Quantitative trait loci controlling plant architectural traits in cotton

Cotton plant architecture is an important characteristic influencing the suitability of specific cotton varieties in cultivation, fiber yield and quality. However, complex multigenic relationships and substantial genotype–environment interaction underlie plant architecture, and will hinder the efficient improvement of these traits in conventional cotton breeding programs. An enhanced understanding of the molecular-genetic regulation of plant morphological developmental can aid in the modification of agronomically relevant traits. In this study, an interspecific Gossypium hirsutum and Gossypium barbadense BC₁ population was used to identify QTL associated with plant architectural traits. Twenty-six single QTL were identified for seven plant architecture traits. The phenotypic variation explained by an individual QTL ranged from 9.56% to 44.57%. In addition, 11 epistatic QTL for fruit branch angle (FBA), plant height (PH), main-stem leaf size (MLS), and fruiting branch internode length (FBI) explained 2.28–15.34% of the phenotypic variation in these traits. The majority of the interactions (60%) occurred between markers linked to QTL influencing the same traits. The QTL detected in this study are expected to be valuable in future breeding programs to develop cultivars exhibiting desirable cotton architecture.     

Quantitative genetics and functional-structural plant growth models: simulation of quantitative trait loci detection for model parameters and application to potential yield optimization

BACKGROUND AND AIMS: Prediction of phenotypic traits from new genotypes under untested environmental conditions is crucial to build simulations of breeding strategies to improve target traits. Although the plant response to environmental stresses is characterized by both architectural and functional plasticity, recent attempts to integrate biological knowledge into genetics models have mainly concerned specific physiological processes or crop models without architecture, and thus may prove limited when studying genotype x environment interactions. Consequently, this paper presents a simulation study introducing genetics into a functional-structural growth model, which gives access to more fundamental traits for quantitative trait loci (QTL) detection and thus to promising tools for yield optimization. METHODS: The GREENLAB model was selected as a reasonable choice to link growth model parameters to QTL. Virtual genes and virtual chromosomes were defined to build a simple genetic model that drove the settings of the species-specific parameters of the model. The QTL Cartographer software was used to study QTL detection of simulated plant traits. A genetic algorithm was implemented to define the ideotype for yield maximization based on the model parameters and the associated allelic combination. KEY RESULTS AND CONCLUSIONS: By keeping the environmental factors constant and using a virtual population with a large number of individuals generated by a Mendelian genetic model, results for an ideal case could be simulated. Virtual QTL detection was compared in the case of phenotypic traits--such as cob weight--and when traits were model parameters, and was found to be more accurate in the latter case. The practical interest of this approach is illustrated by calculating the parameters (and the corresponding genotype) associated with yield optimization of a GREENLAB maize model. The paper discusses the potentials of GREENLAB to represent environment x genotype interactions, in particular through its main state variable, the ratio of biomass supply over demand.     

Using intra‐individual variation in shrub architecture to explain population cover

Plant architecture is related to the performance of long‐lived plants; its role in promoting species coexistence and in successional patterns is now widely recognized. However, because plant architecture involves branching processes, it is highly variable at the intra‐specific level. In this paper, we address two questions: what is the best way to describe plant architecture to obtain meaningful information for explaining population cover: at the whole‐plant level, or at the level of its unitary constituent parts? Further, are there architectural designs related to populations’ success? We evaluated the relative impact of ontogeny and whole‐plant traits on the cover achieved by the populations of five shrub species developing on 25 abandoned farmlands in southwestern Québec (Canada). We compared four ways of analyzing plant architecture: 1–2) using morphological traits described at the scale of a module (an elementary architectural unit made up of all the different types of shoots), with or without taking into account the ontogeny of the whole organism, 3) using the rate of changes during ontogeny as traits, and 4) using whole‐plant traits describing branching processes at a scale larger than modules. We then used variation partitioning to discriminate the actual effects of these traits on percent cover of the species from hidden effects due to plant ontogenesis and population spatial structure. Our results suggest that the predominant variables that effectively describe population cover vary from one species to another. At the same time, whole‐plant architectural traits and the rate of change of morphological traits during ontogeny both have an important effect on population cover. These findings suggest that acknowledging the developmental pattern of woody species can clarify the impact of intra‐specific trait variation on population cover.     

Quantitative trait locus mapping of yield-related components and oligogenic control of the cap color of the button mushroom, Agaricus bisporus

As in other crops, yield is an important trait to be selected for in edible mushrooms, but its inheritance is poorly understood. Therefore, we have investigated the complex genetic architecture of yield-related traits in Agaricus bisporus through the mapping of quantitative trait loci (QTL), using second-generation hybrid progeny derived from a cross between a wild strain and a commercial cultivar. Yield, average weight per mushroom, number of fruiting bodies per m(2), earliness, and cap color were evaluated in two independent experiments. A total of 23 QTL were detected for 7 yield-related traits. These QTL together explained between 21% (two-flushes yield) and 59% (earliness) of the phenotypic variation. Fifteen QTL (65%) were consistent between the two experiments. Four regions underlying significant QTL controlling yield, average weight, and number were detected on linkage groups II, III, IV, and X, suggesting a pleiotropic effect or tight linkage. Up to six QTL were identified for earliness. The PPC1 locus, together with two additional genomic regions, explained up to 90% of the phenotypic variation of the cap color. Alleles from the wild parent showed beneficial effects for some yield traits, suggesting that the wild germ plasm is a valuable source of variation for several agronomic traits. Our results constitute a key step toward marker-assisted selection and provide a solid foundation to go further into the biological mechanisms controlling productive traits in the button mushroom.     

棉花花铃期抗旱性综合评价及指标筛选

以90份国内棉花为材料,在大田采用花铃期胁迫,考察6个农艺性状和单株产量(Y值)指标,采用综合抗旱系数、因子分析、隶属性函数值、聚类分析、灰色关联度和广义遗传力分析相结合的方法,对其抗旱性进行综合评价、抗旱性划分和评价指标筛选。结果表明,基于D值相关性状指标对干旱胁迫关联度位次依次为:单株产量、有效铃数、有效果枝数、株高、单铃重、衣分、第一果枝节位。因子分析表明,3个公因子可代表棉花抗旱性72.45%的原始数据信息量。基于D值和加权抗旱系数(WDC值)的各品种抗旱性排序相近,位居前10位的抗旱品种基本相同。各品种D值与综合抗旱系数(CDC值)、WDC值之间均呈极显著正相关,广义遗传率分析表明D值的遗传率为55.4%,为最高,其次为CDC值、WDC值。各品种Y值与CDC、WDC值间极显著正相关;根据D值将试验材料划分为5个抗旱级别,可较好地反映品种的选育条件及适应地区。试验结果说明基于遗传力大小的综合抗旱指标中用D值为主要参数,WDC为辅助评价参数,评价以单株产量为主要考量目标的棉花抗旱性是适宜且必须的;以抗旱性综合评价方法进行棉花抗旱性综合评价、抗旱性划分和评价指标筛选是可行且有效的。     

Mapping QTLs for improving grain yield using the USDA rice mini-core collection

Yield is the most important and complex trait for genetic improvement in crops, and marker-assisted selection enhances the improvement efficiency. The USDA rice mini-core collection derived from over 18,000 accessions of global origins is an ideal panel for association mapping. We phenotyped 203 O. sativa accessions for 14 agronomic traits and identified 5 that were highly and significantly correlated with grain yield per plant: plant height, plant weight, tillers, panicle length, and kernels/branch. Genotyping with 155 genome-wide molecular markers demonstrated 5 main cluster groups. Linkage disequilibrium (LD) decayed at least 20 cM and marker pairs with significant LD ranged from 4.64 to 6.06% in four main groups. Model comparisons revealed that different dimensions of principal component analysis affected yield and its correlated traits for mapping accuracy, and kinship did not improve the mapping in this collection. Thirty marker–trait associations were highly significant, 4 for yield, 3 for plant height, 6 for plant weight, 9 for tillers, 5 for panicle length and 3 for kernels/branch. Twenty-one markers contributed to the 30 associations, because 8 markers were co-associated with 2 or more traits. Allelic analysis of OSR13, RM471 and RM7003 for their co-associations with yield traits demonstrated that allele 126 bp of RM471 and 108 bp of RM7003 should receive greater attention, because they had the greatest positive effect on yield traits. Tagging the QTLs responsible for multiple yield traits may simultaneously help dissect the complex yield traits and elevate the efficiency to improve grain yield using marker-assisted selection in rice.     

Estimating genetic parameters of architectural and reproductive traits in young macadamia cultivars

Macadamia in the orchard environment is relatively unaltered from its natural form, and there is considerable scope to alter vegetative and reproductive architecture with the aim of improving yield efficiency through breeding. An understanding of the genetic and environmental control of architecture and the dynamics between vegetative and reproductive characteristics are fundamental to identifying traits for yield improvement. This experiment calculated the broad-sense heritability (H) of architectural traits and genetic correlations between vegetative and reproductive traits over 2 years. Cutting-grown clones (n?=?3) of 15 macadamia genotypes were subsampled from a randomised high-density plot planted in 2011 in South East Queensland, Australia, and observed for two seasons between 2015 and 2017. Clonal values from independent linear mixed models for multiple traits were combined in principal component analysis (PCA) to provide an insight to potential genetic relationships between traits, and genetic correlations were calculated from multivariate linear mixed model analysis. At the tree scale, canopy volume and yield had low H (0.07 and 0.14, respectively), implying a strong environmental influence on these complex traits. Architectural components of canopy volume and yield were considered at multiple scales, for which H ranged from 0.06 to 0.68, suggesting architectural traits at lower scales may be manipulated by breeding. Specific traits displayed strong genetic relationships with yield and canopy volume, suggesting that indirect selection for yield efficiency may be possible via selection for architectural and floral traits, to improve future macadamia cultivars.     

Genetic mapping of QTLs affecting productivity and plant architecture in a full-sib cross from non-inbred parents in Cassava (<Emphasis Type="Italic">Manihot esculenta</Emphasis> Crantz)

An attempt was made to identify quantitative trait loci (QTLs) for several productivity and plant architecture traits in a full-sib progeny of 144 individuals from two non-inbred parents in cassava. A molecular linkage map of this cross constructed previously with over 250 markers was the source of molecular markers. The progeny were grown under field conditions at two locations (Palmira and Quilichao) in Colombia and evaluated in 2 years (1998 and 1999) for architecture and productivity traits. Architecture traits evaluated were plant height (PH), branching height (BH), branching levels (BL), branching index (BI), stem portion with leaves (SPL) and leaf area index (LAI). Productivity traits were those related to total dry matter production and distribution, namely fresh root yield (FRY), fresh shoot yield (FSY), harvest index (HI) and the number of storage roots (NR). Phenotypic evaluation of the traits in this population revealed continuous variation for all traits. Broad-sense heritability estimates, ranged from 36% (for NR) to 94% (for BH). Several significant phenotypic correlations were observed between architecture and productivity traits. Primary QTLs, using the single-QTL model, and secondary QTLs, by a primary QTL interaction model, were detected by interval mapping. A total of 30 primary QTLs and 84 secondary QTLs were detected. We identified 35% of detected QTLs in two or more trials, the other QTLs were environment-specific. These results underscore the significant genotype × environment interactions found for most of the traits. Several genomic segments affecting multiple traits were identified and were in agreement with correlation among traits. All QTLs identified for FRY were found associated with either component traits of productivity or architecture traits. This study suggests that QTLs for plant architecture can be used to improve productivity. However an exhaustive search and analysis of QTLs controlling architecture is required before marker-assisted selection (MAS) for increasing productivity can be initiated.Communicated by H. C. Becker     

浙江天童太白山不同群落植物构型比较

植物构型是植株构件在空间上的分配方式,反映了植物对环境的响应策略。通过对浙江天童太白山海拔差异很小的栲树(Castanopsis fargesii)、小叶青冈(Cyclobalanopsis gracilis)和云山青冈(Cyclobalanopsis sessilifolia)群落类型中所有植株的树高、树冠厚度、树冠面积、叶片聚集度、枝下高和距地45 cm基径等植物构型性状,以及树冠曝光指数、土壤含水率、空气温湿度、土壤p H值和风速6个环境因子的测定,分别分析乔灌木层植物构型性状及性状关系在3个群落间的变化规律。结果表明:(1)从栲树到小叶青冈至云山青冈群落,灌木层的树高、树冠厚度、枝下高和距地45 cm基径增加,叶片聚集度减小;乔木层的树高、树冠厚度、树冠面积、枝下高和距地45 cm基径均减小,叶片聚集度增大;(2)3个群落灌木层构型性状间显著相关(P0.001),而乔木层只在中低海拔群落存在相关性;(3)从栲树到小叶青冈至云山青冈群落,乔灌木层的冠层曝光指数显著增加(P0.05);(4)多元逐步回归表明,树冠曝光指数对灌木层构型性状变异的贡献最大,而风速、土壤含水率和p H值对乔木构型性状的变异起主导作用。综上得知,天童太白山乔灌木植物在不同群落间存在构型分异,植物对光资源的竞争是引起灌木构型在不同群落间变化的主要驱动因子,而对乔木植物,其构型变化更多受到风速和土壤含水量的影响。     

Marker-assisted selection for white mold resistance in common bean

A marker-assisted selection (MAS) study was conducted on two recombinant inbred line (RIL) populations of common bean (Phaseolus vulgaris) to test the effectiveness of MAS for resistance to white mold (Sclerotinia sclerotiorum). Markers for quantitative trait loci (QTL) on linkage groups B2 and B7 that were previously associated with resistance and plant architectural avoidance traits in the resistant parent Bunsi were chosen. In the Bunsi/Midland population 10 RILs included in the MAS selected group developed significantly less disease than the control group based on two years of field evaluation under white mold pressure. Growth habit had no significant effect on disease severity or incidence. In the Bunsi/Raven RIL population, disease scores in the MAS selected group were significantly lower than scores in the control group over two years. Additional progress in enhancing resistance to white mold was detected when yield and plant architecture were included in the selection process. Lower disease scores among RILs were observed when comparisons were made to RILs selected using MAS alone. Yield is an important trait that should be considered when selecting for resistance to white mold. Finally the potential of Bunsi as a genetic donor of QTL for white mold resistance was confirmed in both populations studied. This study supported the effectiveness of MAS to enhance selection for a complexly inherited trait such as resistance to white mold in common bean.     

Genetic determinism of the vegetative and reproductive traits in an F1 olive tree progeny

The agronomic performance of fruit trees is significantly influenced by tree internal organization. Introducing architectural traits in breeding programs could thus lead to select new varieties with a regular bearing and lower input demand in order to reduce training and environmental costs. However, an interaction between tree ontogeny and genetic factors is expected. In this study, we investigated the genetic determinism of architectural traits in the olive tree, accounting for tree development over 5 years until first flowering occurrence. We studied an F1 progeny issued from a cross between two contrasted genotypes, ‘Olivière’ and ‘Arbequina’. Tree architecture was decomposed in quantitative traits, related to (1) growth and branching, (2) first flowering and fruiting. Models, including the year of growth, branching order and genotype effects, were built with variance function and covariance structure when necessary. After a model selection, broad sense heritabilities were calculated. During the first 3 years, both the mean values of vegetative traits and genetic factor significance depended on the shoot within-tree position. Dependencies between consecutive years were revealed for traits related to whole tree form. Whole tree form variables showed medium to high broad sense heritability values, whereas reproductive traits were highly heritable. This study demonstrates the existence of ontogenic trends in the olive tree, which result in traits heritable only at the tree periphery. A phenotyping strategy adapted to its architectural characteristics and a list of relevant traits, such as maximal internode length, is proposed. Transgressive effects suggest that genetic progress could be performed in future selection programs.     

Changes in the vertical distribution of leaf area enhanced light interception efficiency in maize over generations of selection

Breeders select for yield, thereby indirectly selecting for traits that contribute to it. We tested if breeding has affected a range of traits involved in plant architecture and light interception, via the analysis of a panel of 60 maize hybrids released from 1950 to 2015. This was based on novel traits calculated from reconstructions derived from a phenotyping platform. The contribution of these traits to light interception was assessed in virtual field canopies composed of 3D plant reconstructions, with a model tested in a real field. Two categories of traits had different contributions to genetic progress. (a) The vertical distribution of leaf area had a high heritability and showed a marked trend over generations of selection. Leaf area tended to be located at lower positions in the canopy, thereby improving light penetration and distribution in the canopy. This potentially increased the carbon availability to ears, via the amount of light absorbed by the intermediate canopy layer. (b) Neither the horizontal distribution of leaves in the relation to plant rows nor the response of light interception to plant density showed appreciable trends with generations. Hence, among many architectural traits, the vertical distribution of leaf area was the main indirect target of selection.     

Identification of QTLs associated with agronomic performance under nitrogen-deficient conditions using chromosome segment substitution lines of a wild rice relative, <Emphasis Type="Italic">Oryza rufipogon</Emphasis>

Improved root system architecture can enhance agronomic performance by increasing water and nitrogen (N) acquisition efficiency. However, little is known about interaction between root system architecture and agronomic performance under field environments. To gain a better understanding about the genetic basis of these relationships, we evaluated a set of chromosome segment substitution lines (CSSLs) derived from crosses between a tropical japonica rice cultivar ‘Curinga’ and a wild species Oryza rufipogon accession IRGC105491. Root system architectural traits were investigated using the CSSLs at 40 days old seedlings using the root basket method under hydroponic conditions, and agronomic performances were also tested under field conditions with different N treatments. Agronomic performances were computed as the ratio of a trait value under low to high N treatments, including grain yield and biomass yield as nitrogen-deficiency tolerance (NDT) traits. Root architecture and NDT trait QTLs were mapped using 238 SNP marker loci. A total of 13 QTLs for root system architectural, NDT and morpho-physiological traits were identified on chromosomes 1, 3, 4, 5, 7, 8, 9, 10 and 12. Interestingly, a QTL for deeper root number was identified the region of SNP markers between id1012330 and id1021697 on chromosome 1 under hydroponic conditions overlapped with a QTL for NDT trait of relative grain yield (qRGY1). These results suggest that deeper root trait is helpful to maintain grain yield under nitrogen-deficient conditions. The QTL associated root architecture could potentially be used in future rice-breeding efforts to increase agronomic performance under nitrogen-deficient conditions.     

Mapping single-locus and epistatic quantitative trait loci for plant architectural traits in chrysanthemum

Plant architecture is important for chrysanthemum cultivation and breeding. To determine the genetic basis of plant architectural traits in chrysanthemum, a population of 142 F1 plants derived from a cross between the creeping ground-cover chrysanthemum cultivar Yuhualuoying and the erect potted cultivar Aoyunhanxiao was used to detect quantitative trait loci (QTL) associated with plant height, plant width, inter-node length and flower neck length. The broad-sense heritability h _B ² for the four plant architectural traits ranged from 0.33 to 0.83, and transgressive segregation was observed. Single-locus QTL analysis revealed a total of five QTL, accounting for 6.0?C16.1% of the phenotypic variation. Additionally, 11 pairs of epistatic QTL were identified, explaining 3.5?C14.5% of the phenotypic variations. The majority of the interactions detected occurred between background loci. These results indicate that both additive and epistatic effects contribute to phenotypic variation in the plant architecture of chrysanthemum. It is expected that the identified markers associated with the additive QTL and epistatic QTL detected in this study will be of importance in future breeding programs to develop chrysanthemum cultivars exhibiting desirable plant architecture.     

Ontogenetic variations in leaf morphology of the tropical rain forest species Dipterocarpus alatus Roxb. ex G. Don

Under natural conditions ontogenetic development often coincides with changes in environmental factors. When explaining variations in leaf parameters, analyses based solely on environmental factors will lead to significant errors if the plant shows substantial ontogenetic variations in leaf properties. We evaluated intraspecific variations in eight morphological leaf traits of Dipterocarpus alatus over six architectural development stages under two different light conditions. An architectural analysis was conducted to distinguish precisely and objectively developmental stages of D. alatus. Leaves were collected on the most recent complete growth unit on the trunks of trees growing under two different light conditions. Eight leaf morphological traits were measured and calculated using ImageJ on greyscale images of leaf tracings. One-way ANOVA and Tukey tests were used to determine differences in leaf traits during ontogeny. The correlation coefficients were compared to determine whether leaf traits correlated more strongly with ontogenetic stage than with light intensity. D. alatus develops through a progressive transformation of its structure and architecture that adds one new axis category stage after stage. Specific leaf area, blade shape index and leaf dissection index decreased whereas blade area, perimeter, length, width and blade dry weight increased. Leaf traits correlated more strongly with ontogenetic stage than with light intensity. Our results demonstrated that studies on the responses of leaf traits to the environment may need to be corrected for an ontogeny effect. To strengthen this conclusion, future work should evaluate leaf variations during the ontogeny of different axis orders and/or axis categories.     

Effects of species and soil‐nitrogen availability on root system architecture traits – study on a set of weed and crop species

Better managing crop : weed competition in cropping systems while reducing both nitrogen and herbicide inputs is a real challenge that requires a better understanding of crop and weed root architecture in relation to soil‐nitrogen availability. An original approach was used which considered the parameters of a simulation model of root architecture as traits to analyse (a) the interspecific diversity of root system architecture, and (b) its response to soil‐nitrogen availability. Two greenhouse experiments were conducted using three crop and nine weed species grown at two contrasted concentrations of soil‐nitrogen availability. Plant traits were measured to characterise both overall plant growth and root architecture, with a focus on primary root emergence, root elongation and branching. The studied root traits varied among species (from a twofold to a fourfold factor, depending on the trait), validating their use as indicators to analyse the interspecific variability of root architecture. The largest interspecies differences were for two traits: ‘maximal apical root diameter’ and ‘interbranch distance’ (distance between two successive laterals on the same root). Conversely, most of the studied root traits varied little with soil‐nitrogen availability (from no variation to a 1.1‐fold factor, depending on the trait) even though soil‐nitrogen availability varied with a 17‐fold factor and impacted the overall shoot and root biomass. So, the root traits used in this article are stable whatever soil‐nitrogen availability. As they reflect processes underlying root system architecture, this low effect of nitrogen suggests that the rules governing root architecture are little affected by plant nitrogen status and soil‐nitrogen availability. We propose that the determinants of differences in root system architecture between soils with contrasted nitrogen availability mainly originate from differences in the amount of carbon allocated to and within the root system. Characterising each plant species by a combination of root traits gave insights regarding the potential species competitive ability for soil resources in agroecosystems.     

Seasonal plasticity is more important than population variability in effects on white clover architecture and productivity

Background and AimsThe drivers of white clover (Trifolium repens) architecture and productivity are still imperfectly understood. Our aim here was to investigate the impact of genetic background, neighbourhood and season on different architectural traits, clover and total biomass yield, as well as the relationship between those traits and yield.MethodsWe grew eight white clover populations in pure stands and in mixed stands with contrasting mixture partners. Over four consecutive regrowth periods within 1 year, we measured trait sizes and determined clover and total yield amounts.Key ResultsThe size of the architectural traits differed between populations and changed in response to neighbourhood and season. Population did not affect the sign or degree of those changes. Among the tested factors, season was by far the most important driver of white clover architecture, with the seasonal pattern notably differing between architectural traits. Clover and total yield were positively related to the architectural traits leaf area, petiole length, internode length and specific leaf area. Whereas the direction of the relationship was widely unaffected, its magnitude was clearly altered by neighbourhood and season.ConclusionsOur results show that seasonal effects are the key for a deeper understanding of the architecture of white clover individuals and to improve the productivity of white clover communities.     

Using a 3-D virtual sunflower to simulate light capture at organ, plant and plot levels: contribution of organ interception, impact of heliotropism and analysis of genotypic differences

BACKGROUND AND AIMS: Light interception is a critical factor in the production of biomass. The study presented here describes a method used to take account of architectural changes over time in sunflower and to estimate absorbed light at the organ level. METHODS: The amount of photosynthetically active radiation absorbed by a plant is estimated on a daily or hourly basis through precise characterization of the light environment and three-dimensional virtual plants built using AMAP software. Several treatments are performed over four experiments and on two genotypes to test the model, quantify the contribution of different organs to light interception and evaluate the impact of heliotropism. KEY RESULTS: This approach is used to simulate the amount of light absorbed at organ and plant scales from crop emergence to maturity. Blades and capitula were the major contributors to light interception, whereas that by petioles and stem was negligible. Light regimen simulations showed that heliotropism decreased the cumulated light intercepted at the plant scale by close to 2.2% over one day. CONCLUSIONS: The approach is useful in characterizing the light environment of organs and the whole plant, especially for studies on heterogeneous canopies or for quantifying genotypic or environmental impacts on plant architecture, where conventional approaches are ineffective. This model paves the way to analyses of genotype-environment interactions and could help establish new selection criteria based on architectural improvement, enhancing plant light interception.     

Seed production of co-occurring species: Regenerative strategies,plant economic spectrum or architectural constraints?

Although plant clonality is an important reproductive strategy complementing seed reproduction, their interrelationship is seldom studied. We evaluated how plant clonality, together with plant economics spectrum and architectural constraints, affect the generative reproduction characteristics of co-existing grassland species. For this purpose, we collected data on seed number, seed mass and seed yield (seed mass x seed number) per shoot of 56 herbaceous species from temperate grasslands in the White Carpathian Mts. (SE Czech Republic).Clonality had a weaker effect on seed traits than leaf economics and plant architecture. Metamer size showed the strongest relationship to seed number per shoot, while leaf dry matter content and canopy height were the most important factors affecting average seed mass in the studied species. Seed yield was affected by both leaf nitrogen and metamer size but only for plants with long lived shoots (di- and polycyclic). The negative correlation between seed mass and seed number per shoot for our dataset was confirmed.Our study did not support the idea that clonality is the most important factor affecting seed production in grassland species and pointed out complex relationships of coordinated traits in coexisting species.     

Plant trait responses to grazing – a global synthesis

Herbivory by domestic and wild ungulates is a major driver of global vegetation dynamics. However, grazing is not considered in dynamic global vegetation models, or more generally in studies of the effects of environmental change on ecosystems at regional to global scale. An obstacle to this is a lack of empirical tests of several hypotheses linking plant traits with grazing. We, therefore, set out to test whether some widely recognized trait responses to grazing are consistent at the global level. We conducted a meta‐analysis of plant trait responses to grazing, based on 197 studies from all major regions of the world, and using six major conceptual models of trait response to grazing as a framework. Data were available for seven plant traits: life history, canopy height, habit, architecture, growth form (forb, graminoid, herbaceous legume, woody), palatability, and geographic origin. Covariates were precipitation and evolutionary history of herbivory. Overall, grazing favoured annual over perennial plants, short plants over tall plants, prostrate over erect plants, and stoloniferous and rosette architecture over tussock architecture. There was no consistent effect of grazing on growth form. Some response patterns were modified by particular combinations of precipitation and history of herbivory. Climatic and historical contexts are therefore essential for understanding plant trait responses to grazing. Our study identifies some key traits to be incorporated into plant functional classifications for the explicit consideration of grazing into global vegetation models used in global change research. Importantly, our results suggest that plant functional type classifications and response rules need to be specific to regions with different climate and herbivory history.