Heterotic growth of hybrids of Arabidopsis thaliana is enhanced by elevated atmospheric CO2.

PREMISE: With the global atmospheric CO2 concentration on the rise, developing crops that can thrive in elevated CO2 has become paramount. We investigated the potential of hybridization as a strategy for creating crops with improved growth in predicted elevated atmospheric CO2. METHODS: We grew parent accessions and their F1 hybrids of Arabidopsis thaliana in ambient and elevated atmospheric CO2 and analyzed numerous growth traits to assess their productivity and underlying mechanisms. RESULTS: The heterotic increase in total dry mass, relative growth rate and leaf net assimilation rate was significantly greater in elevated CO2 than in ambient CO2. The CO2 response of net assimilation rate was positively correlated with the CO2 response of leaf nitrogen productivity and with that of leaf traits such as leaf size and thickness, suggesting that hybridization-induced changes in leaf traits greatly affected the improved performance in elevated CO2. CONCLUSIONS: Vegetative growth of hybrids seems to be enhanced in elevated CO2 due to improved photosynthetic nitrogen-use efficiency compared with parents. The results suggest that hybrid crops should be well-suited for future conditions, but hybrid weeds may also be more competitive.

Does selection occur at the intermediate zone of two insufficiently isolated populations? A whole-genome analysis along an altitudinal gradient.

Adaptive divergence occurs even between insufficiently isolated populations when there is a great difference in environments between their habitats. Individuals present in an intermediate zone of the two divergent populations are expected to have an admixed genetic structure due to gene flow. A selective pressure that acts on the genetically admixed individuals may limit the gene flow and maintain the adaptive divergence. Here, we addressed a question whether selection occurs in the genetically admixed individuals between two divergent populations. Arabidopsis halleri is a perennial montane plant, which has clear phenotypic dimorphisms between highland and lowland habitats in Mt. Ibuki, central Japan. We obtained the whole-genome sequences of Arabidopsis halleri plants along an altitudinal gradient of 359-1,317 m with a high spatial resolution (mean altitudinal interval of 20 m). We found a zone where the highland and lowland genes were mixing (intermediate subpopulation). In the intermediate subpopulation, we identified 5 and 13 genome regions, which included 3 and 8 genes, that had a high frequency of alleles that are accumulated in highland and lowland subpopulations, respectively. In addition, we also found that the frequency of highland alleles of these selected genome regions was smaller in the lowland subpopulation compared with that of the non-selected regions. These results suggest that the selection in the intermediate subpopulation might limit the gene flow and contribute to the adaptive divergence between altitudes. We also identified 7 genome regions that had low heterozygote frequencies in the intermediate subpopulation. We conclude that different types of selection in addition to gene flow occur at the intermediate altitude and shape the genetic structure across altitudes.

Enhanced growth rate under elevated CO2 conditions was observed for transgenic lines of genes identified by intraspecific variation analyses in Arabidopsis thaliana.

KEY MESSAGE: Using the whole genome and growth data of Arabidopsis thaliana ecotypes, we identified two genes associated with enhancement of the growth rate in response to elevated CO2 conditions. Improving plant growth under elevated CO2 conditions may contribute to enhanced agricultural yield under future global climate change. In this study, we examined the genes implicated in the enhancement of growth rates under elevated CO2 conditions by analyzing the growth rates of Arabidopsis thaliana ecotypes originating from various latitudes and altitudes throughout the world. We also performed a genome-wide association study and a transcriptome study to identify single nucleic polymorphisms that were correlated with the relative growth rate (RGR) under elevated CO2 conditions or with CO2 response of RGR. We then selected 43 candidate genes and generated their overexpression and/or RNA interference (RNAi) transgenic mutants for screening. After screening, we have found that RNAi lines of AT3G4000 and AT5G50900 showed significantly higher growth rates under the elevated CO2 condition. As per our findings, we conclude that natural variation includes genetic variation associated with the enhancement of plant productivity under elevated CO2 conditions.

Leaf density and chemical composition explain variation in leaf mass area with spectral composition among 11 widespread forbs in a common garden.

Leaf mass per area (LMA) is a key leaf functional trait correlated with plant strategies dictating morphology, physiology, and biochemistry. Although sunlight is generally accepted as a dominant factor driving LMA, the contribution of each spectral region of sunlight in shaping LMA is poorly understood. In the present study, we grew 11 widespread forb species in a common garden and dissected the traits underpinning differences in LMA, such as its morphological components (leaf density [LD] and leaf thickness [LT]), macroelement, and metabolite composition under five spectral-attenuation treatments: (1) transmitting c. 95% of the whole solar spectrum (> 280 nm), (2) attenuating ultraviolet-B radiation (UV-B), (3) attenuating both UV-A and UV-B radiation, (4) attenuating UV radiation and blue light, (5) attenuating UV radiation, blue, and green light. We found that LMA, LD, and chemical traits varied significantly across species depending on spectral treatments. LMA was significantly increased by UV-B radiation and green light, while LD was increased by UV-A but decreased by blue light. LMA positively correlated with LD across treatments but was only weakly related to LT, suggesting that LD was a better determinate of LMA for this specific treatment. Regarding leaf elemental and metabolite composition, carbon, nitrogen, and total phenolics were all positively correlated with LMA, whereas lignin, non-structural carbohydrates, and soluble sugars had negative relationships with LMA. These trends imply a tradeoff between biomass allocation to structural and metabolically functional components. In conclusion, sunlight can spectrally drive LMA mainly through modifying functional and structural support.

Corrected photochemical reflectance index (PRI) is an effective tool for detecting environmental stresses in agricultural crops under light conditions.

High-throughput detection of plant environmental stresses is required for minimizing the reduction in crop yield. Environmental stresses in plants have primarily been validated by the measurements of photosynthesis with gas exchange and chlorophyll fluorescence, which involve complicated procedures. Remote sensing technologies that monitor leaf reflectance in intact plants enable real-time visualization of plant responses to environmental fluctuations. The photochemical reflectance index (PRI), one of the vegetation indices of spectral leaf reflectance, is related to changes in xanthophyll pigment composition. Xanthophyll dynamics are strongly correlated with plant stress because they contribute to the thermal dissipation of excess energy. However, an accurate assessment of plant stress based on PRI requires correction by baseline PRI (PRIo) in the dark, which is difficult to obtain in the field. In this study, we propose a method to correct the PRI using NPQT, which can be measured under light. By this method, we evaluated responses of excess light energy stress under drought in wild watermelon (Citrullus lanatus L.), a xerophyte. Demonstration on the farm, the stress behaviors were observed in maize (Zea mays L.). Furthermore, the stress status of plants and their recovery following re-watering were captured as visual information. These results suggest that the PRI is an excellent indicator of environmental stress and recovery in plants and could be used as a high-throughput stress detection tool in agriculture.

Linking remote sensing parameters to CO2 assimilation rates at a leaf scale.

Solar-induced chlorophyll fluorescence (SIF) and photochemical reflectance index (PRI) are expected to be useful for remote sensing of photosynthetic activity at various spatial scales. This review discusses how chlorophyll fluorescence and PRI are related to the CO2 assimilation rate at a leaf scale. Light energy absorbed by photosystem II chlorophylls is allocated to photochemistry, fluorescence, and heat dissipation evaluated as non-photochemical quenching (NPQ). PRI is correlated with NPQ because it reflects the composition of xanthophylls, which are involved in heat dissipation. Assuming that NPQ is uniquely related to the photochemical efficiency (quantum yield of photochemistry), photochemical efficiencies can be assessed from either chlorophyll fluorescence or PRI. However, this assumption may not be held under some conditions such as low temperatures and photoinhibitory environments. Even in such cases, photosynthesis may be estimated more accurately if both chlorophyll fluorescence and PRI are determined simultaneously. To convert from photochemical efficiency to CO2 assimilation, environmental responses in stomatal conductance also need to be considered. Models linking chlorophyll fluorescence and PRI with CO2 assimilation rates will contribute to understanding and future prediction of the global carbon cycle.

Estimating leaf photosynthesis of C3 plants grown under different environments from pigment index, photochemical reflectance index, and chlorophyll fluorescence.

Photosynthetic rates vary depending on growth conditions, even within species. Remote sensing techniques have a great potential to predict the photosynthetic rates of leaves with different characteristics. Here, we demonstrate that the photosynthetic rates of leaves acclimated to different light and nutrient conditions can be estimated based on the chlorophyll fluorescence (ChlF), the photochemical reflectance index (PRI), and a chlorophyll index. Chenopodium album plants were grown under different light and nutrient conditions. PRI, ChlF parameters, and CO2/H2O gas exchange rates of leaves were simultaneously determined under the various light and CO2 conditions. PRI was used to assess non-photochemical quenching (NPQ), but the relationship between NPQ and PRI was weakened when the data on leaves grown under different conditions were pooled, because PRI in darkness ([Formula: see text]) changed with the leaf pigment composition. Among 15 pigment indices, we found that [Formula: see text], a reflectance index related to the leaf chlorophyll content, had the best correlation with [Formula: see text] ([Formula: see text]) across the studied leaves, and the correction of PRI by [Formula: see text] improved the predictability of NPQ ([Formula: see text]). Using the steady-state ChlF, the NPQ estimated from PRI and [Formula: see text], and the stomatal conductance coefficient, we calculated the CO2 assimilation rates, which were strongly correlated with the actual rates (RMSE = 4.85 [Formula: see text]mol m[Formula: see text] s[Formula: see text]), irrespective of growth conditions. Our approach has the potential to contribute to a more accurate estimation of photosynthetic rates in remote sensing. However, further studies on species variations and connecting with radiative transfer models are needed to demonstrate this at the canopy scale.

Photosynthesis, chlorophyll fluorescence and photochemical reflectance index in photoinhibited leaves.

Solar-induced chlorophyll (chl) fluorescence (SIF) has been shown to be positively correlated with vegetation photosynthesis, suggesting that it is a useful signal for understanding of environmental responses and spatial heterogeneity of photosynthetic activity at various scales from leaf to the globe. Photosynthesis is often inhibited in stressful environments (photoinhibition), but how photoinhibition influences the relationship between photosynthesis and chl fluorescence remains unclear. Here, I studied light energy allocation among photosynthesis, chl fluorescence and heat dissipation in photoinhibited leaves and tested whether photosynthesis in photoinhibited leaves can be evaluated from chl fluorescence and reflectance spectra in remote sensing. Chl fluorescence and reflection spectra were examined with the pulse amplified modulation (PAM) system and spectroradiometer, respectively. Photoinhibited leaves had lower photosynthetic rates and quantum yields of photochemistry (ΦP) and higher chl fluorescence yields. Consequently, photosynthesis was negatively correlated with chl fluorescence, which contrasts the positive relationships between photosynthesis and SIF observed in past remote sensing studies. This suggests that vegetation photosynthesis evaluated solely from chl fluorescence may be overestimated if the vegetation is dominated by severely photoinhibited leaves. When a model of energy allocation was applied, ΦP estimated from chl fluorescence and photochemical reflectance index (PRI) significantly correlated with the observed ΦP, suggesting that the model is useful to evaluate photosynthetic activities of photoinhibited leaves by remote sensing.

Dividing the pie: A quantitative review on plant density responses.

Plant population density is an important variable in agronomy and forestry and offers an experimental way to better understand plant-plant competition. We made a meta-analysis of responses of even-aged mono-specific stands to population density by quantifying for 3 stand and 33 individual plant variables in 334 experiments how much both plant biomass and phenotypic traits change with a doubling in density. Increasing density increases standing crop per area, but decreases the mean size of its individuals, mostly through reduced tillering and branching. Among the phenotypic traits, stem diameter is negatively affected, but plant height remains remarkably similar, partly due to an increased stem length-to-mass ratio and partly by increased allocation to stems. The reduction in biomass is caused by a lower photosynthetic rate, mainly due to shading of part of the foliage. Total seed mass per plant is also strongly reduced, marginally by lower mass per seed, but mainly because of lower seed numbers. Plants generally have fewer shoot-born roots, but their overall rooting depth seems hardly affected. The phenotypic plasticity responses to high densities correlate strongly with those to low light, and less with those to low nutrients, suggesting that at high density, shading affects plants more than nutrient depletion.

Temperature-related cline in the root mass fraction in East Asian wild radish along the Japanese archipelago.

Wild plants with a wide distribution, including those exposed to a wide variety of environmental conditions, may have variations in key functional traits relevant for agricultural applications. The East Asian wild radish (Raphanus sativus var. raphanistroides) is an appropriate model plant because it is widely distributed and has outstanding sink capacity as well as two cultivars within the species. Multiple common garden trials with 14 populations and three testing sites were conducted across the Japanese archipelago to quantify variations in yield and allocation. Significant inter-population variations and interaction effects with testing sites were detected for the root and shoot mass and the root mass fraction (RMF). While the rank order of the population changed drastically among sites and the variance components of genetic effects were small in yield traits (2.4%-4.7%), RMF displayed a large genetic variance (23.2%) and was consistently higher in the northern populations at all sites. Analyses revealed that the mean temperature of growing season of the seed origin was the most prominent factor explaining variation in RMF, irrespective of the sites. We concluded that the trait of resource allocation had a temperature-related cline and plants in cooler climates could invest more resources into their roots.

Functional shifts in leaves of woody invaders of deciduous forests between their home and away ranges.

Temperate forests are widely invaded by shade-tolerant shrubs and trees, including those of Eastern North America (ENA). However, it remains unknown whether these invaders are 'preadapted' for success in their new ranges due to unique aspects of their evolutionary history or whether selection due to enemy release or other postintroduction processes have driven rapid evolution in the invaded range. We sampled leaf traits of populations of woody understory invaders across light gradients in their native range in Japan and in their invaded ENA range to examine potential phenotypic shifts related to carbon gain and nitrogen use between ranges. We also measured leaf traits in three co-occurring ENA native shrub species. In their invaded range, invaders invested significantly less in leaf chlorophyll content (both per unit leaf mass and area) compared with native range populations of the same species, yet maintained similar rates of photosynthesis in low light. In addition, compared with ENA natives, ENA invaders displayed greater trait variation in response to increasing light availability (forest edges, gaps), giving them a potential advantage over ENA natives in a variety of light conditions. We conclude that, for this group of species, newly evolved phenotypes in the invaded range are more important than preadaptation for their success as shade-tolerant forest invaders.

Plasticity of functional traits and optimality of biomass allocation in elevational ecotypes of Arabidopsis halleri grown at different soil nutrient availabilities.

In mountainous areas, plant distribution is constrained by various environmental stresses. Plasticity and constancy in plant functional traits may relate to optimal strategies at respective habitats and to ecotypic differentiation along elevation. Although plant biomass allocation has been extensively studied in relation to adaptation to soil nutrient availability along elevation, its optimality is still poorly understood. We examined soil nutrient availability in the field and conducted growth analysis for two elevational ecotypes of Arabidopsis halleri grown under different nutrient availabilities. We determined plasticity in morphological and physiological traits and evaluated optimal biomass allocation using an optimality model. Our field investigation indicated that soil nitrogen (N) availability increased rather than decreased with increasing elevation. Our growth analysis revealed that lowland ecotype was more plastic in morphological variables and N concentrations, whereas the highland ecotype was more plastic in other physiological variables such as the net assimilation rate (NAR). The leaf mass ratio (LMR) in the lowland ecotype was moderately plastic at the whole range of N availabilities, whereas LMR in the highland ecotype was very plastic at higher N availabilities only. The optimality model indicated that the LMR of the lowland ecotype was nearly optimal throughout the range of studied N availabilities, whereas that of the highland ecotype was suboptimal at low N availability. These results suggest that highland ecotype is adapted only to high N availability, whereas the lowland ecotype is adapted to a relatively wide range of N availabilities as a result of natural selection in their respective habitats. We conclude that an adaptive differentiation has occurred between the two ecotypes and plasticity in the biomass allocation is directly related to its optimization in changing environments.

Acclimation and adaptation components of the temperature dependence of plant photosynthesis at the global scale.

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.

Modeling leaf CO2 assimilation and Photosystem II photochemistry from chlorophyll fluorescence and the photochemical reflectance index.

We present a simple model to assess the quantum yield of photochemistry (ΦP ) and CO2 assimilation rate from two parameters that are detectable by remote sensing: chlorophyll (chl) fluorescence and the photochemical reflectance index (PRI). ΦP is expressed as a simple function of the chl fluorescence yield (ΦF ) and nonphotochemical quenching (NPQ): ΦP  = 1-bΦF (1 + NPQ). Because NPQ is known to be related with PRI, ΦP can be remotely assessed from solar-induced fluorescence and the PRI. The CO2 assimilation rate can be assessed from the estimated ΦP value with either the maximum carboxylation rate (Vcmax ), the intercellular CO2 concentration (Ci ), or parameters of the stomatal conductance model. The model was applied to experimental data obtained for Chenopodium album leaves under various environmental conditions and was able to successfully predict ΦF values and the CO2 assimilation rate. The present model will improve the accuracy of assessments of gas exchange rates and primary productivity by remote sensing.

Dependence of functional traits related to growth rates and their CO2 response on multiple habitat climate factors across Arabidopsis thaliana populations.

The values of many plant traits are often different even within a species as a result of local adaptation. Here, we studied how multiple climate variables influence trait values in Arabidopsis thaliana grown under common conditions. We examined 9 climate variables and 29 traits related to vegetative growth rate in 44 global A. thaliana accessions grown at ambient or elevated CO2 concentration ([CO2]) and applied a multiple regression analysis. We found that genetic variations in the traits related to growth rates were associated with various climate variables. At ambient [CO2], plant size was positively correlated with precipitation in the original habitat. This may be a result of larger biomass investment in roots at the initial stage in plants adapting to a lower precipitation. Stomatal conductance and photosynthetic nitrogen use efficiency were negatively correlated with vapor pressure deficit, probably as a result of the trade-off between photosynthetic water- and nitrogen-use efficiency. These results suggest that precipitation and air humidity influence belowground and aboveground traits, respectively. Elevated [CO2] altered climate dependences in some of the studied traits. The CO2 response of relative growth rate was negatively correlated with altitude, indicating that plants inhabiting a higher altitude have less plasticity to changing [CO2]. These results are useful not only for understanding evolutionary process but also to predict the plant species that are favored under future global change.