Assessing among‐lineage variability in phylogenetic imputation of functional trait datasets

Phylogenetic imputation has recently emerged as a potentially powerful tool for predicting missing data in functional traits datasets. As such, understanding the limitations of phylogenetic modelling in predicting trait values is critical if we are to use them in subsequent analyses. Previous studies have focused on the relationship between phylogenetic signal and clade‐level prediction accuracy, yet variability in prediction accuracy among individual tips of phylogenies remains largely unexplored. Here, we used simulations of trait evolution along the branches of phylogenetic trees to show how the accuracy of phylogenetic imputations is influenced by the combined effects of 1) the amount of phylogenetic signal in the traits and 2) the branch length of the tips to be imputed. Specifically, we conducted cross‐validation trials to estimate the variability in prediction accuracy among individual tips on the phylogenies (hereafter ‘tip‐level accuracy’). We found that under a Brownian motion model of evolution (BM, Pagel't λ = 1), tip‐level accuracy rapidly decreased with increasing tip branch‐lengths, and only tips of approximately 10% or less of the total height of the trees showed consistently accurate predictions (i.e. cross‐validation R‐squared >0.75). When phylogenetic signal was weak, the effect of tip branch‐length was reduced, becoming negligible for traits simulated with λ < 0.7, where accuracy was in any case low. Our study shows that variability in prediction accuracy among individual tips of the phylogeny should be considered when evaluating the reliability of phylogenetically imputed trait values. To address this challenge, we describe a Monte Carlo‐based method that allows one to estimate the expected tip‐level accuracy of phylogenetic predictions for continuous traits. Our approach identifies gaps in functional trait datasets for which phylogenetic imputation performs poorly, and will help ecologists to design more efficient trait collection campaigns by focusing resources on lineages whose trait values are more uncertain.     

Phylogenetic structural equation modelling reveals no need for an ‘origin’ of the leaf economics spectrum

The leaf economics spectrum (LES) is a prominent ecophysiological paradigm that describes global variation in leaf physiology across plant ecological strategies using a handful of key traits. Nearly a decade ago, Shipley et al. (2006) used structural equation modelling to explore the causal functional relationships among LES traits that give rise to their strong global covariation. They concluded that an unmeasured trait drives LES covariation, sparking efforts to identify the latent physiological trait underlying the ‘origin’ of the LES. Here, we use newly developed phylogenetic structural equation modelling approaches to reassess these conclusions using both global LES data as well as data collected across scales in the genus Helianthus. For global LES data, accounting for phylogenetic non‐independence indicates that no additional unmeasured traits are required to explain LES covariation. Across datasets in Helianthus, trait relationships are highly variable, indicating that global‐scale models may poorly describe LES covariation at non‐global scales.     

Predicting rates of interspecific interaction from phylogenetic trees

Integrating phylogenetic information can potentially improve our ability to explain species' traits, patterns of community assembly, the network structure of communities, and ecosystem function. In this study, we use mathematical models to explore the ecological and evolutionary factors that modulate the explanatory power of phylogenetic information for communities of species that interact within a single trophic level. We find that phylogenetic relationships among species can influence trait evolution and rates of interaction among species, but only under particular models of species interaction. For example, when interactions within communities are mediated by a mechanism of phenotype matching, phylogenetic trees make specific predictions about trait evolution and rates of interaction. In contrast, if interactions within a community depend on a mechanism of phenotype differences, phylogenetic information has little, if any, predictive power for trait evolution and interaction rate. Together, these results make clear and testable predictions for when and how evolutionary history is expected to influence contemporary rates of species interaction.     

Rapid maximum likelihood ancestral state reconstruction of continuous characters: A rerooting‐free algorithm

Ancestral state reconstruction is a method used to study the evolutionary trajectories of quantitative characters on phylogenies. Although efficient methods for univariate ancestral state reconstruction under a Brownian motion model have been described for at least 25 years, to date no generalization has been described to allow more complex evolutionary models, such as multivariate trait evolution, non‐Brownian models, missing data, and within‐species variation. Furthermore, even for simple univariate Brownian motion models, most phylogenetic comparative R packages compute ancestral states via inefficient tree rerooting and full tree traversals at each tree node, making ancestral state reconstruction extremely time‐consuming for large phylogenies. Here, a computationally efficient method for fast maximum likelihood ancestral state reconstruction of continuous characters is described. The algorithm has linear complexity relative to the number of species and outperforms the fastest existing R implementations by several orders of magnitude. The described algorithm is capable of performing ancestral state reconstruction on a 1,000,000‐species phylogeny in fewer than 2 s using a standard laptop, whereas the next fastest R implementation would take several days to complete. The method is generalizable to more complex evolutionary models, such as phylogenetic regression, within‐species variation, non‐Brownian evolutionary models, and multivariate trait evolution. Because this method enables fast repeated computations on phylogenies of virtually any size, implementation of the described algorithm can drastically alleviate the computational burden of many otherwise prohibitively time‐consuming tasks requiring reconstruction of ancestral states, such as phylogenetic imputation of missing data, bootstrapping procedures, Expectation‐Maximization algorithms, and Bayesian estimation. The described ancestral state reconstruction algorithm is implemented in the Rphylopars functions anc.recon and phylopars.     

Combining spatial and phylogenetic eigenvector filtering in trait analysis

Aim To analyse the effects of simultaneously using spatial and phylogenetic information in removing spatial autocorrelation of residuals within a multiple regression framework of trait analysis. Location Switzerland, Europe. Methods We used an eigenvector filtering approach to analyse the relationship between spatial distribution of a trait (flowering phenology) and environmental covariates in a multiple regression framework. Eigenvector filters were calculated from ordinations of distance matrices. Distance matrices were either based on pure spatial information, pure phylogenetic information or spatially structured phylogenetic information. In the multiple regression, those filters were selected which best reduced Moran's I coefficient of residual autocorrelation. These were added as covariates to a regression model of environmental variables explaining trait distribution. Results The simultaneous provision of spatial and phylogenetic information was effectively able to remove residual autocorrelation in the analysis. Adding phylogenetic information was superior to adding purely spatial information. Applying filters showed altered results, i.e. different environmental predictors were seen to be significant. Nevertheless, mean annual temperature and calcareous substrate remained the most important predictors to explain the onset of flowering in Switzerland; namely, the warmer the temperature and the more calcareous the substrate, the earlier the onset of flowering. A sequential approach, i.e. first removing the phylogenetic signal from traits and then applying a spatial analysis, did not provide more information or yield less autocorrelation than simple or purely spatial models. Main conclusions The combination of spatial and spatio‐phylogenetic information is recommended in the analysis of trait distribution data in a multiple regression framework. This approach is an efficient means for reducing residual autocorrelation and for testing the robustness of results, including the indication of incomplete parameterizations, and can facilitate ecological interpretation.     

Scale‐dependence of phylogenetic signal in ecological traits of ectoparasites

The non‐independence of traits among closely related species is a well‐documented phenomenon underpinning modern methods for comparative analyses or prediction of trait values in new species. Surprisingly such studies have mainly focused on life‐history or morphological traits of free‐living organisms, ignoring ecological attributes of parasite species in spite of the fact that they are critical for conservation and human health. We tested for a phylogenetic signal acting on two ecological traits, abundance and host specificity, using data for 218 flea species parasitic on small mammals in 19 regions of the Palaearctic and Nearctic, and a phylogenetic tree for these species. We tested for the presence of a phylogenetic signal at both regional and continental scales using three measures (Abouheif/Moran's I, Pagel's λ, and Blomberg et al.'s K). Our results show 1) a consistent positive phylogenetic signal for flea abundance, but only a weaker and erratic signal for host specificity, and 2) a clear dependence on scale, with the signals being stronger at the continental scale and relatively weaker or inconsistent at the regional scale. Whenever values of Blomberg et al.'s K were found significant, they were <1 suggesting that the effects of phylogeny on the evolution of abundance and host specificity in fleas are weaker than expected from a Brownian motion model. The most striking finding is that, within a continental fauna, closely‐related flea species are characterized by similar levels of abundance, though this pattern is weaker within local assemblages, possibly eroded by local biotic or abiotic conditions. We discuss the link between history (represented by phylogeny) and pattern of variation among species in morphological and ecological traits, and use comparisons between the Palaearctic and Nearctic to infer a role of historical events in the probability of detecting phylogenetic signals.     

Discriminating the effects of phylogenetic hypothesis,tree resolution and clade age estimates on phylogenetic signal measurements

Understanding how species traits evolved over time is the central question to comprehend assembly rules that govern the phylogenetic structure of communities. The measurement of phylogenetic signal (PS) in ecologically relevant traits is a first step to understand phylogenetically structured community patterns. The different methods available to estimate PS make it difficult to choose which is most appropriate. Furthermore, alternative phylogenetic tree hypotheses, node resolution and clade age estimates might influence PS measurements. In this study, we evaluated to what extent these parameters affect different methods of PS analysis, and discuss advantages and disadvantages when selecting which method to use. We measured fruit/seed traits and flowering/fruiting phenology of endozoochoric species occurring in Southern Brazilian Araucaria forests and evaluated their PS using Mantel regressions, phylogenetic eigenvector regressions (PVR) and K statistic. Mantel regressions always gave less significant results compared to PVR and K statistic in all combinations of phylogenetic trees constructed. Moreover, a better phylogenetic resolution affected PS, independently of the method used to estimate it. Morphological seed traits tended to show higher PS than diaspores traits, while PS in flowering/fruiting phenology depended mostly on the method used to estimate it. This study demonstrates that different PS estimates are obtained depending on the chosen method and the phylogenetic tree resolution. This finding has implications for inferences on phylogenetic niche conservatism or ecological processes determining phylogenetic community structure.     

A phylogenetic analysis of macroevolutionary patterns in fermentative yeasts

When novel sources of ecological opportunity are available, physiological innovations can trigger adaptive radiations. This could be the case of yeasts (Saccharomycotina), in which an evolutionary novelty is represented by the capacity to exploit simple sugars from fruits (fermentation). During adaptive radiations, diversification and morphological evolution are predicted to slow‐down after early bursts of diversification. Here, we performed the first comparative phylogenetic analysis in yeasts, testing the “early burst” prediction on species diversification and also on traits of putative ecological relevance (cell‐size and fermentation versatility). We found that speciation rates are constant during the time‐range we considered (ca., 150 millions of years). Phylogenetic signal of both traits was significant (but lower for cell‐size), suggesting that lineages resemble each other in trait‐values. Disparity analysis suggested accelerated evolution (diversification in trait values above Brownian Motion expectations) in cell‐size. We also found a significant phylogenetic regression between cell‐size and fermentation versatility (R² = 0.10), which suggests correlated evolution between both traits. Overall, our results do not support the early burst prediction both in species and traits, but suggest a number of interesting evolutionary patterns, that warrant further exploration. For instance, we show that the Whole Genomic Duplication that affected a whole clade of yeasts, does not seems to have a statistically detectable phenotypic effect at our level of analysis. In this regard, further studies of fermentation under common‐garden conditions combined with comparative analyses are warranted.     

COMPARATIVE METHODS AT THE SPECIES LEVEL: GEOGRAPHIC VARIATION IN MORPHOLOGY AND GROUP SIZE IN GREY-CROWNED BABBLERS (POMATOSTOMUS TEMPORALIS)

We show that a new comparative method that sheds light on evolutionary trends among species may also illuminate trends within species. This finding comes from a phylogenetic autocorrelation analysis of morphological traits among individuals sampled from ten populations of a cooperatively breeding songbird, the Grey-crowned Babbler (Pomatostomus temporalis). Highly variable mitochondrial DNA (mtDNA) sequences from both the eastern (Pomatostomus temporalis temporalis) and western (Pomatostomus temporalis rubeculus) lineages were used to define genetic distances among 120 individuals and to estimate correlations among individuals in wing length, tarsus length, and body weight via an intraspecific weighting matrix. The autoregressive model effectively removed intraspecific correlations for all three morphological variables, and the proportion of the total phenotypic variance due to genealogical relationships varied from 0.68 (weight) to 0.23 (tarsus). The analysis revealed correlations among the specific components of traits, in which none were previously detected (type-I error) and diminished correlations that appeared strong when phylogeny was ignored. Group size was the only trait for which the autoregressive model failed to remove intraspecific correlations, a result likely due to the plasticity, convergence, and clinal variation in this trait in both the eastern and western lineages. The autocorrelation analysis weakened significant negative correlations between group size and total values for wing length and body weight, but the interpretation of this result depends on the adaptive significance ascribed to the “phylogenetic component” of trait values removed by the analysis. Comparative methods employing distance matrices are one useful way of summarizing the pattern of nonhierarchical relationships among conspecific individuals (“tokogenetic” relationships, sensu Hennig).     

Intraspecific trait variation influences physiological performance and fitness in the South Africa shrub genus Protea (Proteaceae)

Background and AimsGlobal plant trait datasets commonly identify trait relationships that are interpreted to reflect fundamental trade-offs associated with plant strategies, but often these trait relationships are not identified when evaluating them at smaller taxonomic and spatial scales. In this study we evaluate trait relationships measured on individual plants for five widespread Protea species in South Africa to determine whether broad-scale patterns of structural trait (e.g. leaf area) and physiological trait (e.g. photosynthetic rates) relationships can be detected within natural populations, and if these traits are themselves related to plant fitness.MethodsWe evaluated the variance structure (i.e. the proportional intraspecific trait variation relative to among-species variation) for nine structural traits and six physiological traits measured in wild populations. We used a multivariate path model to evaluate the relationships between structural traits and physiological traits, and the relationship between these traits and plant size and reproductive effort.Key ResultsWhile intraspecific trait variation is relatively low for structural traits, it accounts for between 50 and 100 % of the variation in physiological traits. Furthermore, we identified few trait associations between any one structural trait and physiological trait, but multivariate regressions revealed clear associations between combinations of structural traits and physiological performance (R² = 0.37–0.64), and almost all traits had detectable associations with plant fitness.ConclusionsIntraspecific variation in structural traits leads to predictable differences in individual-level physiological performance in a multivariate framework, even though the relationship of any particular structural trait to physiological performance may be weak or undetectable. Furthermore, intraspecific variation in both structural and physiological traits leads to differences in plant size and fitness. These results demonstrate the importance of considering measurements of multivariate phenotypes on individual plants when evaluating trait relationships and how trait variation influences predictions of ecological and evolutionary outcomes.     

Regional vs local drivers of phylogenetic and species diversity in stream fish communities

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Phenotypic traits evolution and morphological traits associated with echolocation calls in cryptic horseshoe bats (Rhinolophidae)

Bats provide an excellent casestudy for studying evolution due to their remarkable flight and echolocation capabilities. In this study, we sought to understand the phenotypic evolution of key traits in Rhinolophidae (horseshoe bats) using phylogenetic comparative methods. We aimed to test the phylogenetic signals of traits, and evaluated the best-fit evolutionary models given the data for each trait considering different traits may evolve under different models (i.e., Brownian Motion [BM], Ornstein-Uhlenbeck [OU], and Early Burst [EB]) and reconstruct ancestral character states. We examined how phenotypic characters are associated with echolocation calls and minimum detectable prey size. We measured 34 traits of 10 Asian rhinolophids species (187 individuals). We found that the majority of traits showed a high phylogenetic signal based on Blomberg′s K and Pagel′s λ, but each trait may evolve under different evolutionary models. Sella traits were shown to evolve under stabilizing selection based on OU models, indicating sella traits have the tendency to move forward along the branches toward some medial value in equilibrium. Our findings highlight the importance of sella characters in association with echolocation call emissions in Rhinolophidae, as calls are important for spatial cognition and also influence dietary preferences. Minimum detectable prey size in Rhinolophidae was associated with call frequency, bandwidth, call duration, wingspan, and wing surface area. Ultimately, understanding trait evolution requires sensitivity due to the differential selective pressures which may apply to different characteristics.     

Phylogenetic signal in tooth wear dietary niche proxies

In the absence of independent observational data, ecologists and paleoecologists use proxies for the Eltonian niches of species (i.e., the resource or dietary axes of the niche). Some dietary proxies exploit the fact that mammalian teeth experience wear during mastication, due to both tooth‐on‐tooth and food‐on‐tooth interactions. The distribution and types of wear detectible at micro‐ and macroscales are highly correlated with the resource preferences of individuals and, in turn, species. Because methods that quantify the distribution of tooth wear (i.e., analytical tooth wear methods) do so by direct observation of facets and marks on the teeth of individual animals, dietary inferences derived from them are thought to be independent of the clade to which individuals belong. However, an assumption of clade or phylogenetic independence when making species‐level dietary inferences may be misleading if phylogenetic niche conservatism is widespread among mammals. Herein, we test for phylogenetic signal in data from numerous analytical tooth wear studies, incorporating macrowear (i.e., mesowear) and microwear (i.e., low‐magnification microwear and dental microwear texture analysis). Using two measures of phylogenetic signal, heritability (H²) and Pagel's λ, we find that analytical tooth wear data are not independent of phylogeny and failing to account for such nonindependence leads to overestimation of discriminability among species with different dietary preferences. We suggest that morphological traits inherited from ancestral clades (e.g., tooth shape) influence the ways in which the teeth wear during mastication and constrain the foods individuals of a species can effectively exploit. We do not suggest that tooth wear is simply phylogeny in disguise; the tooth wear of individuals and species likely varies within some range that is set by morphological constraints. We therefore recommend the use of phylogenetic comparative methods in studies of mammalian tooth wear, whenever possible.     

Bias in phylogenetic measurements of extinction and a case study of end‐Permian tetrapods

Extinction risk in the modern world and extinction in the geological past are often linked to aspects of life history or other facets of biology that are phylogenetically conserved within clades. These links can result in phylogenetic clustering of extinction, a measurement comparable across different clades and time periods that can be made in the absence of detailed trait data. This phylogenetic approach is particularly suitable for vertebrate taxa, which often have fragmentary fossil records, but robust, cladistically‐inferred trees. Here we use simulations to investigate the adequacy of measures of phylogenetic clustering of extinction when applied to phylogenies of fossil taxa while assuming a Brownian motion model of trait evolution. We characterize expected biases under a variety of evolutionary and analytical scenarios. Recovery of accurate estimates of extinction clustering depends heavily on the sampling rate, and results can be highly variable across topologies. Clustering is often underestimated at low sampling rates, whereas at high sampling rates it is always overestimated. Sampling rate dictates which cladogram timescaling method will produce the most accurate results, as well as how much of a bias ancestor–descendant pairs introduce. We illustrate this approach by applying two phylogenetic metrics of extinction clustering (Fritz and Purvis's D and Moran's I) to three tetrapod clades across an interval including the Permo‐Triassic mass extinction event. These groups consistently show phylogenetic clustering of extinction, unrelated to change in other quantitative metrics such as taxonomic diversity or extinction intensity.     

不同纬度植物群落系统发育与功能性状结构研究

研究植物群落系统发育和功能性状结构有助于了解植物多样性维持机制及物种间的亲缘关系。甘肃省地理环境复杂,显著而多变的气候梯度形成了区域植被和环境差异,丰富了栖息地类型,具有显著的纵向连通性和纬度隔离性,以甘肃省典型纬度梯度植物群落为研究对象,通过对其进行群落学调查和功能性状测定,计算净亲缘关系指数(Net relatedness index, NRI)和平均成对性状距离(Mean pairwise trait distance, PW)来分析植物群落系统发育结构和功能性状格局对不同纬度的响应。结果表明：(1) Shannon-Weiner多样性指数,物种丰富度,谱系α多样性指数表现出随纬度增加而显著降低的变化趋势(P<0.05),Pielou均匀度指数随纬度的升高没有显著的变化趋势;(2)系统发育结构在高、低纬度上趋于发散状态(NRI<0),在中纬度上又表现出聚集(NRI>0)的谱系结构,表明种间竞争作用减弱,环境过滤作用逐渐增强,随纬度继续升高相似性限制作用在物种聚集过程中占优势;而群落的功能性状结构随着纬度增加表现出与谱系结构相反的状态,因此植物群落的系统发育和功能...     

Joint effect of phylogenetic relatedness and trait selection on the elevational distribution of Rhododendron species

Congeneric species may coexist at fine spatial scales through niche differentiation, however, the magnitude to which the effects of functional traits and phylogenetic relatedness contribute to their distribution along elevational gradients remains understudied. To test the hypothesis that trait and elevational range overlap can affect local speciesʼ coexistence, we first compared phylogenetic relatedness and trait (including morphological traits and leaf elements) divergence among closely related species of Rhododendron L. on Yulong Mountain, China. We then assessed relationships between the overlap of multiple functional traits and the degree of elevational range overlap among species pairs in a phylogenetic context. We found that phylogeny was a good predictor for most functional traits, where closely related species showed higher trait similarity and occupied different elevational niches at our study site. Species pairs of R. subgen. Hymenanthes (Blume) K. Koch showed low elevational range overlap and some species pairs of R. subgen. Rhododendron showed obvious niche differentiation. Trait divergence is greater for species in R. subgen. Rhododendron, and it plays an important role between species pairs with low elevational range overlap. Trait convergent selection takes place between co-occurring closely related species that have high elevational range overlap, which share more functional trait space due to environmental filtering or ecological adaptation in more extreme habitats. Our results highlight the importance of evolutionary history and trait selection for species coexistence at fine ecological scales along environmental gradients.     

Ecological and phylogenetic determinants of life-history patterns among ten loricariid species

We analysed the influence of ecological factors, phylogenetic history and trade-offs between traits on the life-history variation among 10 loricariid species of the middle Paraná River. We measured eight life-history variables and classified the life-history strategies following the equilibrium–periodic–opportunistic (EPO) model. Principal-component analysis of life-history traits segregated species along a gradient from small opportunistic (low fecundity, low parental investment) to large equilibrium (low-medium fecundity, high parental investment) species. A clear periodic strategist was absent in the analysed assemblage. Variation partitioning by canonical phylogenetic ordination analysis showed both a component of variation uniquely explained by phylogenetic history (PH; 32.2%) and a component shared between PH and ecological factors (EF; 37%). The EPO model is a useful tool for predicting correlations among life-history traits and understanding potential demographic responses of species to environmental variation. Life-history patterns observed throughout Loricariidae suggests that this family has diversified across all three endpoint strategies of the EPO model. Our study indicates that evolutionary lineage affiliation at the level of subfamily can be a strong predictor of the life-history strategy used by each species.     

The importance of retaining a phylogenetic perspective in traits‐based community analyses

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Disentangling niche and neutral influences on community assembly: assessing the performance of community phylogenetic structure tests

Patterns of phylogenetic relatedness within communities have been widely used to infer the importance of different ecological and evolutionary processes during community assembly, but little is known about the relative ability of community phylogenetics methods and null models to detect the signature of processes such as dispersal, competition and filtering under different models of trait evolution. Using a metacommunity simulation incorporating quantitative models of trait evolution and community assembly, I assessed the performance of different tests that have been used to measure community phylogenetic structure. All tests were sensitive to the relative phylogenetic signal in species metacommunity abundances and traits; methods that were most sensitive to the effects of niche-based processes on community structure were also more likely to find non-random patterns of community phylogenetic structure under dispersal assembly. When used with a null model that maintained species occurrence frequency in random communities, several metrics could detect niche-based assembly when there was strong phylogenetic signal in species traits, when multiple traits were involved in community assembly, and in the presence of environmental heterogeneity. Interpretations of the causes of community phylogenetic structure should be modified to account for the influence of dispersal.     

Seed viability in Bursera: The relative contribution of environmental variation and phylogenetic relatedness

Seed viability is a crucial factor affecting the regeneration potential of seeds, but there is little information on how this trait varies across habitats, populations, species, and higher taxonomic units, as well as on the relative contributions of evolutionary history and environmental factors to this trait. Here we evaluate the relative contributions of climatic variability and phylogenetic history to seed viability in a group of species of Bursera that belong to two distinct lineages (sections Bursera and Bullockia). We analyzed 39 seed lots from 11 species, comprising several populations and 2 years, and estimated embryo presence and viability in each lot. We examined spatial and temporal variation in viability and analyzed the relationship between this trait and water availability using regression models; the amount of phylogenetic signal in seed viability was also estimated. Mean seed viability was consistently low in species of section Bursera (mean 29.7%) and substantially higher in species of section Bullockia (mean 79.6%). A high proportion of unviable seeds were embryoless. Spatial and temporal variation in seed viability was significant but usually low among populations and species. The relationship between water availability and seed viability was not significant, but the amount of phylogenetic signal in seed viability was high and significant (λ = 0.74). There is a clear difference in seed viability among the two sections of Bursera. During the split of the two sections in the middle Eocene, the reorganization of the genome may have involved changes in fruit morphology associated with differences in parthenocarpy among them.