Paleontological Data Sets Research Articles

A new reconstruction of Phanerozoic Earth evolution: Toward a big-data approach to global paleogeography

Reliable reconstruction of global paleogeography through deep geologic time provides a key surface boundary condition for investigating many first-order Earth system and geodynamic processes such as climate change, geomagnetic field stability, regional geological and tectonic history, and biological evolution. Over the past decade, the development of the GPlates software led to a resurgence of community efforts in creating state-of-the-art plate tectonic models that integrate paleomagnetic, geological, and paleontological datasets, resulting in a plethora of reconstruction models. In this paper, we briefly review the strengths and weaknesses of existing global models, which depict alternative and sometimes contradictory tectonic scenarios. We then provide an overview of the general procedure in our construction of a revised Phanerozoic global paleogeographic model, including (1) evaluation of the paleomagnetic data that quantitatively dictate continental paleolatitudes and orientations, (2) selection of reference frames in which continents were positioned, and (3) calibration of continental longitudes in deep time. We update the apparent polar wander paths (APWPs) of the major continents using a recently developed weighted running mean approach, which rectifies two major issues with the conventional running mean approach regarding missing paleopoles in age windows and the enforced assumption of the Fisherian distribution. We re-evaluate the Phanerozoic continental reconstructions in a paleomagnetic framework using the updated APWPs, and calibrate continental paleolongitudes following the extended orthoversion hypothesis by placing the centroids of supercontinents Rodinia and Pangea 90° apart, with that of Rodinia at ∼90°E. We emphasize that the resulting global model is not intended to provide solutions to all global tectonic issues throughout the entire Phanerozoic Eon. Rather, we present our results as one viable model of Phanerozoic tectonic history which, like many existing interpretations, is built upon our understanding of the paleomagnetic, geological, and paleontological observations. Our goals are for this study to highlight the fundamental differences between reconstruction models and to serve as a starting point for future studies to fill key data gaps and test alternative hypotheses and tectonic scenarios.

Towards investigation of transfer learning framework for Globotruncanita genus and Globotruncana genus microfossils in Genus-Level and Species-Level prediction

The applicability of digital imaging techniques and machine learning models to paleontological datasets is exploring the possibility of predicting microfossils extracted from the rock samples instead of the traditional identifying methodologies under the microscope in a one-by-one way via a domain expert. However, these processes, including labeling, are carried out manually and take a high time-consuming, especially for many quantities and diversity of complex morphological microfossil specimens. In this work, we propose a transfer learning framework based on a custom model CNN (Convolutional Neural Network) and diverse pre-trained deep models (ResNet50, Xception, InceptionV3, VGG6, MobileNet) trained with the millions of images for Globotruncanita genus and Globotruncana genus in genus-level and species-level prediction. The second primary advantage of our framework is able to provide better and more robust decisions for a limited number of microfossil images captured by the low-cost light microscope imaging technology. The comparison of the diverse methods was evaluated with different performance metrics, and the observation of the framework was made to perform high prediction scores reaching up to the outcomes (>99 % accuracy and > 0.99 AUC score for genus-level/>81 % accuracy and > 0.89 AUC score for species-level). As far as we know, this research study is the first attempt to investigate a transfer learning framework to predict the Globotruncanita genus and Globotruncana genus families at the genus-level and species-level microfossils. Overall, it may extend the existing literature on paleontological science and automated/quick classification manner.

Per-Simper, An Innovative Method for Identifying Community Assembly Processes Within Modern, Recent, and Deep-Time Paleontological Assemblages

How biological communities are assembled is an old but lively debate, especially today, as the efficiency of conservation policies depend on our capacity to correctly identify the assembly processes at play within the species assemblages we aim to protect. The wide range of assembly modes, once seen as mutually exclusive hypothesis are now seen as part of a continuum where the opposite ends correspond to niche- and dispersal-assembly perspectives. Niche-assembled communities are closed and balanced with a stable taxonomic composition depending on deterministic processes when dispersal-assembled communities are open, in non-equilibrium state with constantly changing compositions depending on historical process and continuous dispersion between communities. The former must be protected by increasing habitat diversity and heterogeneity when the latter needing high connectivity to ensure dispersal between habitats. Protecting modern at-risk communities will require an understanding of how assembly processes have been affected by past climate change (both recent and ancient) or by the historical exploitation of ecosystems by humans. However, few methods exist that are capable of identifying assembly processes within paleontological datasets and producing time series at multiple scales due to missing information in the vast majority of the fossil record (e.g., abundance, environmental information, highly-resolved phylogeny) or due to limited precision of compatible methods (i.e. random vs. non-random patterns). The new PER-SIMPER method (and its associated DNCImper R package) can be used to identify and quantify the respective roles of niche and dispersal processes from the distribution of occurrences of extinct and extant species. Based on three modes of permutation of the occurrence matrix, I will illustrate PER-SIMPER with deep-time (e.g., trilobites), ancient (e.g. Cenozoic mammals) and modern datasets (e.g. small mountain mammals, host-flea assemblages).

Automatic taxonomic identification based on the Fossil Image Dataset (>415,000 images) and deep convolutional neural networks

AbstractThe rapid and accurate taxonomic identification of fossils is of great significance in paleontology, biostratigraphy, and other fields. However, taxonomic identification is often labor-intensive and tedious, and the requisition of extensive prior knowledge about a taxonomic group also requires long-term training. Moreover, identification results are often inconsistent across researchers and communities. Accordingly, in this study, we used deep learning to support taxonomic identification. We used web crawlers to collect the Fossil Image Dataset (FID) via the Internet, obtaining 415,339 images belonging to 50 fossil clades. Then we trained three powerful convolutional neural networks on a high-performance workstation. The Inception-ResNet-v2 architecture achieved an average accuracy of 0.90 in the test dataset when transfer learning was applied. The clades of microfossils and vertebrate fossils exhibited the highest identification accuracies of 0.95 and 0.90, respectively. In contrast, clades of sponges, bryozoans, and trace fossils with various morphologies or with few samples in the dataset exhibited a performance below 0.80. Visual explanation methods further highlighted the discrepancies among different fossil clades and suggested similarities between the identifications made by machine classifiers and taxonomists. Collecting large paleontological datasets from various sources, such as the literature, digitization of dark data, citizen-science data, and public data from the Internet may further enhance deep learning methods and their adoption. Such developments will also possibly lead to image-based systematic taxonomy to be replaced by machine-aided classification in the future. Pioneering studies can include microfossils and some invertebrate fossils. To contribute to this development, we deployed our model on a server for public access at www.ai-fossil.com.

Biotic and Abiotic Controls on the Phanerozoic History of Marine Animal Biodiversity

During the past 541 million years, marine animals underwent three intervals of diversification (early Cambrian, Ordovician, Cretaceous–Cenozoic) separated by nondirectional fluctuation, suggesting diversity-dependent dynamics with the equilibrium diversity shifting through time. Changes in factors such as shallow-marine habitat area and climate appear to have modulated the nondirectional fluctuations. Directional increases in diversity are best explained by evolutionary innovations in marine animals and primary producers coupled with stepwise increases in the availability of food and oxygen. Increasing intensity of biotic interactions such as predation and disturbance may have led to positive feedbacks on diversification as ecosystems became more complex. Important areas for further research include improving the geographic coverage and temporal resolution of paleontological data sets, as well as deepening our understanding of Earth system evolution and the physiological and ecological traits that modulated organismal responses to environmental change.

Combining Bayesian age models and genetics to investigate population dynamics and extinction of the last mammoths in northern Siberia

To understand the causes and implications of an extinction event, detailed information is necessary. However, this can be challenging when working with poorly resolved paleontological data sets. One approach to increase the data resolution is by combining different methods. In this study, we used both radiocarbon and genetic data to reconstruct the population history and extinction dynamics of the woolly mammoth in northern Siberia. We generated 88 new radiocarbon dates and combined these with previously published dates from 626 specimens to construct Bayesian age models. These models show that mammoths disappeared on the eastern Siberian mainland before the onset of the Younger Dryas (12.9–11.7 ky cal BP). Mammoths did however persist in the northernmost parts of central and western Siberia until the early Holocene. Further genetic results of 131 high quality mitogenomes, including 22 new mitogenomes generated in this study, support the hypothesis that mammoths from, or closely related to, a central and/or west- Siberian population recolonized Wrangel Island over the now submerged northern Siberian plains. As mammoths became trapped on the island due to rising sea levels, they lived another ca. 6000 years on Wrangel Island before eventually going extinct ca. 4000 years ago.

Biogeographic problem-solving reveals the Late Pleistocene translocation of a short-faced bear to the California Channel Islands

An accurate understanding of biodiversity of the past is critical for contextualizing biodiversity patterns and trends in the present. Emerging techniques are refining our ability to decipher otherwise cryptic human-mediated species translocations across the Quaternary, yet these techniques are often used in isolation, rather than part of an interdisciplinary hypothesis-testing toolkit, limiting their scope and application. Here we illustrate the use of such an integrative approach and report the occurrence of North America’s largest terrestrial mammalian carnivore, the short-faced bear, Arctodus simus, from Daisy Cave (CA-SMI-261), an important early human occupation site on the California Channel Islands. We identified the specimen by corroborating morphological, protein, and mitogenomic lines of evidence, and evaluated the potential natural and anthropogenic mechanisms of its transport and deposition. While representing just a single specimen, our combination of techniques opened a window into the behavior of an enigmatic species, suggesting that A. simus was a wide-ranging scavenger utilizing terrestrial and marine carcasses. This discovery highlights the utility of bridging archaeological and paleontological datasets to disentangle complex biogeographic scenarios and reveal unexpected biodiversity for island systems worldwide.

Shell and appendages variability in two allopatric ostracod species seen through the light of molecular data

Ostracod crustaceans are among the most abundant microfossil animals. Understanding intra- and interspecific variability of their shell is of pivotal importance for the interpretation of paleontological data. In comparison to appendages, ostracod shell displays more intraspecific variability (in shape, size, and ornamentation), often as a response to environmental conditions. Shell variability has been studied with sophisticated methods, such as geometric morphometrics (GM), but the conspecificity of examined specimens and populations was never tested. In addition, there are no GM studies of appendages. We build on previously published high cytochrome c oxidase subunit I (COI) divergence rates among populations of a brackish water species, Ishizakiella miurensis (Hanai, 1957). With landmark-based GM analyses of its shell and appendages, and additional genetic markers (ITS, 28S, 18S), we test if the genetic variability is structured in morphospace. This approach is the core of integrative taxonomy paradigm which has been proposed to bring the gap between traditional taxonomy and other disciplines such as evolutionary biology. The results show that it is the shell shape, and not the shape of appendages, that mirrors the molecular phylogeny, and we describe a new species. Our results suggest that the landmark-based GM studies may be useful in paleontological datasets for closely related species delineation. We implement molecular clock and population statistics to discuss speciation processes and phylogeography of the two congeners in Korea and Japan.

Micro Methods for Megafauna: Novel Approaches to Late Quaternary Extinctions and Their Contributions to Faunal Conservation in the Anthropocene.

Drivers of Late Quaternary megafaunal extinctions are relevant to modern conservation policy in a world of growing human population density, climate change, and faunal decline. Traditional debates tend toward global solutions, blaming either dramatic climate change or dispersals of Homo sapiens to new regions. Inherent limitations to archaeological and paleontological data sets often require reliance on scant, poorly resolved lines of evidence. However, recent developments in scientific technologies allow for more local, context-specific approaches. In the present article, we highlight how developments in five such methodologies (radiocarbon approaches, stable isotope analysis, ancient DNA, ancient proteomics, microscopy) have helped drive detailed analysis of specific megafaunal species, their particular ecological settings, and responses to new competitors or predators, climate change, and other external phenomena. The detailed case studies of faunal community composition, extinction chronologies, and demographic trends enabled by these methods examine megafaunal extinctions at scales appropriate for practical understanding of threats against particular species in their habitats today.

Inferring Diversification Rate Variation From Phylogenies With Fossils.

Time-calibrated phylogenies of living species have been widely used to study the tempo and mode of species diversification. However, it is increasingly clear that inferences about species diversification-extinction rates in particular-can be unreliable in the absence of paleontological data. We introduce a general framework based on the fossilized birth-death process for studying speciation-extinction dynamics on phylogenies of extant and extinct species. The model assumes that phylogenies can be modeled as a mixture of distinct evolutionary rate regimes and that a hierarchical Poisson process governs the number of such rate regimes across a tree. We implemented the model in BAMM, a computational framework that uses reversible jump Markov chain Monte Carlo to simulate a posterior distribution of macroevolutionary rate regimes conditional on the branching times and topology of a phylogeny. The implementation, we describe can be applied to paleontological phylogenies, neontological phylogenies, and to phylogenies that include both extant and extinct taxa. We evaluate performance of the model on data sets simulated under a range of diversification scenarios. We find that speciation rates are reliably inferred in the absence of paleontological data. However, the inclusion of fossil observations substantially increases the accuracy of extinction rate estimates. We demonstrate that inferences are relatively robust to at least some violations of model assumptions, including heterogeneity in preservation rates and misspecification of the number of occurrences in paleontological data sets.

Updating a simple model of lunar recession

A classical model of lunar recession is reviewed and updated, where input parameters are taken or inferred from earlier astronomical computation of insolation quantities on Earth back to 0.25 Gyr. Free parameters are (i) the transition age, where mean lunar recession is suddenly lowered, and (ii) the merging age, where Earth-Moon distance (EMD), drops to zero. Predicted mean EMD and length of day (LOD) slightly overstimate their counterparts from the above mentioned astronomical computation. Predicted LOD, where the effect of atmospheric tides and nontidal processes is considered and supposed to be time independent, slightly understimates a linear interpolation from paleontological data related to Phanerozoic, inferred in earlier investigations. If short-period ($\Delta t\approx10^{-3}$ Gyr) EMD fluctuations ($\Delta a\approx\mp0.5R_\oplus$), resulting from the above mentioned astronomical computation back to 0.25 Gyr, occur along the whole evolution of Earth-Moon system (EMS), then the predicted mean EMD is consistent with values inferred from three well studied paleontological data sets: Elatina-Reynella (ER), Big Cottonwood (BC), Weeli Wolli (WW), for a suitable choice of input parameters. The same holds for LOD where, in addition, computed values are consistent with a linear interpolation from paleontological data related to Proterozoic, inferred in earlier investigations. The effect of atmospheric tides and nontidal processes is also discussed. In conclusion, the current model can be considered as a useful zeroth-order approximation to the evaluation of lunar recession and LOD. More accurate paleontological data, expecially in connection with error evaluation, would be desirable in view of improved results and further constraints involving both Astronomy and Paleontology.

The integration of quantitative genetics, paleontology, and neontology reveals genetic underpinnings of primate dental evolution

Developmental genetics research on mice provides a relatively sound understanding of the genes necessary and sufficient to make mammalian teeth. However, mouse dentitions are highly derived compared with human dentitions, complicating the application of these insights to human biology. We used quantitative genetic analyses of data from living nonhuman primates and extensive osteological and paleontological collections to refine our assessment of dental phenotypes so that they better represent how the underlying genetic mechanisms actually influence anatomical variation. We identify ratios that better characterize the output of two dental genetic patterning mechanisms for primate dentitions. These two newly defined phenotypes are heritable with no measurable pleiotropic effects. When we consider how these two phenotypes vary across neontological and paleontological datasets, we find that the major Middle Miocene taxonomic shift in primate diversity is characterized by a shift in these two genetic outputs. Our results build on the mouse model by combining quantitative genetics and paleontology, and thereby elucidate how genetic mechanisms likely underlie major events in primate evolution.

Rocking Earth's biodiversity cradle: challenges, advances, and prospects for conservation paleontology in the tropics

ABSTRACTIncreased human activity and environmental disturbances are currently eroding the high biodiversity of the tropics. Insights from the fossil record have the potential to inform conservation decisions in these regions. Conservation paleontology has played a transformative role in defining appropriate conservation goals in temperate systems, and recent applications in the tropics showcase the broad applicability of this field. Here, we highlight paleontology's role in the conservation of the tropics. We show that community-level and species-level responses commonly detected by paleontologists, such as range shifts, inform present-day population trajectories and functional diversity changes. Furthermore, advances in techniques such as ancient DNA recovery make querying ancient tropical diversity more tractable. These analyses have direct applications to policies ranging from reserve design to species reintroductions. Despite these breakthroughs, much work still remains for conservation paleontology to reach its full potential in the tropics. Increased regional coverage is necessary for areas such as Southeast Asia and the Amazon, two biogeographically important regions with highly threatened faunas. Taxonomic sampling biases must be eliminated, and we call for additional data representing amphibians and birds, which are underrepresented in paleontological data sets of terrestrial vertebrates. We also recommend further analyses of existing reptile collections, which are abundant but underutilized because of a dearth of comparative collections. We highlight recent contributions to conservation paleontology in these taxonomic groups and regions whenever possible, and showcase successful collaborations between paleontologists, neontologists, and conservationists outside of academia to illustrate the influence paleontologists can exert in conservation efforts.Citation for this article: Kemp, M. E., and E. A. Hadly. 2016. Rocking Earth's biodiversity cradle: challenges, advances, and prospects for conservation paleontology in the tropics. Journal of Vertebrate Paleontology. DOI: 10.1080/02724634.2016.1179640.

A framework for detecting natural selection on traits above the species level

Summary To what extent can natural selection act on groupings above the species level? Despite extensive theoretical discussion and growing practical concerns over increased rates of global ecological turnover, the question has largely evaded empirical resolution. A flexible and robust hypothesis‐testing framework for detecting the phenomenon could facilitate significant progress in resolving this issue. We introduce a permutation‐based approach, implemented in the R package perspectev, which provides an explicit test of whether empirical patterns of correlation between upper level trait values and survivorship are reducible to correlations manifested at lower levels. The package is applicable to virtually any nested set of upper‐ and lower level groupings, a wide variety of upper level traits, and both historical and contemporary occurrence data. We apply this approach to five paleontological data sets that represent different magnitudes of extinction and differ in taxonomic breadth, geological timing and geographic extent. Using simulations, we demonstrate that this method is a robust means of detecting irreducibility in the relationship between upper level traits and survivorship, and outline circumstances in which the method is less effective. We also find evidence consistent with previous findings of selection above the species level for geographic range size in North American K‐Pg molluscs and show that this phenomenon was evident for the same molluscan genera globally. Ultimately, we conclude that at certain points in history, some higher level taxonomic groups have survived differentially with respect to geographic range size in a manner that is not explained by the same trait at the species level, and we show that evidence for this phenomenon varies across taxa and extinction events. We release our method as a flexible and easy‐to‐use R package that will allow others to help determine the relative frequency of this macroevolutionary phenomenon, both in the fossil record and in estimates of contemporary extinction risk.

A simple way to improve multivariate analyses of paleoecological data sets

AbstractMultivariate methods such as cluster analysis and ordination are basic to paleoecology, but the messy nature of fossil occurrence data often makes it difficult to recover clear patterns. A recently described faunal similarity index based on the Forbes coefficient improves results when its complement is employed as a distance metric. This index involves adding terms to the Forbes equation and ignoring one of the counts it employs (that of species found in neither of the samples under consideration). Analyses of simulated data matrices demonstrate its advantages. These matrices include large and small samples from two partially overlapping species pools. In a cluster analysis, the widely used Dice coefficient and the Euclidean distance metric both create groupings that reflect sample size, the Simpson index suggests large differences that do not exist, and the corrected Forbes index creates groupings based strictly on true faunal overlap. In a principal coordinates analysis (PCoA) the Forbes index almost removes the sample-size signal but other approaches create a second axis strongly dominated by sample size. Meanwhile, species lists of late Pleistocene mammals from the United States capture biogeographic signals that standard ordination methods do recover, but the adjusted Forbes coefficient spaces the points out more sensibly. Finally, when biome-scale lists for living mammals are added to the data set and extinct species are removed, correspondence analysis misleadingly separates out the biome lists, and PCoA based on the Dice coefficient places them to the edge of the cloud of fossil assemblage data points. PCoA based on the Forbes index places them in more reasonable positions. Thus, only the adjusted Forbes index is able to recover true biological patterns. These results suggest that the index may be useful in analyzing not only paleontological data sets but any data set that includes species lists having highly variable lengths.

Phylogeny, paleontology, and primates: do incomplete fossils bias the tree of life?

Paleontological systematics relies heavily on morphological data that have undergone decay and fossilization. Here, we apply a heuristic means to assess how a fossil's incompleteness detracts from inferring its phylogenetic relationships. We compiled a phylogenetic matrix for primates and simulated the extinction of living species by deleting an extant taxon's molecular data and keeping only those morphological characters present in actual fossils. The choice of characters present in a given living taxon (the subject) was defined by those present in a given fossil (the template). By measuring congruence between a well-corroborated phylogeny to those incorporating artificial fossils, and by comparing real vs. random character distributions and states, we tested the information content of paleontological datasets and determined if extinction of a living species leads to bias in phylogeny reconstruction. We found a positive correlation between fossil completeness and topological congruence. Real fossil templates sampled for 36 or more of the 360 available morphological characters (including dental) performed significantly better than similarly complete templates with random states. Templates dominated by only one partition performed worse than templates with randomly sampled characters across partitions. The template based on the Eocene primate Darwinius masillae performs better than most other templates with a similar number of sampled characters, likely due to preservation of data across multiple partitions. Our results support the interpretation that Darwinius is strepsirhine, not haplorhine, and suggest that paleontological datasets are reliable in primate phylogeny reconstruction.

Mean annual precipitation explains spatiotemporal patterns of Cenozoic mammal beta diversity and latitudinal diversity gradients in North America.

Spatial diversity patterns are thought to be driven by climate-mediated processes. However, temporal patterns of community composition remain poorly studied. We provide two complementary analyses of North American mammal diversity, using (i) a paleontological dataset (2077 localities with 2493 taxon occurrences) spanning 21 discrete subdivisions of the Cenozoic based on North American Land Mammal Ages (36 Ma – present), and (ii) climate space model predictions for 744 extant mammals under eight scenarios of future climate change. Spatial variation in fossil mammal community structure (β diversity) is highest at intermediate values of continental mean annual precipitation (MAP) estimated from paleosols (∼450 mm/year) and declines under both wetter and drier conditions, reflecting diversity patterns of modern mammals. Latitudinal gradients in community change (latitudinal turnover gradients, aka LTGs) increase in strength through the Cenozoic, but also show a cyclical pattern that is significantly explained by MAP. In general, LTGs are weakest when continental MAP is highest, similar to modern tropical ecosystems in which latitudinal diversity gradients are weak or undetectable. Projections under modeled climate change show no substantial change in β diversity or LTG strength for North American mammals. Our results suggest that similar climate-mediated mechanisms might drive spatial and temporal patterns of community composition in both fossil and extant mammals. We also provide empirical evidence that the ecological processes on which climate space models are based are insufficient for accurately forecasting long-term mammalian response to anthropogenic climate change and inclusion of historical parameters may be essential.

Correction to ‘Phylogenetic evidence for a shift in the mode of mammalian body size evolution at the Cretaceous–Palaeogene boundary’, and a note on fitting macroevolutionary models to comparative paleontological data sets

SummaryIn this note, I correct two errors from an earlier paper that investigated tempo and mode of mammalian body size evolution across the Cretaceous‐Palaeogene boundary. Both errors arose from use of branch length rescaling under the Ornstein‐Uhlenbeck process, which I here show to be inappropriate for non‐ultrametric trees. Correction of these errors does not change the conclusions of my original study. However, recognition of the underlying problem highlights that comparative methods developed by biologists for examining trait evolution on ultrametric trees may not always be appropriate for paleontological datasets.

Were There Miocene Meridiolestidans? Assessing the Phylogenetic Placement of Necrolestes patagonensis and the Presence of a 40 Million Year Meridiolestidan Ghost Lineage

The enigmatic mammal Necrolestes patagonensis from the Miocene of Patagonia possesses a highly apomorphic osteological form that has confounded phylogenetic interpretation for over a century. In this time it has been affiliated with both eutherians and metatherians; however, a recent study by Rougier et al. (Proc Natl Acad Sci USA 109:19871–19872, 2012) raises the intriguing possibility that Necrolestes is a relictual member of a clade of South American non-therian dryolestoids, the Meridiolestida. This group is known chiefly from the Cretaceous of South America and assignment of Necrolestes to Meridiolestida implies a ghost lineage of about 40 million years. Such a lengthy ghost lineage requires strong evidence, which minimizes potentially circular assumptions of anatomical homology. Here, we vary the coding of cusp homologies in Necrolestes, previously assumed to diverge from the metatherian pattern, and add zalambdodont and incipiently zalambdodont metatherian taxa to the analyses, in order to assess the effects of non-independent characters and taxon sampling on the original topology. The results of both maximum parsimony and Bayesian analysis using the Mk model show that these possible sources of bias have little effect on the topology and ultimately increase confidence in the placement of Necrolestes in Meridiolestida and its concomitant 40 million year ghost lineage. Additionally, our Bayesian analysis resolves Australosphenida in a trichotomy with Peramus and Vincelestes + Boreosphenida. This contrasts with the majority of existing topologies, and raises interesting questions regarding both the evolution of tribospheny and the use of the Mk model with paleontological datasets.

Let your data run free? The challenge of data redaction in paleontological collections

Abstract The data associated with museum collections are essential components for many types of analysis. Geodetic information, such as latitude and longitude, in particular, are necessary in the analysis of paleontological data sets when investigating the effect of climate change on biodiversity. However, the release of geodetic information can be problematic when those data are used to deplete paleontological resources. This problem and others (such as overcollecting and impact on sensitive ecosystems) are discussed in all disciplines of natural history. Herein we discuss the problem as it pertains to paleontological collections, with particular reference to collections and digitization objectives in the USA, discuss strategies employed for data redaction, and make the case for allowing almost all locality data to be released in the interest of science and an obligation to the public.