Semiparametric Regression in Size-Biased Sampling

Summary .  Size-biased sampling arises when a positive-valued outcome variable is sampled with selection probability proportional to its size. In this article, we propose a semiparametric linear regression model to analyze size-biased outcomes. In our proposed model, the regression parameters of covariates are of major interest, while the distribution of random errors is unspecified. Under the proposed model, we discover that regression parameters are invariant regardless of size-biased sampling. Following this invariance property, we develop a simple estimation procedure for inferences. Our proposed methods are evaluated in simulation studies and applied to two real data analyses.     

Spatial and temporal factors associated with nest survival of Gray Flycatchers in managed ponderosa pine forests

Gray Flycatchers (Empidonax wrightii) breed in a variety of habitats in the arid and semi‐arid regions of the western United States, but little is known about their breeding biology, especially in the northern portion of their range where they nest in ponderosa pine (Pinus ponderosa) forests. From May to July 2014 and 2015, we conducted surveys for singing male Gray Flycatchers along the eastern slope of the Cascade Range in Washington, U.S.A, monitored flycatcher nests, and quantified nest‐site vegetation. We used a logistic‐exposure model fit within a Bayesian framework to model the daily survival probability of flycatcher nests. During the 2 yr of our study, we monitored 141 nests, with 93% in ponderosa pines. Mean clutch size was 3.6 eggs and the mean number of young fledged per nest was 3.2. Predation accounted for 90% of failed nests. We found a positive association between daily nest survival and both nest height and distance of nest substrates from the nearest tree. Flycatchers that locate their nests higher above the ground and further from adjacent trees may be choosing the safest alternative because higher nests may be less exposed to terrestrial predators and nests in trees that are farther from other trees may be less exposed to arboreal predators such as jays (Corvidae) that may forage in patches with connected canopies. Nests in trees farther from other trees may also allow earlier detection of approaching predators and thus aid in nest defense.     

Parameter estimation for the distribution of single cell lag times

In Quantitative Microbial Risk Assessment, it is vital to understand how lag times of individual cells are distributed over a bacterial population. Such identified distributions can be used to predict the time by which, in a growth-supporting environment, a few pathogenic cells can multiply to a poisoning concentration level.We model the lag time of a single cell, inoculated into a new environment, by the delay of the growth function characterizing the generated subpopulation. We introduce an easy-to-implement procedure, based on the method of moments, to estimate the parameters of the distribution of single cell lag times. The advantage of the method is especially apparent for cases where the initial number of cells is small and random, and the culture is detectable only in the exponential growth phase.     

A preliminary analysis of distribution patterns in a large, pantropical genus, Barleria L. (Acanthaceae)

Barleria L. (Acanthaceae) is a large, polymorphic, widespread genus of herbs and shrubs comprising about 300 species, occurring mainly in Africa and Asia but with one species, Barleria oenotheroides Dum.Cours., extending to the New World tropics. Recent completion of a monographic infra-generic classification of the genus (in which seven sections are recognised, and the names of four of these validated in this paper—see Appendix 1), has facilitated a comprehensive analysis of distribution patterns on a global scale. The richest representation of Barleria is in Africa where there are two centres of diversity, one in tropical East Africa (about eighty species) and the other in southern Africa (about seventy species). The number of species tails off rapidly to both the Far East and the West. Barleria shows a marked trans-Atlantic disjunction between West Africa and the Neotropics, with B. oenotheroides shared by these two regions. This type of disjunction, which is known in other genera of the family, cannot be adequately explained in Barleria on the basis of long-distance dispersal or past continental movements. There is a high degree of regional endemism (e.g. 75% for the Indian subcontinent) at both the species and sectional levels within this genus. The degree of similarity between regions is correspondingly low. The endemics in each region tend to belong to only one or a few of the sections. There are few truly widespread taxa within the genus. East and West Africa are the only regions in which all sections are represented. Sections Barleria and Prionitis C.B. Cl. are the most widespread in the genus; Sections Somalia (Oliv.) Lindau, Fissimura M. Balkwill and Stellatohirtae M. Balkwill are mainly restricted to Africa and Sections Chrysothrix M. Balkwill and Cavirostrata M. Balkwill are the most restricted, occurring mainly in India and Sri Lanka. On a local scale, many of the species show highly restricted, clumped distributions; this is apparently related to particular soil types and possibly to the short-distance, ballistic mode of seed dispersal. This account of the biogeography of Barleria is to be regarded as preliminary, as much taxonomic work at the species level remains to be done before a full-scale cladistic biogeographic account can be undertaken. Particular areas worthy of future investigation include establishing the centre of origin of the genus and investigating the basis for the high degree of endemism shown by many of the species.     

Can transposable element copy number distribution parameters be estimated from natural populations of Drosophila melanogaster?

The copy frequency distribution of a transposable element family in a Drosophila melanogaster natural population is generally characterised by the values of the Charlesworths' model parameters α and β (Charlesworth & Charlesworth, 1983). The estimation of these parameters is made using the observed distribution of the occupied sites in a population sample. Several results have been interpreted as due either to the influence of stochastic factors or to deterministic factors (transposition, excision, selection…). The accuracy of this method was tested by estimations performed on samples from simulated populations. The results show that with the sample size usually used for natural population studies, the confidence intervals are too large to reasonably deduce either the element copy number distribution or the values of transposition and excision rate and selective coefficients.     

Cod Gadus morhua L. populations as behavioural units: inference from time series on juvenile abundance in the eastern Skagerrak

Abundance and distribution of cod Gadus morhua in various size intervals and age groups between 2000 and 2005 were followed in coastal trawl surveys. In spite of a reduction in fishing pressure in recent years and high cod recruitment in the Skagerrak region in 2001 and 2003, no recovery could be evidenced. The survey data clearly showed that low cod density areas were not recolonized, even though abundance of juvenile cod remained high for about a year after the recruitment episodes. Increased abundance of fish >400 mm total length was only discernible at some scattered locations where other studies also have suggested local populations still to be present. The intermittent high recruitment has been linked to an inflow of egg and larvae from the North Sea, a theory which also has gained support from genetic studies. It was thus argued that the disappearance of the juvenile cod from the inshore is an effect of a migratory behaviour; the fish of offshore origin eventually leave the coast for the open Skagerrak or the North Sea. These findings support a view on cod populations as essentially behavioural entities, whereas dispersal of early life stages may be less important as a structuring mechanism.