Sentinel Case of Candida auris in the Western United States Following Prolonged Occult Colonization in a Returned Traveler from India.

Candida auris is an emerging multidrug-resistant yeast with high mortality. We report the sentinel C. auris case on the United States West Coast in a patient who relocated from India. We identified close phylogenetic relatedness to the South Asia clade and ERG11 Y132F and FKS1 S639Y mutations potentially explaining antifungal resistance

Historical contingency in species interactions: towards niche-based predictions.

The way species affect one another in ecological communities often depends on the order of species arrival. The magnitude of such historical contingency, known as priority effects, varies across species and environments, but this variation has proven difficult to predict, presenting a major challenge in understanding species interactions and consequences for community structure and function. Here, we argue that improved predictions can be achieved by decomposing species' niches into three components: overlap, impact and requirement. Based on classic theories of community assembly, three hypotheses that emphasise related, but distinct influences of the niche components are proposed: priority effects are stronger among species with higher resource use overlap; species that impact the environment to a greater extent exert stronger priority effects; and species whose growth rate is more sensitive to changes in the environment experience stronger priority effects. Using nectar-inhabiting microorganisms as a model system, we present evidence that these hypotheses complement the conventional hypothesis that focuses on the role of environmental harshness, and show that niches can be twice as predictive when separated into components. Taken together, our hypotheses provide a basis for developing a general framework within which the magnitude of historical contingency in species interactions can be predicted

Uncovering latent structure in valued graphs: A variational approach

As more and more network-structured data sets are available, the statistical analysis of valued graphs has become common place. Looking for a latent structure is one of the many strategies used to better understand the behavior of a network. Several methods already exist for the binary case. We present a model-based strategy to uncover groups of nodes in valued graphs. This framework can be used for a wide span of parametric random graphs models and allows to include covariates. Variational tools allow us to achieve approximate maximum likelihood estimation of the parameters of these models. We provide a simulation study showing that our estimation method performs well over a broad range of situations. We apply this method to analyze host--parasite interaction networks in forest ecosystems.Comment: Published in at http://dx.doi.org/10.1214/10-AOAS361 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Predicting species' tolerance to salinity and alkalinity using distribution data and geochemical modelling: a case study using Australian grasses

BACKGROUND AND AIMS: Salt tolerance has evolved many times independently in different plant groups. One possible explanation for this pattern is that it builds upon a general suite of stress-tolerance traits. If this is the case, then we might expect a correlation between salt tolerance and other tolerances to different environmental stresses. This association has been hypothesized for salt and alkalinity tolerance. However, a major limitation in investigating large-scale patterns of these tolerances is that lists of known tolerant species are incomplete. This study explores whether species' salt and alkalinity tolerance can be predicted using geochemical modelling for Australian grasses. The correlation between taxa found in conditions of high predicted salinity and alkalinity is then assessed. METHODS: Extensive occurrence data for Australian grasses is used together with geochemical modelling to predict values of pH and electrical conductivity to which species are exposed in their natural distributions. Using parametric and phylogeny-corrected tests, the geochemical predictions are evaluated using a list of known halophytes as a control, and it is determined whether taxa that occur in conditions of high predicted salinity are also found in conditions of high predicted alkalinity. KEY RESULTS: It is shown that genera containing known halophytes have higher predicted salinity conditions than those not containing known halophytes. Additionally, taxa occurring in high predicted salinity tend to also occur in high predicted alkalinity. CONCLUSIONS: Geochemical modelling using species' occurrence data is a potentially useful approach to predict species' relative natural tolerance to challenging environmental conditions. The findings also demonstrate a correlation between salinity tolerance and alkalinity tolerance. Further investigations can consider the phylogenetic distribution of specific traits involved in these ecophysiological strategies, ideally by incorporating more complete, finer-scale geochemical information, as well as laboratory experiments.This work was supported by the Australian Research Council

Pollinator or pedigree:Which factors determine the evolution of pollen nutrients?

A prime example of plant-animal interactions is the interaction between plants and pollinators, which typically receive nectar and/or pollen as reward for their pollination service. While nectar provides mostly carbohydrates, pollen represents the main source of protein and lipids for many pollinators. However, the main function of pollen is to carry nutrients for pollen tube growth and thus fertilization. It is unclear whether pollinator attraction exerts a sufficiently strong selective pressure to alter the nutritional profile of pollen, e.g., through increasing its crude protein content or protein-to-lipid ratio, which both strongly affect bee foraging. Pollen nutritional quality may also be merely determined by phylogenetic relatedness, with pollen of closely related plants showing similar nutritional profiles due to shared biosynthetic pathways or floral morphologies. Here, we present a meta-analysis of studies on pollen nutrients to test whether differences in pollen nutrient contents and ratios correlated with plant insect pollinator dependence and/or phylogenetic relatedness. We hypothesized that if pollen nutritional content was affected by pollinator attraction, it should be different (e.g., higher) in highly pollinator-dependent plants, independent of phylogenetic relatedness. We found that crude protein and the protein-to-lipid ratio in pollen strongly correlated with phylogeny. Moreover, pollen protein content was higher in plants depending mostly or exclusively on insect pollination. Pollen nutritional quality thus correlated with both phylogenetic relatedness and pollinator dependency, indicating that, besides producing pollen with sufficient nutrients for reproduction, the nutrient profile of zoophilous plants may have been shaped by their pollinators' nutritional needs

Evidence of strong stabilizing effects on the evolution of boreoeutherian (Mammalia) dental proportions.

The dentition is an extremely important organ in mammals with variation in timing and sequence of eruption, crown morphology, and tooth size enabling a range of behavioral, dietary, and functional adaptations across the class. Within this suite of variable mammalian dental phenotypes, relative sizes of teeth reflect variation in the underlying genetic and developmental mechanisms. Two ratios of postcanine tooth lengths capture the relative size of premolars to molars (premolar-molar module, PMM), and among the three molars (molar module component, MMC), and are known to be heritable, independent of body size, and to vary significantly across primates. Here, we explore how these dental traits vary across mammals more broadly, focusing on terrestrial taxa in the clade of Boreoeutheria (Euarchontoglires and Laurasiatheria). We measured the postcanine teeth of N = 1,523 boreoeutherian mammals spanning six orders, 14 families, 36 genera, and 49 species to test hypotheses about associations between dental proportions and phylogenetic relatedness, diet, and life history in mammals. Boreoeutherian postcanine dental proportions sampled in this study carry conserved phylogenetic signal and are not associated with variation in diet. The incorporation of paleontological data provides further evidence that dental proportions may be slower to change than is dietary specialization. These results have implications for our understanding of dental variation and dietary adaptation in mammals

Phylogenetic signal in amphibian sensitivity to copper sulfate relative to experimental temperature

The release of large quantities of chemicals into the environment represents a major source of environmental disturbance. In recent years, the focus of ecotoxicology has shifted from describing the effects of chemical contaminants on individual species to developing more integrated approaches for predicting and evaluating long term effects of chemicals across species and ecosystems. Traditional ecotoxicology is typically based on data of sensitivity of a few surrogate species to a contaminant and often considers little variability in chemical sensitivity within and among taxonomic groups. This approach assumes that evolutionary history and phylogenetic relatedness among species have little or no impact on species’ sensitivity to chemical compounds. Few studies have tested this assumption. Using phylogenetic comparative methods and published data for amphibians, we show that sensitivity to copper sulfate, a commonly used pesticide, exhibits a strong phylogenetic signal when controlling for experimental temperature. Our results indicate that evolutionary history needs to be accounted for to make accurate predictions of amphibian sensitivity to this contaminant under different temperature scenarios. Since physiological and metabolic traits showing high phylogenetic signal likely underlie variation in species sensitivity to chemical stressors, future studies should evaluate and predict species vulnerability to pollutants using evolutionarily informed approaches