Early environment influences later performance in fishes

Conditions fish encounter during embryogenesis and early life history can leave lasting effects not only on morphology, but also on growth rate, life‐history and behavioural traits. The ecology of offspring can be affected by conditions experienced by their parents and mother in particular. This review summarizes such early impacts and their ecological influences for a variety of teleost species, but with special reference to salmonids. Growth and adult body size, sex ratio, egg size, lifespan and tendency to migrate can all be affected by early influences. Mechanisms behind such phenotypically plastic impacts are not well known, but epigenetic change appears to be one central mechanism. The thermal regime during development and incubation is particularly important, but also early food consumption and intraspecific density can all be responsible for later life‐history variation. For behavioural traits, early experiences with effects on brain, sensory development and cognition appear essential. This may also influence boldness and other social behaviours such as mate choice. At the end of the review, several issues and questions for future studies are given.     

The reproductive behavior of six species of Namib desert tenebrionid beetles (Coleoptera: Tenebrionidae)

The reproductive behavior of six species of tenebrionid beetles (Coleoptera: Tenebrionidae) was studied in the Namib Desert of southern Africa. In three species, males follow closely behind females (following behavior), while in the other three species, males mount females and remain clasped to them for extended periods (riding behavior). Following behavior occurs before and sometimes after copulation, while riding behavior occurs primarily after copulation. Males of all six species guard females from contesting males, although the effectiveness of guarding is greater in riding species. The evolution of the two male mating strategies does not appear to be related to operational sex ratio differences but, rather, to differential tendencies of females to remate. Variation in total pair duration within following and riding species may be attributed partly to species differences in operational sex ratio. However, pair durations are not affected by experimental manipulations of sex ratio in each species.     

Sample Size Determination for Grouped Exponential Observations: A Cost Function Approach

Calculating the required sample size for a desired power at a given type I error level, we often assume that we know the exact time of all subject responses whenever they occur during our study period. It is very common, however, in practice that we only monitor subjects periodically and, therefore, we know only whether responses occur or not during an interval. This paper includes a quantitative discussion of the effect resulting from data grouping or interval censoring on the required sample size when we have two treatment groups. Furthermore, with the goal of exploring the optimum in the number of subjects, the number of examinations per subject for test responses, and the total length of a study time period, this paper also provides a general guideline about how to determine these to minimize the total cost of a study for a desired power at a given α-level. A specified linear cost function that incorporates the costs of obtaining subjects, periodic examinations for test responses of subjects, and the total length of a study period, is assumed, primarily for illustrative purpose.     

An overview of indexes to evaluate terrestrial plants for phytoremediation purposes (Review)

This paper reviews the various factors, coefficients and indexes developed to evaluate terrestrial plant performance in respect to phytoremediation.A brief list of indexes includes the Accumulation factor, Bioabsorption coefficient, Bioaccumulation coefficient, Bioaccumulation factor, Bioconcentration, Bioconcentration coefficient, Bioconcentration factor, Biological absorption coefficient, Biological accumulation coefficient, Biological concentration factor, Biological transfer coefficient, Concentration factor, Enrichment coefficient, Enrichment factor, Extraction coefficient, Index of bioaccumulation, Mobility index, Shoot accumulation factor, Soil host transfer factor, Soil-plant transfer coefficient, Soil-plant transfer factor, Transfer factor and Translocation factor.These indexes represent the result of a ratio calculation between element concentrations in plant parts to that of substrata. In other cases indexes arise from the ratio calculation of element concentrations in two distinct plant parts.In the literature different terms have been attributed to the same ratio and this often represents an overlap in terminology. On the other hand the same term corresponds to several different ratios and this could create confusion and misinterpretation in data comparison.Furthermore, the evaluation of hyperaccumulation, phytostabilization or phytoextraction of plant species is not always performed in the same way. Different plant parts are considered as well as different extraction procedures for both plant and substrata element assessment. As a consequence, a direct comparison between obtained data is not always reliable and possible.In this paper the various available indexes are reviewed, highlighting both the similarity and differences between them with the aim of helping the community in choosing the appropriate term for both data evaluation and comparison. In this author’s opinion there is no need of new terms to define indexes. I would stress the need for conformity to the original definitions and criteria.     

How to deal with oxygen radicals stemming from mitochondrial fatty acid oxidation

Oxygen radical formation in mitochondria is an incompletely understood attribute of eukaryotic cells. Recently, a kinetic model was proposed, in which the ratio between electrons entering the respiratory chain via FADH₂ or NADH determines radical formation. During glucose breakdown, the ratio is low; during fatty acid breakdown, the ratio is high (the ratio increasing—asymptotically—with fatty acid length to 0.5, when compared with 0.2 for glucose). Thus, fatty acid oxidation would generate higher levels of radical formation. As a result, breakdown of fatty acids, performed without generation of extra FADH₂ in mitochondria, could be beneficial for the cell, especially in the case of long and very long chained ones. This possibly has been a major factor in the evolution of peroxisomes. Increased radical formation, as proposed by the model, can also shed light on the lack of neuronal fatty acid oxidation and tells us about hurdles during early eukaryotic evolution. We specifically focus on extending and discussing the model in light of recent publications and findings.     

Asymptotic distributions of kappa statistics and their differences with many raters,many rating categories and two conditions

In clinical research and in more general classification problems, a frequent concern is the reliability of a rating system. In the absence of a gold standard, agreement may be considered as an indication of reliability. When dealing with categorical data, the well‐known kappa statistic is often used to measure agreement. The aim of this paper is to obtain a theoretical result about the asymptotic distribution of the kappa statistic with multiple items, multiple raters, multiple conditions, and multiple rating categories (more than two), based on recent work. The result settles a long lasting quest for the asymptotic variance of the kappa statistic in this situation and allows for the construction of asymptotic confidence intervals. A recent application to clinical endoscopy and to the diagnosis of inflammatory bowel diseases (IBDs) is shortly presented to complement the theoretical perspective.     

Testing the Equality of Dependent Variances

The likelihood ratio test for testing equality of vgE;2 correlated variables is developed. In general, evaluation of the test statistic involves the iterative optimization of a likelihood function with 1 + v(v – 1)/2 parameters. The explicit form of the test statistic is derived in the bivariate case, and an iterative algorithm for determining the maximum likelihood estimates is suggested. A limited Monte Carlo study determines the behavior of the proposed procedure under the null hypothesis and variety of parameter values.