Unravelling causal components of the Ordovician Radiation: the Builth Inlier (central Wales) as a case study

Hypotheses about the causes of biodiversification during the Ordovician have been focused in three main areas: tectonic activity and nutrient supply, palaeogeography, and ecological escalation. There is as yet no consensus on mechanisms, and it is unclear whether it is better to study the patterns at local or regional scales. By applying ecological knowledge to the available palaeontological information, it can be shown that neither tectonic nor palaeogeographic effects could account for the permanence of the diversity rise, in the absence of elements of ecological escalation. However, it may be possible to identify trigger mechanisms resulting in enhanced speciation or reduced extinction. Areas of local diversity increase should be distinguished from speciation centres. An ongoing study of the Middle Ordovician Builth-Llandrindod Inlier of central Wales, conducted over 10 years, has identified elements of all three of the above categories of causal mechanisms affecting local diversity. This implies that the patterns of causal relationship and diversification are complex even at very local scales, and at this stage we should not anticipate a clear correlation of global diversity with any single factor. More data are needed from small-scale but intensive studies before we can generalize about the causal mechanisms of the Ordovician Radiation.     

MOLECULAR PALAEOBIOLOGY

Abstract:  For more than a generation, molecular biology has been used to approach palaeontological problems, and yet only recently have attempts been made to integrate research utilizing the geological and genomic records in uncovering evolutionary history. We codify this approach as Molecular Palaeobiology for which we provide a synthetic framework for studying the interplay among genotype, phenotype and the environment, within the context of deep time. We provide examples of existing studies where molecular and morphological data have been integrated to provide novel insights within each of these variables, and an account of a case study where each variable has been tackled to understand better a single macroevolutionary event: the diversification of metazoan phyla. We show that the promise of this approach extends well beyond research into the evolutionary history of animals and, in particular, we single out plant evolution as the single greatest opportunity waiting to be exploited by molecular palaeobiology. Although most of our examples consider how novel molecular data and techniques have breathed new life into long-standing palaeontological controversies, we argue that this asymmetry in the balance of molecular and morphological evidence is an artefact of the relative 'newness' of molecular data. In particular, palaeontological data provide unique and crucial roles in unravelling evolutionary history given that extinct taxa reveal patterns of character evolution invisible to molecular biology. Finally, we argue that palaeobiologists, rather than molecular biologists, are best placed to exploit the opportunity afforded by molecular palaeobiology, though this will require incorporating the techniques and approaches of molecular biology into their skill-set.     

What Can Causal Networks Tell Us about Metabolic Pathways?

Graphical models describe the linear correlation structure of data and have been used to establish causal relationships among phenotypes in genetic mapping populations. Data are typically collected at a single point in time. Biological processes on the other hand are often non-linear and display time varying dynamics. The extent to which graphical models can recapitulate the architecture of an underlying biological processes is not well understood. We consider metabolic networks with known stoichiometry to address the fundamental question: “What can causal networks tell us about metabolic pathways?”. Using data from an Arabidopsis BaySha population and simulated data from dynamic models of pathway motifs, we assess our ability to reconstruct metabolic pathways using graphical models. Our results highlight the necessity of non-genetic residual biological variation for reliable inference. Recovery of the ordering within a pathway is possible, but should not be expected. Causal inference is sensitive to subtle patterns in the correlation structure that may be driven by a variety of factors, which may not emphasize the substrate-product relationship. We illustrate the effects of metabolic pathway architecture, epistasis and stochastic variation on correlation structure and graphical model-derived networks. We conclude that graphical models should be interpreted cautiously, especially if the implied causal relationships are to be used in the design of intervention strategies.     

The future of the past in the present: biodiversity informatics and geological time

The biological and palaeontological communities have approached the problem of informatics separately, creating a divide between communities that is both technological and sociological in nature. In this paper we describe one new advance towards solving this problem - expanding the Scratchpads platform to deal with geological time. In creating this system we have attempted to make our work open to existing communities by providing a webservice of geological time data via the GBIF Vocabularies site. We have also ensured that our system can adapt to changes in the definition of geological time intervals and is capable of querying datasets independently of the format of geological age data used.     

Biological hierarchies and the nature of extinction

Hierarchy theory recognises that ecological and evolutionary units occur in a nested and interconnected hierarchical system, with cascading effects occurring between hierarchical levels. Different biological disciplines have routinely come into conflict over the primacy of different forcing mechanisms behind evolutionary and ecological change. These disconnects arise partly from differences in perspective (with some researchers favouring ecological forcing mechanisms while others favour developmental/historical mechanisms), as well as differences in the temporal framework in which workers operate. In particular, long‐term palaeontological data often show that large‐scale (macro) patterns of evolution are predominantly dictated by shifts in the abiotic environment, while short‐term (micro) modern biological studies stress the importance of biotic interactions. We propose that thinking about ecological and evolutionary interactions in a hierarchical framework is a fruitful way to resolve these conflicts. Hierarchy theory suggests that changes occurring at lower hierarchical levels can have unexpected, complex effects at higher scales due to emergent interactions between simple systems. In this way, patterns occurring on short‐ and long‐term time scales are equally valid, as changes that are driven from lower levels will manifest in different forms at higher levels. We propose that the dual hierarchy framework fits well with our current understanding of evolutionary and ecological theory. Furthermore, we describe how this framework can be used to understand major extinction events better. Multi‐generational attritional loss of reproductive fitness (MALF) has recently been proposed as the primary mechanism behind extinction events, whereby extinction is explainable solely through processes that result in extirpation of populations through a shutdown of reproduction. While not necessarily explicit, the push to explain extinction through solely population‐level dynamics could be used to suggest that environmentally mediated patterns of extinction or slowed speciation across geological time are largely artefacts of poor preservation or a coarse temporal scale. We demonstrate how MALF fits into a hierarchical framework, showing that MALF can be a primary forcing mechanism at lower scales that still results in differential survivorship patterns at the species and clade level which vary depending upon the initial environmental forcing mechanism. Thus, even if MALF is the primary mechanism of extinction across all mass extinction events, the primary environmental cause of these events will still affect the system and result in differential responses. Therefore, patterns at both temporal scales are relevant.     

Ancient dates or accelerated rates? Morphological clocks and the antiquity of placental mammals

Analyses of a comprehensive morphological character matrix of mammals using ‘relaxed’ clock models (which simultaneously estimate topology, divergence dates and evolutionary rates), either alone or in combination with an 8.5 kb nuclear sequence dataset, retrieve implausibly ancient, Late Jurassic–Early Cretaceous estimates for the initial diversification of Placentalia (crown-group Eutheria). These dates are much older than all recent molecular and palaeontological estimates. They are recovered using two very different clock models, and regardless of whether the tree topology is freely estimated or constrained using scaffolds to match the current consensus placental phylogeny. This raises the possibility that divergence dates have been overestimated in previous analyses that have applied such clock models to morphological and total evidence datasets. Enforcing additional age constraints on selected internal divergences results in only a slight reduction of the age of Placentalia. Constraining Placentalia to less than 93.8 Ma, congruent with recent molecular estimates, does not require major changes in morphological or molecular evolutionary rates. Even constraining Placentalia to less than 66 Ma to match the ‘explosive’ palaeontological model results in only a 10- to 20-fold increase in maximum evolutionary rate for morphology, and fivefold for molecules. The large discrepancies between clock- and fossil-based estimates for divergence dates might therefore be attributable to relatively small changes in evolutionary rates through time, although other explanations (such as overly simplistic models of morphological evolution) need to be investigated. Conversely, dates inferred using relaxed clock models (especially with discrete morphological data and MrBayes) should be treated cautiously, as relatively minor deviations in rate patterns can generate large effects on estimated divergence dates.     

Stable isotopes, ecological integration and environmental change: wolves record atmospheric carbon isotope trend better than tree rings

Large-scale patterns of isotope ratios are detectable in the tissues of organisms, but the variability in these patterns often obscures detection of environmental trends. We show that plants and animals at lower trophic levels are relatively poor indicators of the temporal trend in atmospheric carbon isotope ratios (delta13C) when compared with animals at higher trophic levels. First, we tested how differences in atmospheric delta13C values were transferred across three trophic levels. Second, we compared contemporary delta13C trends (1961-2004) in atmospheric CO2 to delta13C patterns in a tree species (jack pine, Pinus banksiana), large herbivore (moose, Alces alces) and large carnivore (grey wolf, Canis lupus) from North America. Third, we compared palaeontological (approx. 30000 to 12000 14C years before present) atmospheric CO2 trends to delta13C patterns in a tree species (Pinus flexilis, Juniperus sp.), a megaherbivore (bison, Bison antiquus) and a large carnivore (dire wolf, Canis dirus) from the La Brea tar pits (southern California, USA) and Great Basin (western USA). Contrary to previous expectations, we found that the environmental isotope pattern is better represented with increasing trophic level. Our results indicate that museum specimens of large carnivores would best reflect large-scale spatial and temporal patterns of carbon isotopes in the palaeontological record because top predators can act as ecological integrators of environmental change.     

Holocene vegetation change and the mammal faunas of South America and Africa

Aim Although sharing many similarities in their vegetation types, South America and Africa harbour very dissimilar recent mammal faunas, not only taxonomically but also in terms of several faunistic patterns. However late Pleistocene and mid‐Holocene faunas, albeit taxonomically distinct, presented many convergent attributes. Here we propose that the effects of the Holocene climatic change on vegetation physiognomy has played a crucial role in shaping the extant mammalian faunistic patterns. Location South America and Africa from the late Pleistocene to the present. Methods Data presented here have been compiled from many distinct sources, including palaeontological and neontological mammalian studies, palaeoclimatology, palynology, and publications on vegetation ecology. Data on Pleistocene, Holocene and extant mammal faunas of South America and Africa allowed us to establish a number of similar and dissimilar faunistic patterns between the two continents across time. We then considered what changes in vegetation physiognomy would have occurred under the late Pleistocene last glacial maximum (LGM) and the Holocene climatic optimum (HCO) climatic regimes. We have ordained these proposed vegetation changes along rough physiognomic seral stages according to assumptions based on current botanical research. Finally, we have associated our hypothesized vegetation changes in South America and Africa with mammalian faunistic patterns, establishing a putative causal relationship between them. Results The extant mammal faunas of South America and Africa differ widely in taxonomical composition; the number of medium and large species they possess; behavioural and ecological characteristics related to herbivore herding, migration and predation; and biogeographical patterns. All such distinctions are mostly related to the open formation faunas, and have been completely established around the mid‐Holocene. Considering that the mid‐Holocene was a time of greater humidity than the late Pleistocene, vegetation cover in South America and Africa would have been dominated by forest or closed vegetation landscapes, at least for most of their lower altitude tropical regions. We attribute the loss of larger‐sized mammal lineages in South America to the decrease of open vegetation area, and their survival in Africa to the existence of vast savannas in formerly steppic or desertic areas in subtropical Africa, north and south of the equator. Alternative explanations, mostly dealing with the disappearance of South American megamammals, are then reviewed and criticized. Main conclusions The reduction of open formation areas during the HCO in South America and Africa explains most of the present distinct faunistic patterns between the two continents. While South America would have lost most of its open formations within the 30° latitudinal belt, Africa would have kept large areas suitable to the open formation mammalian fauna in areas presently occupied by desert and semi‐arid vegetation. Thus, the same general climatic events that affected South America in the late Pleistocene and Holocene also affected Africa, leading to our present day faunistic dissimilarities by maintaining the African mammalian communities almost unchanged while dramatically altering those of South America.     

Discrete and morphometric traits reveal contrasting patterns and processes in the macroevolutionary history of a clade of scorpions

Many palaeontological studies have investigated the evolution of entire body plans, generally relying on discrete character‐taxon matrices. In contrast, macroevolutionary studies performed by neontologists have mostly focused on morphometric traits. Although these data types are very different, some studies have suggested that they capture common patterns. Nonetheless, the tests employed to support this claim have not explicitly incorporated a phylogenetic framework and may therefore be susceptible to confounding effects due to the presence of common phylogenetic structure. We address this question using the scorpion genus Brachistosternus Pocock 1893 as case study. We make use of a time‐calibrated multilocus molecular phylogeny, and compile discrete and traditional morphometric data sets, both capturing the overall morphology of the organisms. We find that morphospaces derived from these matrices are significantly different, and that the degree of discordance cannot be replicated by simulations of random character evolution. Moreover, we find strong support for contrasting modes of evolution, with discrete characters being congruent with an ‘early burst’ scenario whereas morphometric traits suggest species‐specific adaptations to have driven morphological evolution. The inferred macroevolutionary dynamics are therefore contingent on the choice of character type. Finally, we confirm that metrics of correlation fail to detect these profound differences given common phylogenetic structure in both data sets, and that methods incorporating a phylogenetic framework and accounting for expected covariance should be favoured.     

Conceptualising ‘fossiliferous deposit’ against ‘palaeontological deposit’: some semantic (and epistemological) considerations

This short essay intends to provide insight into the concepts of ‘fossiliferous deposit’ and ‘palaeontological deposit’ by identifying some of their semantic differences. From the moment that fossiliferous deposits are technically accessible to the palaeontologist, they are ‘palaeontological’ ones, but not before. However, not all palaeontological deposits must inevitably be ‘fossiliferous’ deposits in the sense of containing mineralised remains of the anatomical parts of organisms. As a consequence of the existence of fossiliferous deposits, the science of palaeontology exists, with the result that fossiliferous deposits become ‘palaeontological deposits’, together with the non-fossiliferous strata that are able to provide data on the ecological and/or ethological conditions of fossil beings from remains that are not ‘fossils’. From the point of view of philosophy of science, fossiliferous and palaeontological deposits should be considered as two different epistemological (as well as ontological) categories. Consequently, by identifying semantic differences, the concepts of ‘fossiliferous deposit’ and ‘palaeontological deposit’ can be framed better within the philosophical development of the palaeontological sciences. In addition to the central issue addressed in this essay, a brief discussion on the epistemic value of the dichotomy ‘to deposit’ versus ‘to reposit’ applied to palaeontological museology is brought up.     

Biases with the Generalized Euclidean Distance measure in disparity analyses with high levels of missing data

The Generalized Euclidean Distance (GED) measure has been extensively used to conduct morphological disparity analyses based on palaeontological matrices of discrete characters. This is in part because some implementations allow the use of morphological matrices with high percentages of missing data without needing to prune taxa for a subsequent ordination of the data set. Previous studies have suggested that this way of using the GED may generate a bias in the resulting morphospace, but a detailed study of this possible effect has been lacking. Here, we test whether the percentage of missing data for a taxon artificially influences its position in the morphospace, and if missing data affects pre‐ and post‐ordination disparity measures. We find that this use of the GED creates a systematic bias, whereby taxa with higher percentages of missing data are placed closer to the centre of the morphospace than those with more complete scorings. This bias extends into pre‐ and post‐ordination calculations of disparity measures and can lead to erroneous interpretations of disparity patterns, especially if specimens present in a particular time interval or clade have distinct proportions of missing information. We suggest that this implementation of the GED should be used with caution, especially in cases with high percentages of missing data. Results recovered using an alternative distance measure, Maximum Observed Rescaled Distance (MORD), are more robust to missing data. As a consequence, we suggest that MORD is a more appropriate distance measure than GED when analysing data sets with high amounts of missing data.     

Time Delayed Causal Gene Regulatory Network Inference with Hidden Common Causes

Inferring the gene regulatory network (GRN) is crucial to understanding the working of the cell. Many computational methods attempt to infer the GRN from time series expression data, instead of through expensive and time-consuming experiments. However, existing methods make the convenient but unrealistic assumption of causal sufficiency, i.e. all the relevant factors in the causal network have been observed and there are no unobserved common cause. In principle, in the real world, it is impossible to be certain that all relevant factors or common causes have been observed, because some factors may not have been conceived of, and therefore are impossible to measure. In view of this, we have developed a novel algorithm named HCC-CLINDE to infer an GRN from time series data allowing the presence of hidden common cause(s). We assume there is a sparse causal graph (possibly with cycles) of interest, where the variables are continuous and each causal link has a delay (possibly more than one time step). A small but unknown number of variables are not observed. Each unobserved variable has only observed variables as children and parents, with at least two children, and the children are not linked to each other. Since it is difficult to obtain very long time series, our algorithm is also capable of utilizing multiple short time series, which is more realistic. To our knowledge, our algorithm is far less restrictive than previous works. We have performed extensive experiments using synthetic data on GRNs of size up to 100, with up to 10 hidden nodes. The results show that our algorithm can adequately recover the true causal GRN and is robust to slight deviation from Gaussian distribution in the error terms. We have also demonstrated the potential of our algorithm on small YEASTRACT subnetworks using limited real data.     

Estimation of causal effects of a time-varying exposure at multiple time points through multivariable mendelian randomization

Mendelian Randomisation (MR) is a powerful tool in epidemiology that can be used to estimate the causal effect of an exposure on an outcome in the presence of unobserved confounding, by utilising genetic variants as instrumental variables (IVs) for the exposure. The effect estimates obtained from MR studies are often interpreted as the lifetime effect of the exposure in question. However, the causal effects of some exposures are thought to vary throughout an individual’s lifetime with periods during which an exposure has a greater effect on a particular outcome. Multivariable MR (MVMR) is an extension of MR that allows for multiple, potentially highly related, exposures to be included in an MR estimation. MVMR estimates the direct effect of each exposure on the outcome conditional on all the other exposures included in the estimation. We explore the use of MVMR to estimate the direct effect of a single exposure at different time points in an individual’s lifetime on an outcome. We use simulations to illustrate the interpretation of the results from such analyses and the key assumptions required. We show that causal effects at different time periods can be estimated through MVMR when the association between the genetic variants used as instruments and the exposure measured at those time periods varies. However, this estimation will not necessarily identify exact time periods over which an exposure has the most effect on the outcome. Prior knowledge regarding the biological basis of exposure trajectories can help interpretation. We illustrate the method through estimation of the causal effects of childhood and adult BMI on C-Reactive protein and smoking behaviour.     

The application of Correspondence Analysis in palaeontology

Correspondence analysis (CA) is frequently used in the interpretation of palaeontological data, but little is known about the minimum requirements for a result to be valid. Far from being a fundamental mathematical study of CA, this paper aims to present a tool, which may serve to evaluate results obtained in (palaeontological) praxis. We created matrices of random data, grouped by matrix size and varying percentages of zero cells. Each matrix was submitted to CA. Per matrix group the minimum, mean and maximum percentages of total inertia were calculated for the first four axes. We compared these results with several real cases in vertebrate paleontology. Valid conclusions based on CA can only be drawn on percentages that are considerably higher than the axis percentages obtained from random matrices.     

A phylogeny of Cenozoic macroperforate planktonic foraminifera from fossil data

We present a complete phylogeny of macroperforate planktonic foraminifer species of the Cenozoic Era (∼65 million years ago to present). The phylogeny is developed from a large body of palaeontological work that details the evolutionary relationships and stratigraphic (time) distributions of species‐level taxa identified from morphology (‘morphospecies’). Morphospecies are assigned to morphogroups and ecogroups depending on test morphology and inferred habitat, respectively. Because gradual evolution is well documented in this clade, we have identified many instances of morphospecies intergrading over time, allowing us to eliminate ‘pseudospeciation’ and ‘pseudoextinction’ from the record and thereby permit the construction of a more natural phylogeny based on inferred biological lineages. Each cladogenetic event is determined as either budding or bifurcating depending on the pattern of morphological change at the time of branching. This lineage phylogeny provides palaeontologically calibrated ages for each divergence that are entirely independent of molecular data. The tree provides a model system for macroevolutionary studies in the fossil record addressing questions of speciation, extinction, and rates and patterns of evolution.     

Formation binning: a new method for increased temporal resolution in regional studies,applied to the Late Cretaceous dinosaur fossil record of North America

The advent of palaeontological occurrence databases has allowed for detailed reconstruction and analyses of species richness through deep time. While a substantial literature has evolved ensuring that taxa are fairly counted within and between different time periods, how time itself is divided has received less attention. Stage-level or equal-interval age bins have frequently been used for regional and global studies in vertebrate palaeontology. However, when assessing diversity at a regional scale, these resolutions can prove inappropriate with the available data. Herein, we propose a new method of binning geological time for regional studies that intrinsically incorporates the chronostratigraphic heterogeneity of different rock formations to generate unique stratigraphic bins. We use this method to investigate the diversity dynamics of dinosaurs from the Late Cretaceous of the Western Interior of North America prior to the Cretaceous–Palaeogene mass extinction. Increased resolution through formation binning pinpoints the Maastrichtian diversity decline to between 68 and 66 Ma, coinciding with the retreat of the Western Interior Seaway. Diversity curves are shown to exhibit volatile patterns using different binning methods, supporting claims that heterogeneous biases in this time-frame affect the pre-extinction palaeobiological record. We also show that the apparent high endemicity of dinosaurs in the Campanian is a result of non-contemporaneous geological units within large time bins. This study helps to illustrate the utility of high-resolution, regional studies to supplement our understanding of factors governing global diversity in deep time and ultimately how geology is inherently tied to our understanding of past changes in species richness.     

Necessity of chance: biological roulettes and biodiversity

Chance plays an important role in the dynamics of biodiversity. It is largely responsible for the spontaneous processes leading to biological diversification. The mechanisms behind chance belong to two categories: on the one hand, those outside of biological systems, and thus belonging to their environment, on the other hand, those endogenous to these systems. These last mechanisms are present at all levels of the hierarchical organization of the living world, from genes to ecosystems. We propose calling them 'biological roulettes'. Like roulettes in casinos, they could be deterministic processes functioning in chaotic domains and producing results that look as though they had been generated by random processes. The spontaneous appearance and natural selection of these roulettes have led to living systems potentially adapted to new environmental conditions not encountered before. They may even have permitted some of them to survive major upheavals. Moreover, palaeontological data show that the rate of biological diversification accelerates and that living systems become more and more complex over time. That may also increase their resilience. It can be also the consequence of the appearance and the selection of 'biological roulettes' and of chance they generate. They are at the same time products and engines of the evolution. Without them, life would have disappeared from the Earth a long time ago. Thus, they are of primary importance.     

Seasonality of birth in nineteenth- and twentieth-century Austria

We present an analysis of birth seasonality in nine geographical regions within Austria for two time periods, 1881-1912 and 1947-1959. In the early period, geography, climate, and agricultural patterns were related to birth seasonality. By the latter time period, these factors were no longer related to birth seasonality. We propose a "resilience hypothesis," which suggests two levels of causal influences on birth seasonality. First, underlying the three significant features of birth seasonality patterns around the world are only a small number of major causes. But, second, there are a multiplicity of minor causes that result in small perturbations in these otherwise resilient and consistent patterns.