•We evaluated canopy, bark, and leaf traits of upland oaks and common competitors.•Canopy, bark, and leaf litter traits of upland oaks were often those that promote fire.•American beech, red maple, ...and sugar maple traits were linked to low flammability.•Fire suppressing traits of many oak competitors could limit fire restoration.
Shade-tolerant, fire-intolerant tree species are expanding in historically oak-dominated landscapes in the central and eastern U.S. Once established, these species are hypothesized to accelerate their own expansion through canopy, bark, and leaf litter traits that decrease forest flammability, consequently hindering the growth and survival of pyrophytic, shade-intolerant upland oaks (Quercus spp.). To better understand how canopy, bark, and leaf litter traits associated with flammability differ between oaks and common competitors, we quantified these traits in an upland oak forest in western Kentucky for four oak species and five non-oak species varying in shade and fire tolerance. Compared to oaks, American beech (Fagus grandifolia Ehrh.), red maple (Acer rubrum L.), and sugar maple (A. saccharum Marshall.) had: (1) wider, deeper canopies, traits associated with shadier, cooler understory conditions and higher fuel moisture; (2) thinner, smoother bark, traits that increase fire susceptibility, yet produce higher stemflow volume and potentially moister fuels near the tree’s bole; and (3) leaf litter with a higher specific leaf area and surface area:volume ratio, traits linked to higher fuel bed bulk density and fuel moisture. Hickory (Carya spp.) and tulip poplar (Liriodendron tulipifera L.) traits were generally similar to that of oaks. Our findings show that non-oak tree competitors commonly found in upland oak forests display canopy, bark, and leaf litter traits often associated with low flammability, but that the number and array of non-flammable traits varies widely by species and sometimes changes with tree size, leading to a gradient of traits and potentially fire dampening abilities. If these species continue to expand, reduced flammability could limit prescribed fire effectiveness in upland oak restoration.
In this study, Cucurbita pepo L., one of the most cultivated, consumed and economically important crop worldwide, was used as model plant to test the toxic effects of the four most abundant ...microplastics identified in contaminated soils, i.e. polypropylene (PP), polyethylene (PE), polyvinylchloride (PVC), and polyethyleneterephthalate (PET). Cucurbita plants were grown in pots with increasing concentrations of the microplastics, then plant biometry, photosynthetic parameters and ionome of treated vs. untreated samples were compared to evaluate the toxicity of each plastic. All the pollutants impaired root and, especially, shoot growth. Specific and concentration-dependant effects of the different microplastics were found, including reduction in leaf size, chlorophyll content and photosynthetic efficiency, as well as changes in the micro- and macro-elemental profile. Among all the microplastics, PVC was identified as the most toxic and PE as the less toxic material. PVC decreased the dimensions of the leaf lamina, the values of the photosynthetic performance index and the plant iron concentration to a higher extent in respect to the other treatments. Microplastic toxicity exerted on the growth of C. pepo raises concerns about possible yield and economic loss, as well as for risks of a possible transfer into the food chain.
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•Toxic effects of microplastics PP, PE, PVC, and PET were tested on Cucurbita pepo.•Microplastics exerted specific type- and concentration-dependent effects.•Biometry, photosynthetic parameters and ionome were altered by microplastic treatment.•PVC was the most toxic microplastic for Cucurbita pepo whereas PE the less toxic one.
We provide a step-by-step guide for combining measurements of leaf reflectance and leaf traits to build statistical models that estimate traits from reflectance, enabling rapid collection of a ...diverse range of leaf properties.
Abstract
Partial least squares regression (PLSR) modelling is a statistical technique for correlating datasets, and involves the fitting of a linear regression between two matrices. One application of PLSR enables leaf traits to be estimated from hyperspectral optical reflectance data, facilitating rapid, high-throughput, non-destructive plant phenotyping. This technique is of interest and importance in a wide range of contexts including crop breeding and ecosystem monitoring. The lack of a consensus in the literature on how to perform PLSR means that interpreting model results can be challenging, applying existing models to novel datasets can be impossible, and unknown or undisclosed assumptions can lead to incorrect or spurious predictions. We address this lack of consensus by proposing best practices for using PLSR to predict plant traits from leaf-level hyperspectral data, including a discussion of when PLSR is applicable, and recommendations for data collection. We provide a tutorial to demonstrate how to develop a PLSR model, in the form of an R script accompanying this manuscript. This practical guide will assist all those interpreting and using PLSR models to predict leaf traits from spectral data, and advocates for a unified approach to using PLSR for predicting traits from spectra in the plant sciences.
The nitrogen cost of photosynthesis Evans, John R; Clarke, Victoria C
Journal of experimental botany,
01/2019, Letnik:
70, Številka:
1
Journal Article
Recenzirano
Odprti dostop
This review provides a generalized nitrogen budget for a C3 leaf cell, shows the use of nitrogen as a proxy for predicting photosynthetic capacity in ecosystem models and discusses the potential for ...improving crop photosynthesis from a nitrogen perspective.
Abstract
Global food security depends on three main cereal crops (wheat, rice and maize) achieving and maintaining high yields, as well as increasing their future yields. Fundamental to the production of this biomass is photosynthesis. The process of photosynthesis involves a large number of proteins that together account for the majority of the nitrogen in leaves. As large amounts of nitrogen are removed in the harvested grain, this needs to be replaced either from synthetic fertilizer or biological nitrogen fixation. Knowledge about photosynthetic properties of leaves in natural ecosystems is also important, particularly when we consider the potential impacts of climate change. While the relationship between nitrogen and photosynthetic capacity of a leaf differs between species, leaf nitrogen content provides a useful way to incorporate photosynthesis into models of ecosystems and the terrestrial biosphere. This review provides a generalized nitrogen budget for a C3 leaf cell and discusses the potential for improving photosynthesis from a nitrogen perspective.
Drought is one of the most important environmental stresses affecting the productivity of most field crops. Elucidation of the complex mechanisms underlying drought resistance in crops will ...accelerate the development of new varieties with enhanced drought resistance. Here, we provide a brief review on the progress in genetic, genomic, and molecular studies of drought resistance in major crops. Drought resistance is regulated by numerous small-effect loci and hundreds of genes that control various morphological and physiological responses to drought. This review focuses on recent studies of genes that have been well characterized as affecting drought resistance and genes that have been successfully engineered in staple crops. We propose that one significant challenge will be to unravel the complex mechanisms of drought resistance in crops through more intensive and integrative studies in order to find key functional components or machineries that can be used as tools for engineering and breeding drought-resistant crops.
Characterizing variation and association of plant traits is critical for understanding plant adaptation strategies and community assembly mechanisms. However, little is known about the leaf trait ...variations of desert plants and their association with different life forms. We used principal component analysis, Pearson's correlation, phylogenetic independent contrasts, linear mixed model, and variance decomposition to explore the variation and association of 10 leaf traits in 22 desert plants in the arid area of northwest China. We found that: (1) the contribution of interspecific variation to the overall variation was greater than the intraspecific variation of all the studied leaf traits; (2) intraspecific and interspecific variation in leaf traits differed among life forms. Some leaf traits, such as tissue density of shrubs and specific leaf area of herbs, exhibited greater intraspecific than interspecific variation, while other traits exhibited the inverse; (3) desert shrubs corroborate the leaf economic spectrum hypothesis and had a fast acquisitive resource strategy, but herbs may not conform to this hypothesis; (4) there were trade‐offs between leaf traits, which were mediated by phylogeny. Overall, our results suggest that interspecific variation of leaf traits significantly contributes to the total leaf traits variation in desert plants. However, intraspecific variation should not be overlooked. There are contrasts in the resource acquisition strategies between plants life forms. Our results support understanding of the mechanisms underlying community assembly in arid regions and suggest that future works may focus on the variation and association of plant traits at both intra‐ and interspecific scales.
Our results suggest that interspecific variation of leaf traits greatly contributes to the total leaf traits variation in desert plants but intraspecific variation should not be overlooked. There are differences in the resource strategies of plants of different life forms.
Leaf morphology plays a crucial role in predicting the productivity and environmental adaptability of forest trees, making it essential to understand the genetic mechanisms behind leaf variation. In ...natural populations of Populus cathayana, leaf morphology exhibits rich intraspecific variation due to long-term selection. However, there have been no studies that systematically reveal the genetic mechanisms of leaf variation in P. cathayana. To fill this gap and enhance our understanding of leaf variation in P. cathayana, we collected nine leaf traits from the P. cathayana natural population, consisting of 416 accessions, and conducted the preliminary classification of leaf types with four categories. Subsequently, we conducted an analysis of selective sweep and genome-wide association studies (GWAS) to uncover the genetic basis of leaf traits variation. Most of the leaf traits displayed significant correlations, with broad-sense trait heritability ranging from 0.38 to 0.74. In total, three selective sweep methods ultimately identified 278 positively selected candidate regions and 493 genes associated with leaf size. Single-trait and multi-trait GWAS methods detected 13 and 59 genes, respectively. By integrating the results of selective sweep and GWAS, we further identified a total of nine overlapping genes. These genes may play a role in the leaf development process and are closely associated with leaf size. In particular, the gene CBSCBSPB3 (Pca07G009100) located on chromosome 7, was associated with the response to light stimulation. This study will deepen our understanding of the genetic mechanism of leaf adaptive variation in P. cathayana and provide valuable gene resources.
Plants can modify their morphological or physiological traits in response to nutrient availability and to the presence and identity of neighboring individuals. However, few studies have addressed the ...effects of changes in above- and below-ground functional traits for the productivity advantage in intercropping.
We hypothesized that the plasticity of above- and below-ground functional traits of crops in response to nutrients availability and interspecific interactions affects biomass of both crop species and whole intercropping systems.
A 2-year field experiment was performed with two N levels (with and without), two P levels (with and without) and five cropping systems (i.e. sole maize, peanut and soybean, and maize/peanut and maize/soybean intercropping). We measured thirteen above- and below-ground functional traits related to light interception and use efficiency, root length and distribution at the grain filling stage of maize, and final biomass at harvest.
Maize/peanut and maize/soybean intercrops has productivity advantages compared to monoculture, and this was mainly in terms of increases in maize biomass. Compared with monoculture, intercropping increased maize biomass more than it decreased soybean (24 %) or peanut (49 %) biomass. Maize had a yield advantage through greater leaf area, root length and root biomass density when intercropped. Intercropped soybean resisted suppression by maize through increased height and specific leaf area, but intercropped soybean had decreased specific leaf N and biomass. Branch number, leaf area, specific leaf nitrogen and root biomass density of peanut were all suppressed by maize, which caused a large decrease in peanut biomass when intercropped.
Our study provides evidence that changes in above- and below-ground functional traits in response to nutrients availability and interspecific interactions are key to explaining patterns of transgressive overyielding. Our findings can help to better understand the underlying mechanisms that regulate productivity advantages in species mixtures, and have implications for the sustainable management of species-diverse food-production systems.
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•Intercropping increased maize biomass but decreased soybean and peanut biomass.•Intercropped maize had a yield advantage through greater light and nutrient capture.•Intercropped soybean resisted suppression by maize through increased height and SLA.•Leaf area, SLA and root biomass density of peanut were all suppressed by maize.
Abstract
Understanding seasonal variation in photosynthesis is important for understanding and modeling plant productivity. Here, we used shotgun sampling to examine physiological, structural and ...spectral leaf traits of upper canopy, sun-exposed leaves in Quercus coccinea Münchh (scarlet oak) across the growing season in order to understand seasonal trends, explore the mechanisms underpinning physiological change and investigate the impact of extrapolating measurements from a single date to the whole season. We tested the hypothesis that photosynthetic rates and capacities would peak at the summer solstice, i.e., at the time of peak photoperiod. Contrary to expectations, our results reveal a late-season peak in both photosynthetic capacity and rate before the expected sharp decrease at the start of senescence. This late-season maximum occurred after the higher summer temperatures and vapor pressure deficit and was correlated with the recovery of leaf water content and increased stomatal conductance. We modeled photosynthesis at the top of the canopy and found that the simulated results closely tracked the maximum carboxylation capacity of Rubisco. For both photosynthetic capacity and modeled top-of-canopy photosynthesis, the maximum value was therefore not observed at the summer solstice. Rather, in each case, the measurements at and around the solstice were close to the overall seasonal mean, with values later in the season leading to deviations from the mean by up to 41 and 52%, respectively. Overall, we found that the expected Gaussian pattern of photosynthesis was not observed. We conclude that an understanding of species- and environment-specific changes in photosynthesis across the season is essential for correct estimation of seasonal photosynthetic capacity.
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