestimation for A. rubrum in July. The sensitivity of the modeled transpiration estimates was examined across a 30% error range for seven physiological input parameters. The minimum value of stomatal conductance as incident solar radiation tends to zero was determined to be eight times more influential than all other physiological model input parameters. This work quantified the major factors that influence modeled species-specific transpiration and confirmed the ability to scale leaf-level physiological attributes to whole-crown transpiration on a species-specific basis.

A spatially explicit mechanistic model, MAESTRA, was used to separate key parameters affecting transpiration to provide insights into the most influential parameters for accurate predictions of within-crown and within-canopy transpiration. Once validated among Acer rubrum L. genotypes, model responses to different parameterization scenarios were scaled up to stand transpiration (expressed per unit leaf area) to assess how transpiration might be affected by the spatial distribution of foliage properties. For example, when physiological differences were accounted for, differences in leaf width among A. rubrum L. genotypes resulted in a 25% difference in transpiration. An in silico within-canopy sensitivity analysis was conducted over the range of genotype parameter variation observed and under different climate forcing conditions. The analysis revealed that seven of 16 leaf traits had a ≥5% impact on transpiration predictions. Under sparse foliage conditions, comparisons of the present findings with previous studies were in agreement that parameters such as the maximum Rubisco-limited rate of photosynthesis can explain ∼20% of the variability in predicted transpiration. However, the spatial analysis shows how such parameters can decrease or change in importance below the uppermost canopy layer. Alternatively, model sensitivity to leaf width and minimum stomatal conductance was continuous along a vertical canopy depth profile. Foremost, transpiration sensitivity to an observed range of morphological and physiological parameters is examined and the spatial sensitivity of transpiration model predictions to vertical variations in microclimate and foliage density is identified to reduce the uncertainty of current transpiration predictions.