Spatial autocorrelation,phylogenetic constraints,and the causes of sexual dimorphism in primates

Cheverud et al. (1985) apply the important and relatively new methodology of spatial autocorrelation to the quantification of phylogenetic constraints on adaptation and illustrate the use of these methods in an allometric study of sexual dimorphism in body size among extant nonhuman primates. Though of potentially broad applicability, the technique was completely overlooked in a recent review of methods to control for the effects of common descent in comparative studies (Bell, 1989). Their approach therefore deserves a wider recognition. However, their specific conclusion, that phytogeny is the primary determinant of patterns of sexual dimorphism among primates, has been uncritically accepted. We present four main methodological problems with their approach that should temper the interpretation of their analysis: biased phylogenetic relatedness scores, biased sample selection, size dependence in sex dimorphism measurement, and deficiencies in selection of a structural path model. We conclude that, even in terms of the analysis by Cheverud and co-workers (1985), phylogenetic inertia is not the primary reason for body size dimorphism.     

The best of both worlds: Phylogenetic eigenvector regression and mapping

Eigenfunction analyses have been widely used to model patterns of autocorrelation in time, space and phylogeny. In a phylogenetic context, Diniz-Filho et al. (1998) proposed what they called Phylogenetic Eigenvector Regression (PVR), in which pairwise phylogenetic distances among species are submitted to a Principal Coordinate Analysis, and eigenvectors are then used as explanatory variables in regression, correlation or ANOVAs. More recently, a new approach called Phylogenetic Eigenvector Mapping (PEM) was proposed, with the main advantage of explicitly incorporating a model-based warping in phylogenetic distance in which an Ornstein-Uhlenbeck (O-U) process is fitted to data before eigenvector extraction. Here we compared PVR and PEM in respect to estimated phylogenetic signal, correlated evolution under alternative evolutionary models and phylogenetic imputation, using simulated data. Despite similarity between the two approaches, PEM has a slightly higher prediction ability and is more general than the original PVR. Even so, in a conceptual sense, PEM may provide a technique in the best of both worlds, combining the flexibility of data-driven and empirical eigenfunction analyses and the sounding insights provided by evolutionary models well known in comparative analyses.     

Scaling of Sexual Dimorphism in Body Mass: A Phylogenetic Analysis of Rensch's Rule in Primates

We examined the relationship between body mass dimorphism, measured as the natural logarithm of the male/female ratio, and body mass, defined as ln (female mass), with interspecific allometry, phylogenetically independent contrasts, and phylogenetic autocorrelation in 105 primate species. We repeated the analyses for Strepsirhini (N = 23), Haplorhini (N = 82), Platyrrhinii (N = 32), and Catarrhini (N = 47). With independent contrasts, there is statistically significant (p < .05) positive allometry in Primates in general, Haplorhini, and Catarrhini, but not in Strepsirhini or Platyrrhini. The steepest slope (0.134) is for Catarrhini. Results differed when we conducted analyses with traditional interspecific allometry. For example, not only was the Catarrhini slope not statistically significant but also the magnitude of the slope was shallower than that of all other groups, except Strepsirhini. The results indicate that phylogenetic effects influence the scaling of sexual size dimorphism, and that the statistical method used has a large impact on the interpretation of this biological relationship. We discuss issues involved in applying these statistical methods in detail.     

Phylogenetic,spatial and environmental components of extinction risk in carnivores

Aim Extinction risk is non‐randomly distributed across phylogeny and space and is influenced by environmental conditions. We quantified the relative contribution of these factors to extinction risk to unveil the underlying macroecological processes and derive predictive models. Location Global. Methods Based on the IUCN global assessments, we divided 192 carnivore species into two dichotomous classes representing different levels of extinction risk. We used spatial proximity, phylogenetic relationship and environmental variables together with phylogenetic eigenvector regression and spatial eigenvector filters to model and predict threat status. Results Our full models explained between 57% and 96% of the variance in extinction risk. Phylogeny and spatial proximity roughly explained between 21% and 70% of the total variation in all analyses, while the explanatory power of environmental conditions was relatively weaker (up to 15%). Phylogeny and spatial proximity contributed equally to the explained variance in the lower threat level, while spatial proximity was the most important factor in the models of the higher threat level. Prediction of threat status achieved 97% correct assignments. Main conclusions Our approach differs fundamentally from current studies of extinction risk because it does not necessarily rely on life‐history information. We clearly show that instead of treating phylogenetic inertia and spatial signal as statistical nuisances, space and phylogeny should be viewed as very useful in explaining a wide range of phenomena in comparative studies.     

Spatial genetic structure of northern pike (Esox lucius) in the Baltic Sea

The genetic relationships among 337 northern pike (Esox lucius) collected from the coastal zone of the central Baltic region and the Finnish islands of Aland were analysed using five microsatellite loci. Spatial structure was delineated using both traditional F-statistics and individually based approaches including spatial autocorrelation analysis. Our results indicate that the observed genotypic distribution is incompatible with that of a single, panmictic population. Isolation by distance appears important for shaping the genetic structure of pike in this region resulting in a largely continuous genetic change over the study area. Spatial autocorrelation analysis (Moran's I) of individual pairwise genotypic data show significant positive genetic correlation among pike collected within geographical distances of less than c. 100-150 km (genetic patch size). We suggest that the genetic patch size may be used as a preliminary basis for identifying management units for pike in the Baltic Sea.     

Hunting to extinction: biology and regional economy influence extinction risk and the impact of hunting in artiodactyls

Half of all artiodactyls (even-toed hoofed mammals) are threatened with extinction, around double the mammalian average. Here, using a complete species-level phylogeny, we construct a multivariate model to assess for the first time which intrinsic (biological) and extrinsic (anthropogenic and environmental) factors influence variation in extinction risk in artiodactyls. Globally artiodactyls at greatest risk live in economically less developed areas, have older weaning ages and smaller geographical ranges. Our findings suggest that identifying predictors of threat is complicated by interactions between both biological and anthropogenic factors, resulting in differential responses to threatening processes. Artiodactyl species that experience unregulated hunting live in significantly less economically developed areas than those that are not hunted; however, hunted species are more susceptible to extinction if they have slower reproductive rates (older weaning ages). In contrast, risk in non-hunted artiodactyls is unrelated to reproductive rate and more closely associated with the economic development of the region in which they live.     

Phylogenetic autocorrelation and heritability of geographic range size,shape and position of fiddler crabs,genus Uca (Crustacea,Decapoda)

The aim of this study was to evaluate the levels of phylogenetic heritability of the geographical range size, shape and position for 88 species of fiddler crabs of the world, using phylogenetic comparative methods and simulation procedures to evaluate their fit to the neutral model of Brownian motion. The geographical range maps were compiled from literature, and range size was based on the entire length of coastline occupied by each species, and the position of each range was calculated as its latitudinal and longitudinal midpoint. The range shape of each species was based in fractal dimension (box‐counting technique). The evolutionary patterns in the geographical range metrics were explored by phylogenetic correlograms using Moran’s I autocorrelation coefficients, autoregressive method (ARM) and phylogenetic eigenvector regression (PVR). The correlograms were compared with those obtained by simulations of Brownian motion processes across phylogenies. The distribution of geographical range size of fiddler crabs is right‐skewed and weak phylogenetic autocorrelation was observed. On the other hand, there was a strong phylogenetic pattern in the position of the range (mainly along longitudinal axis). Indeed, the ARM and PVR evidenced, respectively, that ca. 86% and 91% of the longitudinal midpoint could be explained by phylogenetic relationships among the species. The strong longitudinal phylogenetic pattern may be due to vicariant allopatric speciation and geographically structured cladogenesis in the group. The traits analysed (geographical range size and position) did not follow a Brownian motion process, thus suggesting that both adaptive ecological and evolutionary processes must be invoked to explain their dynamics, not following a simple neutral inheritance in the fiddler‐crab evolution.     

Phylogenetic eigenvectors and nonstationarity in the evolution of theropod dinosaur skulls

Despite the long‐standing interest in nonstationarity of both phenotypic evolution and diversification rates, only recently have methods been developed to study this property. Here, we propose a methodological expansion of the phylogenetic signal‐representation (PSR) curve based on phylogenetic eigenvectors to test for nonstationarity. The PSR curve is built by plotting the coefficients of determination R² from phylogenetic eigenvector regression (PVR) models increasing the number of phylogenetic eigenvectors against the accumulated eigenvalues. The PSR curve is linear under a stationary model of trait evolution (i.e. the Brownian motion model). Here we describe the distribution of shifts in the models R² and used a randomization procedure to compare observed and simulated shifts along the PSR curve, which allowed detecting nonstationarity in trait evolution. As an applied example, we show that the main evolutionary pattern of variation in the theropod dinosaur skull was nonstationary, with a significant shift in evolutionary rates in derived oviraptorosaurs, an aberrant group of mostly toothless, crested, birdlike theropods. This result is also supported by a recently proposed Bayesian‐based method (AUTEUR). A significant deviation between Ceratosaurus and Limusaurus terminal branches was also detected. We purport that our new approach is a valuable tool for evolutionary biologists, owing to its simplicity, flexibility and comprehensiveness.     

Age–area scaling of extinction debt within isolated terrestrial vertebrate assemblages

A new model of delayed species loss (extinction debt) within isolated communities is applied to a large data set of terrestrial vertebrate assemblages (n = 188) occupying habitat fragments or islands varying greatly in size and age. The model encapsulates previous approaches based on diversity‐dependent (DD) extinction rates while allowing for a more flexible treatment of temporal dynamics. Three important results emerge. First, species loss rate slows down with the age of the isolate, a strong and general pattern largely unnoticed so far. Secondly, while being good candidates in the light of previous works, DD models fail to account for this pattern, a result that necessitates a search for other mechanisms. Thirdly, a simple diversity‐independent model based on area (converted into population size) and age explains 97% of the variability in species loss rate and appears to be a promising predictive tool to handle extinction debt following habitat loss.     

Phylogenetic comparative approaches for studying niche conservatism

Analyses of phylogenetic niche conservatism (PNC) are becoming increasingly common. However, each analysis makes subtly different assumptions about the evolutionary mechanism that generates patterns of niche conservatism. To understand PNC, analyses should be conducted with reference to a clear underlying model, using appropriate methods. Here, we outline five macroevolutionary models that may underlie patterns of PNC (drift, niche retention, phylogenetic inertia, niche filling/shifting and evolutionary rates) and link these to published phylogenetic comparative methods. For each model, we give recent examples from the literature and suggest how the methods can be practically applied. We hope that this will help clarify the niche conservatism literature and encourage people to think about the evolutionary models underlying niche conservatism in their study group.     

Understanding of the impact of chemicals on amphibians: a meta-analytic review

Many studies have assessed the impact of different pollutants on amphibians across a variety of experimental venues (laboratory, mesocosm, and enclosure conditions). Past reviews, using vote-counting methods, have described pollution as one of the major threats faced by amphibians. However, vote-counting methods lack strong statistical power, do not permit one to determine the magnitudes of effects, and do not compare responses among predefined groups. To address these challenges, we conducted a meta-analysis of experimental studies that measured the effects of different chemical pollutants (nitrogenous and phosphorous compounds, pesticides, road deicers, heavy metals, and other wastewater contaminants) at environmentally relevant concentrations on amphibian survival, mass, time to hatching, time to metamorphosis, and frequency of abnormalities. The overall effect size of pollutant exposure was a medium decrease in amphibian survival and mass and a large increase in abnormality frequency. This translates to a 14.3% decrease in survival, a 7.5% decrease in mass, and a 535% increase in abnormality frequency across all studies. In contrast, we found no overall effect of pollutants on time to hatching and time to metamorphosis. We also found that effect sizes differed among experimental venues and among types of pollutants, but we only detected weak differences among amphibian families. These results suggest that variation in sensitivity to contaminants is generally independent of phylogeny. Some publication bias (i.e., selective reporting) was detected, but only for mass and the interaction effect size among stressors. We conclude that the overall impact of pollution on amphibians is moderately to largely negative. This implies that pollutants at environmentally relevant concentrations pose an important threat to amphibians and may play a role in their present global decline.     

Phylogenetic ANOVA: Group‐clade aggregation,biological challenges,and a refined permutation procedure

Phylogenetic regression is frequently used in macroevolutionary studies, and its statistical properties have been thoroughly investigated. By contrast, phylogenetic ANOVA has received relatively less attention, and the conditions leading to incorrect statistical and biological inferences when comparing multivariate phenotypes among groups remain underexplored. Here, we propose a refined method of randomizing residuals in a permutation procedure (RRPP) for evaluating phenotypic differences among groups while conditioning the data on the phylogeny. We show that RRPP displays appropriate statistical properties for both phylogenetic ANOVA and regression models, and for univariate and multivariate datasets. For ANOVA, we find that RRPP exhibits higher statistical power than methods utilizing phylogenetic simulation. Additionally, we investigate how group dispersion across the phylogeny affects inferences, and reveal that highly aggregated groups generate strong and significant correlations with the phylogeny, which reduce statistical power and subsequently affect biological interpretations. We discuss the broader implications of this phylogenetic group aggregation, and its relation to challenges encountered with other comparative methods where one or a few transitions in discrete traits are observed on the phylogeny. Finally, we recommend that phylogenetic comparative studies of continuous trait data use RRPP for assessing the significance of indicator variables as sources of trait variation.     

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).     

The monophyletic origin of delayed implantation in carnivores and its implications

Abstract. In several carnivores a newly fertilized egg enters diapause instead of being directly implanted into the uterus, a phenomenon called delayed implantation. Several hypotheses have been forwarded to explain the utility of this prolonged gestation period, but all of these depend on several independent origins of the character. Here, we conduct a phylogenetic reconstruction of the evolution of delayed implantation in the Carnivora that reveals one basal origin, with additional transitions all having occurred within the Mustelidae. Hence, previous hypotheses relating to its evolution become untestable. Further analyses revealed that the presence or absence of delayed implantation is unrelated to the timing of mating season and birth season. Instead, mustelids with direct implantation are smaller than those with delayed implantation. We therefore suggest that delayed implantation has been selected against in small species due to the relatively higher fecundity costs of a prolonged gestation period.     

Phylogenetic host specificity and understanding parasite sharing in primates

Understanding how parasites are transmitted to new species is of great importance for human health, agriculture and conservation. However, it is still unclear why some parasites are shared by many species, while others have only one host. Using a new measure of ‘phylogenetic host specificity’, we find that most primate parasites with more than one host are phylogenetic generalists, infecting less closely related primates than expected. Evolutionary models suggest that phylogenetic host generalism is driven by a mixture of host–parasite cospeciation and lower rates of parasite extinction. We also show that phylogenetic relatedness is important in most analyses, but fails to fully explain patterns of parasite sharing among primates. Host ecology and geographical distribution emerged as key additional factors that influence contacts among hosts to facilitate sharing. Greater understanding of these factors is therefore crucial to improve our ability to predict future infectious disease risks.     

AN EIGENVECTOR METHOD FOR ESTIMATING PHYLOGENETIC INERTIA

We propose a new method to estimate and correct for phylogenetic inertia in comparative data analysis. The method, called phylogenetic eigenvector regression (PVR) starts by performing a principal coordinate analysis on a pairwise phylogenetic distance matrix between species. Traits under analysis are regressed on eigenvectors retained by a broken-stick model in such a way that estimated values express phylogenetic trends in data and residuals express independent evolution of each species. This partitioning is similar to that realized by the spatial autoregressive method, but the method proposed here overcomes the problem of low statistical performance that occurs with autoregressive method when phylogenetic correlation is low or when sample size is too small to detect it. Also, PVR is easier to perform with large samples because it is based on well-known techniques of multivariate and regression analyses. We evaluated the performance of PVR and compared it with the autoregressive method using real datasets and simulations. A detailed worked example using body size evolution of Carnivora mammals indicated that phylogenetic inertia in this trait is elevated and similarly estimated by both methods. In this example, Type I error at α = 0.05 of PVR was equal to 0.048, but an increase in the number of eigenvectors used in the regression increases the error. Also, similarity between PVR and the autoregressive method, defined by correlation between their residuals, decreased by overestimating the number of eigenvalues necessary to express the phylogenetic distance matrix. To evaluate the influence of cladogram topology on the distribution of eigenvalues extracted from the double-centered phylogenetic distance matrix, we analyzed 100 randomly generated cladograms (up to 100 species). Multiple linear regression of log transformed variables indicated that the number of eigenvalues extracted by the broken-stick model can be fully explained by cladogram topology. Therefore, the broken-stick model is an adequate criterion for determining the correct number of eigenvectors to be used by PVR. We also simulated distinct levels of phylogenetic inertia by producing a trend across 10, 25, and 50 species arranged in “comblike” cladograms and then adding random vectors with increased residual variances around this trend. In doing so, we provide an evaluation of the performance of both methods with data generated under different evolutionary models than tested previously. The results showed that both PVR and autoregressive method are efficient in detecting inertia in data when sample size is relatively high (more than 25 species) and when phylogenetic inertia is high. However, PVR is more efficient at smaller sample sizes and when level of phylogenetic inertia is low. These conclusions were also supported by the analysis of 10 real datasets regarding body size evolution in different animal clades. We concluded that PVR can be a useful alternative to an autoregressive method in comparative data analysis.     

A trait-based approach to determining principles of plant biogeography

Lineage-specific traits determine how plants interact with their surrounding environment. Unrelated species may evolve similar phenotypic characteristics to tolerate, persist in, and invade environments with certain characteristics, resulting in some traits becoming relatively more common in certain types of habitats. Analyses of these general patterns of geographical trait distribution have led to the proposal of general principles to explain how plants diversify in space over time. Trait–environment correlation analyses quantify to what extent unrelated lineages have similar evolutionary responses to a given type of habitat. In this synthesis, I give a short historical overview on trait–environment correlation analyses, from some key observations from classic naturalists to modern approaches using trait evolution models, large phylogenies, and massive data sets of traits and distributions. I discuss some limitations of modern approaches, including the need for more realistic models, the lack of data from tropical areas, and the necessary focus on trait scoring that goes beyond macromorphology. Overcoming these limitations will allow the field to explore new questions related to trait lability and niche evolution and to better identify generalities and exceptions in how plants diversify in space over time.