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Relationships between chlorophyll concentration ([chl]) and SPAD values were determined for birch, wheat, and potato. For all three species, the relationships were non-linear with an increasing slope with increasing SPAD. The relationships for birch and wheat were strong (r (2) approximately 0.9), while the potato relationship was comparatively weak (r (2) approximately 0.5). Birch and wheat had very similar relationships when the chlorophyll concentration was expressed per unit leaf area, but diverged when it was expressed per unit fresh weight. Furthermore, wheat showed similar SPAD-[chl] relationships for two different cultivars and during two different growing seasons. The curvilinear shape of the SPAD-[chl] relationships agreed well with the simulated effects of non-uniform chlorophyll distribution across the leaf surface and multiple scattering, causing deviations from linearity in the high and low SPAD range, respectively. The effect of non-uniformly distributed chlorophyll is likely to be more important in explaining the non-linearity in the empirical relationships, since the effect of scattering was predicted to be comparatively weak. The simulations were based on the algorithm for the calculation of SPAD-502 output values. We suggest that SPAD calibration curves should generally be parameterised as non-linear equations, and we hope that the relationships between [chl] and SPAD and the simulations of the present study can facilitate the interpretation of chlorophyll meter calibrations in relation to optical properties of leaves in future studies.

Summary 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.

Key words: A-C i curve, leaf respiration during the day (R day ), maximum carboxylation rate (V cmax ), net photosynthetic rate at saturating irradiance and at ambient atmospheric CO 2 concentration (A sat ). SummarySimulations of photosynthesis by terrestrial biosphere models typically need a specification of the maximum carboxylation rate (V cmax ). Estimating this parameter using A-C i curves (net photosynthesis, A, vs intercellular CO 2 concentration, C i ) is laborious, which limits availability of V cmax data. However, many multispecies field datasets include net photosynthetic rate at saturating irradiance and at ambient atmospheric CO 2 concentration (A sat ) measurements, from which V cmax can be extracted using a 'one-point method'.We used a global dataset of A-C i curves (564 species from 46 field sites, covering a range of plant functional types) to test the validity of an alternative approach to estimate V cmax from A sat via this 'one-point method'.If leaf respiration during the day (R day ) is known exactly, V cmax can be estimated with an r 2 value of 0.98 and a root-mean-squared error (RMSE) of 8.19 lmol m À2 s À1 . However, R day typically must be estimated. Estimating R day as 1.5% of V cmax, we found that V cmax could be estimated with an r 2 of 0.95 and an RMSE of 17.1 lmol m À2 s À1 . The one-point method provides a robust means to expand current databases of fieldmeasured V cmax , giving new potential to improve vegetation models and quantify the environmental drivers of V cmax variation.

a b s t r a c tTo derive O 3 doseeresponse relationships (DRR) for five European forest trees species and broadleaf deciduous and needleleaf tree plant functional types (PFTs), phytotoxic O 3 doses (PODy) were related to biomass reductions. PODy was calculated using a stomatal flux model with a range of cut-off thresholds (y) indicative of varying detoxification capacities. Linear regression analysis showed that DRR for PFT and individual tree species differed in their robustness. A simplified parameterisation of the flux model was tested and showed that for most non-Mediterranean tree species, this simplified model led to similarly robust DRR as compared to a species-and climate region-specific parameterisation. Experimentally induced soil water stress was not found to substantially reduce PODy, mainly due to the short duration of soil water stress periods. This study validates the stomatal O 3 flux concept and represents a step forward in predicting O 3 damage to forests in a spatially and temporally varying climate.Crown

Increasing both crop productivity and the tolerance of crops to abiotic and biotic stresses is a major challenge for global food security in our rapidly changing climate. For the first time, we show how the spatial variation and severity of tropospheric ozone effects on yield compare with effects of other stresses on a global scale, and discuss mitigating actions against the negative effects of ozone. We show that the sensitivity to ozone declines in the order soybean > wheat > maize > rice, with genotypic variation in response being most pronounced for soybean and rice. Based on stomatal uptake, we estimate that ozone (mean of 2010-2012) reduces global yield annually by 12.4%, 7.1%, 4.4% and 6.1% for soybean, wheat, rice and maize, respectively (the "ozone yield gaps"), adding up to 227 Tg of lost yield. Our modelling shows that the highest ozone-induced production losses for soybean are in North and South America whilst for wheat they are in India and China, for rice in parts of India, Bangladesh, China and Indonesia, and for maize in China and the United States. Crucially, we also show that the same areas are often also at risk of high losses from pests and diseases, heat stress and to a lesser extent aridity and nutrient stress. In a solution-focussed analysis of these results, we provide a crop ideotype with tolerance of multiple stresses (including ozone) and describe how ozone effects could be included in crop breeding programmes. We also discuss altered crop management approaches that could be applied to reduce ozone impacts in the shorter term. Given the severity of ozone effects on staple food crops in areas of the world that are also challenged by other stresses, we recommend increased attention to the benefits that could be gained from addressing the ozone yield gap.

Abstract• Chlorophyll meters such as the SPAD-502 offer a simple, inexpensive and rapid method to estimate foliar chlorophyll content. However, values provided by SPAD-502 are unitless and require empirical calibrations between SPAD units and extracted chlorophyll values.• Leaves of 13 tree species from the tropical rain forest in French Guiana were sampled to select the most appropriate calibration model among the often-used linear, polynomial and exponential models, in addition to a novel homographic model that has a natural asymptote.• The homographic model best accurately predicted total chlorophyll content (μg cm −2 ) from SPAD units (R 2 = 0.89). Interspecific differences in the homographic model parameters explain less than 7% of the variation in chlorophyll content in our data set.• The utility of the general homographic model for a variety of research and management applications clearly outweighs the slight loss of model accuracy due to the abandon of the species' effect.

A key part of the uncertainty in terrestrial feedbacks on climate change is related to how and to what extent nitrogen (N) availability constrains the stimulation of terrestrial productivity by elevated CO 2 (eCO 2 ), and whether or not this constraint will become stronger over time. We explored the ecosystem-scale relationship between responses of plant productivity and N acquisition to eCO 2 in free-air CO 2 enrichment (FACE) experiments in grassland, cropland and forest ecosystems and found that: (i) in all three ecosystem types, this relationship was positive, linear and strong (r 2 = 0.68), but exhibited a negative intercept such that plant N acquisition was decreased by 10% when eCO 2 caused neutral or modest changes in productivity. As the ecosystems were markedly N limited, plants with minimal productivity responses to eCO 2 likely acquired less N than ambient CO 2 -grown counterparts because access was decreased, and not because demand was lower. (ii) Plant N concentration was lower under eCO 2 , and this decrease was independent of the presence or magnitude of eCO 2 -induced productivity enhancement, refuting the long-held hypothesis that this effect results from growth dilution. (iii) Effects of eCO 2 on productivity and N acquisition did not diminish over time, while the typical eCO 2 -induced decrease in plant N concentration did. Our results suggest that, at the decennial timescale covered by FACE studies, N limitation of eCO 2 -induced terrestrial productivity enhancement is associated with negative effects of eCO 2 on plant N acquisition rather than with growth dilution of plant N or processes leading to progressive N limitation.