Daily Canopy Photosynthesis Research Articles

Improving satellite-based modelling of gross primary production in deciduous broadleaf forests by accounting for seasonality in light use efficiency

ABSTRACTVegetation gross primary production (GPP), the photosynthetic yields by green plants per unit area per unit time, is a key metric of carbon flux in understanding the land–atmosphere interactions and terrestrial carbon cycles. Satellite-based light use efficiency (LUE) models are valuable methods to retrieve large-scale terrestrial GPP using remote sensing data. As studies have reported that maximum light use efficiency, a key parameter that is often assumed to be constant in the LUE models, there is a need to explore the effects of LUE seasonality on GPP simulation and ways for correction. This study proposes a method based on leaf area index to account for LUE seasonality and applies it to four different light use efficiency models (i.e., the MOD17 algorithm, the vegetation photosynthesis model, the radiation partitioning model, and the vegetation index model) for comparisons. Based on 59 site-years flux tower data from deciduous broadleaf forest sites in the United States, the results show that all models could simulate daily GPP time series well and explain more than 85.0% variance of tower-based GPP. There is, however, a tendency to overestimate GPP during the non-growing season but underestimate GPP during the growing season. By applying the correction function, GPP simulation using the LUE models improved in all experiments as indicated by increased correlation coefficients, the index of agreement and decreased root-mean-square errors. Among all models, the radiation partitioning model achieves the highest correlation coefficients between modelled and observed daily GPP likely because it considers the influences of direct and diffuse radiation partitioning on daily canopy photosynthesis. Our study indicates that satellite-based light use efficiency models could be successfully applied for deriving daily vegetation GPP and potentially producing daily routine satellite products, while considering the effects of LUE seasonality on canopy could help improve significantly the simulation accuracy of daily GPP in phenology.

A risk-benefit model to simulate vegetation spring onset in response to multi-decadal climate variability: Theoretical basis and applications from the field to the Northern Hemisphere

Vegetation spring onset regulates canopy photosynthetic activities and subsequent ecosystem processes, thereby influencing the complex interactions between the biosphere and the atmosphere. Robust models that predict the timing of vegetation spring onsets are required to account for the ecosystem response and adaption to climate variability. Here, a risk-benefit model is proposed to account for the fundamental tradeoff underlying plant leafing strategies: earlier timing of leaf-out events leads to greater vegetative carbon gain but higher risks associated with hazard damages. The proposed model named the Growing Production-Day (GPD) model uses the cumulative productivity of a hypothetical reference vegetation cover as the overall benefit and predicts the events of vegetation spring onset when a certain threshold that vegetation invests to mitigate potential hazard damages is reached. The daily canopy photosynthesis of the hypothetical reference vegetation cover is simulated by a two-leaf canopy model, which considers sunlit and shaded leaves within a canopy separately and accounts for the biogeochemical processes of canopy radiative transfer, leaf photosynthesis, leaf conductance, leaf transpiration, and soil evaporation. When validated against measurements from available flux tower sites of deciduous broadleaf forests, the two-leaf canopy model accurately simulated daily canopy photosynthesis and evapotranspiration rates, indicated by significant correlations (R2=0.787 and 0.745 for gross primary production and latent heat, respectively) and low root-mean-square errors (RMSE=2.25gCm2day−1 for gross primary production and 21.53Wm−2 for latent heat, respectively) between the observed and modeled values. Based on the two-leaf canopy model, the GPD model predicted the dates of spring onsets accurately for three studied biomes (RMSE=9.10, 5.54, and 12.76days for evergreen needleleaf forests, deciduous broadleaf forests, and grasslands, respectively) as derived from the flux tower data. In addition, the GPD model could simulate the long-term interannual variation of species-level leaf onset dates as obtained from in-situ observations, and capture the spatiotemporal patterns of multi-decadal variation of vegetation spring onsets across the Northern Hemisphere as derived from satellite data. Although the GPD model requires further refinements, it shows promises with respect to simulating vegetation spring onset in response to multi-decadal climate variability.

Instantaneous-to-daily GPP upscaling schemes based on a coupled photosynthesis-stomatal conductance model: correcting the overestimation of GPP by directly using daily average meteorological inputs.

Daily canopy photosynthesis is usually temporally upscaled from instantaneous (i.e., seconds) photosynthesis rate. The nonlinear response of photosynthesis to meteorological variables makes the temporal scaling a significant challenge. In this study, two temporal upscaling schemes of daily photosynthesis, the integrated daily model (IDM) and the segmented daily model (SDM), are presented by considering the diurnal variations of meteorological variables based on a coupled photosynthesis-stomatal conductance model. The two models, as well as a simple average daily model (SADM) with daily average meteorological inputs, were validated using the tower-derived gross primary production (GPP) to assess their abilities in simulating daily photosynthesis. The results showed IDM closely followed the seasonal trend of the tower-derived GPP with an average RMSE of 1.63 g C m(-2) day(-1), and an average Nash-Sutcliffe model efficiency coefficient (E) of 0.87. SDM performed similarly to IDM in GPP simulation but decreased the computation time by >66%. SADM overestimated daily GPP by about 15% during the growing season compared to IDM. Both IDM and SDM greatly decreased the overestimation by SADM, and improved the simulation of daily GPP by reducing the RMSE by 34 and 30%, respectively. The results indicated that IDM and SDM are useful temporal upscaling approaches, and both are superior to SADM in daily GPP simulation because they take into account the diurnally varying responses of photosynthesis to meteorological variables. SDM is computationally more efficient, and therefore more suitable for long-term and large-scale GPP simulations.

Leaf nitrogen distribution to maximize the canopy photosynthesis in rice

The optimum distribution of leaf nitrogen (N) in the canopy of rice plants ( Oryza sativa L.) for maximum daily canopy photosynthesis (DCP) and the optimization effects on DCP were estimated during the grain filling period. The low- and high-density canopies (28.3 and 47.5 plants m −2) and isolated plants were established at heading using plants in pots grown up at the low density until heading to make the same canopy architecture except plant density and the same leaf N distribution at the start of treatment among the two canopies and the isolated plants. The simulation was conducted under two conditions of the upper limit of leaf N. Under condition 1, upper limit of leaf N content was 1.80 g m −2. Under condition 2, upper limits were measured leaf N content in each leaf position at heading. The model indicates that if leaf N content in the upper leaves can be increased with reduction of N in the lower leaves, DCP will increase in any of the plant density, light conditions and under conditions 1 and 2. On a clear day, the estimated increase in DCP was 19–45 and 38–70% in the low- and high-density canopies under condition 1, respectively. Even under condition 2, which is more realistic than condition 1, the increase was up to 21 and 25% in the low- and high-density canopies. These estimates obtained by the present model that incorporates the shading effects of panicles and stems on DCP were higher than the previous reports which did not consider the effects of shading by panicles and stems. In the observed leaf N distribution, the higher the plant density was, the steeper the gradient of the leaf N remained. The gradient in the high-density canopy was closer to that of the predicted optimum leaf N distribution, and likely to contribute to maintaining higher DCP in the canopies. Compared with the hypothetical case in which gradient of leaf N distribution would be more gentle as observed in the isolated plants, the maintained steeper gradient of observed leaf N content in the canopies was estimated to increase DCP by 13 and 5% in the high- and low-density canopy, respectively.

Elevated CO2 and nitrogen availability have interactive effects on canopy carbon gain in rice.

• Here we analysed the effects of CO2 (Ca ) elevation and nitrogen availability on canopy structure, leaf area index (LAI) and canopy photosynthesis of rice (Oryza sativa). • Rice was grown at ambient and elevated Ca (c. 200µmolmol-1 above ambient, using the free-air CO2 enrichment, FACE) and at two N availabilities. We measured leaf area, area-based leaf N contents and leaf photosynthesis, and calculated net daily canopy photosynthesis. • FACE plants had higher light-saturated rates of photosynthesis (Pmax ) and apparent quantum yields than ambient plants, when measured at their own growth CO2 . Ca elevation reduced the total leaf N in the canopy (Nleaf ) but had no effect on LAI, and the average leaf N content (Nleaf /LAI) was therefore reduced by 8%. This reduction corresponded well with our model predictions. Leaf area index increased strongly with N availability, which was also consistent with our model. • Calculated canopy photosynthesis increased more strongly with Nleaf under elevated than under ambient Ca . This indicates that there is an N×Ca interactive effect on canopy carbon gain. This interaction was caused by the increase in LAI with N availability, which enhanced the positive effect of the higher quantum yield under Ca elevation.

Canopy Structure, Light Interception, and Photosynthesis in Maize

The amount and distribution of leaf area and leaf angles in a crop canopy determine how photosynthetically active radiation (PAR) is intercepted and consequently influences canopy photosynthesis and yield. Factors such as plant shape, plant populations, and row width will affect these leaf distributions and can occur in an almost infinite number of different combinations. To supplement experimentation, a mathematical model was developed to use measurements of leaf area and leaf angles in two dimensions (with height and across the row) to calculate PAR interception and canopy photosynthesis. Maize (Zea mays L.) hybrids with phenotypic differences were planted at several plant populations to produce a wide range of two‐dimensional leaf area and leaf angle patterns. The extreme phenotypes, leafy and reduced stature, were included to vary plant height and number of leaves above the ear. Measurements of average PAR at various levels were made in seven different canopies and compared with calculations from the model (R2 of 0.68 and 0.92 for two sets of data). As well, measurements of PAR at 20‐cm increments on transects perpendicular to the row were made in three canopy types at three levels and compared with theoretical calculations (R2 = 0.74). A simple numerical experiment was run to demonstrate the utility of the model where daily canopy photosynthesis was calculated for two row widths and seven plant types. One result was that depending on row widths, plants with very upright leaves can have both the smallest and largest daily canopy photosynthesis.

Retrieval of vegetation clumping index using hot spot signatures measured by POLDER instrument

The potential use of the information from a sampling of the bidirectional reflectance distribution function (BRDF) has suffered from the lack of solid applications in ecology, where it is expected to play the role of an advanced descriptor of vegetation as a complement to hyperspectral measurements. Such a shortcoming stems from the lack of consistent angular data sets with an adequate resolution at global scale. In this context, the POLDER instrument is particularly relevant because it acquires directional radiance signatures at a high angular resolution and thereby provides the first global BRDF product. In this paper, we investigate how to discriminate vegetation types in using only a portion of the BRDF, in particular, the two paramount directional signatures, which are the maximum (hot spot) and the minimum (dark spot) of reflectance observed in the backscattering and forward scattering regions, respectively. A directional index hot–dark spot (HDS) is formulated using these two signatures. It is defined as the normalized difference between the reflectances at the hot spot and dark spot. It is shown that the HDS can be linearly related with the foliage clumping index for three different vegetation types observed by the spaceborne POLDER sensor. The significance of the clumping index mapping for ecological studies is evaluated using the Boreal Ecosystem Productivity Simulator (BEPS). Considering foliage clumping in BEPS, the estimation of daily canopy photosynthesis can differ about 20% for a black spruce site. In this context, it is expected that the findings of this study will have a strong impact on the use of directional optical remote sensing to improve the assessment of terrestrial productivity and carbon cycle.

Daily canopy photosynthesis model through temporal and spatial scaling for remote sensing applications

Because Farquhar’s photosynthesis model is only directly applicable to individual leaves instantaneously, considerable skill is needed to use this model for regional plant growth and carbon budget estimations. In many published models, Farquhar’s equations were applied directly to plant canopies by assuming a plant canopy to function like a big-leaf. This big-leaf approximation is found to be acceptable for estimating seasonal trends of canopy photosynthesis but inadequate for simulating its day-to-day variations, when compared with eddy-covariance and gas-exchange chamber measurements from two boreal forests. The daily variation is greatly dampened in big-leaf simulations because the original leaf-level model is partially modified through replacing stomatal conductance with canopy conductance. Alternative approaches such as separating the canopy into sunlit and shaded leaf groups or stratifying the canopy into multiple layers can avoid the problem. Because of non-linear response of leaf photosynthesis to meteorological variables (radiation, temperature and humidity), considerable errors exist in photosynthesis calculation at daily steps without considering the diurnal variability of the variables. To avoid these non-linear effects, we have developed an analytical solution to a simplified daily integral of Farquhar’s model by considering the general diurnal patterns of meteorological variables. This daily model not only captures the main effects of diurnal variations on photosynthesis but is also computationally efficient for large area applications. Its application is then not restricted by availability of sub-daily meteorological data. This scheme has been tested using measured CO 2 data from the Boreal Ecosystem–Atmosphere Study (BOREAS), which took place in Manitoba and Saskatchewan in 1994 and 1996.

Net primary productivity distribution in the BOREAS region from a process model using satellite and surface data

The purpose of this paper is to upscale tower measurements of net primary productivity (NPP) to the Boreal Ecosystem‐Atmosphere Study (BOREAS) study region by means of remote sensing and modeling. The Boreal Ecosystem Productivity Simulator (BEPS) with a new daily canopy photosynthesis model was first tested in one coniferous and one deciduous site. The simultaneous CO2 flux measurements above and below the tree canopy made it possible to isolate daily net primary productivity of the tree canopy for model validation. Soil water holding capacity and gridded daily meteorological data for the region were used as inputs to BEPS, in addition to 1 km resolution land cover and leaf area index (LAI) maps derived from the advanced very high resolution radiometer (AVHRR) data. NPP statistics for the various cover types in the BOREAS region and in the southern study area (SSA) and the northern study area (NSA) are presented. Strong dependence of NPP on LAI was found for the three major cover types: coniferous forest, deciduous forest and cropland. Since BEPS can compute total photosynthetically active radiation absorbed by the canopy in each pixel, light use efficiencies for NPP and gross primary productivity could also be analyzed. From the model results, the following area‐averaged statistics were obtained for 1994: (1) mean NPP for the BOREAS region of 217 g C m−2 yr−1; (2) mean NPP of forests (excluding burnt areas in the region) equal to 234 g C m−2 yr−1; (3) mean NPP for the SSA and the NSA of 297 and 238 g C m−2 yr−1, respectively; and (4) mean light use efficiency for NPP equal to 0.40, 0.20, and 0.33 g C (MJ APAR)−1 for deciduous forest, coniferous forest, and crops, respectively.

Models of CO 2 and water vapour fluxes from a sparse millet crop in the Sahel

Canopy fluxes of water vapour and CO 2 from a sparse millet crop are simulated on the basis of a leaf scale model designed to predict stomatal conductance, leaf temperature, transpiration rate and photosynthetic rate for millet on a diurnal basis. The modelled leaf fluxes are extrapolated using two different big-leaf approaches. In the traditional big-leaf approach, all leaves are exposed to the same microenvironment which is different from the environmental conditions above the canopy, whereas in the modified big-leaf approach the canopy is regarded as a partly shaded big-leaf. In the sun/shade big-leaf model, soil reflection, diffuse radiation and separate evaluations of the radiation load on sunlit and shaded leaf surfaces are taken into account. Due to the low fraction of shaded leaves in the sparse canopy, the two types of big-leaf models predict both canopy fluxes equally well. The sensitivity of the modelled fluxes to the various input parameters was ranked for the identification of the most important parameters controlling photosynthesis and transpiration. This information is used for identification of more simple scaling models aimed at predicting daily canopy fluxes. The influx of sensible heat to the leaf was found to be an important energy source for transpiration. It was confirmed that daily transpiration can be parameterized by the air humidity gradient using only the leaf area index (LAI) for the evaluation of seasonal changes in bulk stomatal conductance. The photosynthetic rate was found to be most sensitive to radiation and leaf temperature. It is shown that the daily canopy photosynthesis can be estimated on the basis of LAI and midday values (1200 h) of incoming radiation density and leaf temperature.

Estimation of Canopy Photosynthesis in Rice by Means of Daily Increases in Leaf Carbohydrate Concentrations

Procedures for rapid measurement of canopy photosynthesis are needed because current methods are time consuming and labor intensive. Our objective was to demonstrate that daily increases in nonstructural carbohydrates of shoots provide a good estimate of daily canopy photosynthesis for rice (Oryza sativa L.). Four cultivars— ‘IR72’, ‘IR64’, ‘IR50’, and ‘YRL39’— were grown in the field on a verlic tropaquept clay soil. Canopy photosynthesis was measured in the field every 2 h from sunrise (0600 h) to sunset (1800 h) and plotted over time to determine daily photosynthesis. Increases in shoot nonstructural carbohydrates per day were calculated by subtracting sunrise concentrations from those at sunset. Highly significant positive relationships between daily canopy photosynthesis and irradiance (r2 = 0.999) and leaf soluble sugars and irradiance (r2 = 0.981) were observed. Coefficients of determination for relationships between daily canopy photosynthesis and daily increases in leaf soluble sugars were high (r2 = 0.987). Growth stage comparisons showed the highest coefficients of determination at panicle initiation because non‐structural carbohydrates in the shoot were dependent on canopy light interception and photosynthesis. Relationships during flowering were intermediate because the spikelet was the main carbon sink. Removal of panicles at flowering increased coefficients of determination to r2 = 0.8. Relationships among cultivars for daily irradiance versus daily canopy photosynthesis or daily increases in leaf soluble sugars had r2 values of 0.7 to 1.0. We conclude that measuring daily increases in leaf carbohydrates can provide a simple, rapid screening procedure for evaluating canopy photosynthesis in rice.

CO 2 Elevation, Canopy Photosynthesis, and Optimal Leaf Area Index

We studied the effects of CO2 elevation on leaf and canopy photosynthesis and optimal leaf area index (LAI) for stands of the annual species Abutilon theophrasti and Ambrosia artemisiifolia. Leaf photosynthesis was modeled as a function of photosyn- thetic photon flux density (PPFD) and nitrogen content per unit leaf area (NL). There was a curvilinear relationship between the light-saturated rates of leaf photosynthesis (Pmax) and NL. CO2 elevation significantly increased Pmax as a function of NL in both species. Dark respiration (Rd) was linearly correlated with NL. CO2 elevation slightly but significantly increased Rd in Abutilon, while it had no significant effect on Rd in Ambrosia. The initial slope of a light-response curve was determined from quantum yield (4gabs) multiplied by leaf absorptance and then calibrated against NL. Daily canopy photosynthesis, calculated by integration of leaf photosynthesis with the actual distribution of leaf area, leaf N, and PPFD within a canopy, showed fairly good agreement with the canopy photosynthesis estimated from growth analysis. CO2 elevation increased canopy photosynthesis by 30- 50%. Based on the leaf photosynthesis model for Abutilon, we calculated daily canopy photosynthesis for a given LAI and N availability, in which N was assumed to be distributed optimally within a leaf canopy to maximize daily canopy photosynthesis. An optimal LAI to maximize daily canopy photosynthesis was obtained for each level of N availability and this optimum increased with increasing N availability. Contrary to the often predicted increase in LAI with CO2 elevation, the optimum LAI did not increase at high CO2 when N availability was limited. Two factors were suggested to be involved in counteracting the increase in LAI in a high-CO2 world. One is the higher 4abs of plants grown in elevated C02, which makes leaves in the canopy more N limited, favors higher NL and thus lowers optimal LAI. The other is the higher Rd in elevated C02, which leads to higher light compensation points, and lowers optimal LAI.

CO2ELEVATION, CANOPY PHOTOSYNTHESIS, ANDOPTIMAL LEAF AREA INDEX

We studied the effects of CO2 elevation on leaf and canopy photosynthesis and optimal leaf area index (LAI) for stands of the annual species Abutilon theophrasti and Ambrosia artemisiifolia. Leaf photosynthesis was modeled as a function of photosynthetic photon flux density (PPFD) and nitrogen content per unit leaf area (NL). There was a curvilinear relationship between the light-saturated rates of leaf photosynthesis (Pmax) and NL. CO2 elevation significantly increased Pmax as a function of NL in both species. Dark respiration (Rd) was linearly correlated with NL. CO2 elevation slightly but significantly increased Rd in Abutilon, while it had no significant effect on Rd in Ambrosia. The initial slope of a light-response curve was determined from quantum yield (ϕabs) multiplied by leaf absorptance and then calibrated against NL. Daily canopy photosynthesis, calculated by integration of leaf photosynthesis with the actual distribution of leaf area, leaf N, and PPFD within a canopy, showed fairly good agree...

Leaf carbohydrate analysis - a simple method for integrating daily canopy photosynthesis

Leaf carbohydrate analysis - a simple method for integrating daily canopy photosynthesis

Modelling daily net canopy photosynthesis and its adaptation to irradiance and atmospheric CO2 concentration

Abstract A model to calculate the daily rate of net canopy photosynthesis in response to irradiance and atmospheric CO2, incorporating adaptation to growth conditions, is presented. Adaptation is treated by assuming that the plant protein nitrogen content varies so as to maximize daily net photosynthesis through its effect on gross photosynthesis and respiratory losses. Net photosynthesis is calculated using daily mean direct solar and diffusesky radiation components, estimated from total daily solar radiation. The behaviour of the model is consistent with patterns observed in the literature. For maximum net canopy photosynthesis, nitrogen levels in C4 plants are predicted to be significantly lower than for C3. Large changes in single-leaf photosynthetic capacity may not translate into large variation in net canopy photosynthesis. The optimum protein nitrogen level is predicted to decrease with increasing atmospheric CO2. The model implies that the long-term optimum value of the maximum rate of leaf gross photosynthesis will be less than that observed in the short term, and that maintenance respiration will decline in the long term, due to a decrease in the optimum level of plant protein nitrogen at higher CO2 levels. The approach presented is simple enough to be readily incorporated into crop, pasture and ecosystem models, while allowing for representation of several important physiological responses.

Modelling Canopy Production. II. From Single-Leaf Photosynthesis Parameters to Daily Canopy Photosynthesis

This paper presents a simple algorithm for calculating daily canopy photosynthesis given parameters of the single-leaf light response, the canopy extinction coefficient, canopy leaf area index, daylength, daily solar irradiance and daily maximum and minimum temperatures. Analytical expressions are derived for total daily production by a canopy of leaves whose light response is either a rectangular hyperbola or a Blackman response. An expression which gives an excellent approximation to canopy photosynthesis for an arbitrary hyperbolic light response is then derived. These expressions assume photosynthetically active radiation (PAR) within the canopy follows Beer's law, light-saturated photosynthetic rate at any point in the canopy is proportional to the ratio of local PAR to full-sun PAR, diurnal variation of PAR is sinusoidal, and parameters of the single-leaf photosynthetic light response do not vary diurnally. It is shown how these expressions can be used to accommodate diurnal temperature variation of photosynthesis in a simple manner. The accuracy of the approximation to the basic integral of leaf photosynthesis over the canopy and over time is illustrated by applying the algorithm to compute the seasonal variation of daily canopy photosynthesis and comparing these data with corresponding values obtained by numerical integration.

Maximization of Daily Canopy Photosynthesis: Effects of Herbivory on Optimal Nitrogen Distribution

Recent models have shown that higher leaf nitrogen concentration per unit area maximizes nitrogen use efficiency with increasing light intensity. As a result, total canopy photosynthesis is maximized when nitrogen concentrations are higher towards the top of a canopy. Expanding upon this previous work, a model of daily canopy photosynthesis was constructed based on distributions of light, leaf nitrogen, and folivory. The model indicates that the optimal distribution of nitrogen depends significantly upon both the severity and location of folivory. Relative to nitrogen distributions that maximized daily canopy photosynthesis without herbivory, the optimal nitrogen distribution shifted towards either more uniform or skewed distributions when herbivores fed on high nitrogen foliage at the top of the canopy or on low nitrogen foliage towards the bottom of the canopy, respectively. These results suggest that, because foliar losses are balanced by increased irradiance of remaining leaves, plants' nitrogen allocation patterns should depend on how severe defoliation is and whether damage is concentrated towards the top or bottom of a canopy. Moreover, the critical importance of nitrogen distribution to photosynthesis implies that plants should not necessarily minimize loss of leaf area to folivores, but should protect the ratio of total nitrogen to leaf area and the distribution of nitrogen within the canopy. As a corollary to the nutrient stress hypothesis of plant defense theory, the model suggests that plants may need to translocate nutrients to maintain an optimal distribution in the canopy following herbivory. The model reinforces the point that leaf area loss alone is a poor indicator of loss of photosynthetic capacity when nitrogen is non-uniformly distributed among leaves. To accurately assess damage to a plant, one must consider not only what resources have been removed, but what resources remain.

A theoretical analysis of nitrogen and radiation effects on radiation use efficiency in peanut

Radiation use efficiency (RUE) of well-watered crops, measured as grams of biomass accumulated for each megajoule of intercepted total solar radiation, is affected by the level of leaf nitrogen in the canopy and has been related to the canopy specific leaf nitrogen (SLN; g N m-2 leaf area). A number of field experiments on peanut have measured RUE values greater than current theories predict on the basis of their canopy SLN levels. It is possible that these discrepancies between measured and theoretical values may be caused by non-uniform distribution of SLN in the canopy, incident radiation level, and/or the influence of diffuse radiation. In this study, we developed a theoretical framework to predict the consequences of these factors on RUE in peanut and used it to explain the causes of discrepancies between theory and practice. The framework is structured to determine photosynthesis of a layered crop canopy by distributing incident radiation among sunlit and shaded leaves in each layer. It allows for variation in incident direct and diffuse radiation associated with location (latitude), time of year, time of day, and atmospheric condition, which is expressed as the degree of transmission of extra-terrestrial radiation. It also allows for variation in photosynthetic capacity associated with average SLN of the canopy and its distribution in the canopy. Daily canopy photosynthesis, intercepted radiation, and RUE are obtained by numerical integration of instantaneous values calculated at specific times of the day. The framework predicted experimentally determined RUE values accurately and quantified the contribution of each major factor to variation in RUE. On clear days, with high canopy SLN, RUE was predicted to be 1.l g MJ-1. The major cause of previous underestimation of RUE was found to be variation in RUE associated with the level of incident radiation flux density as affected by the degree of atmospheric transmission. RUE increased by up to 0.4 g MJ-1 as atmospheric transmission decreased from 0.75 (clear sky) to 0.35 (heavy cloud). However, varying incident radiation by changing time of year or latitude did not affect RUE. Partitioning incident radiation into direct and diffuse components and consideration of canopy gradients in SLN both had significant effects on RUE, but of a lesser magnitude than effects of degree of atmospheric transmission. The former caused increases in RUE of up to 0.15 g MJ-l, while the latter caused increases of up to 0.13 g MJ-1 at low canopy SLN. Hence, by quantifying the understanding of plant physiological processes and integrating appropriately to the canopy scale, this theoretical framework has explained the causes of discrepancies between measured RUE and previous theoretical estimates.

Mathematical models of the photosynthetic response of tree stands to rising CO2 concentrations and temperatures

ABSTRACTTwo published models of canopy photosynthesis, MAESTRO and BIOMASS, are simulated to examine the response of tree stands to increasing ambient concentrations of carbon dioxide (Ca) and temperatures. The models employ the same equations to described leaf gas exchange, but differ considerably in the level of detail employed to represent canopy structure and radiation environment. Daily rates of canopy photosynthesis simulated by the two models agree to within 10% across a range of CO2 concentrations and temperatures. A doubling of Ca leads to modest increases of simulated daily canopy photosynthesis at low temperatures (10% increase at 10°C), but larger increases at higher temperatures (60% increase at 30°C). The temperature and CO2 dependencies of canopy photosynthesis are interpreted in terms of simulated contributions by quantum‐saturated and non‐saturated foliage. Simulations are presented for periods ranging from a diurnal cycle to several years. Annual canopy photosynthesis simulated by BIOMASS for trees experiencing no water stress is linearly related to simulated annual absorbed photosynthetically active radiation, with light utilization coefficients for carbon of ɛ= 1.66 and 2.07g MJ−1 derived for Ca of 350 and 700 μmol mol−1, respectively.

Photosynthetic Acclimation and Nitrogen Partitioning Within a Lucerne Canopy. II. Stability Through Time and Comparison With a Theoretical Optimum

Nitrogen redistribution between and within leaves was examined in a plot of lucerne (Medicago sativa L. cv. Aurora) in relation to potential canopy photosynthesis. The canopy was sampled during regrowth after cutting and just prior to flowering. As leaves were progressively shaded by the newly produced leaves, nitrogen content fell and photosynthetic acclimation occurred. The rate of acclimation in the canopy was the same as occurred following a step change to 23 or 6% sunlight. The profile of leaf nitrogen content was stable with respect to leaf area index and independent of time of sampling. Optimal profiles of nitrogen distribution between leaves, photosynthetic rate per unit chlorophyll and nitrogen partitioning within leaves were calculated from the relationships between photosynthesis and nitrogen in conjunction with the light environment of the preceding 3 days. The optimal nitrogen content of the leaves should vary in proportion to the relative daily irradiance at each leaf. The observed distribution achieved 88% of the potential daily photosynthesis, while a uniform nitrogen distribution yielded only 80%. Photosynthetic acclimation and nitrogen partitioning within each leaf both responded to daily irradiance similarly to the calculated optimum except at the two extremes. At the top of the canopy, photosynthetic rate per unit of chlorophyll did not increase as much as the calculated optimum, while at the base of the canopy, nitrogen partitioning failed to fall as much as the calculated optimum. This may reflect the constraints on the flexibility of the photosynthetic system. Nitrogen redistribution between leaves made a dramatic contribution to increasing the potential photosynthesis by the canopy. Although acclimation to low irradiance reduced the photosynthetic capacity per unit nitrogen by 12%, the considerable reorganisation of proteins within the thylakoids increased potential daily photosynthesis by 20% over that which would have been gained by a 'sun' leaf. However, in terms of canopy photosynthesis, which is dominated by leaves intercepting most of the light, acclimation contributed only a few per cent to the potential daily canopy photosynthesis.