Effect of simulated macroalgae on the fish assemblage associated with a temperate reef system

Increased habitat complexity is supposed to promote increased diversity, abundance and biomass. This study tested the effect of the macroalgal cover on temperate reef fishes by mimicking macroalgae on artificial reefs in NW Sicily (Mediterranean Sea). Macroalgal cover affected reef fishes in different ways and independently of intrinsic temporal trends. The fish assemblages of manipulated and control artificial reef units differed in the relative abundances of the associated species, but little in species composition. In line with studies in seagrass habitats, fishes were most abundant in reefs covered by artificial macroalgae. Three species (Boops boops, Serranus scriba and Symphodus ocellatus) exhibited consistently greater abundance on vegetated reef units than on control reef units. The total number of species and the abundance of three particular species (S. scriba, S. ocellatus and Thalassoma pavo) displayed temporal trends which were independent on short and large temporal scales. Only fish total biomass and one species (Spicara flexuosa) displayed strong effects of interaction among the experimental factors. Mechanisms to explain these findings are discussed from observational evidence on habitat use and interactions among multiple species. This study highlights that manipulative experiments involving repeated sampling of fish in artificial habitats appear to be a valid approach to study fish-habitat relationships in fluctuating environments. It is also concluded that macroalgae mimics may serve as a tool for restoring lost marine vegetated habitats when current human-induced conditions prevent the recovery of pristine macroalgal stands.     

A Note on the Log‐Rank Test in Life Table Analysis with Correlated Observations

Survival data consisting of independent sets of correlated failure times may arise in many situations. For example, we may take repeated observations of the failure time of interest from each patient or observations of the failure time on siblings, or consider the failure times on littermates in toxicological experiments. Because the failure times taken on the same patient or related family members or from the same litter are likely correlated, use of the classical log‐rank test in these situations can be quite misleading with respect to type I error. To avoid this concern, this paper develops two closed‐form asymptotic summary tests, that account for the intraclass correlation between the failure times within patients or units. In fact, one of these two test includes the classical log‐rank test as a special case when the intraclass correlation equals 0. Furthermore, to evaluate the finite‐sample performance of the two tests developed here, this paper applies Monte Carlo simulation and notes that they can actually perform quite well in a variety of situations considered here.     

Construction of a yeast artificial chromosome library of tomato and identification of cloned segments linked to two disease resistance loci

Summary We have constructed a yeast artificial chromosome (YAC) library of tomato for chromosome walking that contains the equivalent of three haploid genomes (22 000 clones). The source of high molecular weight DNA was leaf protoplasts from the tomato cultivars VFNT cherry and Rio Grande-PtoR, which together contain loci encoding resistance to six pathogens of tomato. Approximately 11 000 YACs have been screened with RFLP markers that cosegregate withTm-2a andPto — loci conferring resistance to tobacco mosaic virus andPseudomonas syringae pv.tomato, respectively. Five YACs were identified that hybridized to the markers and are therefore starting points for chromosome walks to these genes. A subset of the library was characterized for the presence of various repetitive sequences and YACs were identified that carried TGRI, a repeat clustered near the telomeres of most tomato chromosomes, TGRII, an interspersed repeat, and TGRIIl, a repeat that occurs primarily at centromeric sites. Evaluation of the library for organellar sequences revealed that approximately 10% of the clones contain chloroplast sequences. Many of these YAC clones appear to contain the entire 155 kb tomato chloroplast genome. The tomato cultivars used in the library construction, in addition to carrying various disease resistance genes, also contain the wild-type alleles corresponding to most recessive mutations that have been mapped by classical linkage analysis. Thus, in addition to its utility for physical mapping and genome studies, this library should be useful for chromosome walking to genes corresponding to virtually any phenotype that can be scored in a segregating population.     

Use of diluted medium in repeated-batch fermentation for production of lignin peroxidase by <Emphasis Type="Italic">Phanerochaete chrysosporium</Emphasis>

Lignin peroxidase has been extensively studied due to the potential use of this enzyme in environmental pollution control. Important aspects of the production of the enzyme by the white rot fungus, Phanerochaete chrysosporium, include the improvement of yield results and cell maintenance. In the present work, Phanerochaete chrysosporium was immobilized in polyurethane foam and used for repeated-batch fermentations with various dilution of the initial medium (D), and lignin peroxidase production was investigated. The peak of 283 ± 17.5 U lignin peroxidase/l production rate was obtained at a D of 1/5, with significantly lower production rates seen at higher and lower dilution ratios. When six cycles of repeated-batch fermentation were conducted using a D of 1/5, the results revealed that at least four cycles of repeated-batch fermentation were possible with a high lignin peroxidase production rate under a cut-off value of 178 ± 3.87 U/l. Furthermore, the cell-free culture broth could be successfully concentrated to 2,800 U/l by ultrafiltration. Thus, the present study shows that optimizing the dilution of the utilized nutritional medium can improve repeated batch production of lignin peroxidase from immobilized P. chrysosporium, in terms of both cycle number and output.     

Bayesian analysis for nonlinear regression model under skewed errors,with application in growth curves

We have considered a Bayesian approach for the nonlinear regression model by replacing the normal distribution on the error term by some skewed distributions, which account for both skewness and heavy tails or skewness alone. The type of data considered in this paper concerns repeated measurements taken in time on a set of individuals. Such multiple observations on the same individual generally produce serially correlated outcomes. Thus, additionally, our model does allow for a correlation between observations made from the same individual. We have illustrated the procedure using a data set to study the growth curves of a clinic measurement of a group of pregnant women from an obstetrics clinic in Santiago, Chile. Parameter estimation and prediction were carried out using appropriate posterior simulation schemes based in Markov Chain Monte Carlo methods. Besides the deviance information criterion (DIC) and the conditional predictive ordinate (CPO), we suggest the use of proper scoring rules based on the posterior predictive distribution for comparing models. For our data set, all these criteria chose the skew‐t model as the best model for the errors. These DIC and CPO criteria are also validated, for the model proposed here, through a simulation study. As a conclusion of this study, the DIC criterion is not trustful for this kind of complex model.     

Estimating the cumulative risk of a false-positive test in a repeated screening program

The goal of screening tests for a chronic disease such as cancer is early detection and treatment with a consequent reduction in mortality from the disease. Screening tests, however, might produce false positive and false-negative results. With an increasing number of screening tests, it is clear that the risk of a false-positive screen, a finding with potentially significant emotional, financial, and health costs, also increases. Elmore et al. (1998, New England Journal of Medicine 338, 1089-1096), Christiansen et al. (2000, Journal of the National Cancer Institute 92, 1657-1666), and Gelfand and Wang (2000, Statistics in Medicine 19, 1865-1879) investigated this problem under the somewhat unrealistic assumption that the choice of making the decision to drop out at the kth screen does not depend upon the results of the earlier k - 1 screens. In this article we obtain sufficient and necessary conditions for their assumption to hold and use one of them to provide a method for testing the validity of the assumption. A new model which does not depend on their assumption is introduced. The maximum likelihood estimator of the cumulative risk of receiving a false-positive screen under the new model is derived and its asymptotic normality is proved. The extension of the new model by incorporating covariate information is also considered. We apply our testing method and the new model to data from the breast cancer screening trial of the Health Insurance Plan of Greater New York.