Evaluating the use of pairwise dissimilarity metrics in paleoanthropology

Questions of alpha taxonomy are best addressed by comparing unknown specimens to samples of the taxa to which they might belong. However, analysis of the hominin fossil record is riddled with methods that claim to evaluate whether pairs of individual fossils belong to the same species. Two such methods, log se_m and the related STET method, have been introduced and used in studies of fossil hominins. Both methods attempt to quantify morphological dissimilarity for a pair of fossils and then evaluate a null hypothesis of conspecificity using the assumption that pairs of fossils that fall beneath a predefined dissimilarity threshold are likely to belong to the same species, whereas pairs of fossils above that threshold are likely to belong to different species. In this contribution, we address (1) whether these particular methods do what they claim to do, and (2) whether such approaches can ever reliably address the question of conspecificity. We show that log se_m and STET do not reliably measure deviations from shape similarity, and that values of these measures for any pair of fossils are highly dependent upon the number of variables compared. To address these issues we develop a measure of shape dissimilarity, the Standard Deviation of Logged Ratios (s_LR). We suggest that while pairwise dissimilarity metrics that accurately measure deviations from isometry (e.g., s_LR) may be useful for addressing some questions that relate to morphological variation, no pairwise method can reliably answer the question of whether two fossils are conspecific.     

Influence of tree shape and evolutionary time‐scale on phylogenetic diversity metrics

During the last decades, describing, analysing and understanding the phylogenetic structure of species assemblages has been a central theme in both community ecology and macro‐ecology. Among the wide variety of phylogenetic structure metrics, three have been predominant in the literature: Faith's phylogenetic diversity (PD_Faith), which represents the sum of the branch lengths of the phylogenetic tree linking all species of a particular assemblage, the mean pairwise distance between all species in an assemblage (MPD) and the pairwise distance between the closest relatives in an assemblage (MNTD). Comparisons between studies using one or several of these metrics are difficult because there has been no comprehensive evaluation of the phylogenetic properties each metric captures. In particular it is unknown how PD_Faith relates to MDP and MNTD. Consequently, it is possible that apparently opposing patterns in different studies might simply reflect differences in metric properties. Here, we aim to fill this gap by comparing these metrics using simulations and empirical data. We first used simulation experiments to test the influence of community structure and size on the mismatch between metrics whilst varying the shape and size of the phylogenetic tree of the species pool. Second we investigated the mismatch between metrics for two empirical datasets (gut microbes and global carnivoran assemblages). We show that MNTD and PD_Faith provide similar information on phylogenetic structure, and respond similarly to variation in species richness and assemblage structure. However, MPD demonstrate a very different behaviour, and is highly sensitive to deep branching structure. We suggest that by combining complementary metrics that are sensitive to processes operating at different phylogenetic depths (i.e. MPD and MNTD or PD_Faith) we can obtain a better understanding of assemblage structure.     

A guide to phylogenetic metrics for conservation,community ecology and macroecology

The use of phylogenies in ecology is increasingly common and has broadened our understanding of biological diversity. Ecological sub‐disciplines, particularly conservation, community ecology and macroecology, all recognize the value of evolutionary relationships but the resulting development of phylogenetic approaches has led to a proliferation of phylogenetic diversity metrics. The use of many metrics across the sub‐disciplines hampers potential meta‐analyses, syntheses, and generalizations of existing results. Further, there is no guide for selecting the appropriate metric for a given question, and different metrics are frequently used to address similar questions. To improve the choice, application, and interpretation of phylo‐diversity metrics, we organize existing metrics by expanding on a unifying framework for phylogenetic information. Generally, questions about phylogenetic relationships within or between assemblages tend to ask three types of question: how much; how different; or how regular? We show that these questions reflect three dimensions of a phylogenetic tree: richness, divergence, and regularity. We classify 70 existing phylo‐diversity metrics based on their mathematical form within these three dimensions and identify ‘anchor’ representatives: for α‐diversity metrics these are PD (Faith's phylogenetic diversity), MPD (mean pairwise distance), and VPD (variation of pairwise distances). By analysing mathematical formulae and using simulations, we use this framework to identify metrics that mix dimensions, and we provide a guide to choosing and using the most appropriate metrics. We show that metric choice requires connecting the research question with the correct dimension of the framework and that there are logical approaches to selecting and interpreting metrics. The guide outlined herein will help researchers navigate the current jungle of indices.     

Beyond connectedness: why pairwise metrics cannot capture community stability

The connectedness of species in a trophic web has long been a key structural characteristic for both theoreticians and empiricists in their understanding of community stability. In the past decades, there has been a shift from focussing on determining the number of interactions to taking into account their relative strengths. The question is: How do the strengths of the interactions determine the stability of a community? Recently, a metric has been proposed which compares the stability of observed communities in terms of the strength of three‐ and two‐link feedback loops (cycles of interaction strengths). However, it has also been suggested that we do not need to go beyond the pairwise structure of interactions to capture stability. Here, we directly compare the performance of the feedback and pairwise metrics. Using observed food‐web structures, we show that the pairwise metric does not work as a comparator of stability and is many orders of magnitude away from the actual stability values. We argue that metrics based on pairwise‐strength information cannot capture the complex organization of strong and weak links in a community, which is essential for system stability.     

Rethinking the relationship between nestedness and beta diversity: a comment on Baselga (2010)

Baselga [Partitioning the turnover and nestedness components of beta diversity. Global Ecology and Biogeography, 19 , 134–143, 2010] proposed pairwise (β_nes) and multiple‐site (β_NES) beta‐diversity measures to account for the nestedness component of beta diversity. We used empirical, randomly created and idealized matrices to show that both measures are only partially related to nestedness and do not fit certain fundamental requirements for consideration as true nestedness‐resultant dissimilarity measures. Both β_nes and β_NES are influenced by matrix size and fill, and increase or decrease even when nestedness remains constant. Additionally, we demonstrate that β_NES can yield high values even for matrices with no nestedness. We conclude that β_nes and β_NES are not true measures of the nestedness‐resultant dissimilarity between sites. Actually, they quantify how differences in species richness that are not due to species replacement contribute to patterns of beta diversity. Finally, because nestedness is a special case of dissimilarity in species composition due to ordered species loss (or gain), the extent to which differences in species composition is due to nestedness can be measured through an index of nestedness.     

Measuring fractions of beta diversity and their relationships to nestedness: a theoretical and empirical comparison of novel approaches

Beta diversity and nestedness are central concepts of ecology and biogeography and evaluation of their relationships is in the focus of contemporary ecological and conservation research. Beta diversity patterns are originated from two distinct processes: the replacement (or turnover) of species and the loss (or gain) of species leading to richness differences. Nested distributional patterns are generally thought to have a component deriving from beta diversity which is independent of replacement processes. Quantification of these phenomena is often made by calculating a measure of beta diversity, and the resulting value being subsequently partitioned into a contribution by species replacement plus a fraction shared by beta diversity and nestedness. Three methods have been recently proposed for such partitioning, all of them based on pairwise comparisons of sites. In this paper, the performance of these methods was evaluated on theoretical grounds and tested by a simulation study in which different gradients of dissimilarity, with known degrees of species replacement and species loss, were created. Performance was also tested using empirical data addressing land‐use induced changes in endemic arthropod communities of the Terceira Island in the Azores. We found that the partitioning of β_cc (dissimilarity in terms of the Jaccard index) into two additive fractions, β_‐3 (dissimilarity due to species replacement) plus β_rich (dissimilarity due to richness differences) reflects the species replacement and species loss processes across the simulated gradients in an ecologically and mathematically meaningful way, whilst the other two methods lack mathematical consistency and prove conceptually self‐contradictory. Moreover, the first method identified a selective local extinction process for endemic arthropods, triggered by land‐use changes, while the latter two methods overweighted the replacement component and led to false conclusions. Their basic flaw derives from the fact that the proposed replacement and nestedness components (deemed to account for species loss) are not scaled in the same way as the measure that accounts for the total dissimilarity (Sørensen and Jaccard indices). We therefore recommend the use of β_cc=β_‐3+β_rich, since its components are scaled in the same units and their responses are proportional to the replacement and the gain/loss of species.     

Phylogenetic metrics of community similarity

We derive a new metric of community similarity that takes into account the phylogenetic relatedness among species. This metric, phylogenetic community dissimilarity (PCD), can be partitioned into two components, a nonphylogenetic component that reflects shared species between communities (analogous to S?rensen' s similarity metric) and a phylogenetic component that reflects the evolutionary relationships among nonshared species. Therefore, even if a species is not shared between two communities, it will increase the similarity of the two communities if it is phylogenetically related to species in the other community. We illustrate PCD with data on fish and aquatic macrophyte communities from 59 temperate lakes. Dissimilarity between fish communities associated with environmental differences between lakes often has a phylogenetic component, whereas this is not the case for macrophyte communities. With simulations, we then compare PCD with two other metrics of phylogenetic community similarity, II(ST) and UniFrac. Of the three metrics, PCD was best at identifying environmental drivers of community dissimilarity, showing lower variability and greater statistical power. Thus, PCD is a statistically powerful metric that separates the effects of environmental drivers on compositional versus phylogenetic components of community structure.     

Ecological niche modeling re‐examined: A case study with the Darwin's fox

Many previous studies have attempted to assess ecological niche modeling performance using receiver operating characteristic (ROC) approaches, even though diverse problems with this metric have been pointed out in the literature. We explored different evaluation metrics based on independent testing data using the Darwin's Fox (Lycalopex fulvipes) as a detailed case in point. Six ecological niche models (ENMs; generalized linear models, boosted regression trees, Maxent, GARP, multivariable kernel density estimation, and NicheA) were explored and tested using six evaluation metrics (partial ROC, Akaike information criterion, omission rate, cumulative binomial probability), including two novel metrics to quantify model extrapolation versus interpolation (E‐space index I) and extent of extrapolation versus Jaccard similarity (E‐space index II). Different ENMs showed diverse and mixed performance, depending on the evaluation metric used. Because ENMs performed differently according to the evaluation metric employed, model selection should be based on the data available, assumptions necessary, and the particular research question. The typical ROC AUC evaluation approach should be discontinued when only presence data are available, and evaluations in environmental dimensions should be adopted as part of the toolkit of ENM researchers. Our results suggest that selecting Maxent ENM based solely on previous reports of its performance is a questionable practice. Instead, model comparisons, including diverse algorithms and parameterizations, should be the sine qua non for every study using ecological niche modeling. ENM evaluations should be developed using metrics that assess desired model characteristics instead of single measurement of fit between model and data. The metrics proposed herein that assess model performance in environmental space (i.e., E‐space indices I and II) may complement current methods for ENM evaluation.     

Biometric-genetic analysis of genotype dissimilarity: The model and parameters

An additive-dominant model and parameters for biometric-genetic analysis of pair dissimilarity between genotypes have been developed. The analyzed dissimilarity metrics are presumed to be determined by the quantitative traits of plant lines and F₁ hybrids obtained by diallel crossing. Relationships between dissimilarity parameters have been determined, and algorithms for estimating their use, in particular, for detecting the most heterozygous hybrids are suggested.     

Beta‐diversity gradients of butterflies along productivity axes

Aim Several lines of evidence suggest that beta diversity, or dissimilarity in species composition, should increase with productivity: (1) the latitudinal species richness gradient is most closely related to productivity and associated latitudinal beta‐diversity relationships have been described, and (2) the scale dependence of the productivity–diversity relationship implies that there should be a positive productivity–beta‐diversity relationship. However, such a pattern has not yet been demonstrated at broad scales. We test if there is a gradient of increasing beta diversity with productivity. Location Canada. Methods Canada was clustered into regions of similar productivity regimes along three remotely sensed productivity axes (minimum and integrated annual productivity, seasonality of productivity) and elevation. The overall (β_j), turnover (β_sim) and nestedness (β_nes) components of beta diversity within each productivity regime were estimated with pairwise dissimilarity metrics and related to cluster productivity with partial linear regression and with spatial autoregression. Tests were performed for all species, productivity breadth‐based subsets (e.g. species occurring in many and a moderate number of productivity regimes), and pre‐ and post‐1970 butterfly records. Beta diversity between adjacent clusters along the productivity gradients was also evaluated. Results Within‐cluster β_j and β_sim increased with productivity and decreased with seasonality. The converse was true for β_nes. All species subsets responded similarly; however, productivity–beta‐diversity relationships were weaker for the post‐1970 temporal subset and strongest for species of moderate breadth. Between‐cluster beta diversity (β_j) and nestedness (β_nes) declined with productivity. Main conclusions As predicted, beta diversity of communities within productivity regimes was observed to increase with productivity. This pattern was driven largely by a gradient of species turnover. Therefore, beta diversity may make an important contribution to the broad‐scale gradient of species richness with productivity. However, this species richness gradient dominates regional beta diversity between productivity regimes, resulting in decreasing between‐productivity dissimilarity with productivity driven by a concurrent decline in nestedness.     

Multiple site dissimilarity quantifies compositional heterogeneity among several sites,while average pairwise dissimilarity may be misleading

Several measures of multiple site dissimilarity have been proposed to quantify the overall heterogeneity in assemblage composition among any number of sites. It is also a common practice to quantify such overall heterogeneity by averaging pairwise dissimilarities between all pairs of sites in the pool. However, pairwise dissimilarities do not account for patterns of co‐occurrence among more than two sites. In consequence, the average of pairwise dissimilarities may not accurately reflect the overall compositional heterogeneity within a pool of more than two sites. Here I use several idealized examples to illustrate why pairwise dissimilarity measures fail to properly quantify overall heterogeneity. Thereafter, the effect of this potential problem in empirical patterns is exemplified with data of world amphibians. In conclusion, when the attribute of interest is the overall heterogeneity in a pool of sites (i.e. beta diversity) or its turnover or nestedness components, only multiple site dissimilarity measures are recommended.     

Phylogenetic community structure metrics and null models: a review with new methods and software

Competitive exclusion and habitat filtering influence community assembly, but ecologists and evolutionary biologists have not reached consensus on how to quantify patterns that would reveal the action of these processes. Currently, at least 22 α‐diversity and 10 β‐diversity metrics of community phylogenetic structure can be combined with nine null models (eight for β‐diversity metrics), providing 278 potentially distinct approaches to test for phylogenetic clustering and overdispersion. Selecting the appropriate approach for a study is daunting. First, we describe similarities among metrics and null models across variance in phylogeny size and shape, species abundance, and species richness. Second, we develop spatially explicit, individual‐based simulations of neutral, competitive exclusion, or habitat filtering community assembly, and quantify the performance (type I and II error rates) of all 278 metric and null model combinations against each assembly process. Many α‐diversity metrics and null models are at least functionally equivalent, reducing the number of truly unique metrics to 12 and the number of unique metric + null model combinations to 72. An even smaller subset of metric and null model combinations showed robust statistical performance. For α‐diversity metrics, phylogenetic diversity and mean nearest taxon distance were best able to detect habitat filtering, while mean pairwise phylogenetic distance‐based metrics were best able to detect competitive exclusion. Overall, β‐diversity metrics tended to have greater power to detect habitat filtering and competitive exclusion than α‐diversity metrics, but had higher type 1 error in some cases. Across both α‐ and β‐diversity metrics, null model selection affected type I error rates more than metric selection. A null model that maintained species richness, and approximately maintained species occurrence frequency and abundance across sites, exhibited low type I and II error rates. This regional null model simulates neutral dispersal of individuals into local communities by sampling from a regional species pool. We introduce a flexible new R package, metricTester, to facilitate robust analyses of method performance.     

Discriminating antigen and non-antigen using proteome dissimilarity: bacterial antigens

It has been postulated that immunogenicity results from the overall dissimilarity of pathogenic proteins versus the host proteome. We have sought to use this concept to discriminate between antigens and non-antigens of bacterial origin. Sets of 100 known antigenic and nonantigenic peptide sequences from bacteria were compared to human and mouse proteomes. Both antigenic and non-antigenic sequences lacked human or mouse homologues. Observed distributions were compared using the non-parametric Mann-Whitney test. The statistical null hypothesis was accepted, indicating that antigen and non-antigens did not differ significantly. Likewise, we were unable to determine a threshold able to separate meaningfully antigen from non-antigen. Thus, antigens cannot be predicted from pathogen genomes based solely on their dissimilarity to the human genome.     

The relationship between species replacement,dissimilarity derived from nestedness,and nestedness

Aim Beta diversity can be partitioned into two components: dissimilarity due to species replacement and dissimilarity due to nestedness ( Baselga, 2010 , Global Ecology and Biogeography, 19 , 134–143). Several contributions have challenged this approach or proposed alternative frameworks. Here, I review the concepts and methods used in these recent contributions, with the aim of clarifying: (1) the rationale behind the partitioning of beta diversity into species replacement and nestedness‐resultant dissimilarity, (2) how, based on this rationale, numerators and denominators of indices have to match, and (3) how nestedness and nestedness‐resultant dissimilarity are related but different concepts. Innovation The rationale behind measures of species replacement (turnover) dictates that the number of species that are replaced between sites (numerator of the index) has to be relativized with respect to the total number of species that could potentially be replaced (denominator). However, a recently proposed partition of Jaccard dissimilarity fails to do this. In consequence, this partition underestimates the contribution of species replacement and overestimates the contribution of richness differences to total dissimilarity. I show how Jaccard dissimilarity can be partitioned into meaningful turnover and nestedness components, and extend these new indices to multiple‐site situations. Finally the concepts of nestedness and nestedness‐resultant dissimilarity are discussed. Main conclusions Nestedness should be assessed using consistent measures that depend both on paired overlap and matrix filling, e.g. NODF, whereas beta‐diversity patterns should be examined using measures that allow the total dissimilarity to be separated into the components of dissimilarity due to species replacement and dissimilarity due to nestedness. In the case of multiple‐site dissimilarity patterns, averaged pairwise indices should never be used because the mean of the pairwise values is unable to accurately reflect the multiple‐site attributes of dissimilarity.     

Barcoding Neotropical birds: assessing the impact of nonmonophyly in a highly diverse group

In this study, we verified the power of DNA barcodes to discriminate Neotropical birds using Bayesian tree reconstructions of a total of 7404 COI sequences from 1521 species, including 55 Brazilian species with no previous barcode data. We found that 10.4% of species were nonmonophyletic, most likely due to inaccurate taxonomy, incomplete lineage sorting or hybridization. At least 0.5% of the sequences (2.5% of the sampled species) retrieved from GenBank were associated with database errors (poor‐quality sequences, NuMTs, misidentification or unnoticed hybridization). Paraphyletic species (5.8% of the total) can be related to rapid speciation events leading to nonreciprocal monophyly between recently diverged sister species, or to absence of synapomorphies in the small COI region analysed. We also performed two series of genetic distance calculations under the K2P model for intraspecific and interspecific comparisons: the first included all COI sequences, and the second included only monophyletic taxa observed in the Bayesian trees. As expected, the mean and median pairwise distances were smaller for intraspecific than for interspecific comparisons. However, there was no precise ‘barcode gap’, which was shown to be larger in the monophyletic taxon data set than for the data from all species, as expected. Our results indicated that although database errors may explain some of the difficulties in the species discrimination of Neotropical birds, distance‐based barcode assignment may also be compromised because of the high diversity of bird species and more complex speciation events in the Neotropics.     

Metric variation and sexual dimorphism in the dentition of Ouranopithecus macedoniensis

The fossil sample attributed to the late Miocene hominoid taxon Ouranopithecus macedoniensis is characterized by a high degree of dental metric variation. As a result, some researchers support a multiple-species taxonomy for this sample. Other researchers do not think that the sample variation is too great to be accommodated within one species. This study examines variation and sexual dimorphism in mandibular canine and postcanine dental metrics of an Ouranopithecus sample. Bootstrapping (resampling with replacement) of extant hominoid dental metric data is performed to test the hypothesis that the coefficients of variation (CV) and the indices of sexual dimorphism (ISD) of the fossil sample are not significantly different from those of modern great apes. Variation and sexual dimorphism in Ouranopithecus M(1) dimensions were statistically different from those of all extant ape samples; however, most of the dental metrics of Ouranopithecus were neither more variable nor more sexually dimorphic than those of Gorilla and Pongo. Similarly high levels of mandibular molar variation are known to characterize other fossil hominoid species. The Ouranopithecus specimens are morphologically homogeneous and it is probable that all but one specimen included in this study are from a single population. It is unlikely that the sample includes specimens of two sympatric large-bodied hominoid species. For these reasons, a single-species hypothesis is not rejected for the Ouranopithecus macedoniensis material. Correlations between mandibular first molar tooth size dimorphism and body size dimorphism indicate that O. macedoniensis and other extinct hominoids were more sexually size dimorphic than any living great apes, which suggests that social behaviors and life history profiles of these species may have been different from those of living species.     

Deconstructing spatial patterns in species composition of ectoparasite communities: the relative contribution of host composition,environmental variables and geography

Aim We determined whether dissimilarity in species composition between parasite communities depends on geographic distance, environmental dissimilarity or host faunal dissimilarity, for different subsets of parasite species with different levels of host specificity. Location Communities of fleas parasitic on small mammals from 28 different regions of the Palaearctic. Method Dissimilarities in both parasite and host species composition were computed between each pair of regions using the Bray–Curtis index. Geographic distances between regions were also calculated, as were measures of environmental dissimilarity consisting of the pairwise Euclidean distances between regions derived from elevation, vegetation and climatic variables. The 136 flea species included in the dataset were divided into highly host‐specific species (using 1–2 host species per region, on average), moderately host‐specific species (2.2–4 hosts per region) and generalist species (>4 hosts per region). The relative influence of geographic distance, host faunal dissimilarity and environmental dissimilarity on dissimilarity of flea species composition among all regions was analysed for the entire set of flea species as well as for the three above subsets using multiple regressions on distance matrices. Results When including all flea species, dissimilarity in flea species composition was affected by all three independent variables, although the pure effect of dissimilarity in host species composition was the strongest. Results were different when the subsets of fleas differing in host specificity were treated separately. In particular, dissimilarity in species composition of highly host‐specific fleas increased solely with environmental dissimilarity, whereas dissimilarity for both moderately specific and non‐specific fleas increased with both geographic distance and dissimilarity in host species composition. Main conclusions Host specificity seems to dictate which of the three factors considered is most likely to affect the dissimilarity between flea communities. Counter‐intuitively, environmental dissimilarity played a key role in determining dissimilarity in species composition of highly host‐specific fleas, possibly because, although their presence in a region relies on the occurrence of particular host species, their abundance is itself mostly determined by climatic conditions. Our results show that deconstructing communities into subsets of species with different traits can make it easier to uncover the mechanisms shaping geographic patterns of diversity.     

Incorporating Ploidy Diversity into Ecological and Community Genetics

Studies in ecological and community genetics have advanced our understanding of the role of intraspecific diversity in structuring communities and ecosystems. However, in near‐shore marine communities, these studies have mostly been restricted to seagrasses, marsh plants, and oysters. Yet, macroalgae are critically important ecosystem engineers in these communities. Greater intraspecific diversity in a macroalgal ecosystem engineer should result in higher primary and secondary production and community resilience. The paucity of studies investigating the consequences of macroalgal intraspecific genetic variation might be due, in part, to the complexity of macroalgal life cycles. The majority of macroalgae have seemingly subtle, but in actuality, profoundly different life cycles than the more typical animal and angiosperm models. Here, we develop a novel genetic diversity metric, P_HD, that incorporates the ratio of gametophytic to sporophytic thalli in natural populations. This metric scales from 0 to 1 like many common genetic diversity metrics, such as genotypic richness, enabling comparisons among metrics. We discuss P_HD and examples from the literature, with specific reference to the widespread, red seaweed Agarophyton vermiculophyllum. We also discuss a sex diversity metric, P_FM, which also scales from 0 to 1, but fewer studies have identified males and females in natural populations. Nevertheless, by incorporating these novel metrics into the repertoire of diversity metrics, we can explore the role of genetic diversity in community and ecosystem dynamics with an emphasis on the unique biology of many macroalgae, as well as other haplodiplontic taxa such as ferns, foraminiferans, and some fungi.