Global-scale environmental control of plant photosynthetic capacity

Seasonal trends in leaf-level photosynthetic capacity and water use efficiency in a North American Eastern deciduous forest and their impact on canopy-scale gas exchange

Vegetative transpiration (E) and photosynthetic carbon assimilation (A) are known to be seasonally dynamic, with changes in their ratio determining the marginal water use efficiency (WUE). Despite an understanding that stomata play a mechanistic role in regulating WUE, it is still unclear how stomatal and nonstomatal processes influence change in WUE over the course of the growing season. As a result, limited understanding of the primary physiological drivers of seasonal dynamics of canopy WUE remains one of the largest uncertainties in earth system model projections of carbon and water exchange in temperate deciduous forest ecosystems. We investigated seasonal patterns in leaf-level physiological, hydraulic, and anatomical properties, including the seasonal progress of the stomatal slope parameter (g1 ; inversely proportional to WUE) and the maximum carboxylation rate (Vcmax ). Vcmax and g1 were seasonally variable; however, their patterns were not temporally synchronized. g1 generally showed an increasing trend until late in the season, while Vcmax peaked during the midsummer months. Seasonal progression of Vcmax was primarily driven by changes in leaf structural, and anatomical characteristics, while seasonal changes in g1 were most strongly related to changes in Vcmax and leaf hydraulics. Using a seasonally variable Vcmax and g1 to parameterize a canopy-scale gas exchange model increased seasonally aggregated A and E by 3% and 16%, respectively.

Soil nitrogen fertilization reduces relative leaf nitrogen allocation to photosynthesis

The connection between soil nitrogen availability, leaf nitrogen, and photosynthetic capacity is not perfectly understood. Because these three components tend to be positively related over large spatial scales, some posit that soil nitrogen positively drives leaf nitrogen, which positively drives photosynthetic capacity. Alternatively, others posit that photosynthetic capacity is primarily driven by above-ground conditions. Here, we examined the physiological responses of a non-nitrogen-fixing plant (Gossypium hirsutum) and a nitrogen-fixing plant (Glycine max) in a fully factorial combination of light by soil nitrogen availability to help reconcile these competing hypotheses. Soil nitrogen stimulated leaf nitrogen in both species, but the relative proportion of leaf nitrogen used for photosynthetic processes was reduced under elevated soil nitrogen in all light availability treatments due to greater increases in leaf nitrogen content than chlorophyll and leaf biochemical process rates. Leaf nitrogen content and biochemical process rates in G. hirsutum were more responsive to changes in soil nitrogen than those in G. max, probably due to strong G. max investments in root nodulation under low soil nitrogen. Nonetheless, whole-plant growth was significantly enhanced by increased soil nitrogen in both species. Light availability consistently increased relative leaf nitrogen allocation to leaf photosynthesis and whole-plant growth, a pattern that was similar between species. These results suggest that the leaf nitrogen-photosynthesis relationship varies under different soil nitrogen levels and that these species preferentially allocated more nitrogen to plant growth and non-photosynthetic leaf processes, rather than photosynthesis, as soil nitrogen increased.

Acclimation of photosynthetic capacity and foliar respiration in Andean tree species to temperature change

Climate warming is causing compositional changes in Andean tropical montane forests (TMFs). These shifts are hypothesised to result from differential responses to warming of cold- and warm-affiliated species, with the former experiencing mortality and the latter migrating upslope. The thermal acclimation potential of Andean TMFs remains unknown. Along a 2000 m Andean altitudinal gradient, we planted individuals of cold- and warm-affiliated species (under common soil and irrigation), exposing them to the hot and cold extremes of their thermal niches, respectively. We measured the response of net photosynthesis (A_net ), photosynthetic capacity and leaf dark respiration (R_dark ) to warming/cooling, 5 months after planting. In all species, A_net and photosynthetic capacity at 25°C were highest when growing at growth temperatures (T_g ) closest to their thermal means, declining with warming and cooling in cold-affiliated and warm-affiliated species, respectively. When expressed at T_g , photosynthetic capacity and R_dark remained unchanged in cold-affiliated species, but the latter decreased in warm-affiliated counterparts. R_dark at 25°C increased with temperature in all species, but remained unchanged when expressed at T_g . Both species groups acclimated to temperature, but only warm-affiliated species decreased R_dark to photosynthetic capacity ratio at T_g as temperature increased. This could confer them a competitive advantage under future warming.

Shrub Invasion Overrides the Effect of Imposed Drought on the Photosynthetic Capacity and Physiological Responses of Mediterranean Cork Oak Trees

Mediterranean ecosystems face threats from both climate change and shrub invasion. As shrub cover increases, competition for water intensifies, exacerbating the negative effects of drought on ecosystem functioning. However, research into the combined effects of drought and shrub invasion on tree carbon assimilation has been limited. We used a Mediterranean cork oak (Quercus suber) woodland to investigate the effects of drought and shrub invasion by gum rockrose (Cistus ladanifer) on cork oak carbon assimilation and photosynthetic capacity. We established a factorial experiment of imposed drought (ambient and rain exclusion) and shrub invasion (invaded and non-invaded) and measured leaf water potential, stomatal conductance and photosynthesis as well as photosynthetic capacity in cork oak and gum rockrose over one year. We observed distinct detrimental effects of gum rockrose shrub invasion on the physiological responses of cork oak trees throughout the study period. Despite the imposed drought, the impact of shrub invasion was more pronounced, resulting in significant photosynthetic capacity reduction of 57% during summer. Stomatal and non-stomatal limitations were observed under moderate drought in both species. Our findings provide significant knowledge on the impact of gum rockrose invasion on the functioning of cork oak and can be used to improve the representation of photosynthesis in terrestrial biosphere models.

Stomatal conductance, not biochemistry, drives low temperature acclimation of photosynthesis in Populus balsamifera, regardless of nitrogen availability

Low-temperature thermal acclimation may require adjustments to N and water use to sustain photosynthesis because of slow enzyme functioning and high water viscosity. However, understanding of photosynthetic acclimation to temperatures below 11 °C is limited. We acclimated Populus balsamifera to 6 °C and 10 °C (6A and 10A, respectively) and provided the trees with either high or low N fertilizer. We measured net CO₂ assimilation (A_net ), stomatal conductance (g_s ), maximum rates of Rubisco carboxylation (V_cmax ), electron transport (J_max ) and dark respiration (R_d ) at leaf temperatures of 2, 6, 10, 14 and 18 °C, along with leaf N concentrations. The 10A trees had higher A_net than the 6A trees at warmer leaf temperatures, which was correlated with higher g_s in the 10A trees. The instantaneous temperature responses of V_cmax , J_max and R_d were similar for trees from both acclimation temperatures. While soil N availability increased leaf N concentrations, this had no effect on acclimation of photosynthesis or respiration. Our results indicate that acclimation below 11 °C occurred primarily through changes in stomatal conductance, not photosynthetic biochemistry, and was unaffected by short-term N supply. Thermal acclimation of stomatal conductance should therefore be a priority for future carbon cycle model development.

Temperature responses of photosynthesis and respiration in evergreen trees from boreal to tropical latitudes

Evergreen species are widespread across the globe, representing two major plant functional forms in terrestrial models. We reviewed and analysed the responses of photosynthesis and respiration to warming in 101 evergreen species from boreal to tropical biomes. Summertime temperatures affected both latitudinal gas exchange rates and the degree of responsiveness to experimental warming. The decrease in net photosynthesis at 25°C (A_net25 ) was larger with warming in tropical climates than cooler ones. Respiration at 25°C (R₂₅ ) was reduced by 14% in response to warming across species and biomes. Gymnosperms were more sensitive to greater amounts of warming than broadleaved evergreens, with A_net25 and R₂₅ reduced c. 30-40% with > 10°C warming. While standardised rates of carboxylation (V_cmax25 ) and electron transport (J_max25 ) adjusted to warming, the magnitude of this adjustment was not related to warming amount (range 0.6-16°C). The temperature optimum of photosynthesis (T_optA ) increased on average 0.34°C per °C warming. The combination of more constrained acclimation of photosynthesis and increasing respiration rates with warming could possibly result in a reduced carbon sink in future warmer climates. The predictable patterns of thermal acclimation across biomes provide a strong basis to improve modelling predictions of the future terrestrial carbon sink with warming.

Differential Investment Strategies in Leaf Economic Traits Across Climate Regions Worldwide

The leaf economics spectrum (LES) is the leading theory of plant ecological strategies based on functional traits, which explains the trade-off between dry matter investment in leaf structure and the potential rate of resource return, revealing general patterns of leaf economic traits investment for different plant growth types, functional types, or biomes. Prior work has revealed the moderating role of different environmental factors on the LES, but whether the leaf trait bivariate relationships are shifted across climate regions or across continental scales requires further verification. Here we use the Köppen-Geiger climate classification, a very widely used and robust criterion, as a basis for classifying climate regions to explore climatic differences in leaf trait relationships. We compiled five leaf economic traits from a global dataset, including leaf dry matter content (LDMC), specific leaf area (SLA), photosynthesis per unit of leaf dry mass (Amass), leaf nitrogen concentration (Nmass), and leaf phosphorus concentration (Pmass). Moreover, we primarily used the standardized major axis (SMA) analysis to establish leaf trait bivariate relationships and to explore differences in trait relationships across climate regions as well as intercontinental differences within the same climate type. Leaf trait relationships were significantly correlated across almost all subgroups (P < 0.001). However, there was no common slope among different climate zones or climate types and the slopes of the groups fluctuated sharply up and down from the global estimates. The range of variation in the SMA slope of each leaf relationship was as follows: LDMC-SLA relationships (from -0.84 to -0.41); Amass-SLA relationships (from 0.83 to 1.97); Amass-Nmass relationships (from 1.33 to 2.25); Nmass-Pmass relationships (from 0.57 to 1.02). In addition, there was significant slope heterogeneity among continents within the Steppe climate (BS) or the Temperate humid climate (Cf). The shifts of leaf trait relationships in different climate regions provide evidence for environmentally driven differential plant investment in leaf economic traits. Understanding these differences helps to better calibrate various plant-climate models and reminds us that smaller-scale studies may need to be carefully compared with global studies.

The ecology and physiology of fern gametophytes: A methodological synthesis

All green plants alternate between the gametophyte and sporophyte life stages, but only seed-free vascular plants (ferns and lycophytes) have independent, free-living gametophytes. Fern and lycophyte gametophytes are significantly reduced in size and morphological complexity relative to their sporophytic counterparts and have often been overlooked in ecological and physiological studies. Understanding the ecological and physiological factors that directly impact this life stage is of critical importance because the ultimate existence of a sporophyte is dependent upon successful fertilization in the gametophyte generation. Furthermore, previous research has shown that the dual nature of the life cycle and the high dispersibility of spores can result in different geographic patterns between gametophytes and their respective sporophytes. This variation in distribution patterns likely exacerbates the separation of selective pressures acting on gametophyte and sporophyte generations, and can uniquely impact a species' ecology and physiology. Here, we provide a review of historical and contemporary methodologies used to examine ecological and physiological aspects of fern gametophytes, as well as those that allow for comparisons between the two generations. We conclude by suggesting methodological approaches to answer currently outstanding questions. We hope that the information covered herein will serve as a guide to current researchers and stimulate future discoveries in fern gametophyte ecology and physiology.

Temperature acclimation of leaf respiration differs between marsh and mangrove vegetation in a coastal wetland ecotone

Temperature acclimation of leaf respiration (R) is an important determinant of ecosystem responses to temperature and the magnitude of temperature-CO₂ feedbacks as climate warms. Yet, the extent to which temperature acclimation of R exhibits a common pattern across different growth conditions, ecosystems, and plant functional types remains unclear. Here, we measured the short-term temperature response of R at six time points over a 10-month period in two coastal wetland species (Avicennia germinans [C₃ mangrove] and Spartina alterniflora [C₄ marsh grass]) growing under ambient and experimentally warmed temperatures at two sites in a marsh-mangrove ecotone. Leaf nitrogen (N) was determined on a subsample of leaves to explore potential coupling of R and N. We hypothesized that both species would reduce R at 25°C (R²⁵ ) and the short-term temperature sensitivity of R (Q₁₀ ) as air temperature (T_air ) increased across seasons, but the decline would be stronger in Avicennia than in Spartina. For each species, we hypothesized that seasonal temperature acclimation of R would be equivalent in plants grown under ambient and warmed temperatures, demonstrating convergent acclimation. Surprisingly, Avicennia generally increased R²⁵ with increasing growth temperature, although the Q₁₀ declined as seasonal temperatures increased and did so consistently across sites and treatments. Weak temperature acclimation resulted in reduced homeostasis of R in Avicennia. Spartina reduced R²⁵ and the Q₁₀ as seasonal temperatures increased. In Spartina, seasonal temperature acclimation was largely consistent across sites and treatments resulting in greater respiratory homeostasis. We conclude that co-occurring coastal wetland species may show contrasting patterns of respiratory temperature acclimation. Nonetheless, leaf N scaled positively with R²⁵ in both species, highlighting the importance of leaf N in predicting respiratory capacity across a range of growth temperatures. The patterns of respiratory temperature acclimation shown here may improve the predictions of temperature controls of CO₂ fluxes in coastal wetlands.

Spectroscopy outperforms leaf trait relationships for predicting photosynthetic capacity across different forest types

Leaf trait relationships are widely used to predict ecosystem function in terrestrial biosphere models (TBMs), in which leaf maximum carboxylation capacity (V_c,max ), an important trait for modelling photosynthesis, can be inferred from other easier-to-measure traits. However, whether trait-V_c,max relationships are robust across different forest types remains unclear. Here we used measurements of leaf traits, including one morphological trait (leaf mass per area), three biochemical traits (leaf water content, area-based leaf nitrogen content, and leaf chlorophyll content), one physiological trait (V_c,max ), as well as leaf reflectance spectra, and explored their relationships within and across three contrasting forest types in China. We found weak and forest type-specific relationships between V_c,max and the four morphological and biochemical traits (R²  ≤ 0.15), indicated by significantly changing slopes and intercepts across forest types. By contrast, reflectance spectroscopy effectively collapsed the differences in the trait-V_c,max relationships across three forest biomes into a single robust model for V_c,max (R²  = 0.77), and also accurately estimated the four traits (R²  = 0.75-0.94). These findings challenge the traditional use of the empirical trait-V_c,max relationships in TBMs for estimating terrestrial plant photosynthesis, but also highlight spectroscopy as an efficient alternative for characterising V_c,max and multitrait variability, with critical insights into ecosystem modelling and functional trait ecology.

A best-practice guide to predicting plant traits from leaf-level hyperspectral data using partial least squares regression

Partial least squares regression (PLSR) modelling is a statistical technique for correlating datasets, and involves the fitting of a linear regression between two matrices. One application of PLSR enables leaf traits to be estimated from hyperspectral optical reflectance data, facilitating rapid, high-throughput, non-destructive plant phenotyping. This technique is of interest and importance in a wide range of contexts including crop breeding and ecosystem monitoring. The lack of a consensus in the literature on how to perform PLSR means that interpreting model results can be challenging, applying existing models to novel datasets can be impossible, and unknown or undisclosed assumptions can lead to incorrect or spurious predictions. We address this lack of consensus by proposing best practices for using PLSR to predict plant traits from leaf-level hyperspectral data, including a discussion of when PLSR is applicable, and recommendations for data collection. We provide a tutorial to demonstrate how to develop a PLSR model, in the form of an R script accompanying this manuscript. This practical guide will assist all those interpreting and using PLSR models to predict leaf traits from spectral data, and advocates for a unified approach to using PLSR for predicting traits from spectra in the plant sciences.

Including leaf trait information helps empirical estimation of jmax from vcmax in cool-temperate deciduous forests

Understanding the uncertainty in the parameterization of the two photosynthetic capacity parameters, leaf maximum carboxylation rate (Vcmax), and maximum electron transport rate (Jmax), is crucial for modeling and predicting carbon fluxes in terrestrial ecosystems. In gas exchange models, to date, Jmax is typically estimated from Vcmax based on a linear regression. However, recent studies have revealed that this relationship varies, dependent upon species, leaf groups, and time, so it is doubtful that the regression applies universally. Furthermore, far less is known regarding how other leaf traits affect the regression. In this study we analyzed the two key photosynthetic parameters and popularly measurable leaf traits, leaf chlorophyll concentration and leaf mass per area (LMA), of cool-temperate forest stands in Japan, aiming to construct a simple regression applicable to temperate deciduous forests, at least. The analysis was based on a long-term field dataset covering years of data for both sunlit and shaded leaves at different altitudes. Results showed that the best-fitted slope of the regression differed markedly from those previously reported, which were typically acquired from sunlit leaves. LMA had a significant effect on the regression, producing the lowest root mean square errors and the highest ratio of performance to deviation values (RPD = 2.017). Although more data are needed to validate in other ecosystems, our approach at least provides a promising way to substantially improve photosynthesis model predictions, by introducing leaf traits into the popular empirical regression of Jmax against Vcmax, and ultimately to better understand the functioning of the photosynthetic machinery.

Seasonal trends in photosynthesis and leaf traits in scarlet oak

Understanding seasonal variation in photosynthesis is important for understanding and modeling plant productivity. Here, we used shotgun sampling to examine physiological, structural and spectral leaf traits of upper canopy, sun-exposed leaves in Quercus coccinea Münchh (scarlet oak) across the growing season in order to understand seasonal trends, explore the mechanisms underpinning physiological change and investigate the impact of extrapolating measurements from a single date to the whole season. We tested the hypothesis that photosynthetic rates and capacities would peak at the summer solstice, i.e., at the time of peak photoperiod. Contrary to expectations, our results reveal a late-season peak in both photosynthetic capacity and rate before the expected sharp decrease at the start of senescence. This late-season maximum occurred after the higher summer temperatures and vapor pressure deficit and was correlated with the recovery of leaf water content and increased stomatal conductance. We modeled photosynthesis at the top of the canopy and found that the simulated results closely tracked the maximum carboxylation capacity of Rubisco. For both photosynthetic capacity and modeled top-of-canopy photosynthesis, the maximum value was therefore not observed at the summer solstice. Rather, in each case, the measurements at and around the solstice were close to the overall seasonal mean, with values later in the season leading to deviations from the mean by up to 41 and 52%, respectively. Overall, we found that the expected Gaussian pattern of photosynthesis was not observed. We conclude that an understanding of species- and environment-specific changes in photosynthesis across the season is essential for correct estimation of seasonal photosynthetic capacity.

Global variation in the fraction of leaf nitrogen allocated to photosynthesis

Plants invest a considerable amount of leaf nitrogen in the photosynthetic enzyme ribulose-1,5-bisphosphate carboxylase-oxygenase (RuBisCO), forming a strong coupling of nitrogen and photosynthetic capacity. Variability in the nitrogen-photosynthesis relationship indicates different nitrogen use strategies of plants (i.e., the fraction nitrogen allocated to RuBisCO; fLNR), however, the reason for this remains unclear as widely different nitrogen use strategies are adopted in photosynthesis models. Here, we use a comprehensive database of in situ observations, a remote sensing product of leaf chlorophyll and ancillary climate and soil data, to examine the global distribution in fLNR using a random forest model. We find global fLNR is 18.2 ± 6.2%, with its variation largely driven by negative dependence on leaf mass per area and positive dependence on leaf phosphorus. Some climate and soil factors (i.e., light, atmospheric dryness, soil pH, and sand) have considerable positive influences on fLNR regionally. This study provides insight into the nitrogen-photosynthesis relationship of plants globally and an improved understanding of the global distribution of photosynthetic potential.

An optimality-based model explains seasonal variation in C3 plant photosynthetic capacity

The maximum rate of carboxylation (V_cmax ) is an essential leaf trait determining the photosynthetic capacity of plants. Existing approaches for estimating V_cmax at large scale mainly rely on empirical relationships with proxies such as leaf nitrogen/chlorophyll content or hyperspectral reflectance, or on complicated inverse models from gross primary production or solar-induced fluorescence. A novel mechanistic approach based on the assumption that plants optimize resource investment coordinating with environment and growth has been shown to accurately predict C3 plant V_cmax based on mean growing season environmental conditions. However, the ability of optimality theory to explain seasonal variation in V_cmax has not been fully investigated. Here, we adapt an optimality-based model to simulate daily V_cmax,25C (V_cmax at a standardized temperature of 25°C) by incorporating the effects of antecedent environment, which affects current plant functioning, and dynamic light absorption, which coordinates with plant functioning. We then use seasonal V_cmax,25C field measurements from 10 sites across diverse ecosystems to evaluate model performance. Overall, the model explains about 83% of the seasonal variation in C3 plant V_cmax,25C across the 10 sites, with a medium root mean square error of 12.3 μmol m^-2  s^-1 , which suggests that seasonal changes in V_cmax,25C are consistent with optimal plant function. We show that failing to account for acclimation to antecedent environment or coordination with dynamic light absorption dramatically decreases estimation accuracy. Our results show that optimality-based approach can accurately reproduce seasonal variation in canopy photosynthetic potential, and suggest that incorporating such theory into next-generation trait-based terrestrial biosphere models would improve predictions of global photosynthesis.

Components of leaf-trait variation along environmental gradients

Leaf area (LA), mass per area (LMA), nitrogen per unit area (N_area ) and the leaf-internal to ambient CO₂ ratio (χ) are fundamental traits for plant functional ecology and vegetation modelling. Here we aimed to assess how their variation, within and between species, tracks environmental gradients. Measurements were made on 705 species from 116 sites within a broad north-south transect from tropical to temperate Australia. Trait responses to environment were quantified using multiple regression; within- and between-species responses were compared using analysis of covariance and trait-gradient analysis. Leaf area, the leaf economics spectrum (indexed by LMA and N_area ) and χ (from stable carbon isotope ratios) varied almost independently among species. Across sites, however, χ and LA increased with mean growing-season temperature (mGDD₀ ) and decreased with vapour pressure deficit (mVPD₀ ) and soil pH. LMA and N_area showed the reverse pattern. Climate responses agreed with expectations based on optimality principles. Within-species variability contributed < 10% to geographical variation in LA but > 90% for χ, with LMA and N_area intermediate. These findings support the hypothesis that acclimation within individuals, adaptation within species and selection among species combine to create predictable relationships between traits and environment. However, the contribution of acclimation/adaptation vs species selection differs among traits.

Contrasting Dependencies of Photosynthetic Capacity on Leaf Nitrogen in Early- and Late-Successional Tropical Montane Tree Species

Differences in photosynthetic capacity among tree species and tree functional types are currently assumed to be largely driven by variation in leaf nutrient content, particularly nitrogen (N). However, recent studies indicate that leaf N content is often a poor predictor of variation in photosynthetic capacity in tropical trees. In this study, we explored the relative importance of area-based total leaf N content (N_tot) and within-leaf N allocation to photosynthetic capacity versus light-harvesting in controlling the variation in photosynthetic capacity (i.e. V _cmax, J _max) among mature trees of 12 species belonging to either early (ES) or late successional (LS) groups growing in a tropical montane rainforest in Rwanda, Central Africa. Photosynthetic capacity at a common leaf temperature of 25˚C (i.e. maximum rates of Rubisco carboxylation, V _cmax25 and of electron transport, J _max25) was higher in ES than in LS species (+ 58% and 68% for V _cmax25 and J _max25, respectively). While N_tot did not significantly differ between successional groups, the photosynthetic dependency on N_tot was markedly different. In ES species, V _cmax25 was strongly and positively related to N_tot but this was not the case in LS species. However, there was no significant trade-off between relative leaf N investments in compounds maximizing photosynthetic capacity versus compounds maximizing light harvesting. Both leaf dark respiration at 25˚C (+ 33%) and, more surprisingly, apparent photosynthetic quantum yield (+ 35%) was higher in ES than in LS species. Moreover, R_d25 was positively related to N_tot for both ES and LS species. Our results imply that efforts to quantify carbon fluxes of tropical montane rainforests would be improved if they considered contrasting within-leaf N allocation and photosynthetic N_tot dependencies between species with different successional strategies.

Mechanisms underlying leaf photosynthetic acclimation to warming and elevated CO2 as inferred from least-cost optimality theory

The mechanisms responsible for photosynthetic acclimation are not well understood, effectively limiting predictability under future conditions. Least-cost optimality theory can be used to predict the acclimation of photosynthetic capacity based on the assumption that plants maximize carbon uptake while minimizing the associated costs. Here, we use this theory as a null model in combination with multiple datasets of C₃ plant photosynthetic traits to elucidate the mechanisms underlying photosynthetic acclimation to elevated temperature and carbon dioxide (CO₂ ). The model-data comparison showed that leaves decrease the ratio of the maximum rate of electron transport to the maximum rate of Rubisco carboxylation (J_max /V_cmax ) under higher temperatures. The comparison also indicated that resources used for Rubisco and electron transport are reduced under both elevated temperature and CO₂ . Finally, our analysis suggested that plants underinvest in electron transport relative to carboxylation under elevated CO₂ , limiting potential leaf-level photosynthesis under future CO₂ concentrations. Altogether, our results show that acclimation to temperature and CO₂ is primarily related to resource conservation at the leaf level. Under future, warmer, high CO₂ conditions, plants are therefore likely to use less nutrients for leaf-level photosynthesis, which may impact whole-plant to ecosystem functioning.

Maximum carbon uptake rate dominates the interannual variability of global net ecosystem exchange

Terrestrial ecosystems contribute most of the interannual variability (IAV) in atmospheric carbon dioxide (CO₂ ) concentrations, but processes driving the IAV of net ecosystem CO₂ exchange (NEE) remain elusive. For a predictive understanding of the global C cycle, it is imperative to identify indicators associated with ecological processes that determine the IAV of NEE. Here, we decompose the annual NEE of global terrestrial ecosystems into their phenological and physiological components, namely maximum carbon uptake (MCU) and release (MCR), the carbon uptake period (CUP), and two parameters, α and β, that describe the ratio between actual versus hypothetical maximum C sink and source, respectively. Using long-term observed NEE from 66 eddy covariance sites and global products derived from FLUXNET observations, we found that the IAV of NEE is determined predominately by MCU at the global scale, which explains 48% of the IAV of NEE on average while α, CUP, β, and MCR explain 14%, 25%, 2%, and 8%, respectively. These patterns differ in water-limited ecosystems versus temperature- and radiation-limited ecosystems; 31% of the IAV of NEE is determined by the IAV of CUP in water-limited ecosystems, and 60% of the IAV of NEE is determined by the IAV of MCU in temperature- and radiation-limited ecosystems. The Lund-Potsdam-Jena (LPJ) model and the Multi-scale Synthesis and Terrestrial Model Inter-comparison Project (MsTMIP) models underestimate the contribution of MCU to the IAV of NEE by about 18% on average, and overestimate the contribution of CUP by about 25%. This study provides a new perspective on the proximate causes of the IAV of NEE, which suggest that capturing the variability of MCU is critical for modeling the IAV of NEE across most of the global land surface.

Leaf reflectance spectroscopy captures variation in carboxylation capacity across species, canopy environment and leaf age in lowland moist tropical forests

Understanding the pronounced seasonal and spatial variation in leaf carboxylation capacity (V_c,max ) is critical for determining terrestrial carbon cycling in tropical forests. However, an efficient and scalable approach for predicting V_c,max is still lacking. Here the ability of leaf spectroscopy for rapid estimation of V_c,max was tested. V_c,max was estimated using traditional gas exchange methods, and measured reflectance spectra and leaf age in leaves sampled from tropical forests in Panama and Brazil. These data were used to build a model to predict V_c,max from leaf spectra. The results demonstrated that leaf spectroscopy accurately predicts V_c,max of mature leaves in Panamanian tropical forests (R²  = 0.90). However, this single-age model required recalibration when applied to broader leaf demographic classes (i.e. immature leaves). Combined use of spectroscopy models for V_c,max and leaf age enabled construction of the V_c,max -age relationship solely from leaf spectra, which agreed with field observations. This suggests that the spectroscopy technique can capture the seasonal variability in V_c,max , assuming sufficient sampling across diverse species, leaf ages and canopy environments. This finding will aid development of remote sensing approaches that can be used to characterize V_c,max in moist tropical forests and enable an efficient means to parameterize and evaluate terrestrial biosphere models.

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.

Seasonal responses of photosynthetic parameters in maize and sunflower and their relationship with leaf functional traits

Estimates of seasonal variation in photosynthetic capacity (P_c ) are critical for modeling the time course of carbon fluxes. Given the time-intensive nature of calculating P_c parameters via gas exchange, it is appealing to calculate parameter variation via changes in chlorophyll (Chl) and nitrogen (N) content by assuming that P_c scales with these variables. Although seasonal changes in P_c and the relationships between N and P_c have been evaluated in forest canopies, there is limited data on seasonal parameter values in crops, nor is it clear if seasonal changes in P_c can be estimated from leaf traits under the high N fertility of managed systems. We characterized the seasonal variability of the maximum rates of carboxylation (V_cmax ) and electron transport (J_max ) under well-fertilized conditions for maize (Zea mays L.) and sunflower (Helianthus annuus L.) and coupled these data with measurements of Chl, N, and leaf mass per unit area (LMA). The seasonal Chl-N relationship was significant in maize, but not in sunflower. Area-based N-V_cmax relationships were not significant for either crop. Mass-based N-V_cmax relationships were weak in sunflower, but highly significant in maize. Our results suggest that P_c can be seasonally adjusted in maize with reliable estimates of changes in LMA.

Acclimation and adaptation components of the temperature dependence of plant photosynthesis at the global scale

The temperature response of photosynthesis is one of the key factors determining predicted responses to warming in global vegetation models (GVMs). The response may vary geographically, owing to genetic adaptation to climate, and temporally, as a result of acclimation to changes in ambient temperature. Our goal was to develop a robust quantitative global model representing acclimation and adaptation of photosynthetic temperature responses. We quantified and modelled key mechanisms responsible for photosynthetic temperature acclimation and adaptation using a global dataset of photosynthetic CO₂ response curves, including data from 141 C₃ species from tropical rainforest to Arctic tundra. We separated temperature acclimation and adaptation processes by considering seasonal and common-garden datasets, respectively. The observed global variation in the temperature optimum of photosynthesis was primarily explained by biochemical limitations to photosynthesis, rather than stomatal conductance or respiration. We found acclimation to growth temperature to be a stronger driver of this variation than adaptation to temperature at climate of origin. We developed a summary model to represent photosynthetic temperature responses and showed that it predicted the observed global variation in optimal temperatures with high accuracy. This novel algorithm should enable improved prediction of the function of global ecosystems in a warming climate.

Modelled net carbon gain responses to climate change in boreal trees: Impacts of photosynthetic parameter selection and acclimation

Boreal forests are crucial in regulating global vegetation-atmosphere feedbacks, but the impact of climate change on boreal tree carbon fluxes is still unclear. Given the sensitivity of global vegetation models to photosynthetic and respiration parameters, we determined how predictions of net carbon gain (C-gain) respond to variation in these parameters using a stand-level model (MAESTRA). We also modelled how thermal acclimation of photosynthetic and respiratory temperature sensitivity alters predicted net C-gain responses to climate change. We modelled net C-gain of seven common boreal tree species under eight climate scenarios across a latitudinal gradient to capture a range of seasonal temperature conditions. Physiological parameter values were taken from the literature together with different approaches for thermally acclimating photosynthesis and respiration. At high latitudes, net C-gain was stimulated up to 400% by elevated temperatures and CO₂ in the autumn but suppressed at the lowest latitudes during midsummer under climate scenarios that included warming. Modelled net C-gain was more sensitive to photosynthetic capacity parameters (V_cmax , J_max , Arrhenius temperature response parameters, and the ratio of J_max to V_cmax ) than stomatal conductance or respiration parameters. The effect of photosynthetic thermal acclimation depended on the temperatures where it was applied: acclimation reduced net C-gain by 10%-15% within the temperature range where the equations were derived but decreased net C-gain by 175% at temperatures outside this range. Thermal acclimation of respiration had small, but positive, impacts on net C-gain. We show that model simulations are highly sensitive to variation in photosynthetic parameters and highlight the need to better understand the mechanisms and drivers underlying this variability (e.g., whether variability is environmentally and/or biologically driven) for further model improvement.

The validity of optimal leaf traits modelled on environmental conditions

The ratio of leaf intercellular to ambient CO₂ (χ) is modulated by stomatal conductance (g_s ). These quantities link carbon (C) assimilation with transpiration, and along with photosynthetic capacities (V_cmax and J_max ) are required to model terrestrial C uptake. We use optimization criteria based on the growth environment to generate predicted values of photosynthetic and water-use efficiency traits and test these against a unique dataset. Leaf gas-exchange parameters and carbon isotope discrimination were analysed in relation to local climate across a continental network of study sites. Sun-exposed leaves of 50 species at seven sites were measured in contrasting seasons. Values of χ predicted from growth temperature and vapour pressure deficit were closely correlated to ratios derived from C isotope (δ¹³ C) measurements. Correlations were stronger in the growing season. Predicted values of photosynthetic traits, including carboxylation capacity (V_cmax ), derived from δ¹³ C, growth temperature and solar radiation, showed meaningful agreement with inferred values derived from gas-exchange measurements. Between-site differences in water-use efficiency were, however, only weakly linked to the plant's growth environment and did not show seasonal variation. These results support the general hypothesis that many key parameters required by Earth system models are adaptive and predictable from plants' growth environments.

Global photosynthetic capacity is optimized to the environment

Earth system models (ESMs) use photosynthetic capacity, indexed by the maximum Rubisco carboxylation rate (V_cmax), to simulate carbon assimilation and typically rely on empirical estimates, including an assumed dependence on leaf nitrogen determined from soil fertility. In contrast, new theory, based on biochemical coordination and co‐optimization of carboxylation and water costs for photosynthesis, suggests that optimal V_cmax can be predicted from climate alone, irrespective of soil fertility. Here, we develop this theory and find it captures 64% of observed variability in a global, field‐measured V_cmax dataset for C₃ plants. Soil fertility indices explained substantially less variation (32%). These results indicate that environmentally regulated biophysical constraints and light availability are the first‐order drivers of global photosynthetic capacity. Through acclimation and adaptation, plants efficiently utilize resources at the leaf level, thus maximizing potential resource use for growth and reproduction. Our theory offers a robust strategy for dynamically predicting photosynthetic capacity in ESMs.

Leaf-level photosynthetic capacity dynamics in relation to soil and foliar nutrients along forest-savanna boundaries in Ghana and Brazil

Forest-savanna boundaries extend across large parts of the tropics but the variability of photosynthetic capacity in relation to soil and foliar nutrients across these transition zones is poorly understood. For this reason, we compared photosynthetic capacity (maximum rate of carboxylation of Rubisco at 25 C° (Vcmax25), leaf mass, nitrogen (N), phosphorus (P) and potassium (K) per unit leaf area (LMA, Narea, Parea and Karea, respectively), in relation to respective soil nutrients from 89 species at seven sites along forest-savanna ecotones in Ghana and Brazil. Contrary to our expectations, edaphic conditions were not reflected in foliar nutrient concentrations but LMA was slightly higher in lower fertility soils. Overall, each vegetation type within the ecotones demonstrated idiosyncratic and generally weak relationships between Vcmax25 and Narea, Parea and Karea. Species varied significantly in their Vcmax25 ↔ Narea relationship due to reduced investment of total Narea in photosynthetic machinery with increasing LMA. We suggest that studied species in the forest-savanna ecotones do not maximize Vcmax25 per given total Narea due to adaptation to intermittent water availability. Our findings have implications for global modeling of Vcmax25 and forest-savanna ecotone productivity.

Enhanced peak growth of global vegetation and its key mechanisms

The annual peak growth of vegetation is critical in characterizing the capacity of terrestrial ecosystem productivity and shaping the seasonality of atmospheric CO₂ concentrations. The recent greening of global lands suggests an increasing trend of terrestrial vegetation growth, but whether or not the peak growth has been globally enhanced still remains unclear. Here, we use two global datasets of gross primary productivity (GPP) and a satellite-derived Normalized Difference Vegetation Index (NDVI) to characterize recent changes in annual peak vegetation growth (that is, GPP_max and NDVI_max). We demonstrate that the peak in the growth of global vegetation has been linearly increasing during the past three decades. About 65% of the NDVI_max variation is evenly explained by expanding croplands (21%), rising CO₂ (22%) and intensifying nitrogen deposition (22%). The contribution of expanding croplands to the peak growth trend is substantiated by measurements from eddy-flux towers, sun-induced chlorophyll fluorescence and a global database of plant traits, all of which demonstrate that croplands have a higher photosynthetic capacity than other vegetation types. The large contribution of CO₂ is also supported by a meta-analysis of 466 manipulative experiments and 15 terrestrial biosphere models. Furthermore, we show that the contribution of GPP_max to the change in annual GPP is less in the tropics than in other regions. These multiple lines of evidence reveal an increasing trend in the peak growth of global vegetation. The findings highlight the important roles of agricultural intensification and atmospheric changes in reshaping the seasonality of global vegetation growth.

Photosynthetic capacity and leaf nitrogen decline along a controlled climate gradient in provenances of two widely distributed Eucalyptus species

Climate is an important factor limiting tree distributions and adaptation to different thermal environments may influence how tree populations respond to climate warming. Given the current rate of warming, it has been hypothesized that tree populations in warmer, more thermally stable climates may have limited capacity to respond physiologically to warming compared to populations from cooler, more seasonal climates. We determined in a controlled environment how several provenances of widely distributed Eucalyptus tereticornis and E. grandis adjusted their photosynthetic capacity to +3.5°C warming along their native distribution range (~16-38°S) and whether climate of seed origin of the provenances influenced their response to different growth temperatures. We also tested how temperature optima (T_opt ) of photosynthesis and J_max responded to higher growth temperatures. Our results showed increased photosynthesis rates at a standardized temperature with warming in temperate provenances, while rates in tropical provenances were reduced by about 40% compared to their temperate counterparts. Temperature optima of photosynthesis increased as provenances were exposed to warmer growth temperatures. Both species had ~30% reduced photosynthetic capacity in tropical and subtropical provenances related to reduced leaf nitrogen and leaf Rubisco content compared to temperate provenances. Tropical provenances operated closer to their thermal optimum and came within 3% of the T_opt of J_max during the daily temperature maxima. Hence, further warming may negatively affect C uptake and tree growth in warmer climates, whereas eucalypts in cooler climates may benefit from moderate warming.

Phosphorus deficiency alters scaling relationships between leaf gas exchange and associated traits in a wide range of contrasting Eucalyptus species

Phosphorus (P) limitation is known to have substantial impacts on leaf metabolism. However, uncertainty remains around whether P deficiency alters scaling functions linking leaf metabolism to associated traits. We investigated the effect of P deficiency on leaf gas exchange and related leaf traits in 17 contrasting Eucalyptus species that exhibit inherent differences in leaf traits. Saplings were grown under controlled-environment conditions in a glasshouse, where they were subjected to minus and plus P treatments for 15 weeks. P deficiency decreased P concentrations and increased leaf mass per area (LMA) of newly-developed leaves. Rates of photosynthesis (A) and respiration (R) were also reduced in P-deficient plants compared with P-fertilised plants. By contrast, P deficiency had little effect on the temperature sensitivity of R. Irrespective of P treatment, on a log-log basis A and R scaled positively with increasing leaf nitrogen concentration [N] and negatively with increasing LMA. Although P deficiency had limited impact on A-R-LMA relationships, rates of CO2 exchange per unit N were consistently lower in P-deficient plants. Our results highlight the importance of P supply for leaf carbon metabolism and show how P deficiencies (i.e. when excluding confounding genotypic and environmental effects) can have a direct effect on commonly used leaf trait scaling relationships.

Mesophyll conductance does not contribute to greater photosynthetic rate per unit nitrogen in temperate compared with tropical evergreen wet-forest tree leaves

Globally, trees originating from high-rainfall tropical regions typically exhibit lower rates of light-saturated net CO₂ assimilation (A) compared with those from high-rainfall temperate environments, when measured at a common temperature. One factor that has been suggested to contribute towards lower rates of A is lower mesophyll conductance. Using a combination of leaf gas exchange and carbon isotope discrimination measurements, we estimated mesophyll conductance (g_m ) of several Australian tropical and temperate wet-forest trees, grown in a common environment. Maximum Rubisco carboxylation capacity, V_cmax , was obtained from CO₂ response curves. g_m and the drawdown of CO₂ across the mesophyll were both relatively constant. V_cmax estimated on the basis of intercellular CO₂ partial pressure, C_i , was equivalent to that estimated using chloroplastic CO₂ partial pressure, C_c , using 'apparent' and 'true' Rubisco Michaelis-Menten constants, respectively Having ruled out g_m as a possible factor in distorting variations in A between these tropical and temperate trees, attention now needs to be focused on obtaining more detailed information about Rubisco in these species.

Leaf non-structural carbohydrate allocation and C:N:P stoichiometry in response to light acclimation in seedlings of two subtropical shade-tolerant tree species

Light availability greatly affects plant growth and development. In shaded environments, plants must respond to reduced light intensity to ensure a regular rate of photosynthesis to maintain the dynamic balance of nutrients, such as leaf non-structural carbohydrates (NSCs), carbon (C), nitrogen (N) and phosphorus (P). To improve our understanding of the nutrient utilization strategies of understory shade-tolerant plants, we compared the variations in leaf NSCs, C, N and P in response to heterogeneous controlled light conditions between two subtropical evergreen broadleaf shade-tolerant species, Elaeocarpus sylvestris (E. sylvestris) and Illicium henryi (I. henryi). Light intensity treatments were applied at five levels (100%, 52%, 33%, 15% and 6% full sunlight) for 30 weeks to identify the effects of reduced light intensity on leaf NSC allocation patterns and leaf C:N:P stoichiometry characteristics. We found that leaf soluble sugar, starch and NSC concentrations in E. sylvestris showed decreasing trends with reduced light intensity, whereas I. henryi presented slightly increasing trends from 100% to 15% full sunlight and then significant decreases at extremely low light intensity (6% full sunlight). The soluble sugar/starch ratio of E. sylvestris decreased with decreasing light intensity, whereas that of I. henryi remained stable. Moreover, both species exhibited increasing trends in leaf N and P concentrations but limited leaf N:P and C:P ratio fluctuations with decreasing light intensity, revealing their adaptive strategies for poor light environments and their growth strategies under ideal light environments. There were highly significant correlations between leaf NSC variables and C:N:P stoichiometric variables in both species, revealing a trade-off in photosynthesis production between leaf NSC and carbon allocation. Thus, shade-tolerant plants readjusted their allocation of leaf NSCs, C, N and P in response to light acclimation. Redundancy analysis showed that leaf morphological features of both E. sylvestris and I. henryi affected their corresponding leaf nutrient traits. These results improve our understanding of the dynamic balance between leaf NSCs and leaf C, N and P components in the nutritional metabolism of shade-tolerant plants.

KEY MESSAGE

Two species of understory shade-tolerant plants responded differently to varying light intensities in terms of leaf non-structural carbohydrate allocation and the utilization of carbon, nitrogen and phosphorus to balance nutritional metabolism and adapt to environmental stress.

Terrestrial biosphere models underestimate photosynthetic capacity and CO2 assimilation in the Arctic

Terrestrial biosphere models (TBMs) are highly sensitive to model representation of photosynthesis, in particular the parameters maximum carboxylation rate and maximum electron transport rate at 25°C (V_c,max.25 and J_max.25 , respectively). Many TBMs do not include representation of Arctic plants, and those that do rely on understanding and parameterization from temperate species. We measured photosynthetic CO₂ response curves and leaf nitrogen (N) content in species representing the dominant vascular plant functional types found on the coastal tundra near Barrow, Alaska. The activation energies associated with the temperature response functions of V_c,max and J_max were 17% lower than commonly used values. When scaled to 25°C, V_c,max.25 and J_max.25 were two- to five-fold higher than the values used to parameterize current TBMs. This high photosynthetic capacity was attributable to a high leaf N content and the high fraction of N invested in Rubisco. Leaf-level modeling demonstrated that current parameterization of TBMs resulted in a two-fold underestimation of the capacity for leaf-level CO₂ assimilation in Arctic vegetation. This study highlights the poor representation of Arctic photosynthesis in TBMs, and provides the critical data necessary to improve our ability to project the response of the Arctic to global environmental change.

Short-term acclimation to warmer temperatures accelerates leaf carbon exchange processes across plant types

While temperature responses of photosynthesis and plant respiration are known to acclimate over time in many species, few studies have been designed to directly compare process-level differences in acclimation capacity among plant types. We assessed short-term (7 day) temperature acclimation of the maximum rate of Rubisco carboxylation (V_cmax ), the maximum rate of electron transport (J_max ), the maximum rate of phosphoenolpyruvate carboxylase carboxylation (V_pmax ), and foliar dark respiration (R_d ) in 22 plant species that varied in lifespan (annual and perennial), photosynthetic pathway (C₃ and C₄ ), and climate of origin (tropical and nontropical) grown under fertilized, well-watered conditions. In general, acclimation to warmer temperatures increased the rate of each process. The relative increase in different photosynthetic processes varied by plant type, with C₃ species tending to preferentially accelerate CO₂ -limited photosynthetic processes and respiration and C₄ species tending to preferentially accelerate light-limited photosynthetic processes under warmer conditions. R_d acclimation to warmer temperatures caused a reduction in temperature sensitivity that resulted in slower rates at high leaf temperatures. R_d acclimation was similar across plant types. These results suggest that temperature acclimation of the biochemical processes that underlie plant carbon exchange is common across different plant types, but that acclimation to warmer temperatures tends to have a relatively greater positive effect on the processes most limiting to carbon assimilation, which differ by plant type. The acclimation responses observed here suggest that warmer conditions should lead to increased rates of carbon assimilation when water and nutrients are not limiting.

Informing models through empirical relationships between foliar phosphorus, nitrogen and photosynthesis across diverse woody species in tropical forests of Panama

Our objective was to analyze and summarize data describing photosynthetic parameters and foliar nutrient concentrations from tropical forests in Panama to inform model representation of phosphorus (P) limitation of tropical forest productivity. Gas exchange and nutrient content data were collected from 144 observations of upper canopy leaves from at least 65 species at two forest sites in Panama, differing in species composition, rainfall and soil fertility. Photosynthetic parameters were derived from analysis of assimilation rate vs internal CO₂ concentration curves (A/C_i ), and relationships with foliar nitrogen (N) and P content were developed. The relationships between area-based photosynthetic parameters and nutrients were of similar strength for N and P and robust across diverse species and site conditions. The strongest relationship expressed maximum electron transport rate (J_max ) as a multivariate function of both N and P, and this relationship was improved with the inclusion of independent data on wood density. Models that estimate photosynthesis from foliar N would be improved only modestly by including additional data on foliar P, but doing so may increase the capability of models to predict future conditions in P-limited tropical forests, especially when combined with data on edaphic conditions and other environmental drivers.

The impact of alternative trait-scaling hypotheses for the maximum photosynthetic carboxylation rate (Vcmax ) on global gross primary production

The maximum photosynthetic carboxylation rate (V_cmax ) is an influential plant trait that has multiple scaling hypotheses, which is a source of uncertainty in predictive understanding of global gross primary production (GPP). Four trait-scaling hypotheses (plant functional type, nutrient limitation, environmental filtering, and plant plasticity) with nine specific implementations were used to predict global V_cmax distributions and their impact on global GPP in the Sheffield Dynamic Global Vegetation Model (SDGVM). Global GPP varied from 108.1 to 128.2 PgC yr^-1 , 65% of the range of a recent model intercomparison of global GPP. The variation in GPP propagated through to a 27% coefficient of variation in net biome productivity (NBP). All hypotheses produced global GPP that was highly correlated (r = 0.85-0.91) with three proxies of global GPP. Plant functional type-based nutrient limitation, underpinned by a core SDGVM hypothesis that plant nitrogen (N) status is inversely related to increasing costs of N acquisition with increasing soil carbon, adequately reproduced global GPP distributions. Further improvement could be achieved with accurate representation of water sensitivity and agriculture in SDGVM. Mismatch between environmental filtering (the most data-driven hypothesis) and GPP suggested that greater effort is needed understand V_cmax variation in the field, particularly in northern latitudes.

Strong thermal acclimation of photosynthesis in tropical and temperate wet-forest tree species: the importance of altered Rubisco content

Understanding of the extent of acclimation of light-saturated net photosynthesis (A_n ) to temperature (T), and associated underlying mechanisms, remains limited. This is a key knowledge gap given the importance of thermal acclimation for plant functioning, both under current and future higher temperatures, limiting the accuracy and realism of Earth system model (ESM) predictions. Given this, we analysed and modelled T-dependent changes in photosynthetic capacity in 10 wet-forest tree species: six from temperate forests and four from tropical forests. Temperate and tropical species were each acclimated to three daytime growth temperatures (T_growth ): temperate - 15, 20 and 25 °C; tropical - 25, 30 and 35 °C. CO₂ response curves of A_n were used to model maximal rates of RuBP (ribulose-1,5-bisphosphate) carboxylation (V_cmax ) and electron transport (J_max ) at each treatment's respective T_growth and at a common measurement T (25 °C). SDS-PAGE gels were used to determine abundance of the CO₂ -fixing enzyme, Rubisco. Leaf chlorophyll, nitrogen (N) and mass per unit leaf area (LMA) were also determined. For all species and T_growth , A_n at current atmospheric CO₂ partial pressure was Rubisco-limited. Across all species, LMA decreased with increasing T_growth . Similarly, area-based rates of V_cmax at a measurement T of 25 °C (V_cmax²⁵ ) linearly declined with increasing T_growth , linked to a concomitant decline in total leaf protein per unit leaf area and Rubisco as a percentage of leaf N. The decline in Rubisco constrained V_cmax and A_n for leaves developed at higher T_growth and resulted in poor predictions of photosynthesis by currently widely used models that do not account for T_growth -mediated changes in Rubisco abundance that underpin the thermal acclimation response of photosynthesis in wet-forest tree species. A new model is proposed that accounts for the effect of T_growth -mediated declines in V_cmax²⁵ on A_n , complementing current photosynthetic thermal acclimation models that do not account for T sensitivity of V_cmax²⁵ .

Stomatal CO2 responsiveness and photosynthetic capacity of tropical woody species in relation to taxonomy and functional traits

Stomatal CO2 responsiveness and photosynthetic capacity vary greatly among plant species, but the factors controlling these physiological leaf traits are often poorly understood. To explore if these traits are linked to taxonomic group identity and/or to other plant functional traits, we investigated the short-term stomatal CO2 responses and the maximum rates of photosynthetic carboxylation (V cmax) and electron transport (J max) in an evolutionary broad range of tropical woody plant species. The study included 21 species representing four major seed plant taxa: gymnosperms, monocots, rosids and asterids. We found that stomatal closure responses to increased CO2 were stronger in angiosperms than in gymnosperms, and in monocots compared to dicots. Stomatal CO2 responsiveness was not significantly related to any of the other functional traits investigated, while a parameter describing the relationship between photosynthesis and stomatal conductance in combined leaf gas exchange models (g 1) was related to leaf area-specific plant hydraulic conductance. For photosynthesis, we found that the interspecific variation in V cmax and J max was related to within leaf nitrogen (N) allocation rather than to area-based total leaf N content. Within-leaf N allocation and water use were strongly co-ordinated (r 2 = 0.67), such that species with high fractional N investments into compounds maximizing photosynthetic capacity also had high stomatal conductance. We conclude that while stomatal CO2 responsiveness of tropical woody species seems poorly related to other plant functional traits, photosynthetic capacity is linked to fractional within-leaf N allocation rather than total leaf N content and is closely co-ordinated with leaf water use.

Evidence that higher [CO2] increases tree growth sensitivity to temperature: a comparison of modern and paleo oaks

To test tree growth sensitivity to temperature under different ambient CO₂ concentrations, we determined stem radial growth rates as they relate to variation in temperature during the last deglacial period, and compare these to modern tree growth rates as they relate to spatial variation in temperature across the modern species distributional range. Paleo oaks were sampled from Northern Missouri, USA and compared to a pollen-based, high-resolution paleo temperature reconstruction from Northern Illinois, USA. Growth data were from 53 paleo bur oak log cross sections collected in Missouri. These oaks were preserved in river and stream sediments and were radiocarbon-dated to a period of rapid climate change during the last deglaciation (10.5 and 13.3 cal kyr BP). Growth data from modern bur oaks were obtained from increment core collections paired with USDA Forest Service Forest Inventory and Analysis data collected across the Great Plains, Midwest, and Upper Great Lakes regions. For modern oaks growing at an average [CO₂] of 330 ppm, growth sensitivity to temperature (i.e., the slope of growth rate versus temperature) was about twice that of paleo oaks growing at an average [CO₂] of 230 ppm. These data help to confirm that leaf-level predictions that photosynthesis and thus growth will be more sensitive to temperature at higher [CO₂] in mature trees-suggesting that tree growth forest productivity will be increasingly sensitive to temperature under projected global warming and high-[CO₂] conditions.

A roadmap for improving the representation of photosynthesis in Earth system models

Accurate representation of photosynthesis in terrestrial biosphere models (TBMs) is essential for robust projections of global change. However, current representations vary markedly between TBMs, contributing uncertainty to projections of global carbon fluxes. Here we compared the representation of photosynthesis in seven TBMs by examining leaf and canopy level responses of photosynthetic CO₂ assimilation (A) to key environmental variables: light, temperature, CO₂ concentration, vapor pressure deficit and soil water content. We identified research areas where limited process knowledge prevents inclusion of physiological phenomena in current TBMs and research areas where data are urgently needed for model parameterization or evaluation. We provide a roadmap for new science needed to improve the representation of photosynthesis in the next generation of terrestrial biosphere and Earth system models.

Convergent acclimation of leaf photosynthesis and respiration to prevailing ambient temperatures under current and warmer climates in Eucalyptus tereticornis

Understanding physiological acclimation of photosynthesis and respiration is important in elucidating the metabolic performance of trees in a changing climate. Does physiological acclimation to climate warming mirror acclimation to seasonal temperature changes? We grew Eucalyptus tereticornis trees in the field for 14 months inside 9-m tall whole-tree chambers tracking ambient air temperature (Tair ) or ambient Tair  + 3°C (i.e. 'warmed'). We measured light- and CO2 -saturated net photosynthesis (Amax ) and night-time dark respiration (R) each month at 25°C to quantify acclimation. Tree growth was measured, and leaf nitrogen (N) and total nonstructural carbohydrate (TNC) concentrations were determined to investigate mechanisms of acclimation. Warming reduced Amax and R measured at 25°C compared to ambient-grown trees. Both traits also declined as mean daily Tair increased, and did so in a similar way across temperature treatments. Amax and R (at 25°C) both increased as TNC concentrations increased seasonally; these relationships appeared to arise from source-sink imbalances, suggesting potential substrate regulation of thermal acclimation. We found that photosynthesis and respiration each acclimated equivalently to experimental warming and seasonal temperature change of a similar magnitude, reflecting a common, nearly homeostatic constraint on leaf carbon exchange that will be important in governing tree responses to climate warming.

A test of the 'one-point method' for estimating maximum carboxylation capacity from field-measured, light-saturated photosynthesis

Simulations of photosynthesis by terrestrial biosphere models typically need a specification of the maximum carboxylation rate (Vcmax ). Estimating this parameter using A-Ci curves (net photosynthesis, A, vs intercellular CO2 concentration, Ci ) is laborious, which limits availability of Vcmax data. However, many multispecies field datasets include net photosynthetic rate at saturating irradiance and at ambient atmospheric CO2 concentration (Asat ) measurements, from which Vcmax can be extracted using a 'one-point method'. We used a global dataset of A-Ci curves (564 species from 46 field sites, covering a range of plant functional types) to test the validity of an alternative approach to estimate Vcmax from Asat via this 'one-point method'. If leaf respiration during the day (Rday ) is known exactly, Vcmax can be estimated with an r(2) value of 0.98 and a root-mean-squared error (RMSE) of 8.19 μmol m(-2) s(-1) . However, Rday typically must be estimated. Estimating Rday as 1.5% of Vcmax, we found that Vcmax could be estimated with an r(2) of 0.95 and an RMSE of 17.1 μmol m(-2) s(-1) . The one-point method provides a robust means to expand current databases of field-measured Vcmax , giving new potential to improve vegetation models and quantify the environmental drivers of Vcmax variation.