Identifying the Age Cohort Responsible for Transmission in a Natural Outbreak of Bordetella bronchiseptica

Identifying the major routes of disease transmission and reservoirs of infection are needed to increase our understanding of disease dynamics and improve disease control. Despite this, transmission events are rarely observed directly. Here we had the unique opportunity to study natural transmission of Bordetella bronchiseptica – a directly transmitted respiratory pathogen with a wide mammalian host range, including sporadic infection of humans – within a commercial rabbitry to evaluate the relative effects of sex and age on the transmission dynamics therein. We did this by developing an a priori set of hypotheses outlining how natural B. bronchiseptica infections may be transmitted between rabbits. We discriminated between these hypotheses by using force-of-infection estimates coupled with random effects binomial regression analysis of B. bronchiseptica age-prevalence data from within our rabbit population. Force-of-infection analysis allowed us to quantify the apparent prevalence of B. bronchiseptica while correcting for age structure. To determine whether transmission is largely within social groups (in this case litter), or from an external group, we used random-effect binomial regression to evaluate the importance of social mixing in disease spread. Between these two approaches our results support young weanlings – as opposed to, for example, breeder or maternal cohorts – as the age cohort primarily responsible for B. bronchiseptica transmission. Thus age-prevalence data, which is relatively easy to gather in clinical or agricultural settings, can be used to evaluate contact patterns and infer the likely age-cohort responsible for transmission of directly transmitted infections. These insights shed light on the dynamics of disease spread and allow an assessment to be made of the best methods for effective long-term disease control

Green turtles (Chelonia mydas) foraging at Arvoredo Island in Southern Brazil: Genetic characterization and mixed stock analysis through mtDNA control region haplotypes

We analyzed mtDNA control region sequences of green turtles (Chelonia mydas) from Arvoredo Island, a foraging ground in southern Brazil, and identified eight haplotypes. Of these, CM-A8 (64%) and CM-A5 (22%) were dominant, the remainder presenting low frequencies (< 5%). Haplotype (h) and nucleotide (π) diversities were 0.5570 ± 0.0697 and 0.0021 ± 0.0016, respectively. Exact tests of differentiation and AMOVA ΦST pairwise values between the study area and eight other Atlantic foraging grounds revealed significant differences in most areas, except Ubatuba and Rocas/Noronha, in Brazil (p > 0.05). Mixed Stock Analysis, incorporating eleven Atlantic and one Mediterranean rookery as possible sources of individuals, indicated Ascension and Aves islands as the main contributing stocks to the Arvoredo aggregation (68.01% and 22.96%, respectively). These results demonstrate the extensive relationships between Arvoredo Island and other Atlantic foraging and breeding areas. Such an understanding provides a framework for establishing adequate management and conservation strategies for this endangered species

Regression with Empirical Variable Selection: Description of a New Method and Application to Ecological Datasets

Despite recent papers on problems associated with full-model and stepwise regression, their use is still common throughout ecological and environmental disciplines. Alternative approaches, including generating multiple models and comparing them post-hoc using techniques such as Akaike's Information Criterion (AIC), are becoming more popular. However, these are problematic when there are numerous independent variables and interpretation is often difficult when competing models contain many different variables and combinations of variables. Here, we detail a new approach, REVS (Regression with Empirical Variable Selection), which uses all-subsets regression to quantify empirical support for every independent variable. A series of models is created; the first containing the variable with most empirical support, the second containing the first variable and the next most-supported, and so on. The comparatively small number of resultant models (n = the number of predictor variables) means that post-hoc comparison is comparatively quick and easy. When tested on a real dataset – habitat and offspring quality in the great tit (Parus major) – the optimal REVS model explained more variance (higher R2), was more parsimonious (lower AIC), and had greater significance (lower P values), than full, stepwise or all-subsets models; it also had higher predictive accuracy based on split-sample validation. Testing REVS on ten further datasets suggested that this is typical, with R2 values being higher than full or stepwise models (mean improvement = 31% and 7%, respectively). Results are ecologically intuitive as even when there are several competing models, they share a set of “core” variables and differ only in presence/absence of one or two additional variables. We conclude that REVS is useful for analysing complex datasets, including those in ecology and environmental disciplines

Early-life telomere dynamics differ between the sexes and predict growth in the barn swallow (Hirundo rustica)

Telomeres are conserved DNA-protein structures at the termini of eukaryotic chromosomes which contribute to maintenance of genome integrity, and their shortening leads to cell senescence, with negative consequences for organismal functions. Because telomere erosion is influenced by extrinsic and endogenous factors, telomere dynamics may provide a mechanistic basis for evolutionary and physiological trade-offs. Yet, knowledge of fundamental aspects of telomere biology under natural selection regimes, including sex- and context-dependent variation in early-life, and the covariation between telomere dynamics and growth, is scant. In this study of barn swallows (Hirundo rustica) we investigated the sex-dependent telomere erosion during nestling period, and the covariation between relative telomere length and body and plumage growth. Finally, we tested whether any covariation between growth traits and relative telomere length depends on the social environment, as influenced by sibling sex ratio. Relative telomere length declined on average over the period of nestling maximal growth rate (between 7 and 16 days of age) and differently covaried with initial relative telomere length in either sex. The frequency distribution of changes in relative telomere length was bimodal, with most nestlings decreasing and some increasing relative telomere length, but none of the offspring traits predicted the a posteriori identified group to which individual nestlings belonged. Tail and wing length increased with relative telomere length, but more steeply in males than females, and this relationship held both at the within- and among-broods levels. Moreover, the increase in plumage phenotypic values was steeper when the sex ratio of an individual's siblings was female-biased. Our study provides evidence for telomere shortening during early life according to subtly different dynamics in either sex. Furthermore, it shows that the positive covariation between growth and relative telomere length depends on sex as well as social environment, in terms of sibling sex ratio

Regional Management Units for Marine Turtles: A Novel Framework for Prioritizing Conservation and Research across Multiple Scales

Background: Resolving threats to widely distributed marine megafauna requires definition of the geographic distributions of both the threats as well as the population unit(s) of interest. In turn, because individual threats can operate on varying spatial scales, their impacts can affect different segments of a population of the same species. Therefore, integration of multiple tools and techniques - including site-based monitoring, genetic analyses, mark-recapture studies and telemetry - can facilitate robust definitions of population segments at multiple biological and spatial scales to address different management and research challenges. Methodology/Principal Findings: To address these issues for marine turtles, we collated all available studies on marine turtle biogeography, including nesting sites, population abundances and trends, population genetics, and satellite telemetry. We georeferenced this information to generate separate layers for nesting sites, genetic stocks, and core distributions of population segments of all marine turtle species. We then spatially integrated this information from fine-to coarse-spatial scales to develop nested envelope models, or Regional Management Units (RMUs), for marine turtles globally. Conclusions/Significance: The RMU framework is a solution to the challenge of how to organize marine turtles into units of protection above the level of nesting populations, but below the level of species, within regional entities that might be on independent evolutionary trajectories. Among many potential applications, RMUs provide a framework for identifying data gaps, assessing high diversity areas for multiple species and genetic stocks, and evaluating conservation status of marine turtles. Furthermore, RMUs allow for identification of geographic barriers to gene flow, and can provide valuable guidance to marine spatial planning initiatives that integrate spatial distributions of protected species and human activities. In addition, the RMU framework - including maps and supporting metadata - will be an iterative, user-driven tool made publicly available in an online application for comments, improvements, download and analysis

BUGS in the Analysis of Biodiversity Experiments: Species Richness and Composition Are of Similar Importance for Grassland Productivity

The idea that species diversity can influence ecosystem functioning has been controversial and its importance relative to compositional effects hotly debated. Unfortunately, assessing the relative importance of different explanatory variables in complex linear models is not simple. In this paper we assess the relative importance of species richness and species composition in a multilevel model analysis of net aboveground biomass production in grassland biodiversity experiments by estimating variance components for all explanatory variables. We compare the variance components using a recently introduced graphical Bayesian ANOVA. We show that while the use of test statistics and the R2 gives contradictory assessments, the variance components analysis reveals that species richness and composition are of roughly similar importance for primary productivity in grassland biodiversity experiments

Consequences of a large-scale fragmentation experiment for Neotropical bats : disentangling the relative importance of local and landscape-scale effects

Context Habitat loss, fragmentation and degradation are widespread drivers of biodiversity decline. Understanding how habitat quality interacts with landscape context, and how they jointly affect species in human-modified landscapes, is of great importance for informing conservation and management. Objectives We used a whole-ecosystem manipulation experiment in the Brazilian Amazon to investigate the relative roles of local and landscape attributes in affecting bat assemblages at an interior-edge-matrix disturbance gradient. Methods We surveyed bats in 39 sites, comprising continuous forest (CF), fragments, forest edges and intervening secondary regrowth. For each site, we assessed vegetation structure (local-scale variable) and, for five focal scales, quantified habitat amount and four landscape configuration metrics. Results Smaller fragments, edges and regrowth sites had fewer species and higher levels of dominance than CF. Regardless of the landscape scale analysed, species richness and evenness were mostly related to the amount of forest cover. Vegetation structure and configurational metrics were important predictors of abundance, whereby the magnitude and direction of response to configurational metrics were scale-dependent. Responses were ensemble-specific with local-scale vegetation structure being more important for frugivorous than for gleaning animalivorous bats. Conclusions Our study indicates that scale-sensitive measures of landscape structure are needed for a more comprehensive understanding of the effects of fragmentation on tropical biota. Although forest fragments and regrowth habitats can be of conservation significance for tropical bats our results further emphasize that primary forest is of irreplaceable value, underlining that their conservation can only be achieved by the preservation of large expanses of pristine habitat

Land-use effects on local biodiversity in tropical forests vary between continents

The file attached is the Published/publisher’s pdf version of the article

Evidence for the ‘Good Genes’ Model: Association of MHC Class II DRB Alleles with Ectoparasitism and Reproductive State in the Neotropical Lesser Bulldog Bat, Noctilio albiventris

The adaptive immune system has a major impact on parasite resistance and life history strategies. Immunological defence is costly both in terms of immediate activation and long-term maintenance. The ‘good genes’ model predicts that males with genotypes that promote a good disease resistance have the ability to allocate more resources to reproductive effort which favours the transmission of good alleles into future generations. Our study shows a correlation between immune gene constitution (Major Histocompatibility Complex, MHC class II DRB), ectoparasite loads (ticks and bat flies) and the reproductive state in a neotropical bat, Noctilio albiventris. Infestation rates with ectoparasites were linked to specific Noal-DRB alleles, differed among roosts, increased with body size and co-varied with reproductive state particularly in males. Non-reproductive adult males were more infested with ectoparasites than reproductively active males, and they had more often an allele (Noal-DRB*02) associated with a higher tick infestation than reproductively active males or subadults. We conclude that the individual immune gene constitution affects ectoparasite susceptibility, and contributes to fitness relevant trade-offs in male N. albiventris as suggested by the ‘good genes’ model