Abstract. Climate change will include correlated increases in temperature and atmospheric CO2 concentration (Ca). Rising temperatures will increase the ratio of photorespiratory loss of carbon to photosynthetic gain, whilst rising Ca will have an opposing effect. The mechanism of these effects at the level of carboxylation in C3 photosynthesis are quantitatively well understood and provide a basis for models of the response of leaf and canopy carbon exchange to climate change. The principles of such a model are referred to here and used to quantitatively examine the implications of concurrent increase in temperature and Ca. Simulations of leaf photosynthesis show the increase, with elevation of Ca from 350 to 650 μmol mol‐1, in light saturated rates of CO2 uptake (Asat) and maximum quantum yields (φ) to rise with temperature. An increase in Ca from 350 to 650 μmol mol‐1 can increase Asat by 20% at 10°C and by 105% at 35°C, and can raise the temperature optimum of Asat by 5°C. This pattern of change agrees closely with experimental data. At the canopy level, simulations also suggest a strong interaction of increased temperature and CO2 concentration. Predictions are compared with the findings of long‐term field studies. The principles used here suggest that elevated Ca will alter both the magnitude of the response of leaf and canopy carbon gain to rising temperature, and sometimes, the direction of response. Findings question the value of models for predicting plant production in response to climate change which ignore the direct effects of rising Ca and the modifications that rising Ca imposes on the temperature response of net CO2 exchange.

No abstract

No abstract

Numerical rating scales and mechanical visual analogue scales (M-VAS) were compared for their capacity to provide ratio scale measures of experimental pain. Separate estimates of experimental pain sensation intensity and pain unpleasantness were obtained by each method, as were estimates of clinical pain. Orofacial pain patients made numerical scale and VAS ratings in response to noxious thermal stimuli (45-51 degrees C) applied for 5 sec to the forearm by a contact thermode. The derived stimulus-response function was well fit as a power function only in the case of sensory M-VAS. The power function derived from sensory M-VAS ratings predicted temperatures chosen as twice as intense as standard temperatures of 47 degrees C and 48 degrees C, thereby providing evidence for ratio scale characteristics of M-VAS. The stimulus-response function derived from sensory numerical ratings differed from that obtained with M-VAS and did not provide accurate predictions of temperatures perceived as twice intense at 47 degrees C or 48 degrees C. Both M-VAS and numerical rating scales produced reliably different stimulus response functions for pain sensation intensity as compared to pain unpleasantness and both provided consistent measures of experimental and clinical pain intensity. Finally, both mechanical and pencil-and-paper VAS produced very similar stimulus-response functions. The ratio scale properties of M-VAS combined with its ease of administration and scoring in clinical settings offer the possibility of a simple yet powerful pain measurement technology in both research and health care settings.

Increase in demand for our primary foodstuffs is outstripping increase in yields, an expanding gap that indicates large potential food shortages by mid-century. This comes at a time when yield improvements are slowing or stagnating as the approaches of the Green Revolution reach their biological limits. Photosynthesis, which has been improved little in crops and falls far short of its biological limit, emerges as the key remaining route to increase the genetic yield potential of our major crops. Thus, there is a timely need to accelerate our understanding of the photosynthetic process in crops to allow informed and guided improvements via in-silico-assisted genetic engineering. Potential and emerging approaches to improving crop photosynthetic efficiency are discussed, and the new tools needed to realize these changes are presented.

The effects of elevated [CO2] on 25 variables describing soybean physiology, growth and yield are reviewed using meta‐analytic techniques. This is the first meta‐analysis to our knowledge performed on a single crop species and summarizes the effects of 111 studies. These primary studies include numerous soybean growth forms, various stress and experimental treatments, and a range of elevated [CO2] levels (from 450 to 1250 p.p.m.), with a mean of 689 p.p.m. across all studies. Stimulation of soybean leaf CO2 assimilation rate with growth at elevated [CO2] was 39%, despite a 40% decrease in stomatal conductance and a 11% decrease in Rubisco activity. Increased leaf CO2 uptake combined with an 18% stimulation in leaf area to provide a 59% increase in canopy photosynthetic rate. The increase in total dry weight was lower at 37%, and seed yield still lower at 24%. This shows that even in an agronomic species selected for maximum investment in seed, several plant level feedbacks prevent additional investment in reproduction, such that yield fails to reflect fully the increase in whole plant carbon uptake. Large soil containers (> 9 L) have been considered adequate for assessing plant responses to elevated [CO2]. However, in open‐top chamber experiments, soybeans grown in large pots showed a significant threefold smaller stimulation in yield than soybeans grown in the ground. This suggests that conclusions about plant yield based on pot studies, even when using very large containers, are a poor reflection of performance in the absence of any physical restriction on root growth. This review supports a number of current paradigms of plant responses to elevated [CO2]. Namely, stimulation of photosynthesis is greater in plants that fix N and have additional carbohydrate sinks in nodules. This supports the notion that photosynthetic capacity decreases when plants are N‐limited, but not when plants have adequate N and sink strength. The root : shoot ratio did not change with growth at elevated [CO2], sustaining the charge that biomass allocation is unaffected by growth at elevated [CO2] when plant size and ontogeny are considered.

The distribution of resources between enzymes of photosynthetic carbon metabolism might be assumed to have been optimized by natural selection. However, natural selection for survival and fecundity does not necessarily select for maximal photosynthetic productivity. Further, the concentration of a key substrate, atmospheric CO 2 , has changed more over the past 100 years than the past 25 million years, with the likelihood that natural selection has had inadequate time to reoptimize resource partitioning for this change. Could photosynthetic rate be increased by altered partitioning of resources among the enzymes of carbon metabolism? This question is addressed using an ''evolutionary'' algorithm to progressively search for multiple alterations in partitioning that increase photosynthetic rate. To do this, we extended existing metabolic models of C 3 photosynthesis by including the photorespiratory pathway (PCOP) and metabolism to starch and sucrose to develop a complete dynamic model of photosynthetic carbon metabolism. The model consists of linked differential equations, each representing the change of concentration of one metabolite. Initial concentrations of metabolites and maximal activities of enzymes were extracted from the literature. The dynamics of CO 2 fixation and metabolite concentrations were realistically simulated by numerical integration, such that the model could mimic well-established physiological phenomena. For example, a realistic steady-state rate of CO 2 uptake was attained and then reattained after perturbing O 2 concentration. Using an evolutionary algorithm, partitioning of a fixed total amount of protein-nitrogen between enzymes was allowed to vary. The individual with the higher light-saturated photosynthetic rate was selected and used to seed the next generation. After 1,500 generations, photosynthesis was increased substantially. This suggests that the ''typical'' partitioning in C 3 leaves might be suboptimal for maximizing the light-saturated rate of photosynthesis. An overinvestment in PCOP enzymes and underinvestment in Rubisco, sedoheptulose-1,7-bisphosphatase, and fructose-1,6-bisphosphate aldolase were indicated. Increase in sink capacity, such as increase in ADP-glucose pyrophosphorylase, was also indicated to lead to increased CO 2 uptake rate. These results suggest that manipulation of partitioning could greatly increase carbon gain without any increase in the total protein-nitrogen investment in the apparatus for photosynthetic carbon metabolism.

The leaf model of C 3 photosynthesis of Farquhar, von Caemmerer & Berry ( Planta 149, 78-90, 1980) provides the basis for scaling carbon exchange from leaf to canopy and Earth-System models, and is widely used to project biosphere responses to global change. This scaling requires using the leaf model over a wider temperature range than that for which the model was originally parameterized. The leaf model assumes that photosynthetic CO 2 uptake within a leaf is either limited by the rate of ribulose-1,5-bisphosphate (RuBP) regeneration or the activity of RuBP carboxylase-oxygenase (Rubisco). Previously we reported a re-parameterization of the temperature responses of Rubisco activity that proved robust when applied to a range of species. Herein this is extended to re-parameterizing the response of RuBP-limited photosynthesis to temperature. RuBP-limited photosynthesis is assumed to depend on the whole chain electron transport rate, which is described as a three-parameter non-rectangular hyperbolic function of photon flux. Herein these three parameters are determined from simultaneous measurement of chlorophyll fluorescence and CO 2 exchange of tobacco leaves, at temperatures from 10 to 40 ∞ ∞ ∞ ∞ C. All varied significantly with temperature and were modified further with variation in growth temperature from 15 to 35 ∞ ∞ ∞ ∞ C. These parameters closely predicted the response of RuBP-limited photosynthesis to temperature measured in both lemon and poplar and showed a significant improvement over predictions based on earlier parameterizations. We provide the necessary equations for use of the model of Farquhar et al . (1980) with our newly derived temperature functions for predicting both Rubiscoand RuBP-limited photosynthesis.