Optimal photosynthetic use of light by tropical tree crowns achieved by adjustment of individual leaf angles and nitrogen content

Intra-canopy leaf trait variation facilitates high leaf area index and compensatory growth in a clonal woody encroaching shrub

Leaf trait variation enables plants to utilize large gradients of light availability that exist across canopies of high leaf area index (LAI), allowing for greater net carbon gain while reducing light availability for understory competitors. While these canopy dynamics are well understood in forest ecosystems, studies of canopy structure of woody shrubs in grasslands are lacking. To evaluate the investment strategy used by these shrubs, we investigated the vertical distribution of leaf traits and physiology across canopies of Cornus drummondii, the predominant woody encroaching shrub in the Kansas tallgrass prairie. We also examined the impact of disturbance by browsing and grazing on these factors. Our results reveal that leaf mass per area (LMA) and leaf nitrogen per area (Na) varied approximately threefold across canopies of C. drummondii, resulting in major differences in the physiological functioning of leaves. High LMA leaves had high photosynthetic capacity, while low LMA leaves had a novel strategy for maintaining light compensation points below ambient light levels. The vertical allocation of leaf traits in C. drummondii canopies was also modified in response to browsing, which increased light availability at deeper canopy depths. As a result, LMA and Na increased at lower canopy depths, leading to a greater photosynthetic capacity deeper in browsed canopies compared to control canopies. This response, along with increased light availability, facilitated greater photosynthesis and resource-use efficiency deeper in browsed canopies compared to control canopies. Our results illustrate how C. drummondii facilitates high LAI canopies and a compensatory growth response to browsing-both of which are key factors contributing to the success of C. drummondii and other species responsible for grassland woody encroachment.

Anatomical acclimation of mature leaves to increased irradiance in sycamore maple (Acer pseudoplatanus L.)

Trees regenerating in the understory respond to increased availability of light caused by gap formation by undergoing a range of morphological and physiological adjustments. These adjustments include the production of thick, sun-type leaves containing thicker mesophyll and longer palisade cells than in shade-type leaves. We asked whether in the shade-regenerating tree Acer pseudoplatanus, the increase in leaf thickness and expansion of leaf tissues are possible also in leaves that are already fully formed, a response reported so far only for a handful of species. We acclimated potted seedlings to eight levels (from 1 to 100%) of solar irradiance and, in late summer, transferred a subset of them to full sunlight. Within 30 days, the pre-shaded leaves increased leaf mass per area and became thicker mostly due to the elongation of palisade cells, except for the most shaded individuals which suffered irreversible photo-oxidative damage. This anatomical acclimation was accompanied by a transient decline in photosynthetic efficiency of PSII (F_v/F_M), the magnitude of which was related to the degree of pre-shading. The F_v/F_M recovered substantially within the re-acclimation period. However, leaves of transferred plants were shed earlier in the fall, indicating that the acclimation was not fully effective. These results show that A. pseudoplatanus is one of the few known species in which mature leaves may re-acclimate anatomically to increased irradiance. This may be an important mechanism enhancing utilization of gaps created during the growing season.

Anatomical adjustment of mature leaves of sycamore maple (Acer pseudoplatanus L.) to increased irradiance

Trees regenerating in the understory respond to increased availability of light caused by gap formation by undergoing a range of morphological and physiological adjustments. These adjustments include the production of thick, sun-type leaves containing thicker mesophyll and longer palisade cells than in shade-type leaves. We asked whether in the shade-regenerating tree Acer pseudoplatanus, the increase in leaf thickness and expansion of leaf tissues are possible also in leaves that had been fully formed prior to the increase in irradiance, a response reported so far only for a handful of species. We acclimated potted seedlings to eight levels (from 1 to 100%) of solar irradiance and, in late summer, transferred a subset of them to full sunlight. Within 30 days, the shaded leaves increased leaf mass per area and became thicker mostly due to elongation of palisade cells, except for the most shaded individuals which suffered irreversible photo-oxidative damage. This anatomical acclimation was accompanied by partial degradation of chlorophyll and a transient decline in photosynthetic efficiency of PSII (F_v/F_M). These effects were related to the degree of pre-shading. The F_v/F_M recovered substantially within the re-acclimation period. However, leaves of transferred plants were shed significantly earlier in the fall, indicating that the acclimation was not fully effective. These results show that A. pseudoplatanus is one of the few known species in which mature leaves may re-acclimate anatomically to increased irradiance. This may be a potentially important mechanism enhancing utilization of gaps created during the growing season.

A System Dynamics Approach to Model Photosynthesis at Leaf Level Under Fluctuating Light

Photosynthesis has been mainly studied under steady-state conditions even though this assumption results inadequate for assessing the biochemical responses to rapid variations occurring in natural environments. The combination of mathematical models with available data may enhance the understanding of the dynamic responses of plants to fluctuating environments and can be used to make predictions on how photosynthesis would respond to non-steady-state conditions. In this study, we present a leaf level System Dynamics photosynthesis model based and validated on an experiment performed on two soybean varieties, namely, the wild type Eiko and the chlorophyll-deficient mutant MinnGold, grown in constant and fluctuating light conditions. This mutant is known to have similar steady-state photosynthesis compared to the green wild type, but it is found to have less biomass at harvest. It has been hypothesized that this might be due to an unoptimized response to non-steady-state conditions; therefore, this mutant seems appropriate to investigate dynamic photosynthesis. The model explained well the photosynthetic responses of these two varieties to fluctuating and constant light conditions and allowed to make relevant conclusions on the different dynamic responses of the two varieties. Deviations between data and model simulations are mostly evident in the non-photochemical quenching (NPQ) dynamics due to the oversimplified combination of PsbS- and zeaxanthin-dependent kinetics, failing in finely capturing the NPQ responses at different timescales. Nevertheless, due to its simplicity, the model can provide the basis of an upscaled dynamic model at a plant level.

Effects of photosynthetic models on the calculation results of photosynthetic response parameters in young Larix principis-rupprechtii Mayr. plantation

Accurately predicting the crown photosynthesis of trees is necessary for better understanding the C circle in terrestrial ecosystem. However, modeling crown for individual tree is still challenging with the complex crown structure and changeable environmental conditions. This study was conducted to explore model in modeling the photosynthesis light response curve of the tree crown of young Larix principis-rupprechtii Mayr. Plantation. The rectangular hyperbolic model (RHM), non-rectangular hyperbolic model (NRHM), exponential model (EM) and modified rectangular hyperbolic model (MRHM) were used to model the photosynthetic light response curves. The fitting accuracy of these models was tested by comparing determinants coefficients (R2), mean square errors (MSE) and Akaike information criterion (AIC). The results showed that the mean value of R2 of MRHM (R2 = 0.9687) was the highest, whereas MSE value (MSE = 0.0748) and AIC value (AIC = -39.21) were the lowest. The order of fitting accuracy of the four models for Pn-PAR response curve was as follows: MRHM > EM > NRHM > RHM. In addition, the light saturation point (LSP) obtained by MRHM was slightly lower than the observed values, whereas the maximum net photosynthetic rates (Pmax) modeled by the four models were close to the measured values. Therefore, MRHM was superior to other three models in describing the photosynthetic response curve, the accurate values were that the quantum efficiency (α), maximum net photosynthetic rate (Pmax), light saturation point (LSP), light compensation point (LCP) and respiration rate (Rd) were 0.06, 6.06 μmol·m-2s-1, 802.68 μmol·m-2s-1, 10.76 μmol·m-2s-1 and 0.60 μmol·m-2s-1. Moreover, the photosynthetic response parameters values among different layers were also significant. Our findings have critical implications for parameter calibration of photosynthetic models and thus robust prediction of photosynthetic response in forests.

TLSLeAF: automatic leaf angle estimates from single-scan terrestrial laser scanning

Leaf angle distribution (LAD) in forest canopies affects estimates of leaf area, light interception, and global-scale photosynthesis, but is often simplified to a single theoretical value. Here, we present TLSLeAF (Terrestrial Laser Scanning Leaf Angle Function), an automated open-source method of deriving LADs from terrestrial laser scanning. TLSLeAF produces canopy-scale leaf angle and LADs by relying on gridded laser scanning data. The approach increases processing speed, improves angle estimates, and requires minimal user input. Key features are automation, leaf-wood classification, beta parameter output, and implementation in R to increase accessibility for the ecology community. TLSLeAF precisely estimates leaf angle with minimal distance effects on angular estimates while rapidly producing LADs on a consumer-grade machine. We challenge the popular spherical LAD assumption, showing sensitivity to ecosystem type in plant area index and foliage profile estimates that translate to c. 25% and c. 11% increases in canopy net photosynthesis (c. 25%) and solar-induced chlorophyll fluorescence (c. 11%). TLSLeAF can now be applied to the vast catalog of laser scanning data already available from ecosystems around the globe. The ease of use will enable widespread adoption of the method outside of remote-sensing experts, allowing greater accessibility for addressing ecological hypotheses and large-scale ecosystem modeling efforts.

Integrating terrestrial laser scanning with functional-structural plant models to investigate ecological and evolutionary processes of forest communities

BACKGROUND

Woody plants (trees and shrubs) play an important role in terrestrial ecosystems, but their size and longevity make them difficult subjects for traditional experiments. In the last 20 years functional-structural plant models (FSPMs) have evolved: they consider the interplay between plant modular structure, the immediate environment and internal functioning. However, computational constraints and data deficiency have long been limiting factors in a broader application of FSPMs, particularly at the scale of forest communities. Recently, terrestrial laser scanning (TLS), has emerged as an invaluable tool for capturing the 3-D structure of forest communities, thus opening up exciting opportunities to explore and predict forest dynamics with FSPMs.

SCOPE

The potential synergies between TLS-derived data and FSPMs have yet to be fully explored. Here, we summarize recent developments in FSPM and TLS research, with a specific focus on woody plants. We then evaluate the emerging opportunities for applying FSPMs in an ecological and evolutionary context, in light of TLS-derived data, with particular consideration of the challenges posed by scaling up from individual trees to whole forests. Finally, we propose guidelines for incorporating TLS data into the FSPM workflow to encourage overlap of practice amongst researchers.

CONCLUSIONS

We conclude that TLS is a feasible tool to help shift FSPMs from an individual-level modelling technique to a community-level one. The ability to scan multiple trees, of multiple species, in a short amount of time, is paramount to gathering the detailed structural information required for parameterizing FSPMs for forest communities. Conventional techniques, such as repeated manual forest surveys, have their limitations in explaining the driving mechanisms behind observed patterns in 3-D forest structure and dynamics. Therefore, other techniques are valuable to explore how forests might respond to environmental change. A robust synthesis between TLS and FSPMs provides the opportunity to virtually explore the spatial and temporal dynamics of forest communities.

Potential of hotspot solar-induced chlorophyll fluorescence for better tracking terrestrial photosynthesis

Remote sensing of solar-induced fluorescence (SIF) opens a new window for quantifying a key ecological variable, the terrestrial ecosystem gross primary production (GPP), because of the revealed strong SIF-GPP correlation. However, similar to many other remotely sensed metrics, SIF observations suffer from the sun-sensor geometry effects, which may have important impacts on the SIF-GPP relationship but remain poorly understood. Here we used remotely sensed SIF, globally distributed tower GPP data, and a mechanistic model to provide a systematic analysis. Our results reveal that leaf physiology, canopy structure, and sun-sensor geometries all affect the SIF-GPP relationship. In particular, we found that SIF observations in the sun-tracking hotspot direction can be a better proxy of GPP due to the similar responses of light use efficiency and SIF escaping probability in the hotspot direction to the increasing incoming solar radiation. Such conclusions are supported by a variety of modeling simulations and satellite observations over various plant function types, at different time scales and with satellite observational modes. This study demonstrates the potential and advantage of normalizing SIF observations to the hotspot direction for better global GPP estimations. This study also demonstrates the great potentials of current and future spaceborne sun-tracking satellite missions for a significant improvement in measuring and monitoring, at a wide range of spatial and temporal scales, the changes in terrestrial ecosystem GPP in response to anticipated changes in the Earth's environmental conditions.

Determination of the most effective design for the measurement of photosynthetic light-response curves for planted Larix olgensis trees

A photosynthetic light-response (PLR) curve is a mathematical description of a single biochemical process and has been widely applied in many eco-physiological models. To date, many PLR measurement designs have been suggested, although their differences have rarely been explored, and the most effective design has not been determined. In this study, we measured three types of PLR curves (High, Middle and Low) from planted Larix olgensis trees by setting 31 photosynthetically active radiation (PAR) gradients. More than 530 million designs with different combinations of PAR gradients from 5 to 30 measured points were conducted to fit each of the three types of PLR curves. The influence of different PLR measurement designs on the goodness of fit of the PLR curves and the accuracy of the estimated photosynthetic indicators were analysed, and the optimal design was determined. The results showed that the measurement designs with fewer PAR gradients generally resulted in worse predicted accuracy for the photosynthetic indicators. However, the accuracy increased and remained stable when more than ten measurement points were used for the PAR gradients. The mean percent error (M%E) of the estimated maximum net photosynthetic rate (Pmax) and dark respiratory rate (Rd) for the designs with less than ten measurement points were, on average, 16.4 times and 20.1 times greater than those for the designs with more than ten measurement points. For a single tree, a unique PLR curve design generally reduced the accuracy of the predicted photosynthetic indicators. Thus, three optimal measurement designs were provided for the three PLR curve types, in which the root mean square error (RMSE) values reduced by an average of 8.3% and the coefficient of determination (R2) values increased by 0.3%. The optimal design for the High PLR curve type should shift more towards high-intensity PAR values, which is in contrast to the optimal design for the Low PLR curve type, which should shift more towards low-intensity PAR values.

The Leaf Economics Spectrum Constrains Phenotypic Plasticity Across a Light Gradient

The leaf economics spectrum (LES) characterizes multivariate correlations that confine the global diversity of leaf functional traits onto a single axis of variation. Although LES is well established for traits of sun leaves, it is unclear how well LES characterizes the diversity of traits for shade leaves. Here, we evaluate LES using the sun and shade leaves of 75 woody species sampled at the extremes of a within-canopy light gradient in a subtropical forest. Shading significantly decreased the mean values of LMA and the rates of photosynthesis and dark respiration, but had no discernable effect on nitrogen and phosphorus content. Sun and shade leaves manifested the same relationships among N mass, P mass, A mass, and R mass (i.e., the slopes of log-log scaling relations of LES traits did not differ between sun and shade leaves). However, the difference between the normalization constants of shade and sun leaves was correlated with functional trait plasticity. Although the generality of this finding should be evaluated further using larger datasets comprising more phylogenetically diverse taxa and biomes, these findings support a unified LES across shade as well as sun leaves.

Linking vein properties to leaf biomechanics across 58 woody species from a subtropical forest

Leaf venations have elements with relatively lower elasticity than other leaf tissue components, which are thought to contribute to leaf biomechanics. A better mechanistic understanding of relationships between vein traits and leaf mechanical properties is essential for ecologically relevant interpretation of leaf structural variations. We investigated 13 major (first to third order) and minor (>third order) vein traits, six leaf mechanical properties and other structural traits across 58 woody species from a subtropical forest to elucidate how vein traits contribute to leaf biomechanics. Across species, vein dry mass density (ρ_v ), total vein dry mass per leaf area (VMA) and minor vein diameter (VD_min ), but not the lower-order vein density (VLA_1•2 ), were positively correlated with leaf force to punch (F_p ) and force to tear (F_t ). Structural equation models showed that ρ_v and VD_min not only contribute to leaf mechanical properties directly (direct pathway), but also had impacts on leaf biomechanics by influencing leaf thickness and leaf dry mass per area (indirect pathway). Our study demonstrated that vein dry mass density and minor vein diameter are the key vein properties for leaf biomechanics. We also suggest that the mechanical characteristics of venations are potential factors influencing leaf mechanical resistance, structure and leaf economics spectrum.

The "one-point method" for estimating maximum carboxylation capacity of photosynthesis: A cautionary tale

The maximum carboxylation capacity of Rubisco, V_c,max , is an important photosynthetic parameter that is key to accurate estimation of carbon assimilation. The gold-standard technique for determining V_c,max is to derive V_c,max from the initial slope of an A-C_i curve (the response of photosynthesis, A, to intercellular CO₂ concentration, C_i ). Accurate estimates of V_c,max derived from an alternative and rapid "one-point" measurement of photosynthesis could greatly accelerate data collection and model parameterization. We evaluated the practical application of the one-point method in six species measured under standard conditions (saturating irradiance and 400 μmol CO₂ mol^-1 ) and under conditions that would increase the likelihood for successful estimation of V_c,max : (a) ensuring Rubisco-limited A by measuring at 300 μmol CO₂ mol^-1 and (b) allowing time for acclimation to saturating irradiance prior to measurement. The one-point method significantly underestimated V_c,max in four of the six species, providing estimates 21%-32% below fitted values. We identified ribulose-1,5-bisphosphate-limited A, light acclimation, and the use of an assumed respiration rate as factors that limited the effective use of the one-point method to accurately estimate V_c,max . We conclude that the one-point method requires a species-specific understanding of its application, is often unsuccessful, and must be used with caution.

Terrestrial biosphere models may overestimate Arctic CO2 assimilation if they do not account for decreased quantum yield and convexity at low temperature

How terrestrial biosphere models (TBMs) represent leaf photosynthesis and its sensitivity to temperature are two critical components of understanding and predicting the response of the Arctic carbon cycle to global change. We measured the effect of temperature on the response of photosynthesis to irradiance in six Arctic plant species and determined the quantum yield of CO₂ fixation ( ϕCO2 ) and the convexity factor (θ). We also determined leaf absorptance (α) from measured reflectance to calculate ϕCO2 on an absorbed light basis ( ϕCO2.a ) and enabled comparison with nine TBMs. The mean ϕCO2.a was 0.045 mol CO₂  mol^-1 absorbed quanta at 25°C and closely agreed with the mean TBM parameterisation (0.044), but as temperature decreased measured ϕCO2.a diverged from TBMs. At 5°C measured ϕCO2.a was markedly reduced (0.025) and 60% lower than TBM estimates. The θ also showed a significant reduction between 25°C and 5°C. At 5°C θ was 38% lower than the common model parameterisation of 0.7. These data show that TBMs are not accounting for observed reductions in ϕCO2.a and θ that can occur at low temperature. Ignoring these reductions in ϕCO2.a and θ could lead to a marked (45%) overestimation of CO₂ assimilation at subsaturating irradiance and low temperature.

Effect of temporally heterogeneous light on photosynthetic light use efficiency, plant acclimation and growth in Abatia parviflora

Individual leaves have a unique instantaneous photosynthetic photon flux density (PPFD) at which net photosynthetic light use efficiency (ϵL, the ratio between net photosynthesis and PPFD) is maximised (PPFDϵmax). When PPFD is above or below PPFDϵmax, efficiency declines. Thus, we hypothesised that heterogeneous PPFD conditions should increase the amount of time leaves photosynthesise at a PPFD different than PPFDϵmax and result in reduced growth. To date, this prediction has not been rigorously tested. Here, we exposed seedlings of Abatia parviflora Ruiz & Pav to light regimes of equal total daily irradiance but with three different daily time courses of PPFD: constant PPFD (No_H), low heterogeneity (Low_H) and high heterogeneity (High_H). Mean ϵL, leaf daily photosynthesis and plant growth were all significantly higher in No_H and Low_H plants than in High_H plants, supporting our hypothesis. In addition, mean ϵL was positively related to final plant biomass. Unexpectedly, High_H plants had more etiolated stems and more horizontal leaves than No_H and Low_H plants, possibly due to exposure to low PPFD in the morning and afternoon. In conclusion, PPFD heterogeneity had an important effect on average ϵL, photosynthesis and growth, but also on allocation and plant morphology.

Midday Depression vs. Midday Peak in Diurnal Light Interception: Contrasting Patterns at Crown and Leaf Scales in a Tropical Evergreen Tree

Crown architecture usually is heterogeneous as a result of foraging in spatially and temporally heterogeneous light environments. Ecologists are only beginning to identify the importance of temporal heterogeneity for light acquisition in plants, especially at the diurnal scale. Crown architectural heterogeneity often leads to a diurnal variation in light interception. However, maximizing light interception during midday may not be an optimal strategy in environments with excess light. Instead, long-lived plants are expected to show crown architectures and leaf positions that meet the contrasting needs of light interception and avoidance of excess light on a diurnal basis. We expected a midday depression in the diurnal course of light interception both at the whole-crown and leaf scales, as a strategy to avoid the interception of excessive irradiance. We tested this hypothesis in a population of guava trees (Psidium guajava L.) growing in an open tropical grassland. We quantified three crown architectural traits: intra-individual heterogeneity in foliage clumping, crown openness, and leaf position angles. We estimated the diurnal course of light interception at the crown scale using hemispheric photographs, and at the leaf scale using the cosine of solar incidence. Crowns showed a midday depression in light interception, while leaves showed a midday peak. These contrasting patterns were related to architectural traits. At the crown scale, the midday depression of light interception was linked to a greater crown openness and foliage clumping in crown tops than in the lateral parts of the crown. At the leaf scale, an average inclination angle of 45° led to the midday peak in light interception, but with a huge among-leaf variation in position angles. The mismatch in diurnal course of light interception at crown and leaf scales can indicate that different processes are being optimized at each scale. These findings suggest that the diurnal course of light interception may be an important dimension of the resource acquisition strategies of long-lived woody plants. Using a temporal approach as the one applied here may improve our understanding of the diversity of crown architectures found across and within environments.

Enhanced photosynthesis endows seedling growth vigour contributing to the competitive dominance of weedy rice over cultivated rice

BACKGROUND

Weedy rice, as one of the worst paddy field weeds worldwide, bears vigorous seedlings and dominantly competes with cultivated rice causing serious crop yield losses. To elucidate the causes of its stronger seedling vigour endowing its dominant competition with cultivated rice, comparative studies on seedling growth characteristics were conducted among six weedy rice biotypes and the two indica and japonica cultivars Shanyou-63 (SY-63) and Zhendao-8 (ZD-8), respectively, in the greenhouse.

RESULTS

Weedy rice emerged 2 to 3 days earlier, rapidly grew 1.3-1.7 cm taller daily, produced more secondary adventitious roots and greater aboveground fresh biomass than cultivated rice. Moreover, weedy rice exhibited greater photosynthetic pigment content, net photosynthetic rate, stomatal conductance, intercellular CO₂ concentration, transpiration rate, and chlorophyll fluorescence kinetic parameters. An enhanced overall photosynthetic activity in weedy rices was attributed to the combined action of a larger antenna, more active reaction centres and higher quantum yield for electron transfer beyond Q_A .

CONCLUSIONS

Enhanced photosynthesis of weedy rice at the seedling stage should be the main factor for leading to strong competitive dominance over cultivated rice. © 2016 Society of Chemical Industry.

Convergence in leaf size versus twig leaf area scaling: do plants optimize leaf area partitioning?

BACKGROUND AND AIMS

Corner's rule states that thicker twigs bear larger leaves. The exact nature of this relationship and why it should occur has been the subject of numerous studies. It is obvious that thicker twigs should support greater total leaf area ([Formula: see text]) for hydraulical and mechanical reasons. But it is not obvious why mean leaf size ([Formula: see text]) should scale positively with [Formula: see text] We asked what this scaling relationship is within species and how variable it is across species. We then developed a model to explain why these relationships exist.

METHODS

To minimize potential sources of variability, we compared twig properties from six co-occurring and functionally similar species: Acer grandidentatum, Amelanchier alnifolia, Betula occidentalis, Cornus sericea, Populus fremontii and Symphoricarpos oreophilus We modelled the economics of leaf display, weighing the benefit from light absorption against the cost of leaf tissue, to predict the optimal [Formula: see text] combinations under different canopy openings.

KEY RESULTS

We observed a common [Formula: see text] by [Formula: see text] exponent of 0.6, meaning that [Formula: see text]and leaf number on twigs increased in a specific coordination. Common scaling exponents were not supported for relationships between any other measured twig properties. The model consistently predicted positive [Formula: see text] by [Formula: see text] scaling when twigs optimally filled canopy openings. The observed 0·6 exponent was predicted when self-shading decreased with larger canopy opening.

CONCLUSIONS

Our results suggest Corner's rule may be better understood when recast as positive [Formula: see text] by [Formula: see text] scaling. Our model provides a tentative explanation of observed [Formula: see text] by [Formula: see text] scaling and suggests different scaling may exist in different environments.

Exploiting heterogeneous environments: does photosynthetic acclimation optimize carbon gain in fluctuating light?

Plants have evolved complex mechanisms to balance the efficient use of absorbed light energy in photosynthesis with the capacity to use that energy in assimilation, so avoiding potential damage from excess light. This is particularly important under natural light, which can vary according to weather, solar movement and canopy movement. Photosynthetic acclimation is the means by which plants alter their leaf composition and structure over time to enhance photosynthetic efficiency and productivity. However there is no empirical or theoretical basis for understanding how leaves track historic light levels to determine acclimation status, or whether they do this accurately. We hypothesized that in fluctuating light (varying in both intensity and frequency), the light-response characteristics of a leaf should adjust (dynamically acclimate) to maximize daily carbon gain. Using a framework of mathematical modelling based on light-response curves, we have analysed carbon-gain dynamics under various light patterns. The objective was to develop new tools to quantify the precision with which photosynthesis acclimates according to the environment in which plants exist and to test this tool on existing data. We found an inverse relationship between the optimal maximum photosynthetic capacity and the frequency of low to high light transitions. Using experimental data from the literature we were able to show that the observed patterns for acclimation were consistent with a strategy towards maximizing daily carbon gain. Refinement of the model will further determine the precision of acclimation.

Nondestructive diagnostic test for nitrogen nutrition of grapevine (Vitis vinifera L.) based on dualex leaf-clip measurements in the field

Crop nitrogen status is a major issue for crop yield and quality. It is usually assessed by destructive leaf or petiole tissue analysis. A quantitative nondestructive optical estimation of N sufficiency would be a great leap forward toward precision crop management. We therefore calibrated three optical indices against leaf nitrogen content: chlorophyll (Chl), epidermal flavonols, and the nitrogen balance index (NBI), which is the ratio of the former two indices. NBI was the best estimator of leaf N content measured by the Dumas or Kjeldahl method with a root-mean-square error smaller than 2 mg of N g(-1) dry weight, followed by Chl (3 mg g(-1)) and flavonols (4 mg g(-1)). This allowed us to propose the threshold values for the Dualex optical indices that characterize nitrogen supply to grapevines: the first is the threshold below which N supply to the vine can be considered deficient, and the second is the threshold above which N supply is excessive. For a putative optimal N content of 30 mg g(-1) < x < 40 mg g(-1), these thresholds are 30 μg cm(-2) < x < 40 μg cm(-2) for Chl and 11 < x < 18 for NBI at flowering. At bunch closure, for N thresholds of 22 < x < 32, Chl is 29 < x < 37 and NBI is 8 < x < 11, in respective units. These values should be verified and refined in the future for various growth regions and cultivars using the specified protocol. The sample size should be 36-60 leaves from a fixed node position, preferably node no. 5 from the tip of the shoot. An alternative to the use of the NBI would be to discard leaves that are not light exposed by checking their flavonol content and to deduce the N sufficiency directly from the Chl values.

A worldwide analysis of within-canopy variations in leaf structural, chemical and physiological traits across plant functional types

Extensive within-canopy light gradients importantly affect the photosynthetic productivity of leaves in different canopy positions and lead to light-dependent increases in foliage photosynthetic capacity per area (AA). However, the controls on AA variations by changes in underlying traits are poorly known. We constructed an unprecedented worldwide database including 831 within-canopy gradients with standardized light estimates for 304 species belonging to major vascular plant functional types, and analyzed within-canopy variations in 12 key foliage structural, chemical and physiological traits by quantitative separation of the contributions of different traits to photosynthetic acclimation. Although the light-dependent increase in AA is surprisingly similar in different plant functional types, they differ fundamentally in the share of the controls on AA by constituent traits. Species with high rates of canopy development and leaf turnover, exhibiting highly dynamic light environments, actively change AA by nitrogen reallocation among and partitioning within leaves. By contrast, species with slow leaf turnover exhibit a passive AA acclimation response, primarily determined by the acclimation of leaf structure to growth light. This review emphasizes that different combinations of traits are responsible for within-canopy photosynthetic acclimation in different plant functional types, and solves an old enigma of the role of mass- vs area-based traits in vegetation acclimation.

Simultaneous improvement in productivity, water use, and albedo through crop structural modification

Spanning 15% of the global ice-free terrestrial surface, agricultural lands provide an immense and near-term opportunity to address climate change, food, and water security challenges. Through the computationally informed breeding of canopy structural traits away from those of modern cultivars, we show that solutions exist that increase productivity and water use efficiency, while increasing land-surface reflectivity to offset greenhouse gas warming. Plants have evolved to maximize capture of radiation in the upper leaves, thus shading competitors. While important for survival in the wild, this is suboptimal in monoculture crop fields for maximizing productivity and other biogeophysical services. Crop progenitors evolved over the last 25 million years in an atmosphere with less than half the [CO2] projected for 2050. By altering leaf photosynthetic rates, rising [CO2] and temperature may also alter the optimal canopy form. Here using soybean, the world's most important protein crop, as an example we show by applying optimization routines to a micrometeorological leaf canopy model linked to a steady-state model of photosynthesis, that significant gains in production, water use, and reflectivity are possible with no additional demand on resources. By modifying total canopy leaf area, its vertical profile and angular distribution, and shortwave radiation reflectivity, all traits available in most major crop germplasm collections, increases in productivity (7%) are possible with no change in water use or albedo. Alternatively, improvements in water use (13%) or albedo (34%) can likewise be made with no loss of productivity, under Corn Belt climate conditions.

Leaf nitrogen distribution in relation to crown architecture in the tall canopy species, Fagus crenata

The theory of optimal leaf N distribution predicts that the C gain of plants is maximized when the N content per unit area (N(area)) scales with light availability, but most previous studies have demonstrated that the N distribution is not proportional to light availability. In tall trees, the leaves are often clustered on twigs (leaf cluster) and not evenly distributed within the crowns. Thus, we hypothesized that the suboptimal N distribution is partly caused by the limited capacity to translocate N between leaf clusters, and consequently, the relationship between light and N(area) differs for leaves in different clusters. We investigated the light availability and N content of all individual leaves within several leaf clusters on tall trees of a deciduous canopy species Fagus crenata in Japan. We observed that the within-cluster leaf N distribution patterns differed from the between-cluster patterns and the slopes of the relationships between light and N(area) were lower within clusters than between clusters. According to the detailed analysis of the N distribution within leaf clusters, N(area) was greater for current-year shoots with greater light availability or a larger total leaf area. The latter pattern was probably caused by the greater sink strength of the current-year shoots with a larger leaf area. These N distribution patterns suggest that leaf clusters are fairly independent with respect to their N use, and the productivity of real F. crenata crowns may be less than optimal.

Nitrogen-addition effects on leaf traits and photosynthetic carbon gain of boreal forest understory shrubs

Boreal coniferous forests are characterized by fairly open canopies where understory vegetation is an important component of ecosystem C and N cycling. We used an ecophysiological approach to study the effects of N additions on uptake and partitioning of C and N in two dominant understory shrubs: deciduous Vaccinium myrtillus in a Picea abies stand and evergreen Vaccinium vitis-idaea in a Pinus sylvestris stand in northern Sweden. N was added to these stands for 16 and 8 years, respectively, at rates of 0, 12.5, and 50 kg N ha(-1) year(-1). N addition at the highest rate increased foliar N and chlorophyll concentrations in both understory species. Canopy cover of P. abies also increased, decreasing light availability and leaf mass per area of V. myrtillus. Among leaves of either shrub, foliar N content did not explain variation in light-saturated CO2 exchange rates. Instead photosynthetic capacity varied with stomatal conductance possibly reflecting plant hydraulic properties and within-site variation in water availability. Moreover, likely due to increased shading under P. abies and due to water limitations in the sandy soil under P. sylvestris, individuals of the two shrubs did not increase their biomass or shift their allocation between above- and belowground parts in response to N additions. Altogether, our results indicate that the understory shrubs in these systems show little response to N additions in terms of photosynthetic physiology or growth and that changes in their performance are mostly associated with responses of the tree canopy.

Sunflecks in trees and forests: from photosynthetic physiology to global change biology

Sunflecks are brief, intermittent periods of high photon flux density (PFD) that can significantly improve carbon gain in shaded forest understories and lower canopies of trees. In this review, we discuss the physiological basis of leaf-level responses to sunflecks and the mechanisms plants use to tolerate sudden changes in PFD and leaf temperature induced by sunflecks. We also examine the potential effects of climate change stresses (including elevated temperatures, rising CO(2) concentrations and drought) on the ability of tree species to use sunflecks, and advocate more research to improve our predictions of seedling and tree carbon gain in future climates. Lastly, while we have the ability to model realistic responses of photosynthesis to fluctuating PFD, dynamic responses of photosynthesis to sunflecks are not accounted for in current models of canopy carbon uptake, which can lead to substantial overestimates of forest carbon fixation. Since sunflecks are a critical component of seasonal carbon gain for shaded leaves, sunfleck regimes and physiological responses to sunflecks should be incorporated into models to more accurately capture forest carbon dynamics.

Contributions of leaf photosynthetic capacity, leaf angle and self-shading to the maximization of net photosynthesis in Acer saccharum: a modelling assessment

BACKGROUND AND AIMS

Plants are expected to maximize their net photosynthetic gains and efficiently use available resources, but the fundamental principles governing trade-offs in suites of traits related to resource-use optimization remain uncertain. This study investigated whether Acer saccharum (sugar maple) saplings could maximize their net photosynthetic gains through a combination of crown structure and foliar characteristics that let all leaves maximize their photosynthetic light-use efficiency (ε).

METHODS

A functional-structural model, LIGNUM, was used to simulate individuals of different leaf area index (LAI(ind)) together with a genetic algorithm to find distributions of leaf angle (L(A)) and leaf photosynthetic capacity (A(max)) that maximized net carbon gain at the whole-plant level. Saplings grown in either the open or in a forest gap were simulated with A(max) either unconstrained or constrained to an upper value consistent with reported values for A(max) in A. saccharum.

KEY RESULTS

It was found that total net photosynthetic gain was highest when whole-plant PPFD absorption and leaf ε were simultaneously maximized. Maximization of ε required simultaneous adjustments in L(A) and A(max) along gradients of PPFD in the plants. When A(max) was constrained to a maximum, plants growing in the open maximized their PPFD absorption but not ε because PPFD incident on leaves was higher than the PPFD at which ε(max) was attainable. Average leaf ε in constrained plants nonetheless improved with increasing LAI(ind) because of an increase in self-shading.

CONCLUSIONS

It is concluded that there are selective pressures for plants to simultaneously maximize both PPFD absorption at the scale of the whole individual and ε at the scale of leaves, which requires a highly integrated response between L(A), A(max) and LAI(ind). The results also suggest that to maximize ε plants have evolved mechanisms that co-ordinate the L(A) and A(max) of individual leaves with PPFD availability.

Measures of light in studies on light-driven plant plasticity in artificial environments

Within-canopy variation in light results in profound canopy profiles in foliage structural, chemical, and physiological traits. Studies on within-canopy variations in key foliage traits are often conducted in artificial environments, including growth chambers with only artificial light, and greenhouses with and without supplemental light. Canopy patterns in these systems are considered to be representative to outdoor conditions, but in experiments with artificial and supplemental lighting, the intensity of artificial light strongly deceases with the distance from the light source, and natural light intensity in greenhouses is less than outdoors due to limited transmittance of enclosure walls. The implications of such changes in radiation conditions on canopy patterns of foliage traits have not yet been analyzed. We developed model-based methods for retrospective estimation of distance vs. light intensity relationships, for separation of the share of artificial and natural light in experiments with combined light and for estimation of average enclosure transmittance, and estimated daily integrated light at the time of sampling (Q(int,C)), at foliage formation (Q(int,G)), and during foliage lifetime (Q(int,av)). The implications of artificial light environments were analyzed for altogether 25 studies providing information on within-canopy gradients of key foliage traits for 70 species × treatment combinations. Across the studies with artificial light, Q(int,G) for leaves formed at different heights in the canopy varied from 1.8- to 6.4-fold due to changing the distance between light source and growing plants. In experiments with combined lighting, the share of natural light at the top of the plants varied threefold, and the share of natural light strongly increased with increasing depth in the canopy. Foliage nitrogen content was most strongly associated with Q(int,G), but photosynthetic capacity with Q(int,C), emphasizing the importance of explicit description of light environment during foliage lifetime. The reported and estimated transmittances of enclosures varied between 0.27 and 0.85, and lack of consideration of the reduction of light compared with outdoor conditions resulted in major underestimation of foliage plasticity to light. The study emphasizes that plant trait vs. light relationships in artificial systems are not directly comparable to natural environments unless modifications in lighting conditions in artificial environments are taken into account.

Is analysing the nitrogen use at the plant canopy level a matter of choosing the right optimization criterion?

Optimization theory in combination with canopy modeling is potentially a powerful tool for evaluating the adaptive significance of photosynthesis-related plant traits. Yet its successful application has been hampered by a lack of agreement on the appropriate optimization criterion. Here we review how models based on different types of optimization criteria have been used to analyze traits-particularly N reallocation and leaf area indices-that determine photosynthetic nitrogen-use efficiency at the canopy level. By far the most commonly used approach is static-plant simple optimization (SSO). Static-plant simple optimization makes two assumptions: (1) plant traits are considered to be optimal when they maximize whole-stand daily photosynthesis, ignoring competitive interactions between individuals; (2) it assumes static plants, ignoring canopy dynamics (production and loss of leaves, and the reallocation and uptake of nitrogen) and the respiration of nonphotosynthetic tissue. Recent studies have addressed either the former problem through the application of evolutionary game theory (EGT) or the latter by applying dynamic-plant simple optimization (DSO), and have made considerable progress in our understanding of plant photosynthetic traits. However, we argue that future model studies should focus on combining these two approaches. We also point out that field observations can fit predictions from two models based on very different optimization criteria. In order to enhance our understanding of the adaptive significance of photosynthesis-related plant traits, there is thus an urgent need for experiments that test underlying optimization criteria and competing hypotheses about underlying mechanisms of optimization.

Modelling functional trait acclimation for trees of different height in a forest light gradient: emergent patterns driven by carbon gain maximization

Forest trees show large changes in functional traits as they develop from a sapling in the shaded understorey to an adult in the light-exposed canopy. The adaptive function of such changes remains poorly understood. The carbon gain hypothesis suggests that these changes should be adaptive (acclimation) and that they serve to maximize net vegetative or reproductive growth. We explore the carbon gain hypothesis using a mechanistic model that combines an above-ground plant structure, a biochemical photosynthesis model and a biophysical stomatal conductance model. Our simulations show how forest trees that maximize their carbon gain increase their total leaf area, sapwood area and leaf photosynthetic capacity with tree height and light intensity. In turn, they show how forest trees increased crown stomatal conductance and transpiration, and how the carbon budget was affected. These responses in functional traits to tree height (and light availability) largely differed from the responses exhibited by exposed trees. Forest and exposed trees nevertheless shared a number of emergent patterns: they showed a similar decrease in the average leaf water potential and intercellular CO(2) concentration with tree height, and kept almost constant values for the ratio of light absorption to electron transport capacity, the ratio of photosynthetic capacity to water supply capacity, and nitrogen partitioning between electron transport and carboxylation. While most of the predicted qualitative responses in individual traits are consistent with field or lab observations, the empirical support for capacity balances is scarce. We conclude that modelling functional trait optimization and carbon gain maximization from underlying physiological processes and trade-offs generates a set of predictions for functional trait acclimation and maintenance of capacity balances of trees of different height in a forest light gradient, but actual tests of the predicted patterns are still scarce.

Photosynthetic acclimation in relation to nitrogen allocation in cucumber leaves in response to changes in irradiance

Leaves deep in canopies can suddenly be exposed to increased irradiances following e.g. gap formation in forests or pruning in crops. Studies on the acclimation of photosynthesis to increased irradiance have mainly focused on the changes in photosynthetic capacity (A(max)), although actual irradiance often remains below saturating level. We investigated the effect of changes in irradiance on the photosynthesis irradiance response and on nitrogen allocation in fully grown leaves of Cucumis sativus. Leaves that fully developed under low (50 µmol m⁻² s⁻¹) or moderate (200 µmol m⁻² s⁻¹) irradiance were subsequently exposed to, respectively, moderate (LM-leaves) or low (ML-leaves) irradiance or kept at constant irradiance level (LL- and MM-leaves). Acclimation of photosynthesis occurred within 7 days with final A(max) highest in MM-leaves, lowest in LL-leaves and intermediate in ML- and LM-leaves, whereas full acclimation of thylakoid processes underlying photosystem II (PSII) efficiency and non-photochemical quenching occurred in ML- and LM-leaves. Dark respiration correlated with irradiance level, but not with A(max). Light-limited quantum efficiency was similar in all leaves. The increase in photosynthesis at moderate irradiance in LM-leaves was primarily driven by nitrogen import, and nitrogen remained allocated in a similar ratio to Rubisco and bioenergetics, while allocation to light harvesting relatively decreased. A contrary response of nitrogen was associated with the decrease in photosynthesis in ML-leaves. Net assimilation of LM-leaves under moderate irradiance remained lower than in MM-leaves, revealing the importance of photosynthetic acclimation during the leaf developmental phase for crop productivity in scenarios with realistic, moderate fluctuations in irradiance that leaves can be exposed to.

Functional structure of biological communities predicts ecosystem multifunctionality

The accelerating rate of change in biodiversity patterns, mediated by ever increasing human pressures and global warming, demands a better understanding of the relationship between the structure of biological communities and ecosystem functioning (BEF). Recent investigations suggest that the functional structure of communities, i.e. the composition and diversity of functional traits, is the main driver of ecological processes. However, the predictive power of BEF research is still low, the integration of all components of functional community structure as predictors is still lacking, and the multifunctionality of ecosystems (i.e. rates of multiple processes) must be considered. Here, using a multiple-processes framework from grassland biodiversity experiments, we show that functional identity of species and functional divergence among species, rather than species diversity per se, together promote the level of ecosystem multifunctionality with a predictive power of 80%. Our results suggest that primary productivity and decomposition rates, two key ecosystem processes upon which the global carbon cycle depends, are primarily sustained by specialist species, i.e. those that hold specialized combinations of traits and perform particular functions. Contrary to studies focusing on single ecosystem functions and considering species richness as the sole measure of biodiversity, we found a linear and non-saturating effect of the functional structure of communities on ecosystem multifunctionality. Thus, sustaining multiple ecological processes would require focusing on trait dominance and on the degree of community specialization, even in species-rich assemblages.

Sources of variability in canopy reflectance and the convergent properties of plants

How plants interact with sunlight is central to the existence of life and provides a window to the functioning of ecosystems. Although the basic properties of leaf spectra have been known for decades, interpreting canopy-level spectra is more challenging because leaf-level effects are complicated by a host of stem- and canopy-level traits. Progress has been made through empirical analyses and models, although both methods have been hampered by a series of persistent challenges. Here, I review current understanding of plant spectral properties with respect to sources of uncertainty at leaf to canopy scales. I also discuss the role of evolutionary convergence in plant functioning and the difficulty of identifying individual properties among a suite of interrelated traits. A pattern that emerges suggests a synergy among the scattering effects of leaf-, stem- and canopy-level traits that becomes most apparent in the near-infrared (NIR) region. This explains the widespread and well-known importance of the NIR region in vegetation remote sensing, but presents an interesting paradox that has yet to be fully explored: that we can often gain more insight about the functioning of plants by examining wavelengths that are not used in photosynthesis than by examining those that are.

Geometrical similarity analysis of photosynthetic light response curves, light saturation and light use efficiency

Light absorption and use efficiency (LAUE mol mol(-1), daily gross photosynthesis per daily incident light) of each leaf depends on several factors, including the degree of light saturation. It is often discussed that upper canopy leaves exposed to direct sunlight are fully light-saturated. However, we found that upper leaves of three temperate species, a heliophytic perennial herb Helianthus tuberosus, a pioneer tree Alnus japonica, and a late-successional tree Fagus crenata, were not fully light-saturated even under full sunlight. Geometrical analysis of the photosynthetic light response curves revealed that all the curves of the leaves from different canopy positions, as well as from the different species, can be considered as different parts of a single non-rectangular hyperbola. The analysis consistently explained how those leaves were not fully light-saturated. Light use optimization models, called big leaf models, predicted that the degree of light saturation and LAUE are both independent of light environment. From these, we hypothesized that the upper leaves should not be fully light-saturated even under direct sunlight, but instead should share the light limitation with the shaded lower-canopy leaves, so as to utilize strong sunlight efficiently. Supporting this prediction, within a canopy of H. tuberosus, both the degree of light saturation and LAUE were independent of light environment within a canopy, resulting in proportionality between the daily photosynthesis and the daily incident light among the leaves.