Simulations of chlorophyll fluorescence incorporated into the Community Land Model version 4

Several studies have shown that satellite retrievals of solar‐induced chlorophyll fluorescence (SIF) provide useful information on terrestrial photosynthesis or gross primary production (GPP). Here, we have incorporated equations coupling SIF to photosynthesis in a land surface model, the National Center for Atmospheric Research Community Land Model version 4 (NCAR CLM4), and have demonstrated its use as a diagnostic tool for evaluating the calculation of photosynthesis, a key process in a land surface model that strongly influences the carbon, water, and energy cycles. By comparing forward simulations of SIF, essentially as a byproduct of photosynthesis, in CLM4 with observations of actual SIF, it is possible to check whether the model is accurately representing photosynthesis and the processes coupled to it. We provide some background on how SIF is coupled to photosynthesis, describe how SIF was incorporated into CLM4, and demonstrate that our simulated relationship between SIF and GPP values are reasonable when compared with satellite (Greenhouse gases Observing SATellite; GOSAT) and in situ flux‐tower measurements. CLM4 overestimates SIF in tropical forests, and we show that this error can be corrected by adjusting the maximum carboxylation rate (V_max) specified for tropical forests in CLM4. Our study confirms that SIF has the potential to improve photosynthesis simulation and thereby can play a critical role in improving land surface and carbon cycle models.     

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.     

Effects of seasonal and interannual variations in leaf photosynthesis and canopy leaf area index on gross primary production of a cool-temperate deciduous broadleaf forest in Takayama, Japan

Revealing the seasonal and interannual variations in forest canopy photosynthesis is a critical issue in understanding the ecological mechanisms underlying the dynamics of carbon dioxide exchange between the atmosphere and deciduous forests. This study examined the effects of temporal variations of canopy leaf area index (LAI) and leaf photosynthetic capacity [the maximum velocity of carboxylation (V _cmax)] on gross primary production (GPP) of a cool-temperate deciduous broadleaf forest for 5 years in Takayama AsiaFlux site, central Japan. We made two estimations to examine the effects of canopy properties on GPP; one is to incorporate the in situ observation of V _cmax and LAI throughout the growing season, and another considers seasonality of LAI but constantly high V _cmax. The simulations indicated that variation in V _cmax and LAI, especially in the leaf expansion period, had remarkable effects on GPP, and if V _cmax was assumed constant GPP will be overestimated by 15%. Monthly examination of air temperature, radiation, LAI and GPP suggested that spring temperature could affect canopy phenology, and also that GPP in summer was determined mainly by incoming radiation. However, the consequences among these factors responsible for interannual changes of GPP are not straightforward since leaf expansion and senescence patterns and summer meteorological conditions influence GPP independently. This simulation based on in situ ecophysiological research suggests the importance of intensive consideration and understanding of the phenology of leaf photosynthetic capacity and LAI to analyze and predict carbon fixation in forest ecosystems.     

Solar‐induced chlorophyll fluorescence is strongly correlated with terrestrial photosynthesis for a wide variety of biomes: First global analysis based on OCO‐2 and flux tower observations

Solar‐induced chlorophyll fluorescence (SIF) has been increasingly used as a proxy for terrestrial gross primary productivity (GPP). Previous work mainly evaluated the relationship between satellite‐observed SIF and gridded GPP products both based on coarse spatial resolutions. Finer resolution SIF (1.3 km × 2.25 km) measured from the Orbiting Carbon Observatory‐2 (OCO‐2) provides the first opportunity to examine the SIF–GPP relationship at the ecosystem scale using flux tower GPP data. However, it remains unclear how strong the relationship is for each biome and whether a robust, universal relationship exists across a variety of biomes. Here we conducted the first global analysis of the relationship between OCO‐2 SIF and tower GPP for a total of 64 flux sites across the globe encompassing eight major biomes. OCO‐2 SIF showed strong correlations with tower GPP at both midday and daily timescales, with the strongest relationship observed for daily SIF at the 757 nm (R² = 0.72, p < 0.0001). Strong linear relationships between SIF and GPP were consistently found for all biomes (R² = 0.57–0.79, p < 0.0001) except evergreen broadleaf forests (R² = 0.16, p < 0.05) at the daily timescale. A higher slope was found for C₄ grasslands and croplands than for C₃ ecosystems. The generally consistent slope of the relationship among biomes suggests a nearly universal rather than biome‐specific SIF–GPP relationship, and this finding is an important distinction and simplification compared to previous results. SIF was mainly driven by absorbed photosynthetically active radiation and was also influenced by environmental stresses (temperature and water stresses) that determine photosynthetic light use efficiency. OCO‐2 SIF generally had a better performance for predicting GPP than satellite‐derived vegetation indices and a light use efficiency model. The universal SIF–GPP relationship can potentially lead to more accurate GPP estimates regionally or globally. Our findings revealed the remarkable ability of finer resolution SIF observations from OCO‐2 and other new or future missions (e.g., TROPOMI, FLEX) for estimating terrestrial photosynthesis across a wide variety of biomes and identified their potential and limitations for ecosystem functioning and carbon cycle studies.     

Impact of nitrogen allocation on growth and photosynthesis of Miscanthus (Miscanthus × giganteus)

Nitrogen (N) addition typically increases overall plant growth, but the nature of this response depends upon patterns of plant nitrogen allocation that vary throughout the growing season and depend upon canopy position. In this study seasonal variations in leaf traits were investigated across a canopy profile in Miscanthus (Miscanthus × giganteus) under two N treatments (0 and 224 kg ha^?1) to determine whether the growth response of Miscanthus to N fertilization was related to the response of photosynthetic capacity and nitrogen allocation. Miscanthus yielded 24.1 Mg ha^?1 in fertilized plots, a 40% increase compared to control plots. Photosynthetic properties, such as net photosynthesis (A), maximum rate of rubisco carboxylation (V_cmax), stomatal conductance (g_s) and PSII efficiency (F_v'/F_m'), all decreased significantly from the top of the canopy to the bottom, but were not affected by N fertilization. N fertilization increased specific leaf area (SLA) and leaf area index (LAI). Leaf N concentration in different canopy layers was increased by N fertilization and the distribution of N concentration within canopy followed irradiance gradients. These results show that the positive effect of N fertilization on the yield of Miscanthus was unrelated to changes in photosynthetic rates but was achieved mainly by increased canopy leaf area. Vertical measurements through the canopy demonstrated that Miscanthus adapted to the light environment by adjusting leaf morphological and biochemical properties independent of nitrogen treatments. GPP estimated using big leaf and multilayer models varied considerably, suggesting a multilayer model in which V_cmax changes both through time and canopy layer could be adopted into agricultural models to more accurately predict biomass production in biomass crop ecosystems.     

Global Validation of a Process-Based Model on Vegetation Gross Primary Production Using Eddy Covariance Observations

Gross Primary Production (GPP) is the largest flux in the global carbon cycle. However, large uncertainties in current global estimations persist. In this study, we examined the performance of a process-based model (Integrated BIosphere Simulator, IBIS) at 62 eddy covariance sites around the world. Our results indicated that the IBIS model explained 60% of the observed variation in daily GPP at all validation sites. Comparison with a satellite-based vegetation model (Eddy Covariance-Light Use Efficiency, EC-LUE) revealed that the IBIS simulations yielded comparable GPP results as the EC-LUE model. Global mean GPP estimated by the IBIS model was 107.50±1.37 Pg C year⁻¹ (mean value ± standard deviation) across the vegetated area for the period 2000–2006, consistent with the results of the EC-LUE model (109.39±1.48 Pg C year⁻¹). To evaluate the uncertainty introduced by the parameter V_cmax, which represents the maximum photosynthetic capacity, we inversed V_cmax using Markov Chain-Monte Carlo (MCMC) procedures. Using the inversed V_cmax values, the simulated global GPP increased by 16.5 Pg C year⁻¹, indicating that IBIS model is sensitive to V_cmax, and large uncertainty exists in model parameterization.     

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.     

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.     

Surprising lack of sensitivity of biochemical limitation of photosynthesis of nine tree species to open‐air experimental warming and reduced rainfall in a southern boreal forest

Photosynthetic biochemical limitation parameters (i.e., V_cmax, J_max and J_max:V_cmax ratio) are sensitive to temperature and water availability, but whether these parameters in cold climate species at biome ecotones are positively or negatively influenced by projected changes in global temperature and water availability remains uncertain. Prior exploration of this question has largely involved greenhouse based short‐term manipulative studies with mixed results in terms of direction and magnitude of responses. To address this question in a more realistic context, we examined the effects of increased temperature and rainfall reduction on the biochemical limitations of photosynthesis using a long‐term chamber‐less manipulative experiment located in northern Minnesota, USA. Nine tree species from the boreal‐temperate ecotone were grown in natural neighborhoods under ambient and elevated (+3.4°C) growing season temperatures and ambient or reduced (≈40% of rainfall removed) summer rainfall. Apparent rubisco carboxylation and RuBP regeneration standardized to 25°C (V_cmax25°C and J_max25°C, respectively) were estimated based on AC_i curves measured in situ over three growing seasons. Our primary objective was to test whether species would downregulate V_cmax25°C and J_max25°C in response to warming and reduced rainfall, with such responses expected to be greatest in species with the coldest and most humid native ranges, respectively. These hypotheses were not supported, as there were no overall main treatment effects on V_cmax25°C or J_max25°C (p > .14). However, J_max:V_cmax ratio decreased significantly with warming (p = .0178), whereas interactions between warming and rainfall reduction on the J_max25°C to V_cmax25°C ratio were not significant. The insensitivity of photosynthetic parameters to warming contrasts with many prior studies done under larger temperature differentials and often fixed daytime temperatures. In sum, plants growing in relatively realistic conditions under naturally varying temperatures and soil moisture levels were remarkably insensitive in terms of their J_max25°C and V_cmax25°C when grown at elevated temperatures, reduced rainfall, or both combined.     

Chlorophyll fluorescence tracks seasonal variations of photosynthesis from leaf to canopy in a temperate forest

Accurate estimation of terrestrial gross primary productivity (GPP) remains a challenge despite its importance in the global carbon cycle. Chlorophyll fluorescence (ChlF) has been recently adopted to understand photosynthesis and its response to the environment, particularly with remote sensing data. However, it remains unclear how ChlF and photosynthesis are linked at different spatial scales across the growing season. We examined seasonal relationships between ChlF and photosynthesis at the leaf, canopy, and ecosystem scales and explored how leaf‐level ChlF was linked with canopy‐scale solar‐induced chlorophyll fluorescence (SIF) in a temperate deciduous forest at Harvard Forest, Massachusetts, USA. Our results show that ChlF captured the seasonal variations of photosynthesis with significant linear relationships between ChlF and photosynthesis across the growing season over different spatial scales (R² = 0.73, 0.77, and 0.86 at leaf, canopy, and satellite scales, respectively; P < 0.0001). We developed a model to estimate GPP from the tower‐based measurement of SIF and leaf‐level ChlF parameters. The estimation of GPP from this model agreed well with flux tower observations of GPP (R² = 0.68; P < 0.0001), demonstrating the potential of SIF for modeling GPP. At the leaf scale, we found that leaf F_q’/F_m’, the fraction of absorbed photons that are used for photochemistry for a light‐adapted measurement from a pulse amplitude modulation fluorometer, was the best leaf fluorescence parameter to correlate with canopy SIF yield (SIF/APAR, R² = 0.79; P < 0.0001). We also found that canopy SIF and SIF‐derived GPP (GPP_SIF) were strongly correlated to leaf‐level biochemistry and canopy structure, including chlorophyll content (R² = 0.65 for canopy GPP_SIF and chlorophyll content; P < 0.0001), leaf area index (LAI) (R² = 0.35 for canopy GPP_SIF and LAI; P < 0.0001), and normalized difference vegetation index (NDVI) (R² = 0.36 for canopy GPP_SIF and NDVI; P < 0.0001). Our results suggest that ChlF can be a powerful tool to track photosynthetic rates at leaf, canopy, and ecosystem scales.     

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.     

Terrestrial gross primary production: Using NIRV to scale from site to globe

Terrestrial photosynthesis is the largest and one of the most uncertain fluxes in the global carbon cycle. We find that near‐infrared reflectance of vegetation (NIR_V), a remotely sensed measure of canopy structure, accurately predicts photosynthesis at FLUXNET validation sites at monthly to annual timescales (R² = 0.68), without the need for difficult to acquire information about environmental factors that constrain photosynthesis at short timescales. Scaling the relationship between gross primary production (GPP) and NIR_V from FLUXNET eddy covariance sites, we estimate global annual terrestrial photosynthesis to be 147 Pg C/year (95% credible interval 131–163 Pg C/year), which falls between bottom‐up GPP estimates and the top‐down global constraint on GPP from oxygen isotopes. NIR_V‐derived estimates of GPP are systematically higher than existing bottom‐up estimates, especially throughout the midlatitudes. Progress in improving estimated GPP from NIR_V can come from improved cloud screening in satellite data and increased resolution of vegetation characteristics, especially details about plant photosynthetic pathway.     

Contrasting acclimation responses to elevated CO2 and warming between an evergreen and a deciduous boreal conifer

Rising atmospheric carbon dioxide (CO₂) concentrations may warm northern latitudes up to 8°C by the end of the century. Boreal forests play a large role in the global carbon cycle, and the responses of northern trees to climate change will thus impact the trajectory of future CO₂ increases. We grew two North American boreal tree species at a range of future climate conditions to assess how growth and carbon fluxes were altered by high CO₂ and warming. Black spruce (Picea mariana, an evergreen conifer) and tamarack (Larix laricina, a deciduous conifer) were grown under ambient (407 ppm) or elevated CO₂ (750 ppm) and either ambient temperatures, a 4°C warming, or an 8°C warming. In both species, the thermal optimum of net photosynthesis (T_optA) increased and maximum photosynthetic rates declined in warm‐grown seedlings, but the strength of these changes varied between species. Photosynthetic capacity (maximum rates of Rubisco carboxylation, V_cmax, and of electron transport, J_max) was reduced in warm‐grown seedlings, correlating with reductions in leaf N and chlorophyll concentrations. Warming increased the activation energy for V_cmax and J_max (E_aV and E_aJ, respectively) and the thermal optimum for J_max. In both species, the T_optA was positively correlated with both E_aV and E_aJ, but negatively correlated with the ratio of J_max/V_cmax. Respiration acclimated to elevated temperatures, but there were no treatment effects on the Q₁₀ of respiration (the increase in respiration for a 10°C increase in leaf temperature). A warming of 4°C increased biomass in tamarack, while warming reduced biomass in spruce. We show that climate change is likely to negatively affect photosynthesis and growth in black spruce more than in tamarack, and that parameters used to model photosynthesis in dynamic global vegetation models (E_aV and E_aJ) show no response to elevated CO₂.     

Measured and modelled leaf and stand‐scale productivity across a soil moisture gradient and a severe drought

Environmental controls on carbon dynamics operate at a range of interacting scales from the leaf to landscape. The key questions of this study addressed the influence of water and nitrogen (N) availability on Pinus palustris (Mill.) physiology and primary productivity across leaf and canopy scales, linking the soil‐plant‐atmosphere (SPA) model to leaf and stand‐scale flux and leaf trait/canopy data. We present previously unreported ecophysiological parameters (e.g. V_cmax and J_max) for P. palustris and the first modelled estimates of its annual gross primary productivity (GPP) across xeric and mesic sites and under extreme drought. Annual mesic site P. palustris GPP was ～23% greater than at the xeric site. However, at the leaf level, xeric trees had higher net photosynthetic rates, and water and light use efficiency. At the canopy scale, GPP was limited by light interception (canopy level), but co‐limited by nitrogen and water at the leaf level. Contrary to expectations, the impacts of an intense growing season drought were greater at the mesic site. Modelling indicated a 10% greater decrease in mesic GPP compared with the xeric site. Xeric P. palustris trees exhibited drought‐tolerant behaviour that contrasted with mesic trees' drought‐avoidance behaviour.     

Seasonal variation in leaf properties and ecosystem carbon budget in a cool-temperate deciduous broad-leaved forest: simulation analysis at Takayama site, Japan

Seasonal changes in gross primary production (GPP) and net ecosystem production (NEP) in temperate deciduous forests are mostly driven by environmental conditions and the phenology of leaf demography. This study addresses another factor, temporal changes in leaf properties, i.e., leaf aging from emergence to senescence. A process-based model was used to link the ecosystem-scale carbon budget with leaf-level properties on the basis of field observation and scaling procedures; temporal variations in leaf thickness (leaf mass per area, LMA), photosynthetic rubisco (V_cmax) and electron-transport (J_max) capacity, and dark respiration (R_d) were empirically parameterized. The model was applied to a cool-temperate deciduous broad-leaved forest at Takayama, in central Japan, and validated with data of net ecosystem CO₂ exchange (NEE=–NEP) measured using the eddy-covariance method. NEP of the Takayama site varied seasonally from 3 g C m^–2 day^–1 net source in late winter to 5 g C m^–2 day^–1 net sink in early to mid-summer. A sensitivity experiment showed that removing the leaf-aging effect changed the seasonal CO₂ exchange pattern, and led to overestimation of annual GPP by 6% and annual NEP by 38%. We found that seasonal variation in V_cmax affected the seasonal pattern and annual budget of CO₂ exchange most strongly; LMA and R_d had moderate influences. The rapid change in V_cmax and R_d during leaf emergence and senescence was important in evaluating GPP and NEP of the temperate deciduous forest.     

Potential and limitations of inferring ecosystem photosynthetic capacity from leaf functional traits

The aim of this study was to systematically analyze the potential and limitations of using plant functional trait observations from global databases versus in situ data to improve our understanding of vegetation impacts on ecosystem functional properties (EFPs). Using ecosystem photosynthetic capacity as an example, we first provide an objective approach to derive robust EFP estimates from gross primary productivity (GPP) obtained from eddy covariance flux measurements. Second, we investigate the impact of synchronizing EFPs and plant functional traits in time and space to evaluate their relationships, and the extent to which we can benefit from global plant trait databases to explain the variability of ecosystem photosynthetic capacity. Finally, we identify a set of plant functional traits controlling ecosystem photosynthetic capacity at selected sites. Suitable estimates of the ecosystem photosynthetic capacity can be derived from light response curve of GPP responding to radiation (photosynthetically active radiation or absorbed photosynthetically active radiation). Although the effect of climate is minimized in these calculations, the estimates indicate substantial interannual variation of the photosynthetic capacity, even after removing site‐years with confounding factors like disturbance such as fire events. The relationships between foliar nitrogen concentration and ecosystem photosynthetic capacity are tighter when both of the measurements are synchronized in space and time. When using multiple plant traits simultaneously as predictors for ecosystem photosynthetic capacity variation, the combination of leaf carbon to nitrogen ratio with leaf phosphorus content explains the variance of ecosystem photosynthetic capacity best (adjusted R² = 0.55). Overall, this study provides an objective approach to identify links between leaf level traits and canopy level processes and highlights the relevance of the dynamic nature of ecosystems. Synchronizing measurements of eddy covariance fluxes and plant traits in time and space is shown to be highly relevant to better understand the importance of intra‐ and interspecific trait variation on ecosystem functioning.     

Temperature response of parameters of a biochemically based model of photosynthesis. II. A review of experimental data

The temperature dependence of C₃ photosynthesis is known to vary with growth environment and with species. In an attempt to quantify this variability, a commonly used biochemically based photosynthesis model was parameterized from 19 gas exchange studies on tree and crop species. The parameter values obtained described the shape and amplitude of the temperature responses of the maximum rate of Rubisco activity (V_cmax) and the potential rate of electron transport (J_max). Original data sets were used for this review, as it is shown that derived values of V_cmax and its temperature response depend strongly on assumptions made in derivation. Values of J_max and V_cmax at 25 °C varied considerably among species but were strongly correlated, with an average J_max : V_cmax ratio of 1·67. Two species grown in cold climates, however, had lower ratios. In all studies, the J_max : V_cmax ratio declined strongly with measurement temperature. The relative temperature responses of J_max and V_cmax were relatively constant among tree species. Activation energies averaged 50 kJ mol^?1 for J_max and 65 kJ mol^?1 for V_cmax, and for most species temperature optima averaged 33 °C for J_max and 40 °C for V_cmax. However, the cold climate tree species had low temperature optima for both J_max(19 °C) and V_cmax (29 °C), suggesting acclimation of both processes to growth temperature. Crop species had somewhat different temperature responses, with higher activation energies for both J_max and V_cmax, implying narrower peaks in the temperature response for these species. The results thus suggest that both growth environment and plant type can influence the photosynthetic response to temperature. Based on these results, several suggestions are made to improve modelling of temperature responses.     

Acclimation of leaf respiration consistent with optimal photosynthetic capacity

Plant respiration is an important contributor to the proposed positive global carbon‐cycle feedback to climate change. However, as a major component, leaf mitochondrial (‘dark’) respiration (R_d) differs among species adapted to contrasting environments and is known to acclimate to sustained changes in temperature. No accepted theory explains these phenomena or predicts its magnitude. Here we propose that the acclimation of R_d follows an optimal behaviour related to the need to maintain long‐term average photosynthetic capacity (V_cmax) so that available environmental resources can be most efficiently used for photosynthesis. To test this hypothesis, we extend photosynthetic co‐ordination theory to predict the acclimation of R_d to growth temperature via a link to V_cmax, and compare predictions to a global set of measurements from 112 sites spanning all terrestrial biomes. This extended co‐ordination theory predicts that field‐measured R_d and V_cmax accessed at growth temperature (R_d,tg and V_cmax,tg) should increase by 3.7% and 5.5% per degree increase in growth temperature. These acclimated responses to growth temperature are less steep than the corresponding instantaneous responses, which increase 8.1% and 9.9% per degree of measurement temperature for R_d and V_cmax respectively. Data‐fitted responses proof indistinguishable from the values predicted by our theory, and smaller than the instantaneous responses. Theory and data are also shown to agree that the basal rates of both R_d and V_cmax assessed at 25°C (R_d,25 and V_cmax,25) decline by ~4.4% per degree increase in growth temperature. These results provide a parsimonious general theory for R_d acclimation to temperature that is simpler—and potentially more reliable—than the plant functional type‐based leaf respiration schemes currently employed in most ecosystem and land‐surface models.     

Uptake kinetics and storage capacity of dissolved inorganic phosphorus and corresponding dissolved inorganic nitrate uptake in Saccharina latissima and Laminaria digitata (Phaeophyceae)

Uptake rates of dissolved inorganic phosphorus and dissolved inorganic nitrogen under unsaturated and saturated conditions were studied in young sporophytes of the seaweeds Saccharina latissima and Laminaria digitata (Phaeophyceae) using a “pulse‐and‐chase” assay under fully controlled laboratory conditions. In a subsequent second “pulse‐and‐chase” assay, internal storage capacity (ISC) was calculated based on V_M and the parameter for photosynthetic efficiency F_v/F_m. Sporophytes of S. latissima showed a V_S of 0.80 ± 0.03 μmol · cm^?2 · d^?1 and a V_M of 0.30 ± 0.09 μmol · cm^?2 · d^?1 for dissolved inorganic phosphate (DIP), whereas V_S for DIN was 11.26 ± 0.56 μmol · cm^?2 · d^?1 and V_M was 3.94 ± 0.67 μmol · cm^?2 · d^?1. In L. digitata, uptake kinetics for DIP and DIN were substantially lower: V_S for DIP did not exceed 0.38 ± 0.03 μmol · cm^?2 · d^?1 while V_M for DIP was 0.22 ± 0.01 μmol · cm^?2 · d^?1. V_S for DIN was 3.92 ± 0.08 μmol · cm^?2 · d^?1 and the V_M for DIN was 1.81 ± 0.38 μmol · cm^?2 · d^?1. Accordingly, S. latissima exhibited a larger ISC for DIP (27 μmol · cm^?2) than L. digitata (10 μmol · cm^?2), and was able to maintain high growth rates for a longer period under limiting DIP conditions. Our standardized data add to the physiological understanding of S. latissima and L. digitata, thus helping to identify potential locations for their cultivation. This could further contribute to the development and modification of applications in a bio‐based economy, for example, in evaluating the potential for bioremediation in integrated multitrophic aquacultures that produce biomass simultaneously for use in the food, feed, and energy industries.     

Is productivity of mesic savannas light limited or water limited? Results of a simulation study

A soil–plant–atmosphere model was used to estimate gross primary productivity (GPP) and evapotranspiration (ET) of a tropical savanna in Australia. This paper describes model modifications required to simulate the substantial C4 grass understory together with C3 trees. The model was further improved to include a seasonal distribution of leaf area and foliar nitrogen through 10 canopy layers. Model outputs were compared with a 5‐year eddy covariance dataset. Adding the C4 photosynthesis component improved the model efficiency and root‐mean‐squared error (RMSE) for total ecosystem GPP by better emulating annual peaks and troughs in GPP across wet and dry seasons. The C4 photosynthesis component had minimal impact on modelled values of ET. Outputs of GPP from the modified model agreed well with measured values, explaining between 79% and 90% of the variance and having a low RMSE (0.003–0.281 g C m^?2 day^?1). Approximately, 40% of total annual GPP was contributed by C4 grasses. Total (trees and grasses) wet season GPP was approximately 75–80% of total annual GPP. Light‐use efficiency (LUE) was largest for the wet season and smallest in the dry season and C4 LUE was larger than that of the trees. A sensitivity analysis of GPP revealed that daily GPP was most sensitive to changes in leaf area index (LAI) and foliar nitrogen (N_f) and relatively insensitive to changes in maximum carboxylation rate (V_cmax), maximum electron transport rate (J_max) and minimum leaf water potential (ψ_min). The modified model was also able to represent daily and seasonal patterns in ET, (explaining 68–81% of variance) with a low RMSE (0.038–0.19 mm day^?1). Current values of N_f, LAI and other parameters appear to be colimiting for maximizing GPP. By manipulating LAI and soil moisture content inputs, we show that modelled GPP is limited by light interception rather than water availability at this site.