Intraspecific trait variability shapes leaf trait response to altered fire regimes

Background and AimsUnderstanding impacts of altered disturbance regimes on community structure and function is a key goal for community ecology. Functional traits link species composition to ecosystem functioning. Changes in the distribution of functional traits at community scales in response to disturbance can be driven not only by shifts in species composition, but also by shifts in intraspecific trait values. Understanding the relative importance of these two processes has important implications for predicting community responses to altered disturbance regimes.MethodsWe experimentally manipulated fire return intervals in replicated blocks of a fire-adapted, longleaf pine (Pinus palustris) ecosystem in North Carolina, USA and measured specific leaf area (SLA), leaf dry matter content (LDMC) and compositional responses along a lowland to upland gradient over a 4 year period. Plots were burned between zero and four times. Using a trait-based approach, we simulate hypothetical scenarios which allow species presence, abundance or trait values to vary over time and compare these with observed traits to understand the relative contributions of each of these three processes to observed trait patterns at the study site. We addressed the following questions. (1) How do changes in the fire regime affect community composition, structure and community-level trait responses? (2) Are these effects consistent across a gradient of fire intensity? (3) What are the relative contributions of species turnover, changes in abundance and changes in intraspecific trait values to observed changes in community-weighted mean (CWM) traits in response to altered fire regime?Key ResultsWe found strong evidence that altered fire return interval impacted understorey plant communities. The number of fires a plot experienced significantly affected the magnitude of its compositional change and shifted the ecotone boundary separating shrub-dominated lowland areas from grass-dominated upland areas, with suppression sites (0 burns) experiencing an upland shift and annual burn sites a lowland shift. We found significant effects of burn regimes on the CWM of SLA, and that observed shifts in both SLA and LDMC were driven primarily by intraspecific changes in trait values.ConclusionsIn a fire-adapted ecosystem, increased fire frequency altered community composition and structure of the ecosystem through changes in the position of the shrub line. We also found that plant traits responded directionally to increased fire frequency, with SLA decreasing in response to fire frequency across the environmental gradient. For both SLA and LDMC, nearly all of the observed changes in CWM traits were driven by intraspecific variation.     

Quantitative trait locus analysis of longitudinal quantitative trait data in complex pedigrees

There is currently considerable interest in genetic analysis of quantitative traits such as blood pressure and body mass index. Despite the fact that these traits change throughout life they are commonly analyzed only at a single time point. The genetic basis of such traits can be better understood by collecting and effectively analyzing longitudinal data. Analyses of these data are complicated by the need to incorporate information from complex pedigree structures and genetic markers. We propose conducting longitudinal quantitative trait locus (QTL) analyses on such data sets by using a flexible random regression estimation technique. The relationship between genetic effects at different ages is efficiently modeled using covariance functions (CFs). Using simulated data we show that the change in genetic effects over time can be well characterized using CFs and that including parameters to model the change in effect with age can provide substantial increases in power to detect QTL compared with repeated measure or univariate techniques. The asymptotic distributions of the methods used are investigated and methods for overcoming the practical difficulties in fitting CFs are discussed. The CF-based techniques should allow efficient multivariate analyses of many data sets in human and natural population genetics.     

A nonadaptive dental trait

Compared to other anthropoid females, female cercopithecoids possess hypertrophied honing premolars (P₃) yet lack hypertrophied maxillary canines. In addition, female cercopithecoid maxillary canines are often tip-blunted, the crown rarely extends down to the entire shearing surface on the buccal face of P₃, and honing wear is usually confined to a small fraction of its hypertrophied buccal surface. The likely reason why the female P₃ has an unusually long buccal face is that genes involved in the expression of this morphology are also in males, for which the hypertrophied condition is adaptive—it serves as the honing surface for their hypertrophied canines. The data suggest that the hypertrophied P₃ of females is the correlated and nonadaptive response of an homologous characteristic. The possibility that this occurs in other female anthropoids and in other parts of the C/P complex is discussed, as well as the relevance of this phenomenon for understanding human canine evolution and identifying other traits which may also be examples of correlated response.     

Local trait organization established

Traditionally, ecological theory on community assembly and Applied Vegetation Science are considered distinct. Fischer et al. (this issue of Applied Vegetation Science), however, show neatly how differences in trait composition between resident and colonizing species could be established. By using an environmental context‐specific approach, the analysis bridges the gap between application and more theoretical understanding of vegetation ecology.     

Sensitized polygenic trait analysis

Genetic variation in many biological processes and evolutionary adaptations is caused by polygenes – genes that act in combination to affect a particular trait. Despite the recent identification of several polygenes, many remain to be found, suggesting that new experimental and analytical methods are needed to facilitate their discovery. Here we discuss sensitized polygenetic trait analysis, a method that has emerged recently for simplifying the genetic analysis of polygenic traits. The method uses a known single gene mutation in linkage testing crosses to ‘sensitize’ the analysis. By increasing the frequency of affected individuals in segregating populations, linkages are more readily detected. This method has considerable potential, especially given the increasing variety of mutations that can be used to sensitize the genetic analysis of polygenic traits.     

Intraspecific trait variability matters

Intraspecific trait variability (ITV) plays a central part in various ecological processes, though using mean trait values may be sufficient in some instances. Ecologists need thus to find under which circumstances. Carlucci et al. (2014, this issue) bring new evidence on the importance of ITV for community assembly across a strong gradient. Sampling design may affect ITV quantification across gradients.     

Female preference for trait symmetry in addition to trait size in swordtail fish

Interest in fluctuating asymmetries, random deviations from perfect bilateral symmetry, has spread to studies of sexual selection because of the intriguing idea that females could use the degree of asymmetry of a male trait to assess the genetic quality of potential mates. The evidence that females prefer males with symmetrical sexual signals, however, remains controversial. A problem that applies to most previous studies is that preference for trait size can be misinterpreted as preference for symmetry, even when overall trait size is held constant, if females assess trait size by the largest minimum on one side. If overall trait size is equal between males, the asymmetrical males will have the maximum and minimum trait size, and so preference to mate with symmetrical males could actually reflect a preference to avoid males with the minimum trait on one side. Xiphophorus cortezi females preferred males with symmetrical bar numbers when the minimum number of bars was held constant. The strength of female preference for the symmetrical males was negatively correlated with the strength of preference the same females had for bar number. These results clearly demonstrate that females preferred trait symmetry in addition to trait size.     

Phylogenetic patterns of trait and trait plasticity evolution: Insights from amphibian embryos

Environmental variation favors the evolution of phenotypic plasticity. For many species, we understand the costs and benefits of different phenotypes, but we lack a broad understanding of how plastic traits evolve across large clades. Using identical experiments conducted across North America, we examined prey responses to predator cues. We quantified five life‐history traits and the magnitude of their plasticity for 23 amphibian species/populations (spanning three families and five genera) when exposed to no cues, crushed‐egg cues, and predatory crayfish cues. Embryonic responses varied considerably among species and phylogenetic signal was common among the traits, whereas phylogenetic signal was rare for trait plasticities. Among trait‐evolution models, the Ornstein–Uhlenbeck (OU) model provided the best fit or was essentially tied with Brownian motion. Using the best fitting model, evolutionary rates for plasticities were higher than traits for three life‐history traits and lower for two. These data suggest that the evolution of life‐history traits in amphibian embryos is more constrained by a species’ position in the phylogeny than is the evolution of life history plasticities. The fact that an OU model of trait evolution was often a good fit to patterns of trait variation may indicate adaptive optima for traits and their plasticities.     

Multiple trait multiple interval mapping of quantitative trait loci from inbred line crosses

ABSTRACT: BACKGROUND: Although many experiments have measurements on multiple traits, most studies performed the analysis of mapping of quantitative trait loci (QTL) for each trait separately using single trait analysis. Single trait analysis does not take advantage of possible genetic and environmental correlations between traits. In this paper, we propose a novel statistical method for multiple trait multiple interval mapping (MTMIM) of QTL for inbred line crosses. We also develop a novel score-based method for estimating genome-wide significance level of putative QTL effects suitable for the MTMIM model. The MTMIM method is implemented in the freely available and widely used Windows QTL Cartographer software. RESULTS: Throughout the paper, we provide compelling empirical evidences that: (1) the score-based threshold maintains proper type I error rate and tends to keep false discovery rate within an acceptable level; (2) the MTMIM method can deliver better parameter estimates and power than single trait multiple interval mapping method; (3) an analysis of Drosophila dataset illustrates how the MTMIM method can better extract information from datasets with measurements in multiple traits. CONCLUSIONS: The MTMIM method represents a convenient statistical framework to test hypotheses of pleiotropic QTL versus closely linked nonpleiotropic QTL, QTL by environment interaction, and to estimate the total genotypic variance-covariance matrix between traits and to decompose it in terms of QTL-specific variance-covariance matrices, therefore, providing more details on the genetic architecture of complex traits.     

A bivariate quantitative genetic model for a threshold trait and a survival trait

Many of the functional traits considered in animal breeding can be analyzed as threshold traits or survival traits with examples including disease traits, conformation scores, calving difficulty and longevity. In this paper we derive and implement a bivariate quantitative genetic model for a threshold character and a survival trait that are genetically and environmentally correlated. For the survival trait, we considered the Weibull log-normal animal frailty model. A Bayesian approach using Gibbs sampling was adopted in which model parameters were augmented with unobserved liabilities associated with the threshold trait. The fully conditional posterior distributions associated with parameters of the threshold trait reduced to well known distributions. For the survival trait the two baseline Weibull parameters were updated jointly by a Metropolis-Hastings step. The remaining model parameters with non-normalized fully conditional distributions were updated univariately using adaptive rejection sampling. The Gibbs sampler was tested in a simulation study and illustrated in a joint analysis of calving difficulty and longevity of dairy cattle. The simulation study showed that the estimated marginal posterior distributions covered well and placed high density to the true values used in the simulation of data. The data analysis of calving difficulty and longevity showed that genetic variation exists for both traits. The additive genetic correlation was moderately favorable with marginal posterior mean equal to 0.37 and 95% central posterior credibility interval ranging between 0.11 and 0.61. Therefore, this study suggests that selection for improving one of the two traits will be beneficial for the other trait as well.     

A bivariate quantitative genetic model for a linear Gaussian trait and a survival trait

With the increasing use of survival models in animal breeding to address the genetic aspects of mainly longevity of livestock but also disease traits, the need for methods to infer genetic correlations and to do multivariate evaluations of survival traits and other types of traits has become increasingly important. In this study we derived and implemented a bivariate quantitative genetic model for a linear Gaussian and a survival trait that are genetically and environmentally correlated. For the survival trait, we considered the Weibull log-normal animal frailty model. A Bayesian approach using Gibbs sampling was adopted. Model parameters were inferred from their marginal posterior distributions. The required fully conditional posterior distributions were derived and issues on implementation are discussed. The two Weibull baseline parameters were updated jointly using a Metropolis-Hasting step. The remaining model parameters with non-normalized fully conditional distributions were updated univariately using adaptive rejection sampling. Simulation results showed that the estimated marginal posterior distributions covered well and placed high density to the true parameter values used in the simulation of data. In conclusion, the proposed method allows inferring additive genetic and environmental correlations, and doing multivariate genetic evaluation of a linear Gaussian trait and a survival trait.     

Social personality trait and fitness

Several recent studies have explored various aspects of animal personality and their ecological consequences. However, the processes responsible for the maintenance of personality variability within a population are still largely unknown. We have recently demonstrated that social personality traits exist in the common lizard (Lacerta vivipara) and that the variation in sociability provides an explanation for variable dispersal responses within a given species. However, we need to know the fitness consequences of variation in sociability across environmental contexts in order to better understand the maintenance of such variation. In order to achieve this, we investigated the relationship between sociability and survival, body growth and fecundity, in one-year-old individuals in semi-natural populations with varying density. 'Asocial' and 'social' lizards displayed different fitness outcomes in populations of different densities. Asocial lizards survived better in low-density populations, while social females reproduced better. Spatiotemporal variation in environmental conditions might thus be the process underlying the maintenance of these personality traits within a population. Finally, we also discuss the position of sociability in a more general individual behavioural pattern including boldness, exploration and aggressiveness.     

Quantitative trait loci in Drosophila

Phenotypic variation for quantitative traits results from the simultaneous segregation of alleles at multiple quantitative trait loci. Understanding the genetic architecture of quantitative traits begins with mapping quantitative trait loci to broad genomic regions and ends with the molecular definition of quantitative trait loci alleles. This has been accomplished for some quantitative trait loci in Drosophila. Drosophila quantitative trait loci have sex-, environment- and genotype-specific effects, and are often associated with molecular polymorphisms in non-coding regions of candidate genes. These observations offer valuable lessons to those seeking to understand quantitative traits in other organisms, including humans.     

Mapping quantitative trait loci for binary trait in the F2:3 design

In the analysis of inheritance of quantitative traits with low heritability, an F_2:3 design that genotypes plants in F₂ and phenotypes plants in F_2:3 progeny is often used in plant genetics. Although statistical approaches for mapping quantitative trait loci (QTL) in the F_2:3 design have been well developed, those for binary traits of biological interest and economic importance are seldom addressed. In this study, an attempt was made to map binary trait loci (BTL) in the F_2:3 design. The fundamental idea was: the F₂ plants were genotyped, all phenotypic values of each F_2:3 progeny were measured for binary trait, and these binary trait values and the marker genotype informations were used to detect BTL under the penetrance and liability models. The proposed method was verified by a series of Monte-Carlo simulation experiments. These results showed that maximum likelihood approaches under the penetrance and liability models provide accurate estimates for the effects and the locations of BTL with high statistical power, even under of low heritability. Moreover, the penetrance model is as efficient as the liability model, and the F_2:3 design is more efficient than classical F₂ design, even though only a single progeny is collected from each F_2:3 family. With the maximum likelihood approaches under the penetrance and the liability models developed in this study, we can map binary traits as we can do for quantitative trait in the F_2:3 design.     

Developmental trait evolution in trilobites

We performed a tree-based analysis of trilobite postembryonic development in a sample of 60 species for which quantitative data on segmentation and growth increments between putative successive instars are available, and that spans much of the temporal, phylogenetic, and habitat range of the group. Three developmental traits were investigated: the developmental mode of trunk segmentation, the average per-molt growth rate, and the conformity to a constant per-molt growth rate (Dyar's rule), for which an original metric was devised. Growth rates are within the normal range with respect to other arthropods and show overall conformity to Dyar's rule. Randomization tests indicate statistically significant phylogenetic signal for growth in early juveniles but not in later stages. Among five evolutionary models fit via maximum likelihood, one in which growth rates vary independently among species, analogous to Brownian motion on a star phylogeny, is the best supported in all ontogenetic stages, although a model with a single, stationary peak to which growth rates are attracted also garners nontrivial support. These results are not consistent with unbounded, Brownian-motion-like evolutionary dynamics, but instead suggest the influence of an adaptive zone. Our results suggest that developmental traits in trilobites were relatively labile during evolutionary history.