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Glasshouse study was carried out to evaluate the impacts of water deficit stress (WDS) on leaf growth and photosynthetic pigments of four maize varieties at the Institute of Agricultural Research and Training, Ibadan. Seeds from ‘TZPBSR-W’, ‘ILE1OB’, ‘ART98SW6OB’ and ‘DTESYNSTR’ maize varieties were sown in sixty-four pots in a 4 x 4 factorial CR Design(r=4). The WDS treatments include 100%, 75%, 50% and 25% field capacities (FC). Data were taken weekly on specific leaf weight (SLW), leaf area (LA), leaf weight (LWT) and crop growth rate. At four weeks of WDS, extracts were obtained from 0.2 g cut leaf sample using 96% (v/v) ethanol. Light absorbance of the ethanolic leaf extract (cholorophyll-a (665 nm), chlorophyll-b (649 nm), total chlorophyll and the carotenoids (440 nm)) were read using spectrophotometer. From the results, WDS significantly reduced SLW, LWT, LA and CGR (p<0.001). The SLW ranged from 0.027±0.0 (g cm-2) (‘ART98SW6OB’) to 0.034±0.0 (g cm-2) (‘DTESYNSTR’), while the LA ranged from 269.7±25.4 (cm2) (‘ART98SW6OB’) to 220.9±20.9 (cm2) (‘ILE1OB’). Water deficit stress significantly reduced chlorophyll-b (p<0.01), chlorophyll-a and total chlorophyll (p<0.001) and the carotenoid (p<0.05). Chlorophyll-a ranged from 0.038±0.0 mg/g (‘DTESYNSTR’) to 0.050±0.0 mg/g (‘TZPBSR-W’), chlorophyll-b ranged from 0.021 mg/g (‘ART98SW6OB’) to 0.040 mg/g (‘TZPBSR-W’), total chlorophyll ranged from 0.063±0.0 mg/g (‘ART98SW6OB’) to 0.093±0.0 mg/g (‘TZPBSR-W’), while the carotenoid ranged from 0.084±0.08 mg/g (‘ART98SW6OB’) to 0.115±0.09 mg/g (‘TZPBSR-W’). The WDS and Variety interaction on photosynthetic pigments were significant (p<0.05). The Leaf growth traits, photosynthetic pigments and over all crop growth in maize are impaired when subjected to water deficit stress.

Leaf hyperspectral reflectance can be used by the wheat physiology and breeding communities to rapidly estimate Rubisco activity, electron transport rate, leaf nitrogen, leaf dry mass per area, and relative chlorophyll content. Abstract Improving photosynthesis to raise wheat yield potential has emerged as a major target for wheat physiologists. Photosynthesis-related traits, such as nitrogen per unit leaf area (Narea) and leaf dry mass per area (LMA), require laborious, destructive, laboratory-based methods, while physiological traits underpinning photosynthetic capacity, such as maximum Rubisco activity normalized to 25 °C (Vcmax25) and electron transport rate (J), require time-consuming gas exchange measurements. The aim of this study was to assess whether hyperspectral reflectance (350-2500 nm) can be used to rapidly estimate these traits on intact wheat leaves. Predictive models were constructed using gas exchange and hyperspectral reflectance data from 76 genotypes grown in glasshouses with different nitrogen levels and/or in the field under yield potential conditions. Models were developed using half of the observed data with the remainder used for validation, yielding correlation coefficients (R2 values) of 0.62 for Vcmax25, 0.7 for J, 0.81 for SPAD, 0.89 for LMA, and 0.93 for Narea, with bias <0.7%. The models were tested on elite lines and landraces that had not been used to create the models. The bias varied between −2.3% and −5.5% while relative error of prediction was similar for SPAD but slightly greater for LMA and Narea.

Leaf hydraulic conductance plays a role in stomatal closure during soil drought, and reduction in CO2 diffusion is a strong driver of the photosynthetic decline during drought. Abstract Understanding the physiological responses of crops to drought is important for ensuring sustained crop productivity under climate change, which is expected to exacerbate the frequency and intensity of periods of drought. Drought responses involve multiple traits, and the correlations between these traits are poorly understood. Using a variety of techniques, we estimated the changes in gas exchange, leaf hydraulic conductance, and leaf turgor in rice (Oryza sativa) in response to both short- and long-term soil drought. We performed a photosynthetic limitation analysis to quantify the contributions of each limiting factor to the resultant overall decrease in photosynthesis during drought. Biomass, leaf area, and leaf width significantly decreased during the 2-week drought treatment, but leaf mass per area and leaf vein density increased. Light-saturated photosynthetic rate declined dramatically during soil drought, mainly due to the decrease in stomatal conductance (gs) and mesophyll conductance (gm). Stomatal modeling suggested that the decline in leaf hydraulic conductance explained most of the decrease in stomatal closure during the drought treatment, and may also trigger the drought-related decrease of stomatal conductance and mesophyll conductance. The results of this study provide insight into the regulation of carbon assimilation under drought conditions.

Adaptation to drought involves complex interactions of traits that vary within and among species. To date, few data are available to quantify within-species variation in functional traits and they are rarely integrated into mechanistic models to improve predictions of species response to climate change.We quantified intraspecific variation in functional traits of two Hakea species growing along an aridity gradient in southeastern Australia. Measured traits were later used to parameterise the model SurEau to simulate a transplantation experiment to identify the limits of drought tolerance.Embolism resistance varied between species but not across populations. Instead, populations adjusted to drier conditions via contrasting sets of trait trade-offs that facilitated homeostasis of plant water status. The species from relatively mesic climate, Hakea dactyloides, relied on tight stomatal control whereas the species from xeric climate, Hakea leucoptera dramatically increased Huber value and leaf mass per area, while leaf area index (LAI) and epidermal conductance (g(min)) decreased. With trait variability, SurEau predicts the plasticity of LAI and g(min) buffers the impact of increasing aridity on population persistence.Knowledge of within-species variability in multiple drought tolerance traits will be crucial to accurately predict species distributional limits.

• Increases in leaf mass per area (LMA) are commonly observed in response to environmental stresses and are achieved through increases in leaf thickness and/or leaf density. Here, we investigated how the two underlying components of LMA differ in relation to species native climates and phylogeny, across deciduous and evergreen species. • Using a phylogenetic approach, we quantified anatomical, compositional and climatic variables from 40 deciduous and 45 evergreen Quercus species from across the Northern Hemisphere growing in a common garden. • Deciduous species from shorter growing seasons tended to have leaves with lower LMA and leaf thickness than those from longer growing seasons, while the opposite pattern was found for evergreens. For both habits, LMA and thickness increased in arid environments. However, this shift was associated with increased leaf density in evergreens but reduced density in deciduous species. • Deciduous and evergreen oaks showed fundamental leaf morphological differences that revealed a diverse adaptive response. While LMA in deciduous species may have diversified in tight coordination with thickness mainly modulated by aridity, diversification of LMA within evergreens appears to be dependent on the infrageneric group, with diversification in leaf thickness modulated by both aridity and cold, while diversification in leaf density is only modulated by aridity.

• Large intraspecific functional trait variation strongly impacts many aspects of communities and ecosystems, and is the medium upon which evolution works. Yet intraspecific trait variation is inconsistent and hard to predict across traits, species and locations. • We measured within-species variation in leaf mass per area (LMA), leaf dry matter content (LDMC), branch wood density (WD), and allocation to stem area vs leaf area in branches (branch Huber value (HV)) across the aridity range of seven Australian eucalypts and a co-occurring Acacia species to explore how traits and their variances change with aridity. • Within species, we found consistent increases in LMA, LDMC and WD and HV with increasing aridity, resulting in consistent trait coordination across leaves and branches. However, this coordination only emerged across sites with large climate differences. Unlike trait means, patterns of trait variance with aridity were mixed across populations and species. Only LDMC showed constrained trait variation in more xeric species and drier populations that could indicate limits to plasticity or heritable trait variation. • Our results highlight that climate can drive consistent within-species trait patterns, but that patterns might often be obscured by the complex nature of morphological traits, sampling incomplete species ranges or sampling confounded stress gradients

• Leaf trait relationships are widely used to predict ecosystem function in terrestrial biosphere models (TBMs), in which leaf maximum carboxylation capacity (Vc,max), an important trait for modelling photosynthesis, can be inferred from other easier-to-measure traits. However, whether trait–Vc,max relationships are robust across different forest types remains unclear. • Here we used measurements of leaf traits, including one morphological trait (leaf mass per area), three biochemical traits (leaf water content, area-based leaf nitrogen content, and leaf chlorophyll content), one physiological trait (Vc,max), as well as leaf reflectance spectra, and explored their relationships within and across three contrasting forest types in China. • We found weak and forest type-specific relationships between Vc,max and the four morphological and biochemical traits (R² ≤ 0.15), indicated by significantly changing slopes and intercepts across forest types. By contrast, reflectance spectroscopy effectively collapsed the differences in the trait–Vc,max relationships across three forest biomes into a single robust model for Vc,max (R² = 0.77), and also accurately estimated the four traits (R² = 0.75–0.94). • These findings challenge the traditional use of the empirical trait–Vc,max relationships in TBMs for estimating terrestrial plant photosynthesis, but also highlight spectroscopy as an efficient alternative for characterising Vc,max and multitrait variability, with critical insights into ecosystem modelling and functional trait ecology.

• Foliar functional traits are widely used to characterize leaf and canopy properties that drive ecosystem processes and to infer physiological processes in Earth system models. Imaging spectroscopy provides great potential to map foliar traits to characterize continuous functional variation and diversity, but few studies have demonstrated consistent methods for mapping multiple traits across biomes. • With airborne imaging spectroscopy data and field data from 19 sites, we developed trait models using partial least squares regression, and mapped 26 foliar traits in seven NEON (National Ecological Observatory Network) ecoregions (domains) including temperate and subtropical forests and grasslands of eastern North America. • Model validation accuracy varied among traits (normalized root mean squared error, 9.1– 19.4%; coefficient of determination, 0.28–0.82), with phenolic concentration, leaf mass per area and equivalent water thickness performing best across domains. Across all trait maps, 90% of vegetated pixels had reasonable values for one trait, and 28–81% provided high confidence for multiple traits concurrently. • Maps of 26 traits and their uncertainties for eastern US NEON sites are available for download, and are being expanded to the western United States and tundra/boreal zone. These data enable better understanding of trait variations and relationships over large areas, calibration of ecosystem models, and assessment of continental-scale functional diversity.

Parthenium hysterophorus L. (Asteraceae) is a highly prevalent invasive species in subtropical regions across the world. It has recently been seen to shift from low (subtropical) to high (sub-temperate) elevations. Nevertheless, there is a dearth of research investigating the adaptive responses and the significance of leaf functional traits in promoting the expansion to high elevations. The current study investigated the variations and trade-offs among 14 leaf traits (structural, photosynthetic, and nutrient content) of P. hysterophorus across different elevations in the western Himalayas, India. Plots measuring 20 × 40 m were established at different elevations (700 m, 1100 m, 1400 m, and 1800 m) to collect leaf trait data for P. hysterophorus . Along the elevational gradient, significant variations were noticed in leaf morphological parameters, leaf nutrient content, and leaf photosynthetic parameters. Significant increases were observed in the specific leaf area, leaf thickness, and chlorophyll a , total chlorophyll and carotenoid content, as well as leaf nitrogen and phosphorus content with elevation. On the other hand, there were reductions in the amount of chlorophyll b , photosynthetic efficiency, leaf dry matter content, leaf mass per area, and leaf water content. The trait-trait relationships between leaf water content and dry weight and between leaf area and dry weight were stronger at higher elevations. The results show that leaf trait variability and trait-trait correlations are very important for sustaining plant fitness and growth rates in low-temperature, high-irradiance, resource-limited environments at relatively high elevations. To summarise, the findings suggest that P. hysterophorus can expand its range to higher elevations by broadening its functional niche through changes in leaf traits and resource utilisation strategies.

Intercropping can obtain yield advantages, but the mechanism of yield advantages of maize-legume intercropping is still unclear. Then, we explored the effects of cropping systems and N input on yield advantages in a two-year experiment. Cropping systems included monoculture maize ( Zea mays L.) (MM), monoculture soybean ( Glycine max L. Merr.) (MS), monoculture peanut ( Arachis hypogaea L.) (MP), maize-soybean substitutive relay intercropping (IMS), and maize-peanut substitutive strip intercropping (IMP). N input included without N (N0) and N addition (N1). Results showed that maize’s leaf area index was 31.0% and 34.6% higher in IMS and IMP than in MM. The specific leaf weight and chlorophyll a (chl a) of maize were notably higher by 8.0% and 18.8% in IMS, 3.1%, and 18.6% in IMP compared with MM. Finally, N addition resulted in a higher thousand kernels weight of maize in IMS and IMP than that in MM. More dry matter accumulated and partitioned to the grain, maize's averaged partial land equivalent ratio and the net effect were 0.76 and 2.75 t ha −1 in IMS, 0.78 and 2.83 t ha −1 in IMP. The leaf area index and specific leaf weight of intercropped soybean were 16.8% and 26% higher than MS. Although soybean suffers from shade during coexistence, recovered growth strengthens leaf functional traits and increases dry matter accumulation. The averaged partial land equivalent ratio and the net effect of intercropped soybean were 0.76 and 0.47 t ha −1 . The leaf area index and specific leaf weight of peanuts in IMP were 69.1% and 14.4% lower than in the MP. The chlorophyll a and chlorophyll b of peanut in MP were 17.0% and 24.4% higher than in IMP. A less dry matter was partitioned to the grain for intercropped peanut. The averaged pLER and NE of intercropped peanuts were 0.26 and -0.55 t ha −1 . In conclusion, the strengthened leaf functional traits promote dry matter accumulation, maize-soybean relay intercropping obtained a win–win yield advantage, and maize-peanut strip intercropping achieved a trade-off yield advantage.