The biogeographic legacy of an imperilled taxon provides a foundation for assessing lineage diversification,demography and conservation genetics

Aim To test alternative biogeographic hypotheses related to the diversification of a montane mammal (Zapus hudsonius luteus) endemic to the American Southwest. Location South‐western United States. Methods We used statistical phylogeographic analyses of mitochondrial DNA (1512 bp; two genes) from 93 individuals from six geographic regions to test diversification hypotheses. Species distribution models of climate and fossil records were integrated to assess contemporary and historical distributions and barriers to gene flow. We calculated dates of divergence and examined historical demography using coalescent simulations. Results We documented monophyly of Z. h. luteus represented by 19 segregated haplotypes. Predicted current distribution generally coincided with known localities, while predicted paleodistributions suggested that this lineage was widespread throughout lower elevations of the American Southwest and on the Edwards Plateau (as documented by the fossil record). Population size did not change substantially during a westward shift in range that occurred in the last 100 k generations. Results supported fragmentation of a common ancestor during the Holocene as the most plausible explanation for genetic structure. Main conclusions Monophyletic Z. h. luteus reflects fragmentation of a common ancestor with recent (Holocene) upslope colonization of disjunct montane areas. We refute the hypotheses of in situ divergence or origins from a Colorado Piedmont ancestor. Instead, westward colonization from the Edwards Plateau during the Wisconsin followed by Holocene fragmentation, which serves as a generalized biogeographic hypothesis for species associated with mesic graminoid habitats in the American Southwest. Further exploration of these signatures using independent nuclear DNA is warranted. Key conservation implications are (1) Z. h. luteus is a monophyletic lineage on an independent evolutionary trajectory; (2) Z. h. luteus shared a recent common ancestor with Z. h. pallidus (not Z. h. preblei); (3) mtDNA does not reflect recent population declines; and (4) coalescent simulations and species distribution models reflect Holocene fragmentation.     

PmMGST3, a novel microsomal glutathione S-transferase gene in the dinoflagellate Prorocentrum minimum, is a potential biomarker of oxidative stress

In this study, we evaluated a novel microsomal glutathione S-transferase3 (MGST3) gene from the dinoflagellate Prorocentrum minimum, and examined its expression pattern in response to copper-and nickel-induced stresses. The full length of PmMGST3 was 732 bp, ranging from the dinoflagellate splice leader (DinoSL) sequence to the poly (A) tail, covering a 441-bp ORF, 97-bp 5′UTR, and 194-bp 3′UTR. The PmMGST3 was up-regulated by metals, including copper and nickel. The highest up-regulation levels of the PmMGST3 were found under 0.1 mg/L copper and 0.5 mg/L nickel treatment, respectively. In addition, the PmMGST3 was gradually up-regulated by 0.1 mg/L copper with increasing exposure time. Furthermore, ROS production and reduced GSH was measured in the copper treated cells. A significant increased ROS production and reduced GSH were found in the copper treated cells. These results suggest that PmMGST3 may be related to defense mechanisms associated with oxidative stress in dinoflagellates.     

Flexible Regression Model Selection for Survival Probabilities: With Application to AIDS

Summary Clinicians are often interested in the effect of covariates on survival probabilities at prespecified study times. Because different factors can be associated with the risk of short‐ and long‐term failure, a flexible modeling strategy is pursued. Given a set of multiple candidate working models, an objective methodology is proposed that aims to construct consistent and asymptotically normal estimators of regression coefficients and average prediction error for each working model, that are free from the nuisance censoring variable. It requires the conditional distribution of censoring given covariates to be modeled. The model selection strategy uses stepup or stepdown multiple hypothesis testing procedures that control either the proportion of false positives or generalized familywise error rate when comparing models based on estimates of average prediction error. The context can actually be cast as a missing data problem, where augmented inverse probability weighted complete case estimators of regression coefficients and prediction error can be used ( Tsiatis, 2006 , Semiparametric Theory and Missing Data). A simulation study and an interesting analysis of a recent AIDS trial are provided.     

Uncertainty for Data with Non-Detects: Air Toxic Emissions from Combustion

Air toxic emission factor datasets often contain one or more points below a single or multiple detection limits and such datasets are referred to as “censored.” Conventional methods used to deal with censored datasets include removing non-detects, replacing the censored points with zero, half of the detection limit, or the detection limit. However, the estimated means of the censored dataset by conventional methods are usually biased. Maximum likelihood estimation (MLE) and bootstrap simulation have been demonstrated as a statistically robust method to quantify variability and uncertainty of censored datasets and can provide asymptotically unbiased mean estimates. The MLE/bootstrap method is applied to 16 cases of censored air toxic emission factors, including benzene, formaldehyde, benzo(a)pyrene, mercury, arsenic, cadmium, total chromium, chromium VI and lead from coal, fuel oil, and/or wood waste external combustion sources. The proportion of censored values in the emission factor data ranges from 4 to 80%. Key factors that influence the estimated uncertainty in the mean of censored data are sample size and inter-unit variability. The largest range of uncertainty in the mean was obtained for the external coal combustion benzene emission factor, with 95 confidence interval of the mean equal to minus 93 to plus 411%.     

IS YOUR PHYLOGENY INFORMATIVE? MEASURING THE POWER OF COMPARATIVE METHODS

Phylogenetic comparative methods may fail to produce meaningful results when either the underlying model is inappropriate or the data contain insufficient information to inform the inference. The ability to measure the statistical power of these methods has become crucial to ensure that data quantity keeps pace with growing model complexity. Through simulations, we show that commonly applied model choice methods based on information criteria can have remarkably high error rates; this can be a problem because methods to estimate the uncertainty or power are not widely known or applied. Furthermore, the power of comparative methods can depend significantly on the structure of the data. We describe a Monte Carlo-based method which addresses both of these challenges, and show how this approach both quantifies and substantially reduces errors relative to information criteria. The method also produces meaningful confidence intervals for model parameters. We illustrate how the power to distinguish different models, such as varying levels of selection, varies both with number of taxa and structure of the phylogeny. We provide an open-source implementation in the pmc ("Phylogenetic Monte Carlo") package for the R programming language. We hope such power analysis becomes a routine part of model comparison in comparative methods.     

Testing for Poisson Zero Inflation in Disease Mapping

When analyzing mortality data due to rare diseases in small areas, it is common to find several health zones with no mortality cases. In these circumstances, the classical homogeneous model based on the Poisson distribution used to estimate the relative risks within each area may encounter lack of fit due to a disproportionately large frequency of zeros. To cope with these zeros, the zero inflated Poisson model can be used. In this paper, we propose a test for detecting zero inflation in the context of disease mapping which is based on bootstrap techniques. The test is illustrated using male mortality data due to brain cancer in Navarra, Spain. In addition, comparisons with other tests for Poisson zero inflation such as the score test and the likelihood ratio test are carried out in terms of empirical power and size using the brain cancer scenario. The proposed bootstrap test has good power and size and works well when detecting the excess of zeros in small area data sets. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Demography and mass-rearing of Carposina sasakii Matsumura (Lepidoptera: Carposinidae) reared on Golden Delicious and Red Fuji apples in the laboratory

Carposina sasakii Matsumura (Lepidoptera: Carposinidae), is one of the most serious fruit-boring pests in over ten species of fruit trees, and is especially damaging apples in the northern of China. The application of new planting systems, i.e., high-density and dwarfing rootstock orchard systems with mixed apple varieties, makes it important to study the fitness of C. sasakii on these apple varieties to gain fundamental knowledge for use in pest management involving this insect. In this study, life table data of C. sasakii were collected using Golden Delicious and Red Fuji apples as hosts. The egg-larva duration of male C. sasakii reared on Golden Delicious apples (22.81 d) was significantly shorter than that reared on Red Fuji apples (24.27 d). The egg-larva mortality in Golden Delicious apples (59.00%) was lower than that in Red Fuji apples (72.49%). The mortality of the pupal stage, however, was higher in Golden Delicious (10.51%) than in Red Fuji (0%). The total oviposition period (TPOP) on Golden Delicious apples (32.94 d) was significantly shorter than in individuals reared on Red Fuji apples (34.19 d). The intrinsic rate of increase (r = 0.0581 d⁻¹), net reproductive rate (R₀ = 7.57 offspring), and finite rate of increase (λ = 1.0598 d⁻¹) were all higher on Golden Delicious than those on Red Fuji. When the net reproductive rate (R₀) was used, the harvest rate of pupae was higher (0.8678) when reared on Golden Delicious apples than when reared on Red Fuji apples (0.8398). When a large cohort size (n = 200) was used for effective bootstrap sample, the P_E values for C. sasakii reared on Golden Delicious apples and Red Fuji apples were both almost equal to 1. For C. sasakii culturing purposes, Golden Delicious apples would be more productive than Red Fuji.     

Target-capture phylogenomics provide insights on gene and species tree discordances in Old World treefrogs (Anura: Rhacophoridae)

Genome-scale data have greatly facilitated the resolution of recalcitrant nodes that Sanger-based datasets have been unable to resolve. However, phylogenomic studies continue to use traditional methods such as bootstrapping to estimate branch support; and high bootstrap values are still interpreted as providing strong support for the correct topology. Furthermore, relatively little attention has been given to assessing discordances between gene and species trees, and the underlying processes that produce phylogenetic conflict. We generated novel genomic datasets to characterize and determine the causes of discordance in Old World treefrogs (Family: Rhacophoridae)—a group that is fraught with conflicting and poorly supported topologies among major clades. Additionally, a suite of data filtering strategies and analytical methods were applied to assess their impact on phylogenetic inference. We showed that incomplete lineage sorting was detected at all nodes that exhibited high levels of discordance. Those nodes were also associated with extremely short internal branches. We also clearly demonstrate that bootstrap values do not reflect uncertainty or confidence for the correct topology and, hence, should not be used as a measure of branch support in phylogenomic datasets. Overall, we showed that phylogenetic discordances in Old World treefrogs resulted from incomplete lineage sorting and that species tree inference can be improved using a multi-faceted, total-evidence approach, which uses the most amount of data and considers results from different analytical methods and datasets.     

Incorporating harvest rates into the sex-age-kill model for white-tailed deer

Although monitoring population trends is an essential component of game species management, wildlife managers rarely have complete counts of abundance. Often, they rely on population models to monitor population trends. As imperfect representations of real-world populations, models must be rigorously evaluated to be applied appropriately. Previous research has evaluated population models for white-tailed deer (Odocoileus virginianus); however, the precision and reliability of these models when tested against empirical measures of variability and bias largely is untested. We were able to statistically evaluate the Pennsylvania sex-age-kill (PASAK) population model using realistic error measured using data from 1,131 radiocollared white-tailed deer in Pennsylvania from 2002 to 2008. We used these data and harvest data (number killed, age-sex structure, etc.) to estimate precision of abundance estimates, identify the most efficient harvest data collection with respect to precision of parameter estimates, and evaluate PASAK model robustness to violation of assumptions. Median coefficient of variation (CV) estimates by Wildlife Management Unit, 13.2% in the most recent year, were slightly above benchmarks recommended for managing game species populations. Doubling reporting rates by hunters or doubling the number of deer checked by personnel in the field reduced median CVs to recommended levels. The PASAK model was robust to errors in estimates for adult male harvest rates but was sensitive to errors in subadult male harvest rates, especially in populations with lower harvest rates. In particular, an error in subadult (1.5-yr-old) male harvest rates resulted in the opposite error in subadult male, adult female, and juvenile population estimates. Also, evidence of a greater harvest probability for subadult female deer when compared with adult (≥2.5-yr-old) female deer resulted in a 9.5% underestimate of the population using the PASAK model. Because obtaining appropriate sample sizes, by management unit, to estimate harvest rate parameters each year may be too expensive, assumptions of constant annual harvest rates may be necessary. However, if changes in harvest regulations or hunter behavior influence subadult male harvest rates, the PASAK model could provide an unreliable index to population changes. © 2012 The Wildlife Society.     

Phylogeny and biogeography of highly diverged freshwater fish species (Leuciscinae,Cyprinidae, Teleostei) inferred from mitochondrial genome analysis

The distribution of freshwater taxa is a good biogeographic model to study pattern and process of vicariance and dispersal. The subfamily Leuciscinae (Cyprinidae, Teleostei) consists of many species distributed widely in Eurasia and North America. Leuciscinae have been divided into two phyletic groups, leuciscin and phoxinin. The phylogenetic relationships between major clades within the subfamily are poorly understood, largely because of the overwhelming diversity of the group. The origin of the Far Eastern phoxinin is an interesting question regarding the evolutionary history of Leuciscinae. Here we present phylogenetic analysis of 31 species of Leuciscinae and outgroups based on complete mitochondrial genome sequences to clarify the phylogenetic relationships and to infer the evolutionary history of the subfamily.