Age-dependent extinction and the neutral theory of biodiversity.

Red Queen (RQ) theory states that adaptation does not protect species from extinction because their competitors are continually adapting alongside them. RQ was founded on the apparent independence of extinction risk and fossil taxon age, but analytical developments have since demonstrated that age-dependent extinction is widespread, usually most intense among young species. Here, we develop ecological neutral theory as a general framework for modeling fossil species survivorship under incomplete sampling. We show that it provides an excellent fit to a high-resolution dataset of species durations for Paleozoic zooplankton and more broadly can account for age-dependent extinction seen throughout the fossil record. Unlike widely used alternative models, the neutral model has parameters with biological meaning, thereby generating testable hypotheses on changes in ancient ecosystems. The success of this approach suggests reinterpretations of mass extinctions and of scaling in eco-evolutionary systems. Intense extinction among young species does not necessarily refute RQ or require a special explanation but can instead be parsimoniously explained by neutral dynamics operating across species regardless of age.

Unveiling the underlying drivers of Phanerozoic marine diversification.

In investigating global patterns of biodiversity through deep time, many large-scale drivers of diversification have been proposed, both biotic and abiotic. However, few robust conclusions about these hypothesized effectors or their roles have been drawn. Here, we use a linear stochastic differential equation (SDE) framework to test for the presence of underlying drivers of diversification patterns before examining specific hypothesized drivers. Using a global dataset of observations of skeletonized marine fossils, we infer origination, extinction and sampling rates (collectively called fossil time series) throughout the Phanerozoic using a capture-mark-recapture approach. Using linear SDEs, we then compare models including and excluding hidden (i.e. unmeasured) drivers of these fossil time series. We find evidence of large-scale underlying drivers of marine Phanerozoic diversification rates and present quantitative characterizations of these. We then test whether changing global temperature, sea-level, marine sediment area or continental fragmentation could act as drivers of the fossil time series. We show that it is unlikely any of these four abiotic factors are the hidden drivers we identified, though there is evidence for correlative links between sediment area and origination/extinction rates. Our characterization of the hidden drivers of Phanerozoic diversification and sampling will aid in the search for their ultimate identities.

Trait-fitness associations do not predict within-species phenotypic evolution over 2 million years.

Long-term patterns of phenotypic change are the cumulative results of tens of thousands to millions of years of evolution. Yet, empirical and theoretical studies of phenotypic selection are largely based on contemporary populations. The challenges in studying phenotypic evolution, in particular trait-fitness associations in the deep past, are barriers to linking micro- and macroevolution. Here, we capitalize on the unique opportunity offered by a marine colonial organism commonly preserved in the fossil record to investigate trait-fitness associations over 2 Myr. We use the density of female polymorphs in colonies of Antartothoa tongima as a proxy for fecundity, a fitness component, and investigate multivariate signals of trait-fitness associations in six time intervals on the backdrop of Pleistocene climatic shifts. We detect negative trait-fitness associations for feeding polymorph (autozooid) sizes, positive associations for autozooid shape but no particular relationship between fecundity and brood chamber size. In addition, we demonstrate that long-term trait patterns are explained by palaeoclimate (as approximated by ∂18O), and to a lesser extent by ecological interactions (i.e. overgrowth competition and substrate crowding). Our analyses show that macroevolutionary outcomes of trait evolution are not a simple scaling-up from the trait-fitness associations.

When fossil clades 'compete': local dominance, global diversification dynamics and causation.

Examining the supposition that local-scale competition drives macroevolutionary patterns has become a familiar goal in fossil biodiversity studies. However, it is an elusive goal, hampered by inadequate confirmation of ecological equivalence and interactive processes between clades, patchy sampling, few comparative analyses of local species assemblages over long geological intervals, and a dearth of appropriate statistical tools. We address these concerns by reevaluating one of the classic examples of clade displacement in the fossil record, in which cheilostome bryozoans surpass the once dominant cyclostomes. Here, we analyse a newly expanded and vetted compilation of 40 190 fossil species occurrences to estimate cheilostome and cyclostome patterns of species proportions within assemblages, global genus richness and genus origination and extinction rates while accounting for sampling. Comparison of time-series models using linear stochastic differential equations suggests that inter-clade genus origination and extinction rates are causally linked to each other in a complex feedback relationship rather than by simple correlations or unidirectional relationships, and that these rates are not causally linked to changing within-assemblage proportions of cheilostome versus cyclostome species.

A genome-skimmed phylogeny of a widespread bryozoan family, Adeonidae.

BACKGROUND: Understanding the phylogenetic relationships among species is one of the main goals of systematic biology. Simultaneously, credible phylogenetic hypotheses are often the first requirement for unveiling the evolutionary history of traits and for modelling macroevolutionary processes. However, many non-model taxa have not yet been sequenced to an extent such that statistically well-supported molecular phylogenies can be constructed for these purposes. Here, we use a genome-skimming approach to extract sequence information for 15 mitochondrial and 2 ribosomal operon genes from the cheilostome bryozoan family, Adeonidae, Busk, 1884, whose current systematics is based purely on morphological traits. The members of the Adeonidae are, like all cheilostome bryozoans, benthic, colonial, marine organisms. Adeonids are also geographically widely-distributed, often locally common, and are sometimes important habitat-builders. RESULTS: We successfully genome-skimmed 35 adeonid colonies representing 6 genera (Adeona, Adeonellopsis, Bracebridgia, Adeonella, Laminopora and Cucullipora). We also contributed 16 new, circularised mitochondrial genomes to the eight previously published for cheilostome bryozoans. Using the aforementioned mitochondrial and ribosomal genes, we inferred the relationships among these 35 samples. Contrary to some previous suggestions, the Adeonidae is a robustly supported monophyletic clade. However, the genera Adeonella and Laminopora are in need of revision: Adeonella is polyphyletic and Laminopora paraphyletically forms a clade with some Adeonella species. Additionally, we assign a sequence clustering identity using cox1 barcoding region of 99% at the species and 83% at the genus level. CONCLUSIONS: We provide sequence data, obtained via genome-skimming, that greatly increases the resolution of the phylogenetic relationships within the adeonids. We present a highly-supported topology based on 17 genes and substantially increase availability of circularised cheilostome mitochondrial genomes, and highlight how we can extend our pipeline to other bryozoans.

Text-mined fossil biodiversity dynamics using machine learning.

Documented occurrences of fossil taxa are the empirical foundation for understanding large-scale biodiversity changes and evolutionary dynamics in deep time. The fossil record contains vast amounts of understudied taxa. Yet the compilation of huge volumes of data remains a labour-intensive impediment to a more complete understanding of Earth's biodiversity history. Even so, many occurrence records of species and genera in these taxa can be uncovered in the palaeontological literature. Here, we extract observations of fossils and their inferred ages from unstructured text in books and scientific articles using machine-learning approaches. We use Bryozoa, a group of marine invertebrates with a rich fossil record, as a case study. Building on recent advances in computational linguistics, we develop a pipeline to recognize taxonomic names and geologic time intervals in published literature and use supervised learning to machine-read whether the species in question occurred in a given age interval. Intermediate machine error rates appear comparable to human error rates in a simple trial, and resulting genus richness curves capture the main features of published fossil diversity studies of bryozoans. We believe our automated pipeline, that greatly reduced the time required to compile our dataset, can help others compile similar data for other taxa.

Millions of Years Behind: Slow Adaptation of Ruminants to Grasslands.

The Late Cretaceous appearance of grasses, followed by the Cenozoic advancement of grasslands as dominant biomes, has contributed to the evolution of a range of specialized herbivores adapted to new diets, as well as to increasingly open and arid habitats. Many mammals including ruminants, the most diversified ungulate suborder, evolved high-crowned (hypsodont) teeth as an adaptation to tooth-wearing diets and habitats. The impact of different causes of tooth wear is still a matter of debate, and the temporal pattern of hypsodonty evolution in relation to the evolution of grasslands remains unclear. We present an improved time-calibrated molecular phylogeny of Cetartiodactyla, with phylogenetic reconstruction of ancestral ruminant diets and habitats, based on characteristics of extant taxa. Using this timeline, as well as the fossil record of grasslands, we conduct phylogenetic comparative analyses showing that hypsodonty in ruminants evolved as an adaptation to both diet and habitat. Our results demonstrate a slow, perhaps constrained, evolution of hypsodonty toward estimated optimal states, excluding the possibility of immediate adaptation. This augments recent findings that slow adaptation is not uncommon on million-year time scales.

Model Adequacy and Microevolutionary Explanations for Stasis in the Fossil Record.

Long-term phenotypic stasis is frequently observed in the fossil record, but not readily predicted from microevolutionary theory. To test competing explanations for stasis on macroevolutionary timescales we need reliably estimated parameters from appropriate evolutionary models that adequately describe the evolutionary trait dynamics. Here, we develop tests to assess the adequacy of the most commonly used stasis model in evolutionary biology and apply them to time series of phenotypic traits from fossil lineages. Of the 572 fossil time series we analyzed from the literature, 263 time series showed a better fit to the stasis model relative to alternative models, but only 172 of those fitted the stasis model in both relative and absolute terms. The estimated trait variances from these 172 time series do not correlate with rough proxies of effective population size. Our preliminary investigation of the fixed-optimum hypothesis hence fails to give empirical support to the idea that genetic drift around a constant trait optimum is an explanation for stasis in the fossil record. We argue that optima following stationary processes on the adaptive landscape is a viable hypothesis for stasis that needs further investigation. We end by discussing how investigations of model adequacy can be a valuable approach for increasing our understanding of the dynamics of the adaptive landscape on macroevolutionary timescales.

Relative size predicts competitive outcome through 2 million years.

Competition is an important biotic interaction that influences survival and reproduction. While competition on ecological timescales has received great attention, little is known about competition on evolutionary timescales. Do competitive abilities change over hundreds of thousands to millions of years? Can we predict competitive outcomes using phenotypic traits? How much do traits that confer competitive advantage and competitive outcomes change? Here we show, using communities of encrusting marine bryozoans spanning more than 2 million years, that size is a significant determinant of overgrowth outcomes: colonies with larger zooids tend to overgrow colonies with smaller zooids. We also detected temporally coordinated changes in average zooid sizes, suggesting that different species responded to a common external driver. Although species-specific average zooid sizes change over evolutionary timescales, species-specific competitive abilities seem relatively stable, suggesting that traits other than zooid size also control overgrowth outcomes and/or that evolutionary constraints are involved.

Common species link global ecosystems to climate change: dynamical evidence in the planktonic fossil record.

Common species shape the world around us, and changes in their commonness signify large-scale shifts in ecosystem structure and function. However, our understanding of long-term ecosystem response to environmental forcing in the deep past is centred on species richness, neglecting the disproportional impact of common species. Here, we use common and widespread species of planktonic foraminifera in deep-sea sediments to track changes in observed global occupancy (proportion of sampled sites at which a species is present and observed) through the turbulent climatic history of the last 65 Myr. Our approach is sensitive to relative changes in global abundance of the species set and robust to factors that bias richness estimators. Using three independent methods for detecting causality, we show that the observed global occupancy of planktonic foraminifera has been dynamically coupled to past oceanographic changes captured in deep-ocean temperature reconstructions. The causal inference does not imply a direct mechanism, but is consistent with an indirect, time-delayed causal linkage. Given the strong quantitative evidence that a dynamical coupling exists, we hypothesize that mixotrophy (symbiont hosting) may be an ecological factor linking the global abundance of planktonic foraminifera to long-term climate changes via the relative extent of oligotrophic oceans.

Interspecific interactions through 2 million years: are competitive outcomes predictable?

Ecological interactions affect the survival and reproduction of individuals. However, ecological interactions are notoriously difficult to measure in extinct populations, hindering our understanding of how the outcomes of interactions such as competition vary in time and influence long-term evolutionary changes. Here, the outcomes of spatial competition in a temporally continuous community over evolutionary timescales are presented for the first time. Our research domain is encrusting cheilostome bryozoans from the Wanganui Basin of New Zealand over a ca 2 Myr time period (Pleistocene to Recent). We find that a subset of species can be identified as consistent winners, and others as consistent losers, in the sense that they win or lose interspecific competitive encounters statistically more often than the null hypothesis of 50%. Most species do not improve or worsen in their competitive abilities through the 2 Myr period, but a minority of species are winners in some intervals and losers in others. We found that conspecifics tend to cluster spatially and interact more often than expected under a null hypothesis: most of these are stand-off interactions where the two colonies involved stopped growing at edges of encounter. Counterintuitively, competitive ability has no bearing on ecological dominance.

Ecological interactions on macroevolutionary time scales: clams and brachiopods are more than ships that pass in the night.

Competition among organisms has ecological and evolutionary consequences. However, whether the consequences of competition are manifested and measureable on macroevolutionary time scales is equivocal. Marine bivalves and brachiopods have overlapping niches such that competition for food and space may occur. Moreover, there is a long-standing debate over whether bivalves outcompeted brachiopods evolutionarily, because brachiopod diversity declined through time while bivalve diversity increased. To answer this question, we estimate the origination and extinction dynamics of fossil marine bivalve and brachiopod genera from the Ordovician through to the Recent while simultaneously accounting for incomplete sampling. Then, using stochastic differential equations, we assess statistical relationships among diversification and sampling dynamics of brachiopods and bivalves and five paleoenvironmental proxies. None of these potential environmental drivers had any detectable influence on brachiopod or bivalve diversification. In contrast, elevated bivalve extinction rates causally increased brachiopod origination rates, suggesting that bivalves have suppressed brachiopod evolution.

The role of biotic forces in driving macroevolution: beyond the Red Queen.

A multitude of hypotheses claim that abiotic factors are the main drivers of macroevolutionary change. By contrast, Van Valen's Red Queen hypothesis is often put forward as the sole representative of the view that biotic forcing is the main evolutionary driver. This imbalance of hypotheses does not reflect our current knowledge: theoretical work demonstrates the plausibility of biotically driven long-term evolution, whereas empirical work suggests a central role for biotic forcing in macroevolution. We call for a more pluralistic view of how biotic forces may drive long-term evolution that is compatible with both phenotypic stasis in the fossil record and with non-constant extinction rates. Promising avenues of research include contrasting predictions from relevant theories within ecology and macroevolution, as well as embracing both abiotic and biotic proxies while modelling long-term evolutionary data. By fitting models describing hypotheses of biotically driven macroevolution to data, we could dissect their predictions and transcend beyond pattern description, possibly narrowing the divide between our current understanding of micro- and macroevolution.

Marine extinction risk shaped by trait-environment interactions over 500 million years.

Perhaps the most pressing issue in predicting biotic responses to present and future global change is understanding how environmental factors shape the relationship between ecological traits and extinction risk. The fossil record provides millions of years of insight into how extinction selectivity (i.e., differential extinction risk) is shaped by interactions between ecological traits and environmental conditions. Numerous paleontological studies have examined trait-based extinction selectivity; however, the extent to which these patterns are shaped by environmental conditions is poorly understood due to a lack of quantitative synthesis across studies. We conducted a meta-analysis of published studies on fossil marine bivalves and gastropods that span 458 million years to uncover how global environmental and geochemical changes covary with trait-based extinction selectivity. We focused on geographic range size and life habit (i.e., infaunal vs. epifaunal), two of the most important and commonly examined predictors of extinction selectivity. We used geochemical proxies related to global climate, as well as indicators of ocean acidification, to infer average global environmental conditions. Life-habit selectivity is weakly dependent on environmental conditions, with infaunal species relatively buffered from extinction during warmer climate states. In contrast, the odds of taxa with broad geographic ranges surviving an extinction (>2500 km for genera, >500 km for species) are on average three times greater than narrow-ranging taxa (estimate of odds ratio: 2.8, 95% confidence interval = 2.3-3.5), regardless of the prevailing global environmental conditions. The environmental independence of geographic range size extinction selectivity emphasizes the critical role of geographic range size in setting conservation priorities.

Bayesian estimation of speciation and extinction from incomplete fossil occurrence data.

The temporal dynamics of species diversity are shaped by variations in the rates of speciation and extinction, and there is a long history of inferring these rates using first and last appearances of taxa in the fossil record. Understanding diversity dynamics critically depends on unbiased estimates of the unobserved times of speciation and extinction for all lineages, but the inference of these parameters is challenging due to the complex nature of the available data. Here, we present a new probabilistic framework to jointly estimate species-specific times of speciation and extinction and the rates of the underlying birth-death process based on the fossil record. The rates are allowed to vary through time independently of each other, and the probability of preservation and sampling is explicitly incorporated in the model to estimate the true lifespan of each lineage. We implement a Bayesian algorithm to assess the presence of rate shifts by exploring alternative diversification models. Tests on a range of simulated data sets reveal the accuracy and robustness of our approach against violations of the underlying assumptions and various degrees of data incompleteness. Finally, we demonstrate the application of our method with the diversification of the mammal family Rhinocerotidae and reveal a complex history of repeated and independent temporal shifts of both speciation and extinction rates, leading to the expansion and subsequent decline of the group. The estimated parameters of the birth-death process implemented here are directly comparable with those obtained from dated molecular phylogenies. Thus, our model represents a step towards integrating phylogenetic and fossil information to infer macroevolutionary processes.

A model for global diversity in response to temperature change over geological time scales, with reference to planktic organisms.

There are strong propositions in the literature that abiotic factors override biotic drivers of diversity on time scales of the fossil record. In order to study the interaction of biotic and abiotic forces on long term changes, we devise a spatio-temporal discrete-time Markov process model of macroevolution featuring population formation, speciation, migration and extinction, where populations are free to migrate. In our model, the extinction probability of these populations is controlled by latitudinally and temporally varying environment (temperature) and competition. Although our model is general enough to be applicable to disparate taxa, we explicitly address planktic organisms, which are assumed to disperse freely without barriers over the Earth's oceans. While rapid and drastic environmental changes tend to eliminate many species, generalists preferentially survive and hence leave generalist descendants. In other words, environmental fluctuations result in generalist descendants which are resilient to future environmental changes. Periods of stable or slow environmental changes lead to more specialist species and higher population numbers. Simulating Cenozoic diversity dynamics with both competition and the environmental component of our model produces diversity curves that reflect current empirical knowledge, which cannot be obtained with just one component. Our model predicts that the average temperature optimum at which planktic species thrive best has declined over the Neogene, following the trend of global average temperatures.

A dynamic global equilibrium in carnivoran diversification over 20 million years.

The ecological and evolutionary processes leading to present-day biological diversity can be inferred by reconstructing the phylogeny of living organisms, and then modelling potential processes that could have produced this genealogy. A more direct approach is to estimate past processes from the fossil record. The Carnivora (Mammalia) has both substantial extant species richness and a rich fossil record. We compiled species-level data for over 10 000 fossil occurrences of nearly 1400 carnivoran species. Using this compilation, we estimated extinction, speciation and net diversification for carnivorans through the Neogene (22-2 Ma), while simultaneously modelling sampling probability. Our analyses show that caniforms (dogs, bears and relatives) have higher speciation and extinction rates than feliforms (cats, hyenas and relatives), but lower rates of net diversification. We also find that despite continual species turnover, net carnivoran diversification through the Neogene is surprisingly stable, suggesting a saturated adaptive zone, despite restructuring of the physical environment. This result is strikingly different from analyses of carnivoran diversification estimated from extant species alone. Two intervals show elevated diversification rates (13-12 Ma and 4-3 Ma), although the precise causal factors behind the two peaks in carnivoran diversification remain open questions.

Cross-disciplinary information for understanding macroevolution.

Many different macroevolutionary models can produce the same observations. Despite efforts in building more complex and realistic models, it may still be difficult to distinguish the processes that have generated the biodiversity we observe. In this opinion we argue that we can make new progress by reaching out across disciplines, relying on independent data and theory to constrain macroevolutionary inference. Using mainly paleontological insights and data, we illustrate how we can eliminate less plausible or implausible models, and/or parts of parameter space, while applying comparative phylogenetic approaches. We emphasize that such cross-disciplinary insights and data can be drawn between many other disciplines relevant to macroevolution. We urge cross-disciplinary training, and collaboration using common-use databases as a platform for increasing our understanding.

Measurement theory and paleobiology.

Measurement theory, a branch of applied mathematics, offers guiding principles for extracting meaning from empirical observations and is applicable to any science involving measurements. Measurement theory is highly relevant in paleobiology because statistical approaches assuming ratio-scaled variables are commonly used on data belonging to nominal and ordinal scale types. We provide an informal introduction to representational measurement theory and argue for its importance in robust scientific inquiry. Although measurement theory is widely applicable in paleobiology research, we use the study of disparity to illustrate measurement theoretical challenges in the quantitative study of the fossil record. Respecting the inherent properties of different measurements enables meaningful inferences about evolutionary and ecological processes from paleontological data.

Conceptual and empirical bridges between micro- and macroevolution.

Explaining broad molecular, phenotypic and species biodiversity patterns necessitates a unifying framework spanning multiple evolutionary scales. Here we argue that although substantial effort has been made to reconcile microevolution and macroevolution, much work remains to identify the links between biological processes at play. We highlight four major questions of evolutionary biology whose solutions require conceptual bridges between micro and macroevolution. We review potential avenues for future research to establish how mechanisms at one scale (drift, mutation, migration, selection) translate to processes at the other scale (speciation, extinction, biogeographic dispersal) and vice versa. We propose ways in which current comparative methods to infer molecular evolution, phenotypic evolution and species diversification could be improved to specifically address these questions. We conclude that researchers are in a better position than ever before to build a synthesis to understand how microevolutionary dynamics unfold over millions of years.