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.

Worldwide measurements of nearly 130 C3 species covering all major plant functional types are analysed in conjunction with model simulations to determine the effects of mesophyll conductance (g(m)) on photosynthetic parameters and their relationships estimated from A/Ci curves. We find that an assumption of infinite g(m) results in up to 75% underestimation for maximum carboxylation rate V(cmax), 60% for maximum electron transport rate J(max), and 40% for triose phosphate utilization rate T(u) . V(cmax) is most sensitive, J(max) is less sensitive, and T(u) has the least sensitivity to the variation of g(m). Because of this asymmetrical effect of g(m), the ratios of J(max) to V(cmax), T(u) to V(cmax) and T(u) to J(max) are all overestimated. An infinite g(m) assumption also limits the freedom of variation of estimated parameters and artificially constrains parameter relationships to stronger shapes. These findings suggest the importance of quantifying g(m) for understanding in situ photosynthetic machinery functioning. We show that a nonzero resistance to CO2 movement in chloroplasts has small effects on estimated parameters. A non-linear function with gm as input is developed to convert the parameters estimated under an assumption of infinite gm to proper values. This function will facilitate gm representation in global carbon cycle models.

Shrubs are multi-stemmed short woody plants, more widespread than trees, important in many ecosystems, neglected in ecology compared to herbs and trees, but currently in focus due to their global expansion. We present a novel model based on scaling relationships and four hypotheses to explain the adaptive significance of shrubs, including a review of the literature with a test of one hypothesis. Our model describes advantages for a small shrub compared to a small tree with the same above-ground woody volume, based on larger cross-sectional stem area, larger area of photosynthetic tissue in bark and stem, larger vascular cambium area, larger epidermis (bark) area, and larger area for sprouting, and faster production of twigs and canopy. These components form our Hypothesis 1 that predicts higher growth rate for a small shrub than a small tree. This prediction was supported by available relevant empirical studies (14 publications). Further, a shrub will produce seeds faster than a tree (Hypothesis 2), multiple stems in shrubs insure future survival and growth if one or more stems die (Hypothesis 3), and three structural traits of short shrub stems improve survival compared to tall tree stems (Hypothesis 4)—all hypotheses have some empirical support. Multi-stemmed trees may be distinguished from shrubs by more upright stems, reducing bending moment. Improved understanding of shrubs can clarify their recent expansion on savannas, grasslands, and alpine heaths. More experiments and other empirical studies, followed by more elaborate models, are needed to understand why the shrub growth form is successful in many habitats.

SummaryOur 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 CO 2 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.

Atmospheric carbon dioxide levels have increased by∼25% over the last 50 years. While more carbon dioxide can initially stimulate plant photosynthesis, we found that long-term (12 years) exposure of sweetgum trees to elevated carbon dioxide resulted in no stimulation of photosynthesis. The loss of initial increases in photosynthesis was due to low leaf nitrogen levels, which suggests other limiting resources may moderate future impacts of elevated carbon dioxide on photosynthesis.

We are conducting a large-scale, long-term climate change response experiment in an ombrotrophic peat bog in Minnesota to evaluate the effects of warming and elevated CO 2 on ecosystem processes using empirical and modeling approaches. To better frame future assessments of peatland responses to climate change, we characterized and compared spatial vs. temporal variation in measured C cycle processes and their environmental drivers. We also conducted a sensitivity analysis of a peatland C model to identify how variation in ecosystem parameters contributes to model prediction uncertainty. High spatial variability in C cycle processes resulted in the inability to determine if the bog was a C source or sink, as the 95% confidence interval ranged from a source of 50 g C m -2 yr -1 to a sink of 67 g C m -2 yr -1 . Model sensitivity analysis also identified that spatial variation in tree and shrub photosynthesis, allocation characteristics, and maintenance respiration all contributed to large variations in the pretreatment estimates of net C balance. Variation in ecosystem processes can be more thoroughly characterized if more measurements are collected for parameters that are highly variable over space and time, and especially if those measurements encompass environmental gradients that may be driving the spatial and temporal variation (e.g., hummock vs. hollow microtopographies, and wet vs. dry years). Together, the coupled modeling and empirical approaches indicate that variability in C cycle processes and their drivers must be taken into account when interpreting the significance of experimental warming and elevated CO 2 treatments. Core Ideas• We compared spatial vs. temporal variation in C cycle processes and drivers in a bog.• The bog was indistinguishable as a C source or sink because of high spatial variation.• Sensitive C cycle parameters in the model differed under ambient vs. warming scenarios.• Characterizing pretreatment variability is necessary when interpreting warming effects.Abbreviations: ELM_SPRUCE; SPRUCE-specific version of the Energy Exascale Earth System model; ANPP, aboveground net primary production; CI, confidence interval; [CO 2 ], CO 2 concentration; DOC, dissolved organic C; flnr, fraction of leaf N in ribulose-1,5-biphosphate carboxylase/

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Multi-species mixed plantations can be designed to meet social, economic, and environmental objectives during forest restoration. This paper reports results from an experiment in southern Sweden concerning the influence of three different fast growing nurse tree species on the cover of herbaceous vegetation and on the performance of several target tree species. After 10 years, the nurse trees had reduced the competing herbaceous vegetation but the effect was weak and it may take more than a decade to achieve effective vegetation control. The nurse tree species Betula pendula and Larix x eurolepis did improve stem form in some target tree species, but had a minor effect on survival and growth. The open conditions before crown closure of nurse trees strongly influence seedling performance and so delayed planting of target tree species may provide a means to avoid those conditions. Survival and growth differed greatly among the tree species. Besides the two nurse tree species mentioned above, high survival was found in Picea abies and Quercus robur and intermediate survival in Fagus sylvatica, Tilia cordata, and in the N-fixing nurse tree Alnus glutinosa. Survival was low in the target tree species Fraxinus excelsior L. and Prunus avium. For restoration practitioners, our results illustrate the potential of using nurse trees for rapidly building a new forest structure and simultaneously increase productivity, which might be a cost-effective strategy for forest restoration.