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Incorporating morphological data into modern phylogenies allows integration of fossil evidence, facilitating divergence dating and macroevolutionary inferences. Improvements in the phylogenetic utility of morphological data have been sought via Procrustes-based geometric morphometrics (GMM), but with mixed success and little clarity over what anatomical areas are most suitable. Here, we assess GMM-based phylogenetic reconstructions in a heavily sampled source of discrete characters for mammalian phylogenetics—the basicranium—in 57 species of marsupial mammals, compared with the remainder of the cranium. We show less phylogenetic signal in the basicranium compared with a ‘Rest of Cranium’ partition, using diverse metrics of phylogenetic signal ( K mult , phylogenetically aligned principal components analysis, comparisons of UPGMA/neighbour-joining/parsimony trees and cophenetic distances to a reference phylogeny) for scaled, Procrustes-aligned landmarks and allometry-corrected residuals. Surprisingly, a similar pattern emerged from parsimony-based analyses of discrete cranial characters. The consistent results across methods suggest that easily computed metrics such as K mult can provide good guidance on phylogenetic information in a landmarking configuration. In addition, GMM data may be less informative for intricate but conservative anatomical regions such as the basicranium, while better—but not necessarily novel—phylogenetic information can be expected for broadly characterized shapes such as entire bones. This article is part of the theme issue ‘The mammalian skull: development, structure and function’.

The study of functional diversity (FD) provides ways to understand phenomena as complex as community assembly or the dynamics of biodiversity change under multiple pressures. Different frameworks are used to quantify FD, either based on dissimilarity matrices (e.g., Rao entropy, functional dendrograms) or multidimensional spaces (e.g. convex hulls, kernel-density hypervolumes). While the first does not enable the measurement of FD within a richness/divergence/regularity framework, or results in the distortion of the functional space, the latter does not allow for comparisons with phylogenetic diversity (PD) measures and can be extremely sensitive to outliers.We propose the use of neighbor-joining trees (NJ) to represent and quantify functional diversity in a way that combines the strengths of current FD frameworks without many of their weaknesses. Our proposal is also uniquely suited for studies that compare FD with PD, as both share the use of trees (NJ or others) and the same mathematical principles.We test the ability of this novel framework to represent the initial functional distances between species with minimal functional space distortion and sensitivity to outliers. The results using NJ are compared with conventional functional dendrograms, convex hulls, and kernel-density hypervolumes using both simulated and empirical datasets.Using NJ we demonstrate that it is possible to combine much of the flexibility provided by multidimensional spaces with the simplicity of tree-based representations. Moreover, the method is directly comparable with PD measures, and enables quantification of the richness, divergence and regularity of the functional space.

1AbstractPatterns of biological diversity across the tree of life are the result of millions of years of evolutionary history and are shaped by natural selection. A long-standing proposal is that most morphological diversity at a macroevolutionary scale (among species) arises along a microevolutionary “line of least resistance”. However, we frequently observe major shifts in phenotypes among lineages [1, 2, 3], suggesting that species or clades may also evolve away from the line of least resistance [4]. At the macroevolutionary scale, evolution along a common major axis has been termed elaboration whereas evolution away from that major axis is termed innovation [5]. The extent to which species and clades elaborate or innovate is poorly understood. Of particular importance is the potential contribution of reorientations of phenotypic trait space (innovation) among clades to contribute to the origins and maintenance of biodiversity across scales from the macro-to mega-evolutionary scale. Here we apply new multi-trait methods that model the nested covariance structure of traits to evaluate the magnitude and distribution of elaboration and innovation in the evolution of bird beaks. Our analyses show that elaboration dominates species-level phenotypic divergence, consistent with microevolutionary theory. However, innovation is surprisingly common at the clade level suggesting multiple routes to phenotypic innovation throughout avian evolutionary history. Our results highlight the importance of scale in our understanding of deep time evolution. While we find that elaboration dominates at macroevolutionary scales (i.e. species diverging within clades), the major axis of phenotypic change at megaevolutionary scales is an emergent property of innovation across clades. Taken together we suggest that innovation and elaboration are ubiquitous routes for phenotypic change but that their contribution to diversity is dependent on scale. The macroevolutionary axes of multivariate evolution are frequently reoriented throughout the history of life, opening up new avenues for evolution to explore.

The biogeographic distribution of diversity among populations of threatened mammalian species is generally investigated using population genetics. However, intraspecific phenotypic diversity is rarely assessed beyond taxonomy‐focused linear measurements or qualitative descriptions. Here, we use a technique widely used in the evolutionary sciences—geometric morphometrics—to characterize shape diversity in the skull of an endangered marsupial, the northern quoll, across its 5,000 km distribution range along Northern Australia. Skull shape is a proxy for feeding, behavior, and phenotypic differentiation, allowing us to ask whether populations can be distinguished and whether patterns of variation indicate adaptability to changing environmental conditions. We analyzed skull shape in 101 individuals across four mainland populations and several islands. We assessed the contribution of population, size, sex, rainfall, temperature, and geography to skull shape variation using principal component analysis, Procrustes ANOVA, and variation partitioning analyses. The populations harbor similar amounts of broadly overlapping skull shape variation, with relatively low geographic effects. Size predicted skull shape best, coinciding with braincase size variation and differences in zygomatic arches. Size‐adjusted differences in populations explained less variation with far smaller effect sizes, relating to changes in the insertion areas of masticatory muscles, as well as the upper muzzle and incisor region. Climatic and geographic variables contributed little. Strikingly, the vast majority of shape variation—76%—remained unexplained. Our results suggest a uniform intraspecific scope for shape variation, possibly due to allometric constraints or phenotypic plasticity beyond the relatively strong allometric effect. The lack of local adaptation indicates that cross‐breeding between populations will not reduce local morphological skull (and probably general musculoskeletal) adaptation because none exists. However, the potential for heritable morphological variation (e.g., specialization to local diets) seems exceedingly limited. We conclude that 3D geometric morphometrics can provide a comprehensive, statistically rigorous phenomic contribution to genetic‐based conservation studies., The diversity among populations of threatened mammalian species is generally investigated through population genetics. Here, we characterize shape intraspecific diversity with geometric morphometrics in the skull of an endangered marsupial. Our results suggest a uniform within‐species scope for shape variation, possibly due to phenotypic plasticity or allometric constraints. Thus, the potential for heritable morphological variation, such as specialization to local diets, seems exceedingly limited.

1. The use of functional diversity analyses in ecology has grown exponentially over the past two decades, broadening our understanding of biological diversity and its change across space and time. Virtually all ecological sub-disciplines recognise the critical value of looking at species and communities from a functional perspective, and this has led to a proliferation of methods for estimating contrasting dimensions of functional diversity.\ud \ud \ud \ud 2. Differences between these methods and their development generated terminological inconsistencies and confusion about the selection of the most appropriate approach for addressing any particular ecological question, hampering the potential for comparative studies, simulation exercises and meta-analyses.\ud \ud \ud \ud 3. Two general mathematical frameworks for estimating functional diversity are prevailing: those based on dissimilarity matrices (e.g. Rao entropy, functional dendrograms) and those relying on multidimensional spaces, constructed as either convex hulls or probabilistic hypervolumes.\ud \ud \ud \ud 4. We review these frameworks, discuss their strengths and weaknesses and provide an overview of the main R packages performing these calculations. In parallel, we propose a way for organising functional diversity metrics in a unified scheme to quantify the richness, divergence and regularity of species or individuals under each framework. This overview offers a roadmap for confidently approaching functional diversity analyses both theoretically and practically.

Among vertebrates, placental mammals are particularly variable in the covariance between their cranial shapes and body size (allometry), with the notable exception of rodents. Australian murid rodents present an opportunity to assess the cause of this anomaly because they radiated on an ecologically diverse continent unique for lacking other terrestrial placentals. Here we used 3D geometric morphometrics to quantify species-level and evolutionary allometries in 38 species (317 crania) from all Australian murid genera. We ask if ecological opportunity resulted in greater allometric diversity; conversely, we test if intrinsic constraints and/or stabilizing selection conserved allometry. To increase confidence in species-level allometric slopes, we introduce a new phylogeny-based method of bootstrapping and randomly resampling across the whole sample. We found exceedingly conserved allometry across the 10 million year split between Mus and the clade containing Australian murids. Cranial shapes followed craniofacial evolutionary allometry (CREA) patterns, with larger species having relatively longer snouts and smaller braincases. CREA is consistent with both intrinsic constraints and stabilizing selection hypotheses for conserved allometry. However, large-bodied frugivores evolved faster, while carnivorous specialists showed skull modifications known to conflict with masticatory efficiency. These results suggest a strong role of stabilizing selection on the masticatory apparatus of murid rodents.

Studies of biodiversity through deep time have been a staple for biologists and paleontologists for over 60 years. Investigations of species richness (diversity) revealed that at least five mass extinctions punctuated the last half billion years, each seeing the rapid demise of a large proportion of contemporary taxa. In contrast to diversity, the response of morphological diversity (disparity) to mass extinctions is unclear. Generally, diversity and disparity are decoupled, such that diversity may decline as morphological disparity increases, and vice versa. Here, we develop simulations to model disparity changes across mass extinctions using continuous traits and birth‐death trees. We find no simple null for disparity change following a mass extinction but do observe general patterns. The range of trait values decreases following either random or trait‐selective mass extinctions, whereas variance and the density of morphospace occupation only decline following trait‐selective events. General trends may differentiate random and trait‐selective mass extinctions, but methods struggle to identify trait selectivity. Long‐term effects of mass extinction trait selectivity change support for phylogenetic comparative methods away from the simulated Brownian motion toward Ornstein‐Uhlenbeck and Early Burst models. We find that morphological change over mass extinction is best studied by quantifying multiple aspects of morphospace occupation.

Endochondral bone is the main internal skeletal tissue of nearly all osteichthyans—the group comprising more than 60,000 living species of bony fishes and tetrapods. Chondrichthyans (sharks and their kin) are the living sister group of osteichthyans and have primarily cartilaginous endoskeletons, long considered the ancestral condition for all jawed vertebrates (gnathostomes). The absence of bone in modern jawless fishes and the absence of endochondral ossification in early fossil gnathostomes appear to lend support to this conclusion. Here we report the discovery of extensive endochondral bone in Minjinia turgenensis, a new genus and species of ‘placoderm’-like fish from the Early Devonian (Pragian) of western Mongolia described using X-ray computed microtomography. The fossil consists of a partial skull roof and braincase with anatomical details providing strong evidence of placement in the gnathostome stem group. However, its endochondral space is filled with an extensive network of fine trabeculae resembling the endochondral bone of osteichthyans. Phylogenetic analyses place this new taxon as a proximate sister group of the gnathostome crown. These results provide direct support for theories of generalized bone loss in chondrichthyans. Furthermore, they revive theories of a phylogenetically deeper origin of endochondral bone and its absence in chondrichthyans as a secondary condition. Minjinia turgenensis, an Early Devonian fish, preserves anatomical details consistent with it being a stem gnathostome, but also endochondral bone similar to that of osteichthyans. These findings suggest that endochondral bone is an ancestral condition subsequently lost in chondrichthyans.

Multidimensional analysis of traits are now common in ecology and evolution and are based on trait spaces in which each dimension summarizes the observed trait combination (a morphospace or an ecospace). Observations of interest will typically occupy a subset of this space, and researchers will calculate one or more measures to quantify how organisms inhabit that space. In macroevolution and ecology, these measures called disparity or dissimilarity metrics are generalized as space occupancy measures. Researchers use these measures to investigate how space occupancy changes through time, in relation to other groups of organisms, or in response to global environmental changes. However, the mathematical and biological meaning of most space occupancy measures is vague with the majority of widely used measures lacking formal description. Here, we propose a broad classification of space occupancy measures into three categories that capture changes in size, density, or position. We study the behavior of 25 measures to changes in trait space size, density, and position on simulated and empirical datasets. We find that no measure describes all of trait space aspects but that some are better at capturing certain aspects. Our results confirm the three broad categories (size, density, and position) and allow us to relate changes in any of these categories to biological phenomena. Because the choice of space occupancy measures is specific to the data and question, we introduced https://tguillerme.shinyapps.io/moms/moms, a tool to both visualize and capture changes in space occupancy for any measurement. https://tguillerme.shinyapps.io/moms/moms is designed to help workers choose the right space occupancy measures, given the properties of their trait space and their biological question. By providing guidelines and common vocabulary for space occupancy analysis, we hope to help bridging the gap in multidimensional research between ecology and evolution., Different measurements of multidimensional space occupancy can give different results and are affected by the multidimensional space properties and biological question. This paper provides a guideline of what different measurements are capturing and in which context they can be useful for answering biological questions.

Biological data is multivariate in essence: many traits in organisms covary with each other in space and time. This causes biologists to either reduce these to a manageable number of variables or, increasingly, to use multivariate toolkits. One such toolkit is based on creating a multidimensional space where the variables are the axes. It is then possible to measure diverse aspects of the distribution of some observation (e.g. species) in this space. For example, if studying morphology, one can create a morphospace for two groups of species, measure the volume occupied by each of these groups and then test whether these two volumes are significantly different or not. There are as many definitions of these multidimensional spaces, metrics and tests as there are questions that can be tackled with such methods. Many of these methods are implemented in specific software or r packages. However, the definition of the space, metric and test is often dependent on the software/package and authors points of view or specific questions. This can unfortunately hamper researchers’ ability to apply different methods that best suits their specific questions. Here I present the dispRity package, a flexible R package for performing multidimensional analysis. It allows users to define each step of the analysis (whether it is the space, the metric or the test) through a highly modular architecture where each definition can be passed as a function. It also provides a tidy interface through the dispRity object, allowing users to easily run reproducible multivariate analysis. The dispRity package also comes with an extend manual regularly updated following users’ questions or suggestions. Furthermore, the package contains some simulation tools (e.g to simulate complex multidimensional space or morphological data). Finally, it also contains a suite of utility functions to work with dispRity objects aimed at helping users to develop their own multidimensional metrics and/or tests.

Disparity-through-time analyses can be used to determine how morphological diversity changes in response to mass extinctions, or to investigate the drivers of morphological change. These analyses are routinely applied to palaeobiological datasets, yet, although there is much discussion about how to best calculate disparity, there has been little consideration of how taxa should be sub-sampled through time. Standard practice is to group taxa into discrete time bins, often based on stratigraphic periods. However, this can introduce biases when bins are of unequal size, and implicitly assumes a punctuated model of evolution. In addition, many time bins may have few or no taxa, meaning that disparity cannot be calculated for the bin and making it harder to complete downstream analyses. Here we describe a different method to complement the disparity-through-time tool-kit: time-slicing. This method uses a time-calibrated phylogenetic tree to sample disparity-through-time at any fixed point in time rather than binning taxa. It uses all available data (tips, nodes and branches) to increase the power of the analyses, specifies the implied model of evolution (punctuated or gradual), and is implemented in R. We test the time-slicing method on four example datasets and compare its performance in common disparity-through-time analyses. We find that the way we time sub-sample taxa can change our interpretations of the results of disparity-through-time analyses. We advise using multiple methods for time sub-sampling taxa, rather than just time binning, to gain a better understanding disparity-through-time.

BackgroundWithin-species skull shape variation of marsupial mammals is widely considered low and strongly size-dependent (allometric), possibly due to developmental constraints arising from the altricial birth of marsupials. However, species whose skulls are impacted by strong muscular stresses – particularly those produced through mastication of tough food items – may not display such intrinsic patterns very clearly because of the known plastic response of bone to muscle activity of the individual. In such cases, allometry may not dominate within-species shape variation, even if it is a driver of evolutionary shape divergence; ordination of shape in a geometric morphometric context through principal component analysis (PCA) should reveal main variation in areas under masticatory stress (incisor region/zygomatic arches/mandibular ramus); but this main variation should emerge from high individual variability and thus have low eigenvalues.ResultsWe assessed the evidence for high individual variation through 3D geometric morphometric shape analysis of crania and mandibles of three species of grazing-specialized wombats, whose diet of tough grasses puts considerable strain on their masticatory system. As expected, we found little allometry and low Principal Component 1 (PC1) eigenvalues within crania and mandibles of all three species. Also as expected, the main variation was in the muzzle, zygomatic arches, and masticatory muscle attachments of the mandibular ramus. We then implemented a new test to ask if the landmark variation reflected on PC1 was reflected in individuals with opposite PC1 scores and with opposite shapes in Procrustes space. This showed that correspondence between individual and ordinated shape variation was limited, indicating high levels of individual variability in the masticatory apparatus.DiscussionOur results are inconsistent with hypotheses that skull shape variation within marsupial species reflects a constraint pattern. Rather, they support suggestions that individual plasticity can be an important determinant of within-species shape variation in marsupials (and possibly other mammals) with high masticatory stresses, making it difficult to understand the degree to which intrinsic constraints act on shape variation at the within-species level. We conclude that studies that link micro- and macroevolutionary patterns of shape variation might benefit from a focus on species with low-impact mastication, such as carnivorous or frugivorous species.

Analyses of morphological disparity have been used to characterize and investigate the evolution of variation in the anatomy, function and ecology of organisms since the 1980s. While a diversity of methods have been employed, it is unclear whether they provide equivalent insights. Here, we review the most commonly used approaches for characterizing and analysing morphological disparity, all of which have associated limitations that, if ignored, can lead to misinterpretation. We propose best practice guidelines for disparity analyses, while noting that there can be no ‘one-size-fits-all’ approach. The available tools should always be used in the context of a specific biological question that will determine data and method selection at every stage of the analysis.

Phylogenetic analysis algorithms require the assumption of character independence - a condition generally acknowledged to be violated by morphological data. Correlation between characters can originate from intra-organismal features, shared phylogenetic history or forced by particular character-state coding schemes. Although the two first sources can be investigated by biologists a posteriori and the third one can be avoided a priori with good practices, phylogenetic software do not distinguish between any of them.In this study, we propose a new metric of raw character difference as a proxy for character correlation. Using thorough simulations, we test the effect of increasing or decreasing character differences on tree topology. Overall, we found an expected positive effect of reducing character correlations on recovering the correct topology. However, this effect is less important for matrices with a small number of taxa (25 in our simulations) where reducing character correlation is not more effective than randomly drawing characters. Furthermore, in bigger matrices (350 characters), there is a strong effect of the inference method with Bayesian trees being consistently less affected by character correlation than maximum parsimony trees.These results suggest that ignoring the problem of character correlation or independence can often impact topology in phylogenetic analysis. However, encouragingly, they also suggest that, unless correlation is actively maximised or minimised, probabilistic methods can easily accommodate for a random correlation between characters.

To fully understand macroevolutionary patterns and processes, we need to include both extant and extinct species in our models. This requires phylogenetic trees with both living and fossil taxa at the tips. One way to infer such phylogenies is the Total Evidence approach which uses molecular data from living taxa and morphological data from living and fossil taxa. Although the Total Evidence approach is very promising, it requires a great deal of data that can be hard to collect. Therefore this method is likely to suffer from missing data issues that may affect its ability to infer correct phylogenies. Here we use simulations to assess the effects of missing data on tree topologies inferred from Total Evidence matrices. We investigate three major factors that directly affect the completeness and the size of the morphological part of the matrix: the proportion of living taxa with no morphological data, the amount of missing data in the fossil record, and the overall number of morphological characters in the matrix. We infer phylogenies from complete matrices and from matrices with various amounts of missing data, and then compare missing data topologies to the "best" tree topology inferred using the complete matrix. We find that the number of living taxa with morphological characters and the overall number of morphological characters in the matrix, are more important than the amount of missing data in the fossil record for recovering the "best" tree topology. Therefore, we suggest that sampling effort should be focused on morphological data collection for living species to increase the accuracy of topological inference in a Total Evidence framework. Additionally, we find that Bayesian methods consistently outperform other tree inference methods. We therefore recommend using Bayesian consensus trees to fix the tree topology prior to further analyses.

KH acknowledges support from the Marie Curie Research Grants Scheme, grant [749594] and Science Foundation Ireland awarded to Yvonne Buckley. TG acknowledges support from European Research Council under the European Union’s Seventh Framework Programme (FP/2007–2013)/ERC Grant Agreement number 311092 awarded to Martin D. Brazeau. AJ was funded by a research scholarship administered by the Fulbright Commission of Ireland and in conjunction with the Marine Institute of Ireland. SB & RI are funded by an ERC consolidators grant (STATEMIG: 310820). The data used to fit the regression models, along with the code itself is bundled within the R package and is available on GitHub https://github.com/healyke/SIDER, with the data also on Figshare https://figshare.com/articles/Dataset_for_the_SIDER_R_package/4737481. Data available from the Dryad Digital Repository: http://dx.doi.org/10.5061/dryad.c6035 (Healy et al. 2017). Stable isotope mixing models (SIMMs) are an important tool used to study species' trophic ecology. These models are dependent on, and sensitive to, the choice of trophic discrimination factors (TDF) representing the offset in stable isotope delta values between a consumer and their food source when they are at equilibrium. Ideally, controlled feeding trials should be conducted to determine the appropriate TDF for each consumer, tissue type, food source, and isotope combination used in a study. In reality however, this is often not feasible nor practical. In the absence of species-specific information, many researchers either default to an average TDF value for the major taxonomic group of their consumer, or they choose the nearest phylogenetic neighbour for which a TDF is available. Here, we present the SIDER package for R, which uses a phylogenetic regression model based on a compiled dataset to impute (estimate) a TDF of a consumer. We apply information on the tissue type and feeding ecology of the consumer, all of which are known to affect TDFs, using Bayesian inference. Presently, our approach can estimate TDFs for two commonly used isotopes (nitrogen and carbon), for species of mammals and birds with or without previous TDF information. The estimated posterior probability provides both a mean and variance, reflecting the uncertainty of the estimate, and can be subsequently used in the current suite of SIMM software. SIDER allows users to place a greater degree of confidence on their choice of TDF and its associated uncertainty, thereby leading to more robust predictions about trophic relationships in cases where study-specific data from feeding trials is unavailable. The underlying database can be updated readily to incorporate more stable isotope tracers, replicates and taxonomic groups to further increase the confidence in dietary estimates from stable isotope mixing models, as this information becomes available. Postprint

Non-independence of characters is a real phenomenon in phylogenetic data matrices, even though phylogenetic reconstruction algorithms generally assume character independence. In morphological datasets, the problem results in characters that cannot be applied to certain terminal taxa, with this inapplicability treated as “missing data” in a popular method of character coding. However, this treatment is known to create spurious tree length estimates on certain topologies, potentially leading to erroneous results in phylogenetic searches. Here we present a single-character algorithm for ancestral states reconstruction in datasets that have been coded using reductive coding. The algorithm uses up to four traversals on a tree to resolve final ancestral states – which are required in full before a tree can be scored. The algorithm employs explicit criteria for the resolution of ambiguity in applicable/inapplicable dichotomies and the optimization of missing data. We score trees following a previously published procedure that minimizes homoplasy over all characters. Our analysis of published datasets shows that, compared to traditional methods, our new method identifies different trees as “optimal”; as such, correcting for inapplicable data may significantly alter the outcome of tree searches.

Morphological data play a key role in the inference of biological relationships and evolutionary history and are essential for the interpretation of the fossil record. The hierarchical interdependence of many morphological characters, however, complicates phylogenetic analysis. In particular, many characters only apply to a subset of terminal taxa. The widely used “reductive coding” approach treats taxa in which a character is inapplicable as though the character’s state is simply missing (unknown). This approach has long been known to create spurious tree length estimates on certain topologies, potentially leading to erroneous results in phylogenetic searches—but pratical solutions have yet to be proposed and implemented. Here, we present a single-character algorithm for reconstructing ancestral states in reductively coded data sets, following the theoretical guideline of minimizing homoplasy over all characters. Our algorithm uses up to three traversals to score a tree, and a fourth to fully resolve final states at each node within the tree. We use explicit criteria to resolve ambiguity in applicable/inapplicable dichotomies, and to optimize missing data. So that it can be applied to single characters, the algorithm employs local optimization; as such, the method provides a fast but approximate inference of ancestral states and tree score. The application of our method to published morphological data sets indicates that, compared to traditional methods, it identifies different trees as “optimal.” As such, the use of our algorithm to handle inapplicable data may significantly alter the outcome of tree searches, modifying the inferred placement of living and fossil taxa and potentially leading to major differences in reconstructions of evolutionary history.

Historical patterns of diversity, biogeography and faunal turnover remain poorly understood for Wallacea, the biologically and geologically complex island region between the Asian and Australian continental shelves. A distinctive Quaternary vertebrate fauna containing the small-bodied hominin Homo floresiensis , pygmy Stegodon proboscideans, varanids and giant murids has been described from Flores, but Quaternary faunas are poorly known from most other Lesser Sunda Islands. We report the discovery of extensive new fossil vertebrate collections from Pleistocene and Holocene deposits on Sumba, a large Wallacean island situated less than 50 km south of Flores. A fossil assemblage recovered from a Pleistocene deposit at Lewapaku in the interior highlands of Sumba, which may be close to 1 million years old, contains a series of skeletal elements of a very small Stegodon referable to S. sumbaensis , a tooth attributable to Varanus komodoensis , and fragmentary remains of unidentified giant murids. Holocene cave deposits at Mahaniwa dated to approximately 2000–3500 BP yielded extensive material of two new genera of endemic large-bodied murids, as well as fossils of an extinct frugivorous varanid. This new baseline for reconstructing Wallacean faunal histories reveals that Sumba's Quaternary vertebrate fauna, although phylogenetically distinctive, was comparable in diversity and composition to the Quaternary fauna of Flores, suggesting that similar assemblages may have characterized Quaternary terrestrial ecosystems on many or all of the larger Lesser Sunda Islands.

1. Stable isotope analysis is a widely used tool for the reconstruction and interpretation of animal diets and trophic relationships. Analytical tools have improved the robustness of inferring the relative contribution of different prey sources to an animal’s diet by accounting for many of the sources of variation in isotopic data. One major source of uncertainty is Trophic Discrimination Factor (TDF), the change in isotopic signatures between consumers’ tissues and their food sources. This parameter can have a profound impact on model predictions, but often, it is not feasible to estimate a species’ TDF value and so researchers often use aggregated or taxon level estimates, an assumption that in turn has major implications for the interpretation of subsequent analyses. 2. We collected extensive carbon (δ13C) and nitrogen (δ15N) TDF data on mammals and birds from published literature. We then used a Bayesian linear modelling approach to determine if, and to what extent, variation in TDF values can be attributed to a species’ ecology, physiology, phylogenetic relationships and experimental variation. Finally, we developed a Bayesian imputation approach to estimate unknown TDF values and compared the accuracy of this tool using a series of cross-validation tests. 3. Our results show that, for birds and mammals, TDF values are influenced by phylogeny, tissue type sampled, diet of consumer, isotopic signature of food source, and the error associated with the measurement of TDF within a species. Furthermore, our cross-validation tests determined that, our tool can (i) produce accurate estimates of TDF values with a mean distance of 0.2 ‰ from observed TDF values, and (ii) provide an estimate of the precision associated with these estimates, with species presence in the data allowing for a reduced level of uncertainty. 4. By incorporating various sources of variation and reflecting the levels of uncertainty associated with TDF estimates our novel tool will contribute to more accurate and honest reconstructions and interpretations of animal diets and trophic interactions. This tool can be extended readily to include other taxa and sources of variation as data becomes available. To facilitate this, we provide a step-by-step guide and code for this tool: Discrimination Estimation in R (DEsiR)

Despite its prevalence, the importance of scavenging to carnivores is difficult to ascertain in modern day forms and impossible to study directly in extinct species. Yet, there are certain intrinsic and environmental features of a species that push it towards a scavenging lifestyle. These can be thought of as some of the principal parameters in optimal foraging theory namely, encounter rate and handling time. We use these components to highlight the morphologies and environments that would have been conducive to scavenging over geological time by focusing on the dominant vertebrate groups of the land, sea and air. The result is a synthesis on the natural history of scavenging. The features that make up our qualitative scale of scavenging can be applied to any given species and allow us to judge the likely importance of this foraging behaviour. This article is protected by copyright. All rights reserved.

Analyses of living and fossil taxa are crucial for understanding biodiversity through time. The total evidence method allows living and fossil taxa to be combined in phylogenies, using molecular data for living taxa and morphological data for living and fossil taxa. With this method, substantial overlap of coded anatomical characters among living and fossil taxa is vital for accurately inferring topology. However, although molecular data for living species are widely available, scientists generating morphological data mainly focus on fossils. Therefore, there are fewer coded anatomical characters in living taxa, even in well-studied groups such as mammals. We investigated the number of coded anatomical characters available in phylogenetic matrices for living mammals and how these were phylogenetically distributed across orders. Eleven of 28 mammalian orders have less than 25% species with available characters; this has implications for the accurate placement of fossils, although the issue is less pronounced at higher taxonomic levels. In most orders, species with available characters are randomly distributed across the phylogeny, which may reduce the impact of the problem. We suggest that increased morphological data collection efforts for living taxa are needed to produce accurate total evidence phylogenies.

Maximum lifespan in birds and mammals varies strongly with body mass such that large species tend to live longer than smaller species. However, many species live far longer than expected given their body mass. This may reflect interspecific variation in extrinsic mortality, as life-history theory predicts investment in long-term survival is under positive selection when extrinsic mortality is reduced. Here, we investigate how multiple ecological and mode-of-life traits that should reduce extrinsic mortality (including volancy (flight capability), activity period, foraging environment and fossoriality), simultaneously influence lifespan across endotherms. Using novel phylogenetic comparative analyses and to our knowledge, the most species analysed to date ( n = 1368), we show that, over and above the effect of body mass, the most important factor enabling longer lifespan is the ability to fly. Within volant species, lifespan depended upon when (day, night, dusk or dawn), but not where (in the air, in trees or on the ground), species are active. However, the opposite was true for non-volant species, where lifespan correlated positively with both arboreality and fossoriality. Our results highlight that when studying the molecular basis behind cellular processes such as those underlying lifespan, it is important to consider the ecological selection pressures that shaped them over evolutionary time.