Ctenophores are direct developers that reproduce continuously beginning very early after hatching.

A substantial body of literature reports that ctenophores exhibit an apparently unique life history characterized by biphasic sexual reproduction, the first phase of which is called larval reproduction or dissogeny. Whether this strategy is plastically deployed or a typical part of these species' life history was unknown. In contrast to previous reports, we show that the ctenophore Mnemiopsis leidyi does not have separate phases of early and adult reproduction, regardless of the morphological transition to what has been considered the adult form. Rather, these ctenophores begin to reproduce at a small body size and spawn continuously from this point onward under adequate environmental conditions. They do not display a gap in productivity for metamorphosis or other physiological transition at a certain body size. Furthermore, nutritional and environmental constraints on fecundity are similar in both small and large animals. Our results provide critical parameters for understanding resource partitioning between growth and reproduction in this taxon, with implications for management of this species in its invaded range. Finally, we report an observation of similarly small-size spawning in a beroid ctenophore, which is morphologically, ecologically, and phylogenetically distinct from other ctenophores reported to spawn at small sizes. We conclude that spawning at small body size should be considered as the default, on-time developmental trajectory rather than as precocious, stress-induced, or otherwise unusual for ctenophores. The ancestral ctenophore was likely a direct developer, consistent with the hypothesis that multiphasic life cycles were introduced after the divergence of the ctenophore lineage.

Correction: Convergent evolution of diverse Bacillus anthracis outbreak strains toward altered surface oligosaccharides that modulate anthrax pathogenesis.

[This corrects the article DOI: 10.1371/journal.pbio.3001052.].

Convergent evolution of diverse Bacillus anthracis outbreak strains toward altered surface oligosaccharides that modulate anthrax pathogenesis.

Bacillus anthracis, a spore-forming gram-positive bacterium, causes anthrax. The external surface of the exosporium is coated with glycosylated proteins. The sugar additions are capped with the unique monosaccharide anthrose. The West African Group (WAG) B. anthracis have mutations rendering them anthrose deficient. Through genome sequencing, we identified 2 different large chromosomal deletions within the anthrose biosynthetic operon of B. anthracis strains from Chile and Poland. In silico analysis identified an anthrose-deficient strain in the anthrax outbreak among European heroin users. Anthrose-deficient strains are no longer restricted to West Africa so the role of anthrose in physiology and pathogenesis was investigated in B. anthracis Sterne. Loss of anthrose delayed spore germination and enhanced sporulation. Spores without anthrose were phagocytized at higher rates than spores with anthrose, indicating that anthrose may serve an antiphagocytic function on the spore surface. The anthrose mutant had half the LD50 and decreased time to death (TTD) of wild type and complement B. anthracis Sterne in the A/J mouse model. Following infection, anthrose mutant bacteria were more abundant in the spleen, indicating enhanced dissemination of Sterne anthrose mutant. At low sample sizes in the A/J mouse model, the mortality of ΔantC-infected mice challenged by intranasal or subcutaneous routes was 20% greater than wild type. Competitive index (CI) studies indicated that spores without anthrose disseminated to organs more extensively than a complemented mutant. Death process modeling using mouse mortality dynamics suggested that larger sample sizes would lead to significantly higher deaths in anthrose-negative infected animals. The model was tested by infecting Galleria mellonella with spores and confirmed the anthrose mutant was significantly more lethal. Vaccination studies in the A/J mouse model showed that the human vaccine protected against high-dose challenges of the nonencapsulated Sterne-based anthrose mutant. This work begins to identify the physiologic and pathogenic consequences of convergent anthrose mutations in B. anthracis.

Coalescence modeling of intrainfection Bacillus anthracis populations allows estimation of infection parameters in wild populations.

Bacillus anthracis, the etiological agent of anthrax, is a well-established model organism. For B. anthracis and most other infectious diseases, knowledge regarding transmission and infection parameters in natural systems, in large part, comprises data gathered from closely controlled laboratory experiments. Fatal, natural anthrax infections transmit the bacterium through new host-pathogen contacts at carcass sites, which can occur years after death of the previous host. For the period between contact and death, all of our knowledge is based upon experimental data from domestic livestock and laboratory animals. Here we use a noninvasive method to explore the dynamics of anthrax infections, by evaluating the terminal diversity of B. anthracis in anthrax carcasses. We present an application of population genetics theory, specifically, coalescence modeling, to intrainfection populations of B. anthracis to derive estimates for the duration of the acute phase of the infection and effective population size converted to the number of colony-forming units establishing infection in wild plains zebra (Equus quagga). Founding populations are small, a few colony-forming units, and infections are rapid, lasting roughly between 1 d and 3 d in the wild. Our results closely reflect experimental data, showing that small founding populations progress acutely, killing the host within days. We believe this method is amendable to other bacterial diseases from wild, domestic, and human systems.

Entropy, Statistical Evidence, and Scientific Inference: Evidence Functions in Theory and Applications.

Scope and Goals of the Special Issue: There is a growing realization that despite being the essential tool of modern data-based scientific discovery and model testing, statistics has major problems [...].

The relationship of C and N stable isotopes to high-latitude moss-associated N2 fixation.

Moss-associated N2 fixation by epiphytic microbes is a key biogeochemical process in nutrient-limited high-latitude ecosystems. Abiotic drivers, such as temperature and moisture, and the identity of host mosses are critical sources of variation in N2 fixation rates. An understanding of the potential interaction between these factors is essential for predicting N inputs as moss communities change with the climate. To further understand the drivers and results of N2 fixation rate variation, we obtained natural abundance values of C and N isotopes and an associated rate of N2 fixation with 15N2 gas incubations in 34 moss species collected in three regions across Alaska, USA. We hypothesized that δ15N values would increase toward 0‰ with higher N2 fixation to reflect the increasing contribution of fixed N2 in moss biomass. Second, we hypothesized that δ13C and N2 fixation would be positively related, as enriched δ13C signatures reflect abiotic conditions favorable to N2 fixation. We expected that the magnitude of these relationships would vary among types of host mosses, reflecting differences in anatomy and habitat. We found little support for our first hypothesis, with only a modest positive relationship between N2 fixation rates and δ15N in a structural equation model. We found a significant positive relationship between δ13C and N2 fixation only in Hypnales, where the probability of N2 fixation activity reached 95% when δ13C values exceeded - 30.4‰. We conclude that moisture and temperature interact strongly with host moss identity in determining the extent to which abiotic conditions impact associated N2 fixation rates.

A parametric interpretation of Bayesian Nonparametric Inference from Gene Genealogies: Linking ecological, population genetics and evolutionary processes.

Using a nonparametric Bayesian approach Palacios and Minin (2013) dramatically improved the accuracy, precision of Bayesian inference of population size trajectories from gene genealogies. These authors proposed an extension of a Gaussian Process (GP) nonparametric inferential method for the intensity function of non-homogeneous Poisson processes. They found that not only the statistical properties of the estimators were improved with their method, but also, that key aspects of the demographic histories were recovered. The authors' work represents the first Bayesian nonparametric solution to this inferential problem because they specify a convenient prior belief without a particular functional form on the population trajectory. Their approach works so well and provides such a profound understanding of the biological process, that the question arises as to how truly "biology-free" their approach really is. Using well-known concepts of stochastic population dynamics, here I demonstrate that in fact, Palacios and Minin's GP model can be cast as a parametric population growth model with density dependence and environmental stochasticity. Making this link between population genetics and stochastic population dynamics modeling provides novel insights into eliciting biologically meaningful priors for the trajectory of the effective population size. The results presented here also bring novel understanding of GP as models for the evolution of a trait. Thus, the ecological principles foundation of Palacios and Minin (2013)'s prior adds to the conceptual and scientific value of these authors' inferential approach. I conclude this note by listing a series of insights brought about by this connection with Ecology.

Functional Traits, Flocking Propensity, and Perceived Predation Risk in an Amazonian Understory Bird Community.

Within a community, different species might share similar predation risks, and, thus, the ability of species to signal and interpret heterospecific threat information may determine species' associations. We combined observational, experimental, and phylogenetic approaches to determine the extent to which evolutionary history and functional traits determined flocking propensity and perceived predation risk (response to heterospecific alarm calls) in a lowland Amazonian bird community. We predicted that small birds that feed myopically and out in the open would have higher flocking propensities and account for a higher proportion of positive responses to alarms. Using generalized linear models and the incorporation of phylogeny on data from 56 species, our results suggest that phylogenetic relationships alongside body size, foraging height, vegetation density, and response to alarm calls influence flocking propensity. Conversely, phylogenetic relationships did not influence response to heterospecific alarm calls. Among functional traits, however, foraging strategy, foraging density, and flocking propensity partially explained responses to alarm calls. Our results suggest that flocking propensity and perceived predation risk are positively related and that functional ecological traits and evolutionary history may explain certain species' associations.

Density-dependent state-space model for population-abundance data with unequal time intervals.

The Gompertz state-space (GSS) model is a stochastic model for analyzing time-series observations of population abundances. The GSS model combines density dependence, environmental process noise, and observation error toward estimating quantities of interest in biological monitoring and population viability analysis. However, existing methods for estimating the model parameters apply only to population data with equal time intervals between observations. In the present paper, we extend the GSS model to data with unequal time intervals, by embedding it within a state-space version of the Ornstein-Uhlenbeck process, a continuous-time model of an equilibrating stochastic system. Maximum likelihood and restricted maximum likelihood calculations for the Ornstein-Uhlenbeck state-space model involve only numerical maximization of an explicit multivariate normal likelihood, and so the extension allows for easy bootstrapping, yielding confidence intervals for model parameters, statistical hypothesis testing of density dependence, and selection among sub-models using information criteria. Ecologists and managers previously drawn to models lacking density dependence or observation error because such models accommodated unequal time intervals (for example, due to missing data) now have an alternative analysis framework incorporating density dependence, process noise, and observation error.

Assessing parameter identifiability in phylogenetic models using data cloning.

The success of model-based methods in phylogenetics has motivated much research aimed at generating new, biologically informative models. This new computer-intensive approach to phylogenetics demands validation studies and sound measures of performance. To date there has been little practical guidance available as to when and why the parameters in a particular model can be identified reliably. Here, we illustrate how Data Cloning (DC), a recently developed methodology to compute the maximum likelihood estimates along with their asymptotic variance, can be used to diagnose structural parameter nonidentifiability (NI) and distinguish it from other parameter estimability problems, including when parameters are structurally identifiable, but are not estimable in a given data set (INE), and when parameters are identifiable, and estimable, but only weakly so (WE). The application of the DC theorem uses well-known and widely used Bayesian computational techniques. With the DC approach, practitioners can use Bayesian phylogenetics software to diagnose nonidentifiability. Theoreticians and practitioners alike now have a powerful, yet simple tool to detect nonidentifiability while investigating complex modeling scenarios, where getting closed-form expressions in a probabilistic study is complicated. Furthermore, here we also show how DC can be used as a tool to examine and eliminate the influence of the priors, in particular if the process of prior elicitation is not straightforward. Finally, when applied to phylogenetic inference, DC can be used to study at least two important statistical questions: assessing identifiability of discrete parameters, like the tree topology, and developing efficient sampling methods for computationally expensive posterior densities.

Beyond the spore, the exosporium sugar anthrose impacts vegetative Bacillus anthracis gene regulation in cis and trans.

The Bacillus anthracis exosporium nap is the outermost portion of spore that interacts with the environment and host systems. Changes to this layer have the potential to impact wide-ranging physiological and immunological processes. The unique sugar, anthrose, normally coats the exosporium nap at its most distal points. We previously identified additional mechanisms rendering B. anthracis anthrose negative. In this work, several new ant - B. anthracis strains are identified and the impact of anthrose negativity on spore physiology is investigated. We demonstrate that live-attenuated Sterne vaccines as well as culture filtrate anthrax vaccines generate antibodies targeting non-protein components of the spore. The role of anthrose as a vegetative B. anthracis Sterne signaling molecule is implicated by luminescent expression strain assays, RNA-seq experiments, and toxin secretion analysis by western blot. Pure anthrose and the sporulation-inducing nucleoside analogue decoyinine had similar effects on toxin expression. Co-culture experiments demonstrated gene expression changes in B. anthracis depend on intracellular anthrose status (cis) in addition to anthrose status of extracellular interactions (trans). These findings provide a mechanism for how a unique spore-specific sugar residue affects physiology, expression and genetics of vegetative B. anthracis with impacts on the ecology, pathogenesis, and vaccinology of anthrax.

Spatial and phylogenetic patterns reveal hidden infection sources of Bacillus anthracis in an anthrax outbreak in Son La province, Vietnam.

Bacillus anthracis, the bacterial cause of anthrax, is a zoonosis affecting livestock and wildlife often spilling over into humans. In Vietnam, anthrax has been nationally reportable since 2015 with cases occurring annually, mostly in the northern provinces. In April 2022, an outbreak was reported in Son La province following the butchering of a water buffalo, Bubalus bubalis. A total of 137 humans from three villages were likely exposed to contaminated meat from the animal. Early epidemiological investigations suggested a single animal was involved in all exposures. Five B. anthracis isolates were recovered from human clinical cases along with one from the buffalo hide, another from associated maggots, and one from soil at the carcass site. The isolates were whole genome sequenced, allowing global, regional, and local molecular epidemiological analyses of the outbreak strains. All recovered B. anthracis belong to the A.Br.001/002 lineage based on canonical single nucleotide polymorphism analysis (canSNP). Although not previously identified in Vietnam, this lineage has been identified in the nearby countries of China, India, Indonesia, Thailand, as well as Australia. A twenty-five marker multi-locus variable number tandem repeat analysis (MLVA-25) was used to investigate the relationship between human, soil, and buffalo strains. Locally, four MLVA-25 genotypes were identified from the eight isolates. This level of genetic diversity is unusual for the limited geography and timing of cases and differs from past literature using MLVA-25. The coupled spatial and phylogenetic data suggest this outbreak originated from multiple, likely undetected, animal sources. These findings were further supported by local news reports that identified at least two additional buffalo deaths beyond the initial animal sampled in response to the human cases. Future outbreak response should include intensive surveillance for additional animal cases and additional molecular epidemiological traceback to identify pathogen sources.

Anthrax Surveillance and the Limited Overlap Between Obligate Scavengers and Endemic Anthrax Zones in the United States.

Anthrax is a zoonosis caused by the spore-forming bacterium Bacillus anthracis, with potential for high fatality rate, especially in herbivores. Upon host death, spores can enter the soil surrounding the carcass and be ingested by other animals feeding in the same location. Accordingly, surveillance to quickly identify and decontaminate anthrax carcasses is crucial to outbreak prevention. In endemic anthrax areas such as Texas and Africa, vultures are used as a surveillance tool for identifying presence and location of dead animals. However, many anthrax outbreaks in the United States have occurred in areas outside the ranges of both black and turkey vultures. Here, we used a longitudinal camera trap survey at carcass sites in southwestern Montana to investigate the utility of facultative avian scavengers on disease and carcass surveillance in a reemerging anthrax risk zone. From August 2016 to September 2018, camera traps at 11 carcass sites were triggered 1996 times by avian scavengers. While the majority were facultative avian scavengers such as corvids and eagles, our results suggest that facultative scavengers cannot replace vultures as a surveillance tool in this ecosystem due to their absence during the anthrax risk period (June to August), reduced search efficiency, or low flight patterns. We found that the conditions in Montana likely parallel systems elsewhere in the continental United States. Using ecological niche models of B. anthracis distribution overlaid with relative abundance maps of turkey vultures, we found that much of North Dakota, South Dakota, Minnesota, Wyoming, Nebraska, and Iowa have areas of anthrax risk, but low or absent turkey vulture populations. Without vultures in these areas, surveillance capacity is reduced, and it becomes more difficult to identify anthrax cases, meaning fewer carcasses are decontaminated, and consequently, outbreaks could become more frequent or severe.

Factors influencing scavenger guilds and scavenging efficiency in Southwestern Montana.

Scavenging of carrion shapes ecological landscapes by influencing scavenger population demography, increasing inter- and intra-specific interactions, and generating ecosystem services such as nutrient cycling and disease moderation. Previous research found the cues promoting, or the constraints limiting, an individual's propensity or ability to scavenge vary widely, depending on anthropogenic and environmental factors. Here we investigated differences in scavenging patterns in a complex scavenger guild in Southwestern Montana. We used camera traps established at 13 carcass sites to monitor carcass detection, visitation, and consumption times, during 2016-2018 and generalized linear models to explore the influence of carcass characteristics, habitat features, and seasonality, on carcass selection and scavenging efficiency. We found that scavenger species diversity was higher at higher elevations and in grassland habitats. Scavenging efficiency was influenced inter alia by seasonality, distance to water, and elevation. We found that most carcass consumption was via facultative scavengers (bears, wolves, magpies, Corvus spp.) rather than turkey vultures, the only obligate scavengers in the study area. However, growing populations of turkey vultures may lead to increased competition with facultative scavengers over carrion, and could have cascading effects on food webs in this ecosystem.

The bacterial communities of Alaskan mosses and their contributions to N2-fixation.

BACKGROUND: Mosses in high-latitude ecosystems harbor diverse bacterial taxa, including N2-fixers which are key contributors to nitrogen dynamics in these systems. Yet the relative importance of moss host species, and environmental factors, in structuring these microbial communities and their N2-fixing potential remains unclear. We studied 26 boreal and tundra moss species across 24 sites in Alaska, USA, from 61 to 69° N. We used cultivation-independent approaches to characterize the variation in moss-associated bacterial communities as a function of host species identity and site characteristics. We also measured N2-fixation rates via 15N2 isotopic enrichment and identified potential N2-fixing bacteria using available literature and genomic information. RESULTS: Host species identity and host evolutionary history were both highly predictive of moss microbiome composition, highlighting strong phylogenetic coherence in these microbial communities. Although less important, light availability and temperature also influenced composition of the moss microbiome. Finally, we identified putative N2-fixing bacteria specific to some moss hosts, including potential N2-fixing bacteria outside well-studied cyanobacterial clades. CONCLUSIONS: The strong effect of host identity on moss-associated bacterial communities demonstrates mosses' utility for understanding plant-microbe interactions in non-leguminous systems. Our work also highlights the likely importance of novel bacterial taxa to N2-fixation in high-latitude ecosystems. Video Abstract.

Replicated sampling increases efficiency in monitoring biological populations.

Observation or sampling error in population monitoring can cause serious degradation of the inferences, such as estimates of trend or risk, that ecologists and managers frequently seek to make with time-series observations of population abundances. We show that replicating the sampling process can considerably improve the information obtained from population monitoring. At each sampling time the sampling method would be repeated, either simultaneously or within a short time. In this study we examine the potential value of replicated sampling to population monitoring using a density-dependent population model. We modify an existing population time-series model, the Gompertz state-space model, to incorporate replicated sampling, and we develop maximum-likelihood and restricted maximum-likelihood estimates of model parameters. Depending on sampling protocols, replication may or may not entail substantial extra cost. Some sampling programs already have replicated samples, but the samples are aggregated or pooled into one estimate of population abundance; such practice of aggregating samples, according to our model, loses considerable information about model parameters. The gains from replicated sampling are realized in substantially improved statistical inferences about model parameters, especially inferences for sorting out the contributions of process noise and observation error to observed population variability.

Ungulate use of locally infectious zones in a re-emerging anthrax risk area.

Environmentally mediated indirect pathogen transmission is linked to host movement and foraging in areas where pathogens are maintained in the environment. In the case of anthrax, spores of the causative bacterium Bacillus anthracis are released into the environment following host death and create locally infectious zones (LIZs) around carcass sites; by grazing at LIZs, herbivores are potentially exposed to spores. Here, we used camera traps to assess how ungulate species use carcass sites in southwestern Montana and evaluated how these behaviours may promote indirect anthrax transmission, thus providing, to our knowledge, the first detailed documentation and study of the fine-scale mechanisms underlying foraging-based disease transmission in this ecosystem. We found that carcasses at LIZs significantly increased aboveground biomass of vegetation and concentrations of sodium and phosphorus, potentially making these sites more appealing to grazers. Host behavioural responses to LIZs varied depending on species, sex, season and carcass age; but, overall, our results demonstrated that carcasses or carcass sites serve as an attractant to herbivores in this system. Attraction to LIZs probably represents an increased risk of exposure to B. anthracis and, consequently, increased anthrax transmission rates. Accordingly, continued anthrax surveillance and control strategies are critical in this system.

Evolution of diversity in spatially structured Escherichia coli populations.

The stochastic Ricker population model was used to investigate the generation and maintenance of genetic diversity in a bacterial population grown in a spatially structured environment. In particular, we showed that Escherichia coli undergoes dramatic genetic diversification when grown as a biofilm. Using a novel biofilm entrapment method, we retrieved 64 clones from each of six different depths of a mature biofilm, and after subculturing for approximately 30 generations, we measured their growth kinetics in three different media. We fit a stochastic Ricker population growth model to the recorded growth curves. The growth kinetics of clonal lineages descendant from cells sampled at different biofilm depths varied as a function of both the depth in the biofilm and the growth medium used. We concluded that differences in the growth dynamics of clones were heritable and arose during adaptive evolution under local conditions in a spatially heterogeneous environment. We postulate that under nutrient-limited conditions, selective sweeps would be protracted and would be insufficient to purge less-fit variants, a phenomenon that would allow the coexistence of genetically distinct clones. These findings contribute to the current understanding of biofilm ecology and complement current hypotheses for the maintenance and generation of microbial diversity in spatially structured environments.

Hierarchical models in ecology: confidence intervals, hypothesis testing, and model selection using data cloning.

Hierarchical statistical models are increasingly being used to describe complex ecological processes. The data cloning (DC) method is a new general technique that uses Markov chain Monte Carlo (MCMC) algorithms to compute maximum likelihood (ML) estimates along with their asymptotic variance estimates for hierarchical models. Despite its generality, the method has two inferential limitations. First, it only provides Wald-type confidence intervals, known to be inaccurate in small samples. Second, it only yields ML parameter estimates, but not the maximized likelihood values used for profile likelihood intervals, likelihood ratio hypothesis tests, and information-theoretic model selection. Here we describe how to overcome these inferential limitations with a computationally efficient method for calculating likelihood ratios via data cloning. The ability to calculate likelihood ratios allows one to do hypothesis tests, construct accurate confidence intervals and undertake information-based model selection with hierarchical models in a frequentist context. To demonstrate the use of these tools with complex ecological models, we reanalyze part of Gause's classic Paramecium data with state-space population models containing both environmental noise and sampling error. The analysis results include improved confidence intervals for parameters, a hypothesis test of laboratory replication, and a comparison of the Beverton-Holt and the Ricker growth forms based on a model selection index.