Multiple outgroups can cause random rooting in phylogenomics.

Outgroup selection has been a major challenge since the rise of phylogenetics, and it has remained so in the phylogenomic era. Our goal here is to use large phylogenomic animal datasets to examine the impact of outgroup selection on the final topology. The results of our analyses further solidify the fact that distant outgroups can cause random rooting, and that this holds for concatenated and coalescent-based methods. The results also indicate that the standard practice of using multiple outgroups often causes random rooting. Most researchers go out of their way to get multiple outgroups, as this has been standard practice for decades. Based on our findings, this practice should stop. Instead, our results suggest that a single (most closely) related relative should be selected as the outgroup, unless all outgroups are roughly equally closely related to the ingroup.

Rewilding in Miniature: Suburban Meadows Can Improve Soil Microbial Biodiversity and Soil Health.

Lawns are a ubiquitous, human-made environment created for human enjoyment, leisure, and aesthetics. While net positive for carbon storage, lawns can have negative environmental impacts. Lawns require frequent mowing, which produces high levels of CO2 pollution and kills off native plants. Lawn fertilizing creates its own environmental pollution. One (presumed) ecologically-friendly alternative to lawns is restoration, or rewilding, of these spaces as meadows, which need less maintenance (e.g., infrequent mowing). However, little work has compared lawns against small-scale meadows for biodiversity outside of pollinator studies. Here, we tested the hypotheses that compared to lawns, meadows have (1) unique and higher levels of soil microbial biodiversity and (2) different soil physical and chemical characteristics. We conducted bacterial (16S) and fungal (ITS2) metabarcoding, and found that both bacteria and fungi are indeed more diverse in meadows (significantly so for bacteria). Species composition between meadows and lawns was significantly different for both types of microbes, including higher levels of mycorrhizal fungi in meadows. We also found that chemistry (e.g., potassium and metrics relating to pH) differed significantly between lawns and meadows and was more optimal for plant growth in the meadows. We believe these differences are caused by the different organisms dwelling in these habitats. In summary, these findings point to notable-positive-shifts in microbial and chemical compositions within meadows, further indicating that meadow restoration benefits biodiversity and soil health.

An Environmental DNA Primer for Microbial and Restoration Ecology.

Environmental DNA (eDNA) sequencing-DNA collected from the environment from living cells or shed DNA-was first developed for working with microbes and has greatly benefitted microbial ecologists for decades since. These tools have only become increasingly powerful with the advent of metabarcoding and metagenomics. Most new studies that examine diverse assemblages of bacteria, archaea, protists, fungi, and viruses lean heavily into eDNA using these newer technologies, as the necessary sequencing technology and bioinformatic tools have become increasingly affordable and user friendly. However, eDNA methods are rapidly evolving, and sometimes it can feel overwhelming to simply keep up with the basics. In this review, we provide a starting point for microbial ecologists who are new to DNA-based methods by detailing the eDNA methods that are most pertinent, including study design, sample collection and storage, selecting the right sequencing technology, lab protocols, equipment, and a few bioinformatic tools. Furthermore, we focus on how eDNA work can benefit restoration and what modifications are needed when working in this subfield.

An individual differences perspective on pragmatic abilities in the preschool years.

Pragmatic abilities are fundamental to successful language use and learning. Individual differences studies contribute to understanding the psychological processes involved in pragmatic reasoning. Small sample sizes, insufficient measurement tools, and a lack of theoretical precision have hindered progress, however. Three studies addressed these challenges in three- to 5-year-old German-speaking children (N = 228, 121 female). Studies 1 and 2 assessed the psychometric properties of six pragmatics tasks. Study 3 investigated relations among pragmatics tasks and between pragmatics and other cognitive abilities. The tasks were found to measure stable variation between individuals. Via a computational cognitive model, individual differences were traced back to a latent pragmatics construct. This presents the basis for understanding the relations between pragmatics and other cognitive abilities. RESEARCH HIGHLIGHTS: Individual differences in pragmatic abilities are important to understanding variation in language development. Research in this domain lacks a precise theoretical framework and psychometrically high-quality measures. We present six tasks capturing a wide range of pragmatic abilities with excellent re-test reliability. We use a computational cognitive model to provide a substantive theory of individual differences in pragmatic abilities.

Morphological Characters Can Strongly Influence Early Animal Relationships Inferred from Phylogenomic Data Sets.

There are considerable phylogenetic incongruencies between morphological and phylogenomic data for the deep evolution of animals. This has contributed to a heated debate over the earliest-branching lineage of the animal kingdom: the sister to all other Metazoa (SOM). Here, we use published phylogenomic data sets ($\sim $45,000-400,000 characters in size with $\sim $15-100 taxa) that focus on early metazoan phylogeny to evaluate the impact of incorporating morphological data sets ($\sim $15-275 characters). We additionally use small exemplar data sets to quantify how increased taxon sampling can help stabilize phylogenetic inferences. We apply a plethora of common methods, that is, likelihood models and their "equivalent" under parsimony: character weighting schemes. Our results are at odds with the typical view of phylogenomics, that is, that genomic-scale data sets will swamp out inferences from morphological data. Instead, weighting morphological data 2-10$\times $ in both likelihood and parsimony can in some cases "flip" which phylum is inferred to be the SOM. This typically results in the molecular hypothesis of Ctenophora as the SOM flipping to Porifera (or occasionally Placozoa). However, greater taxon sampling improves phylogenetic stability, with some of the larger molecular data sets ($>$200,000 characters and up to $\sim $100 taxa) showing node stability even with $\geqq100\times $ upweighting of morphological data. Accordingly, our analyses have three strong messages. 1) The assumption that genomic data will automatically "swamp out" morphological data is not always true for the SOM question. Morphological data have a strong influence in our analyses of combined data sets, even when outnumbered thousands of times by molecular data. Morphology therefore should not be counted out a priori. 2) We here quantify for the first time how the stability of the SOM node improves for several genomic data sets when the taxon sampling is increased. 3) The patterns of "flipping points" (i.e., the weighting of morphological data it takes to change the inferred SOM) carry information about the phylogenetic stability of matrices. The weighting space is an innovative way to assess comparability of data sets that could be developed into a new sensitivity analysis tool. [Metazoa; Morphology; Phylogenomics; Weighting.].

Selection, drift, and constraint in cypridinid luciferases and the diversification of bioluminescent signals in sea fireflies.

Understanding the genetic causes of evolutionary diversification is challenging because differences across species are complex, often involving many genes. However, cases where single or few genetic loci affect a trait that varies dramatically across a radiation of species provide tractable opportunities to understand the genetics of diversification. Here, we begin to explore how diversification of bioluminescent signals across species of cypridinid ostracods ("sea fireflies") was influenced by evolution of a single gene, cypridinid-luciferase. In addition to emission spectra ("colour") of bioluminescence from 21 cypridinid species, we report 13 new c-luciferase genes from de novo transcriptomes, including in vitro assays to confirm function of four of those genes. Our comparative analyses suggest some amino acid sites in c-luciferase evolved under episodic diversifying selection and may be associated with changes in both enzyme kinetics and colour, two enzymatic functions that directly impact the phenotype of bioluminescent signals. The analyses also suggest multiple other amino acid positions in c-luciferase evolved neutrally or under purifying selection, and may have impacted the variation of colour of bioluminescent signals across genera. Previous mutagenesis studies at candidate sites show epistatic interactions, which could constrain the evolution of c-luciferase function. This work provides important steps toward understanding the genetic basis of diversification of behavioural signals across multiple species, suggesting different evolutionary processes act at different times during a radiation of species. These results set the stage for additional mutagenesis studies that could explicitly link selection, drift, and constraint to the evolution of phenotypic diversification.

Privileged Functional Connectivity between the Visual Word Form Area and the Language System.

The visual word form area (VWFA) is a region in the left occipitotemporal sulcus of literate individuals that is purportedly specialized for visual word recognition. However, there is considerable controversy about its functional specificity and connectivity, with some arguing that it serves as a domain-general, rather than word-specific, visual processor. The VWFA is a critical region for testing hypotheses about the nature of cortical organization, because it is known to develop only through experience (i.e., reading acquisition), and widespread literacy is too recent to have influenced genetic determinants of brain organization. Using a combination of advanced fMRI analysis techniques, including individual functional localization, multivoxel pattern analysis, and high-resolution resting-state functional connectivity (RSFC) analyses, with data from 33 healthy adult human participants, we demonstrate that (1) the VWFA can discriminate words from nonword letter strings (pseudowords); (2) the VWFA has preferential RSFC with Wernicke's area and other core regions of the language system; and (3) the strength of the RSFC between the VWFA and Wernicke's area predicts performance on a semantic classification task with words but not other categories of visual stimuli. Our results are consistent with the hypothesis that the VWFA is specialized for lexical processing of real words because of its functional connectivity with Wernicke's area.SIGNIFICANCE STATEMENT The visual word form area (VWFA) is critical for determining the nature of category-related organization of the ventral visual system. However, its functional specificity and connectivity are fiercely debated. Recent work concluded that the VWFA is a domain-general, rather than word-specific, visual processor with no preferential functional connectivity with the language system. Using more advanced techniques, our results stand in stark contrast to these earlier findings. We demonstrate that the VWFA is highly specialized for lexical processing of real words, and that a fundamental factor driving this specialization is its preferential intrinsic functional connectivity with core regions of the language system. Our results support the hypothesis that intrinsic functional connectivity contributes to category-related specialization within the human ventral visual system.

Worms that suck: Phylogenetic analysis of Hirudinea solidifies the position of Acanthobdellida and necessitates the dissolution of Rhynchobdellida.

Annelids possessing a posterior sucker and a fixed number of somites - most famously leeches (Hirudinida), but also crayfish worms (Branchiobdellida) and salmonid parasites (Acanthobdellida) - form a clade; however, determining the relationships between these orders has proven challenging. Here, we compile the largest molecular phylogenetic dataset yet analysed for these groups, including new sequences for key taxa. We find robust model-based support for a clade formed by Hirudinida and Acanthobdellida, contrasting the largest prior studies. We determine that conflicting prior studies included contaminant sequences for Acanthobdella peledina. In addition to this broad-scale comparison, the size of our dataset grants us invaluable insight into the internal relationships of leeches and crayfish worms. Of particular importance, a largely marine clade of leeches (Piscicolidae and Ozobranchidae) is recovered as sister to all remaining Hirudinida. This necessitates the dissolution of the paraphyletic suborder Rhynchobdellida into two new suborders (Oceanobdelliformes and Glossiphoniiformes). Likewise, we decompose Arhynchobdellida into its respective suborders: Hirudiniformes, Erpobdelliformes, and the new, monotypic, Americobdelliformes.

A Bayesian decision-making framework for replication.

Replication is the cornerstone of science - but when and why? Not all studies need replication, especially when resources are limited. We propose that a decision-making framework based on Bayesian philosophy of science provides a basis for choosing which studies to replicate.

Phylogenetic analysis of Placobdella (Hirudinea: Rhynchobdellida: Glossiphoniidae) with consideration of COI variation.

Placobdella is a genus of blood-feeding leeches in the family Glossiphoniidae. Historically, species of Placobdella have posed difficulty for systematists owing to a lack of informative morphological characters and the preponderance of inadequate or incomplete species descriptions. Here, we conduct a phylogenetic analysis of 55 individuals representing 20 of the 24 currently recognized nominal taxa using COI, ND1, 12S rDNA and ITS sequences under parsimony, maximum likelihood and Bayesian inference. We also examine the isolated COI phylogeny for the genus using an expanded dataset encompassing three additional species not included in the concatenated dataset. Finally, we assess genetic variation at the COI locus to validate initial specimen identifications and estimate how COI variation may reflect species boundaries. We conclude that Placobdella is a monophyletic group that places as the sister group to a clade formed by the genera Haementeria and Helobdella. We discuss the evolutionary implications of several internal relationships that are robustly resolved by all three optimality criteria, paying particular attention to the apparent fluidity of morphological characters exhibited by members of Placobdella. We also find preliminary evidence for the presence of cryptic and undescribed diversity within the genus.

A Global eDNA Comparison of Freshwater Bacterioplankton Assemblages Focusing on Large-River Floodplain Lakes of Brazil.

With its network of lotic and lentic habitats that shift during changes in seasonal connection, the tropical and subtropical large-river systems represent possibly the most dynamic of all aquatic environments. Pelagic water samples were collected from Brazilian floodplain lakes (total n = 58) in four flood-pulsed systems (Amazon [n = 21], Araguaia [n = 14], Paraná [n = 15], and Pantanal [n = 8]) in 2011-2012 and sequenced via 454 for bacterial environmental DNA using 16S amplicons; additional abiotic field and laboratory measurements were collected for the assayed lakes. We report here a global comparison of the bacterioplankton makeup of freshwater systems, focusing on a comparison of Brazilian lakes with similar freshwater systems across the globe. The results indicate a surprising similarity at higher taxonomic levels of the bacterioplankton in Brazilian freshwater with global sites. However, substantial novel diversity at the family level was also observed for the Brazilian freshwater systems. Brazilian freshwater bacterioplankton richness was relatively average globally. Ordination results indicate that Brazilian bacterioplankton composition is unique from other areas of the globe. Using Brazil-only ordinations, floodplain system differentiation most strongly correlated with dissolved oxygen, pH, and phosphate. Our data on Brazilian freshwater systems in combination with analysis of a collection of freshwater environmental samples from across the globe offers the first regional picture of bacterioplankton diversity in these important freshwater systems.

Avoiding frostbite: It helps to learn from others.

Machines that learn and think like people must be able to learn from others. Social learning speeds up the learning process and - in combination with language - is a gateway to abstract and unobservable information. Social learning also facilitates the accumulation of knowledge across generations, helping people and artificial intelligences learn things that no individual could learn in a lifetime.

Functional connectivity constrains the category-related organization of human ventral occipitotemporal cortex.

One of the most robust and oft-replicated findings in cognitive neuroscience is that several spatially distinct, functionally dissociable ventral occipitotemporal cortex (VOTC) regions respond preferentially to different categories of concrete entities. However, the determinants of this category-related organization remain to be fully determined. One recent proposal is that privileged connectivity of these VOTC regions with other regions that store and/or process category-relevant properties may be a major contributing factor. To test this hypothesis, we used a multicategory functional magnetic resonance imaging (MRI) localizer to individually define category-related brain regions of interest (ROIs) in a large group of subjects (n = 33). We then used these ROIs in resting-state functional connectivity MRI analyses to explore spontaneous functional connectivity among these regions. We demonstrate that during rest, distinct category-preferential VOTC regions show differentially stronger functional connectivity with other regions that have congruent category-preference, as defined by the functional localizer. Importantly, a "tool"-preferential region in the left medial fusiform gyrus showed differentially stronger functional connectivity with other left lateralized cortical regions associated with perceiving and knowing about common tools-posterior middle temporal gyrus (involved in perception of nonbiological motion), lateral parietal cortex (critical for reaching, grasping, manipulating), and ventral premotor cortex (involved in storing/executing motor programs)-relative to other category-related regions in VOTC of both the right and left hemisphere. Our findings support the claim that privileged connectivity with other cortical regions that store and/or process category-relevant properties constrains the category-related organization of VOTC.

Environmental DNA Isolation, Validation, and Preservation Methods.

Environmental DNA (eDNA) workflows contain many familiar molecular-lab techniques, but also employ several unique methodologies. When working with eDNA, it is essential to avoid contamination from the point of collection through preservation and select a meaningful negative control. As eDNA can be obtained from a variety of samples and habitats (e.g., soil, water, air, or tissue), protocols will vary depending on usage. Samples may require additional steps to dilute, block, or remove inhibitors or physically break up samples or filters. Thereafter, standard DNA isolation techniques (kit-based or phenol:chloroform:isoamyl [PCI]) are employed. Once DNA is extracted, it is typically quantified using a fluorometer. Yields vary greatly, but are important to know prior to amplification of the gene(s) of interest. Long-term storage of both the sampled material and the extracted DNA is encouraged, as it provides a backup for spilled/contaminated samples, lost data, reanalysis, and future studies using newer technology. Storage in a freezer is often ideal; however, some storage buffers (e.g., Longmires) require that filters or swabs are kept at room temperature to prevent precipitation of buffer-related solutes. These baseline methods for eDNA isolation, validation, and preservation are detailed in this protocol chapter. In addition, we outline a cost-effective, homebrew extraction protocol optimized to extract eDNA.

Association between anesthesiologist age and litigation.

BACKGROUND: : The threat of being sued is a concern for many anesthesiologists. This paper asks whether litigation brought against anesthesiologists is associated with the age of the anesthesiologist. METHODS: : Institutional research ethics approval was granted. We obtained billing data for all procedures performed by specialist anesthesiologists stratified into three age groups (less than 51, 51-64, and 65 and older) from British Columbia, Quebec, and Ontario for the 10-yr period from Jan. 1, 1993 to Dec. 31, 2002. We also obtained all litigations (including disability weighted claims) handled by the Canadian Medical Protective Association during the same time period in which the Canadian Medical Protective Association experts considered the anesthesiologist cited to be at least partially responsible for the adverse event leading to the complaint. RESULTS: : In univariate analysis with the less than 51 age group as the reference category, the litigation rate ratio for the 51-64 age group was 1.14 (95% CI: 0.99-1.32) and for the 65 and older age group was 1.50 (95% CI: 1.14-1.97). Our analyses using disability weighted claims showed the 51-64 group to have 1.31 (95% CI: 0.95-1.80) and 65 and older group to have 1.94 (95% CI: 1.41-2.67) relative increase in disability compared to the less than 51 age group. CONCLUSIONS: : We found a higher frequency of litigation and a greater severity of injury in patients treated by anesthesiologists in the 65 and older group. The reasons for these findings should become an active field of research.

Logic, Probability, and Pragmatics in Syllogistic Reasoning.

Syllogistic reasoning lies at the intriguing intersection of natural and formal reasoning of language and logic. Syllogisms comprise a formal system of reasoning yet make use of natural language quantifiers (e.g., all, some) and invite natural language conclusions. The conclusions people tend to draw from syllogisms, however, deviate substantially from the purely logical system. Are principles of natural language understanding to blame? We introduce a probabilistic pragmatic perspective on syllogistic reasoning: We decompose reasoning with natural language arguments into two subproblems: language comprehension and language production. We formalize models of these processes within the Rational Speech Act framework and explore the pressures that pragmatic reasoning places on the production of conclusions. We test our models on a recent, large data set of syllogistic reasoning and find that the selection process of conclusions from syllogisms are best modeled as a pragmatic speaker who has the goal of aligning the beliefs of a naive listener with those of their own. We compare our model to previously published models that implement two alternative theories-Mental Models and Probability Heuristics-finding that our model quantitatively predicts the full distributions of responses as well as or better than previous accounts, but with far fewer parameters. Our results suggest that human syllogistic reasoning may be best understood not as a poor approximation to ideal logical reasoning, but rather as rational probabilistic inference in support of natural communication.

Warm (for Winter): Inferring Comparison Classes in Communication.

The meanings of natural language utterances depend heavily on context. Yet, what counts as context is often only implicit in conversation. The utterance it's warm outside signals that the temperature outside is relatively high, but the temperature could be high relative to a number of different comparison classes: other days of the year, other weeks, other seasons, etc. Theories of context sensitivity in language agree that the comparison class is a crucial variable for understanding meaning, but little is known about how a listener decides upon the comparison class. Using the case study of gradable adjectives (e.g., warm), we extend a Bayesian model of pragmatic inference to reason flexibly about the comparison class and test its qualitative predictions in a large-scale free-production experiment. We find that human listeners infer the comparison class by reasoning about the kinds of observations that would be remarkable enough for a speaker to mention, given the speaker and listener's shared knowledge of the world. Further, we quantitatively synthesize the model and data using Bayesian data analysis, which reveals that usage frequency and a preference for basic-level categories are two main factors in comparison class inference. This work presents new data and reveals the mechanisms by which human listeners recover the relevant aspects of context when understanding language.

Great ape communication as contextual social inference: a computational modelling perspective.

Human communication has been described as a contextual social inference process. Research into great ape communication has been inspired by this view to look for the evolutionary roots of the social, cognitive and interactional processes involved in human communication. This approach has been highly productive, yet it is partly compromised by the widespread focus on how great apes use and understand individual signals. This paper introduces a computational model that formalizes great ape communication as a multi-faceted social inference process that integrates (a) information contained in the signals that make up an utterance, (b) the relationship between communicative partners and (c) the social context. This model makes accurate qualitative and quantitative predictions about real-world communicative interactions between semi-wild-living chimpanzees. When enriched with a pragmatic reasoning process, the model explains repeatedly reported differences between humans and great apes in the interpretation of ambiguous signals (e.g. pointing or iconic gestures). This approach has direct implications for observational and experimental studies of great ape communication and provides a new tool for theorizing about the evolution of uniquely human communication. This article is part of the theme issue 'Revisiting the human 'interaction engine': comparative approaches to social action coordination'.

Predicting pragmatic cue integration in adults' and children's inferences about novel word meanings.

Language is learned in complex social settings where listeners must reconstruct speakers' intended meanings from context. To navigate this challenge, children can use pragmatic reasoning to learn the meaning of unfamiliar words. A critical challenge for pragmatic reasoning is that it requires integrating multiple information sources, which have typically been studied separately. Here we study this integration process. First, we experimentally isolate two sources of pragmatic information: expectations about informative communication and common ground. Next, we use a probabilistic model of conversational reasoning to formalize how these information sources should be combined and how this process might develop. We use this model to generate quantitative predictions, which we test against new experimental data from 3- to 5-year-old children (N = 243) and adults (N = 694). Results show close alignment between model predictions and data. Furthermore, the model provided a better explanation of the data compared with simpler alternative models assuming that participants selectively ignore one information source. This work integrates distinct sets of findings regarding information sources for early language learning and suggests that pragmatic reasoning models can provide a quantitative framework for understanding developmental changes in language learning. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Modeling Individual Differences in Children's Information Integration During Pragmatic Word Learning.

Pragmatics is foundational to language use and learning. Computational cognitive models have been successfully used to predict pragmatic phenomena in adults and children - on an aggregate level. It is unclear if they can be used to predict behavior on an individual level. We address this question in children (N = 60, 3- to 5-year-olds), taking advantage of recent work on pragmatic cue integration. In Part 1, we use data from four independent tasks to estimate child-specific sensitivity parameters to three information sources: semantic knowledge, expectations about speaker informativeness, and sensitivity to common ground. In Part 2, we use these parameters to generate participant-specific trial-by-trial predictions for a new task that jointly manipulated all three information sources. The model accurately predicted children's behavior in the majority of trials. This work advances a substantive theory of individual differences in which the primary locus of developmental variation is sensitivity to individual information sources.