Assesses the macroevolutionary turnover of paleotropical planktic graptolites during the Late Ordovician Mass Extinction (LOME) via automated sequencing and capture-mark-recapture modeling. Graptolites exhibited a succession of turnover pulses (sensu Elizabeth Vrba) that were coincident with the main phases of the Hirnantian glaciation and during which the Diplograptina experienced declining metapopulation size, elevated extinction, zero species originations, and ultimately, complete extermination. Concurrently, the Neograptina (latest Katian temperate zone immigrants) exhibit pulses of both extinction and adaptive radiation. Thus, the LOME involved intense species selection and the wholesale alteration of the clade diversity structure of a major element of the zooplankton. The LOME is unlikely to have been a direct effect of ocean anoxia or sampling bias but rather resulted from Hirnantian climate change, which altered nutrient supplies and plankton community compositions along with ecological displacement and loss of habitat that together drove the succession of turnover pulses. This title is also available as open access on Cambridge Core.

A uniform, high-resolution geological timescale is essential for studying Earth's history, including the dynamics of biodiversity and environmental change. Quantitative stratigraphy combines stratigraphic data with statistical and computational approaches into a global timescale that allows them to be correlated simultaneously. For example, Constrained Optimization (CONOP), built upon Graphic Correlation, sequences geological events to generate a composite sequence by resolving inconsistencies among stratigraphic records. However, CONOP determines only the global order of events (e.g., first or last appearances of species) and cannot assign ages to local records, e.g., a locally observed fossil occurrence. Horizon Annealing (HA) addresses this by using a simulated annealing algorithm to sequence sampling "horizons" while preserving local stratigraphic details. Here, we report HORizon SEquencing (HORSE), a generalized and optimized method for HA, with an implementation including parallel computing and genetic algorithms to enable fast, automatic stratigraphic correlation on large datasets. We evaluate HORSE, HA, and CONOP on three datasets-two empirical and one simulated-and assess their performance in terms of accuracy, efficiency, and robustness. HORSE greatly outperforms HA in computational efficiency and performs comparably to CONOP in event sequencing with greater robustness. Beyond constructing high-resolution geological timescales or life histories in deep time, HORSE uniquely preserves local stratigraphic information, enabling applications in palaeogeographical or palaeoecological studies, as well as evaluations of preservation and sampling biases-capabilities not possible with CONOP.

The inconclusive category in forensics reporting is the appropriate response in many cases, but it poses challenges in estimating an "error rate". We discuss the use of a class of information-theoretic measures related to cross entropy as an alternative set of metrics that allows for performance evaluation of results presented using multi-category reporting scales. This paper shows how this class of performance metrics, and in particular the log likelihood ratio cost, which is already in use with likelihood ratio forensic reporting methods and in machine learning communities, can be readily adapted for use with the widely used multiple category conclusions scales. Bayesian credible intervals on these metrics can be estimated using numerical methods. The application of these metrics to published test results is shown. It is demonstrated, using these test results, that reducing the number of categories used in a proficiency test from five or six to three increases the cross entropy, indicating that the higher number of categories was justified, as it they increased the level of agreement with ground truth.

There has been extensive recent discussion of the difficulty in estimating meaningful error rates in forensic firearms examinations, and other areas of pattern evidence. The 2016 President’s Council of Advisors on Science and Technology (PCAST) report was clear in criticizing many forensic disciplines as lacking the types of studies that would provide error rate measurements seen in other scientific fields. However, there is a substantial lack of consensus on the approach to measuring an “error rate” for fields such as forensic firearm examination that include in the conclusion scale the “inconclusive” category, as occurs in the Association of Firearm and Tool Mark Examiners (AFTE) Range of Conclusions and many other such fields. Many authors appear to assume the error rate calculated in the binary decision model is the only appropriate way to report errors, but there have been attempts made to adapt the error rate from the binary decision model to scientific fields in which the inconclusive category is viewed as a meaningful outcome of the examination process. In this study we present three neural networks of differing complexity and performance trained to classify the outlines of ejector marks on cartridge cases fired from different firearm models, as a model system for examining the performance of various metrics of error in systems using the inconclusive category. We also discuss an entropy, or information, based method to assess the similarity of classifications to ground truth that is applicable to range of conclusion scales, even when the inconclusive category is used.

AbstractThe symbiotic relationship between dinoflagellate algae in the family Symbiodiniaceae and scleractinian corals forms the base of the tropical reef ecosystem. In scleractinian corals, recruits acquire symbionts either “vertically” from the maternal colony or initially lack symbionts and acquire them “horizontally” from the environment. Regardless of the mode of acquisition, coral species and individual colonies harbor only a subset of the highly diverse complex of species/taxa within the Symbiodiniaceae. This suggests a genetic basis for specificity, but local environmental conditions and/or symbiont availability may also play a role in determining which symbionts within the Symbiodiniaceae are initially taken up by the host. To address the relative importance of genetic and environmental drivers of symbiont uptake/establishment, we examined the acquisition of these dinoflagellate symbionts in one to three‐month‐old recruits of Orbicella faveolata to compare symbiont types present in recruits to those of parental populations versus co‐occurring adults in their destination reef. Variation in chloroplast 23S ribosomal DNA and in three polymorphic microsatellite loci was examined. We found that, in general, symbiont communities within adult colonies differed between reefs, suggesting that endemism is common among symbiont populations of O. faveolata on a local scale. Among recruits, initial symbiont acquisition was selective. O. faveolata recruits only acquired a subset of locally available symbionts, and these generally did not reflect symbiont populations in adults at either the parental or the outplant reef. Instead, symbiont communities within new recruits at a given outplant site and region tended to be similar to each other, regardless of parental source population. These results suggest temporal variation in the local symbiont source pool, although other possible drivers behind the distinct difference between symbionts within O. faveolata adults and new generations of recruits may include different ontogenetic requirements and/or reduced host selectivity in early ontogeny.

This paper presents a new quantitative approach to the study of Asian lacquers using surface metrology, and two data science approaches: feature engineering and convolutional deep neural networks, as used in machine vision or image recognition applications. The types of Asian lacquers and additives have a quantifiable impact on the topography of the resulting surface. To understand the unaged and aged characteristics, 15 different formulas of Asian lacquer were prepared using laccol, thitsiol and urushiol with the most common additives: oils, pigments and resins. These were studied with the surface metrology instrumental technique of confocal microscopy.

While type determination on bullets has been performed for over a century, type determination on cartridge cases is often overlooked. Presented here is an example of type determination of ejector marks on cartridge cases from Glock and Smith & Wesson Sigma series pistols using Naïve Bayes and Random Forest classification methods. The shapes of ejector marks were captured from images of test‐fired cartridge cases and subjected to multivariate analysis. Naïve Bayes and Random Forest methods were used to assign the ejector shapes to the correct class of firearm with success rates as high as 98%. This method is easily implemented with equipment already available in crime laboratories and can serve as an investigative lead in the form of a list of firearms that could have fired the evidence. Paired with the FBI's General Rifling Characteristics (GRC) database, this could be an invaluable resource for firearm evidence at crime scenes.

Although extinction risk has been found to have a consistent negative relationship with geographic range across wide temporal and taxonomic scales, the effect has been difficult to disentangle from factors such as sampling, ecological niche, or clade. In addition, studies of extinction risk have focused on benthic invertebrates with less work on planktic taxa. We employed a global set of 1114 planktic graptolite species from the Ordovician to lower Devonian to analyze the predictive power of species' traits and abiotic factors on extinction risk, combining general linear models (GLMs), partial least-squares regression (PLSR), and permutation tests. Factors included measures of geographic range, sampling, and graptolite-specific factors such as clade, biofacies affiliation, shallow water tolerance, and age cohorts split at the base of the Katian and Rhuddanian stages.The percent variance in durations explained varied substantially between taxon subsets from 12% to 45%. Overall commonness, the correlated effects of geographic range and sampling, was the strongest, most consistent factor (12-30% variance explained), with clade and age cohort adding up to 18% and other factors <10%. Surprisingly, geographic range alone contributed little explanatory power (<5%). It is likely that this is a consequence of a nonlinear relationship between geographic range and extinction risk, wherein the largest reductions in extinction risk are gained from moderate expansion of small geographic ranges. Thus, even large differences in range size between graptolite species did not lead to a proportionate difference in extinction risk because of the large average ranges of these species. Finally, we emphasize that the common practice of determining the geographic range of taxa from the union of all occurrences over their duration poses a substantial risk of overestimating the geographic scope of the realized ecological niche and, thus, of further conflating sampling effects on observed duration with the biological effects of range size on extinction risk.

We introduce the partial least squares (PLS) statistical analysis that quantifies and predicts the observed relationships among normal fault slip, fracturing associated with the fault, and lithology. We describe the systematic process for constructing a multivariate PLS model that predicts the average fracture frequency and the width of fracture-dominated fault damage zones from fault, lithologic and fracture data. Conversely, the model can also predict normal fault net slip for a defined lithology given the average fracture frequency and width of a fracture-dominated fault damage zone, hereafter defined as a fracture intensification domain (FID). Fracture, fault and lithologic data were collected in the Mohawk Valley of New York State from outcrops in the Upper Ordovician Utica Group and Lorraine Group. Data collection was focused on faults with observable slip, associated FIDs, and no observable lateral restriction. Our statistical analysis used three variables to describe the geometry of the FID: FID width (FIDw), average fracture frequency within the FID (FIDƒ), and the power law regression exponent (FIDR) of the least squares trend line. We incorporated additional data from literature and tested multiple PLS models in order to refine the analysis using quality indicators provided by the PLS summary statistics output. Variables included in the final predictive model included FIDw, FIDƒ, fault slip, grain size and clay percent. Fault slip and grain size were found to have a positive covariance with FIDw while clay percent had a negative covariance. Fault slip, grain size and clay percent all showed a negative covariance with FIDƒ. Results from this research indicate that increasing fault slip leads to wider FIDs and lower average fracture frequency within the FID. The lower average fracture frequency in wider FIDs is primarily attributed to an increase in the length of the low-frequency FID tail away from the associated fault. A possible secondary influence reducing fracture frequency is due to the progressive development of a fault core at the expense of the adjacent damage zone and the consumption of the highest-frequency fractures adjacent to the fault surface.

Horizon annealing (HA) provides a method to order all horizons in a chronostratigraphic data set, including marker beds and isotopic excursions, as well as horizons that lack exact local markers (such as taxon first appearances) and are, thus, constrained only by local stratigraphical order. Global stratotype section and point (GSSP) levels placed within an HA composite succession can be precisely correlated with levels in all other sections in the composite that span the same interval. We present two approaches to the quantitative assessment of the uncertainty or error in the placement of horizons within the composite section: a permutation method (jackknife analysis) and a sensitivity analysis (the relaxed fit curve). From jackknife analysis, we calculate a standard deviation (sigma) of the variation in horizon placements and estimate the 95% confidence interval of the variation in horizon placement within the composite. We also directly assess the relative stability of event positions using the results of the jackknife. These approaches provide an objective method for assessing the relative strengths of GSSP candidates, in which we prefer those sections and horizons that are the most precisely controlled in the HA composite. Integration of biostratigraphical, chemostratigraphical and lithostratigraphical marker horizons into the HA process markedly improves levels of constraint within the composite compared to biostratigraphical data alone. In a temporally scaled composite, the 95% confidence intervals on horizon placements could be used to estimate temporal resolution. In our study, we estimate that the average temporal resolution is approximately 319 kyr, which approaches the range of that needed to test hypotheses of orbitally driven cyclicity.

Comparative Bullet Lead Analysis (CBLA) was discredited as a forensic discipline largely due to the absence of cross-discipline input, primarily metallurgical and statistical, during development and forensic/judicial application of the practice. Of particular significance to the eventual demise of CBLA practice was ignorance of the role of statistics in assessing probative value of claimed bullet "matches" at both the production and retail distribution levels, leading to overstated testimonial claims by expert witnesses. Bitemark comparisons have come under substantial criticism in the last few years, both due to exonerations based on DNA evidence and to research efforts questioning the claimed uniqueness of bitemarks. The fields of fire and arson investigation and of firearm and toolmark comparison are similar to CBLA and bitemarks in the absence of effective statistical support for these practices. The features of the first two disciplines are examined in systemic detail to enhance understanding as to why they became discredited forensic practices, and to identify aspects of the second two disciplines that pose significant concern to critics.

Significance Climate change during Late Ordovician mass extinction drove an ecologically selective decline in the abundance of deep-water macrozooplankton, accompanied by a shift to simpler, less even communities. These results indicate that the species abundance structure of planktic communities may be a leading indicator of the effects of climate change on biodiversity and a more sensitive gauge of those effects than taxonomic diversity change alone. Additionally, we present a Bayesian likelihood method of habitat inference that may be applicable to other similar cases.

Males of sibling orchid bees Euglossa viridissima and Euglossa dilemma are morphologically cryptic, except for the number and shape of mandibular teeth. An alternative morph of E. viridissima has a third tooth similar to males of E. dilemma . We used this model system to evaluate the potential of wing morphometrics for the resolution of these groups. We found differences in the size characters of forewings of E. viridissima and E. dilemma albeit with substantial overlapping amongst them. However, geometric morphometrics of forewing vein intersections separated both species and, to a lesser extent, morphotypes. A discriminant analysis of the shape of the radial cell showed separation between all three groups, too, albeit with higher misclassification between E. viridissima and E. dilemma . We show that sibling cryptic species and morphotypes can be identified by geometric morphometrics, supporting its application with other methods as powerful aids to infrageneric taxonomy in bees.