Global photosynthetic capacity is optimized to the environment.

Earth system models (ESMs) use photosynthetic capacity, indexed by the maximum Rubisco carboxylation rate (Vcmax ), 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 Vcmax 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 Vcmax 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.

Long-term water stress leads to acclimation of drought sensitivity of photosynthetic capacity in xeric but not riparian Eucalyptus species.

BACKGROUND AND AIMS: Experimental drought is well documented to induce a decline in photosynthetic capacity. However, if given time to acclimate to low water availability, the photosynthetic responses of plants to low soil moisture content may differ from those found in short-term experiments. This study aims to test whether plants acclimate to long-term water stress by modifying the functional relationships between photosynthetic traits and water stress, and whether species of contrasting habitat differ in their degree of acclimation. METHODS: Three Eucalyptus taxa from xeric and riparian habitats were compared with regard to their gas exchange responses under short- and long-term drought. Photosynthetic parameters were measured after 2 and 4 months of watering treatments, namely field capacity or partial drought. At 4 months, all plants were watered to field capacity, then watering was stopped. Further measurements were made during the subsequent 'drying-down', continuing until stomata were closed. KEY RESULTS: Two months of partial drought consistently reduced assimilation rate, stomatal sensitivity parameters (g1), apparent maximum Rubisco activity (V'(cmax)) and maximum electron transport rate (J'(max)). Eucalyptus occidentalis from the xeric habitat showed the smallest decline in V'(cmax) and J'(max); however, after 4 months, V'(cmax) and J'(max) had recovered. Species differed in their degree of V'(cmax) acclimation. Eucalyptus occidentalis showed significant acclimation of the pre-dawn leaf water potential at which the V'(cmax) and 'true' V(cmax) (accounting for mesophyll conductance) declined most steeply during drying-down. CONCLUSIONS: The findings indicate carbon loss under prolonged drought could be over-estimated without accounting for acclimation. In particular, (1) species from contrasting habitats differed in the magnitude of V'(cmax) reduction in short-term drought; (2) long-term drought allowed the possibility of acclimation, such that V'(cmax) reduction was mitigated; (3) xeric species showed a greater degree of V'(cmax) acclimation; and (4) photosynthetic acclimation involves hydraulic adjustments to reduce water loss while maintaining photosynthesis.

Evolution Law of Structural Form and Heat Transfer Performance of Thermal Insulation System.

Building thermal insulation and energy conservation have become urgent problems in the field of civil engineering because they are important for achieving the goal of carbon neutralization. Thermal conductivity is an important index for evaluating the thermal insulation of materials. To study the influence of different porosity levels on the thermal conductivity of materials, this paper established a random distribution model using MATLAB and conducted a comparative analysis using COMSOL finite element software and classical theoretical numerical calculation formulas. The thermal conductivity of composite materials was determined based on a theoretical calculation formula and COMSOL software simulations, and the theoretical calculation results and simulation results were compared with the measured thermal conductivity of the composites. Furthermore, the influence of the width of the gaps between the materials on the heat transfer process was simulated in the fabricated roof structure. The results showed the following: (1) The thermal conductivity values calculated using the Zimmerman model were quite different from those calculated using the Campbell-Allen model and those calculated using the COMSOL software; (2) The thermal conductivity values calculated using the theoretical calculation formula were lower than the measured data, and the maximum relative error was more than 29%. The COMSOL simulation results were in good agreement with the measured data, and the relative error was less than 5%; (3) When the gap width was less than 60 mm, it increased linearly with the heat transfer coefficient. The heat transfer coefficient increased slowly when the gap width was greater than 60 mm. This was mainly due to the thermal bridge effect inside the insulation system. Based on these research results, a thermal insulation system was prepared in a factory.

Modeling Light Response of Electron Transport Rate and Its Allocation for Ribulose Biphosphate Carboxylation and Oxygenation.

Accurately describing the light response curve of electron transport rate (J-I curve) and allocation of electron flow for ribulose biphosphate (RuBP) carboxylation (J C-I curve) and that for oxygenation (J O-I curve) is fundamental for modeling of light relations of electron flow at the whole-plant and ecosystem scales. The non-rectangular hyperbolic model (hereafter, NH model) has been widely used to characterize light response of net photosynthesis rate (A n; A n-I curve) and J-I curve. However, NH model has been reported to overestimate the maximum A n (A nmax) and the maximum J (J max), largely due to its asymptotic function. Meanwhile, few efforts have been delivered for describing J C-I and J O-I curves. The long-standing challenge on describing A n-I and J-I curves have been resolved by a recently developed A n-I and J-I models (hereafter, Ye model), which adopt a nonasymptotic function. To test whether Ye model can resolve the challenge of NH model in reproducing J-I, J C-I and J O-I curves over light-limited, light-saturated, and photoinhibitory I levels, we compared the performances of Ye model and NH model against measurements on two C3 crops (Triticum aestivum L. and Glycine max L.) grown in field. The results showed that NH model significantly overestimated the A nmax and J max for both species, which can be accurately obtained by Ye model. Furthermore, NH model significantly overestimated the maximum electron flow for carboxylation (J C-max) but not the maximum electron flow for oxygenation (J O-max) for both species, disclosing the reason underlying the long-standing problem of NH model-overestimation of J max and A nmax.

Quantifying Light Response of Leaf-Scale Water-Use Efficiency and Its Interrelationships With Photosynthesis and Stomatal Conductance in C3 and C4 Species.

Light intensity (I) is the most dynamic and significant environmental variable affecting photosynthesis (A n), stomatal conductance (g s), transpiration (T r), and water-use efficiency (WUE). Currently, studies characterizing leaf-scale WUE-I responses are rare and key questions have not been answered. In particular, (1) What shape does the response function take? (2) Are there maximum intrinsic (WUEi; WUEi-max) and instantaneous WUE (WUEinst; WUEinst-max) at the corresponding saturation irradiances (I i-sat and I inst-sat)? This study developed WUEi-I and WUEinst-I models sharing the same non-asymptotic function with previously published A n-I and g s-I models. Observation-modeling intercomparison was conducted for field-grown plants of soybean (C3) and grain amaranth (C4) to assess the robustness of our models versus the non-rectangular hyperbola models (NH models). Both types of models can reproduce WUE-I curves well over light-limited range. However, at light-saturated range, NH models overestimated WUEi-max and WUEinst-max and cannot return I i-sat and I inst-sat due to its asymptotic function. Moreover, NH models cannot describe the down-regulation of WUE induced by high light, on which our models described well. The results showed that WUEi and WUEinst increased rapidly within low range of I, driven by uncoupled photosynthesis and stomatal responsiveness. Initial response rapidity of WUEi was higher than WUEinst because the greatest increase of A n and T r occurred at low g s. C4 species showed higher WUEi-max and WUEinst-max than C3 species-at similar I i-sat and I inst-sat. Our intercomparison highlighted larger discrepancy between WUEi-I and WUEinst-I responses in C3 than C4 species, quantitatively characterizing an important advantage of C4 photosynthetic pathway-higher A n gain but lower T r cost per unit of g s change. Our models can accurately return the wealth of key quantities defining species-specific WUE-I responses-besides A n-I and g s-I responses. The key advantage is its robustness in characterizing these entangled responses over a wide I range from light-limited to light-inhibitory light intensities, through adopting the same analytical framework and the explicit and consistent definitions on these responses. Our models are of significance for physiologists and modelers-and also for breeders screening for genotypes concurrently achieving maximized photosynthesis and optimized WUE.

Comparing two measures of leaf photorespiration rate across a wide range of light intensities.

Suppression of photorespiration by low O2 concentrations (Method 1) and simultaneous measurements of gas exchange and chlorophyll fluorescence (Method 2) are often used to estimate leaf photorespiration rate (Rp) of C3 plants. However, it is largely unknown whether Method 1 and Method 2 can be used equivalently in estimating Rp. Using a field experiment on two wheat cultivars (T. aestivum JM22 and T. aestivum Z39-118) whose leaf gas exchange and chlorophyll fluorescence at low and normal O2 concentrations (2% versus 21% O2) were simultaneously measured across a wide range of light intensities (I), this study assessed the impacts of the two measures on Rp and its response under changing irradiance conditions. All the above quantities increased with the increasing I until reaching the cultivar-specific maximum values and the corresponding saturation light intensities. However, there were significant differences between Rp estimated by Method 1 and Method 2 at the I range from 150 to 2000 µmol m-2 s-1 for T. aestivum JM22 and from 150 to 1000 µmol m-2 s-1 for T. aestivum Z39-118. These findings demonstrated that the two methods cannot be used equivalently under changing irradiance conditions.

Bridging Drought Experiment and Modeling: Representing the Differential Sensitivities of Leaf Gas Exchange to Drought.

Global climate change is expected to increase drought duration and intensity in certain regions while increasing rainfall in others. The quantitative consequences of increased drought for ecosystems are not easy to predict. Process-based models must be informed by experiments to determine the resilience of plants and ecosystems from different climates. Here, we demonstrate what and how experimentally derived quantitative information can improve the representation of stomatal and non-stomatal photosynthetic responses to drought in large-scale vegetation models. In particular, we review literature on the answers to four key questions: (1) Which photosynthetic processes are affected under short-term drought? (2) How do the stomatal and non-stomatal responses to short-term drought vary among species originating from different hydro-climates? (3) Do plants acclimate to prolonged water stress, and do mesic and xeric species differ in their degree of acclimation? (4) Does inclusion of experimentally based plant functional type specific stomatal and non-stomatal response functions to drought help Land Surface Models to reproduce key features of ecosystem responses to drought? We highlighted the need for evaluating model representations of the fundamental eco-physiological processes under drought. Taking differential drought sensitivity of different vegetation into account is necessary for Land Surface Models to accurately model drought responses, or the drought impacts on vegetation in drier environments may be over-estimated.