Strengths and Limitations of Period Estimation Methods for Circadian Data

A key step in the analysis of circadian data is to make an accurate estimate of the underlying period. There are many different techniques and algorithms for determining period, all with different assumptions and with differing levels of complexity. Choosing which algorithm, which implementation and which measures of accuracy to use can offer many pitfalls, especially for the non-expert. We have developed the BioDare system, an online service allowing data-sharing (including public dissemination), data-processing and analysis. Circadian experiments are the main focus of BioDare hence performing period analysis is a major feature of the system. Six methods have been incorporated into BioDare: Enright and Lomb-Scargle periodograms, FFT-NLLS, mFourfit, MESA and Spectrum Resampling. Here we review those six techniques, explain the principles behind each algorithm and evaluate their performance. In order to quantify the methods'' accuracy, we examine the algorithms against artificial mathematical test signals and model-generated mRNA data. Our re-implementation of each method in Java allows meaningful comparisons of the computational complexity and computing time associated with each algorithm. Finally, we provide guidelines on which algorithms are most appropriate for which data types, and recommendations on experimental design to extract optimal data for analysis.     

Evaluating range‐expansion models for calculating nonnative species' expansion rate

Species range shifts associated with environmental change or biological invasions are increasingly important study areas. However, quantifying range expansion rates may be heavily influenced by methodology and/or sampling bias. We compared expansion rate estimates of Roesel''s bush-cricket (Metrioptera roeselii, Hagenbach 1822), a nonnative species currently expanding its range in south-central Sweden, from range statistic models based on distance measures (mean, median, 95^th gamma quantile, marginal mean, maximum, and conditional maximum) and an area-based method (grid occupancy). We used sampling simulations to determine the sensitivity of the different methods to incomplete sampling across the species'' range. For periods when we had comprehensive survey data, range expansion estimates clustered into two groups: (1) those calculated from range margin statistics (gamma, marginal mean, maximum, and conditional maximum: ˜3 km/year), and (2) those calculated from the central tendency (mean and median) and the area-based method of grid occupancy (˜1.5 km/year). Range statistic measures differed greatly in their sensitivity to sampling effort; the proportion of sampling required to achieve an estimate within 10% of the true value ranged from 0.17 to 0.9. Grid occupancy and median were most sensitive to sampling effort, and the maximum and gamma quantile the least. If periods with incomplete sampling were included in the range expansion calculations, this generally lowered the estimates (range 16–72%), with exception of the gamma quantile that was slightly higher (6%). Care should be taken when interpreting rate expansion estimates from data sampled from only a fraction of the full distribution. Methods based on the central tendency will give rates approximately half that of methods based on the range margin. The gamma quantile method appears to be the most robust to incomplete sampling bias and should be considered as the method of choice when sampling the entire distribution is not possible.     

Child Mortality Estimation: Consistency of Under-Five Mortality Rate Estimates Using Full Birth Histories and Summary Birth Histories

Background

Given the lack of complete vital registration data in most developing countries, for many countries it is not possible to accurately estimate under-five mortality rates from vital registration systems. Heavy reliance is often placed on direct and indirect methods for analyzing data collected from birth histories to estimate under-five mortality rates. Yet few systematic comparisons of these methods have been undertaken. This paper investigates whether analysts should use both direct and indirect estimates from full birth histories, and under what circumstances indirect estimates derived from summary birth histories should be used.

Methods and Findings

Usings Demographic and Health Surveys data from West Africa, East Africa, Latin America, and South/Southeast Asia, I quantify the differences between direct and indirect estimates of under-five mortality rates, analyze data quality issues, note the relative effects of these issues, and test whether these issues explain the observed differences. I find that indirect estimates are generally consistent with direct estimates, after adjustment for fertility change and birth transference, but don''t add substantial additional insight beyond direct estimates. However, choice of direct or indirect method was found to be important in terms of both the adjustment for data errors and the assumptions made about fertility.

Conclusions

Although adjusted indirect estimates are generally consistent with adjusted direct estimates, some notable inconsistencies were observed for countries that had experienced either a political or economic crisis or stalled health transition in their recent past. This result suggests that when a population has experienced a smooth mortality decline or only short periods of excess mortality, both adjusted methods perform equally well. However, the observed inconsistencies identified suggest that the indirect method is particularly prone to bias resulting from violations of its strong assumptions about recent mortality and fertility. Hence, indirect estimates of under-five mortality rates from summary birth histories should be used only for populations that have experienced either smooth mortality declines or only short periods of excess mortality in their recent past. Please see later in the article for the Editors'' Summary.     

Measuring Under-Five Mortality: Validation of New Low-Cost Methods

Background

There has been increasing interest in measuring under-five mortality as a health indicator and as a critical measure of human development. In countries with complete vital registration systems that capture all births and deaths, under-five mortality can be directly calculated. In the absence of a complete vital registration system, however, child mortality must be estimated using surveys that ask women to report the births and deaths of their children. Two survey methods exist for capturing this information: summary birth histories and complete birth histories. A summary birth history requires a minimum of only two questions: how many live births has each mother had and how many of them have survived. Indirect methods are then applied using the information from these two questions and the age of the mother to estimate under-five mortality going back in time prior to the survey. Estimates generated from complete birth histories are viewed as the most accurate when surveys are required to estimate under-five mortality, especially for the most recent time periods. However, it is much more costly and labor intensive to collect these detailed data, especially for the purpose of generating small area estimates. As a result, there is a demand for improvement of the methods employing summary birth history data to produce more accurate as well as subnational estimates of child mortality.

Methods and Findings

We used data from 166 Demographic and Health Surveys (DHS) to develop new empirically based methods of estimating under-five mortality using children ever born and children dead data. We then validated them using both in- and out-of-sample analyses. We developed a range of methods on the basis of three dimensions of the problem: (1) approximating the average length of exposure to mortality from a mother''s set of children using either maternal age or time since first birth; (2) using cohort and period measures of the fraction of children ever born that are dead; and (3) capturing country and regional variation in the age pattern of fertility and mortality. We focused on improving estimates in the most recent time periods prior to a survey where the traditional indirect methods fail. In addition, all of our methods incorporated uncertainty. Validated against under-five estimates generated from complete birth histories, our methods outperformed the standard indirect method by an average of 43.7% (95% confidence interval [CI] 41.2–45.2). In the 5 y prior to the survey, the new methods resulted in a 53.3% (95% CI 51.3–55.2) improvement. To illustrate the value of this method for local area estimation, we applied our new methods to an analysis of summary birth histories in the 1990, 2000, and 2005 Mexican censuses, generating subnational estimates of under-five mortality for each of 233 jurisdictions.

Conclusions

The new methods significantly improve the estimation of under-five mortality using summary birth history data. In areas without vital registration data, summary birth histories can provide accurate estimates of child mortality. Because only two questions are required of a female respondent to generate these data, they can easily be included in existing survey programs as well as routine censuses of the population. With the wider application of these methods to census data, countries now have the means to generate estimates for subnational areas and population subgroups, important for measuring and addressing health inequalities and developing local policy to improve child survival. Please see later in the article for the Editors'' Summary     

Field Evaluation of Alternative Earthen Final Covers

Five methods to assess percolation rate from alternative earthen final covers (AEFCs) are described in the context of the precision with which the percolation rate can be estimated: trend analysis, tracer methods, water balance method, Darcy's Law calculations, and lysimetry. Trend evaluation of water content data is the least precise method because it cannot be used alone to assess the percolation rate. The precision of percolation rates estimated using tracer methods depends on the tracer concentration, percolation rate, and the sensitivity of the chemical extraction and analysis methods. Percolation rates determined using the water balance method have a precision of approximately 100 mm/yr in humid climates and 50 mm/yr in semiarid and drier climates, which is too large to demonstrate that an AEFC is meeting typical equivalency criterion (30 mm/yr or less). In most cases, the precision will be much poorer. Percolation rates computed using Darcy's Law with measured profiles of water content and matric suction typically have a precision that is about two orders of magnitude (or more) greater than the computed percolation rate. The Darcy's Law method can only be used for performance assessment if the estimated percolation rate is much smaller than the equivalency criterion and preferential flow is not present. Lysimetry provides the most precise estimates of percolation rate, but the precision depends on the method used to measure the collected water. The lysimeter used in the Alternative Cover Assessment Program (ACAP), which is described in this paper, can be used to estimate percolation rates with a precision between 0.00004 to 0.5 mm/yr, depending on the measurement method and the flow rates.     

Estimating perinatal critical windows of susceptibility to environmental mixtures via structured Bayesian regression tree pairs

Maternal exposure to environmental chemicals during pregnancy can alter birth and children's health outcomes. Research seeks to identify critical windows, time periods when exposures can change future health outcomes, and estimate the exposure–response relationship. Existing statistical approaches focus on estimation of the association between maternal exposure to a single environmental chemical observed at high temporal resolution (e.g., weekly throughout pregnancy) and children's health outcomes. Extending to multiple chemicals observed at high temporal resolution poses a dimensionality problem and statistical methods are lacking. We propose a regression tree–based model for mixtures of exposures observed at high temporal resolution. The proposed approach uses an additive ensemble of tree pairs that defines structured main effects and interactions between time-resolved predictors and performs variable selection to select out of the model predictors not correlated with the outcome. In simulation, we show that the tree-based approach performs better than existing methods for a single exposure and can accurately estimate critical windows in the exposure–response relation for mixtures. We apply our method to estimate the relationship between five exposures measured weekly throughout pregnancy and birth weight in a Denver, Colorado, birth cohort. We identified critical windows during which fine particulate matter, sulfur dioxide, and temperature are negatively associated with birth weight and an interaction between fine particulate matter and temperature. Software is made available in the R package dlmtree.     

Using soundscape recordings to estimate bird species abundance, richness, and composition

ABSTRACT Point counts are the most frequently used technique for sampling bird populations and communities, but have well‐known limitations such as inter‐ and intraobserver errors and limited availability of expert field observers. The use of acoustic recordings to survey birds offers solutions to these limitations. We designed a Soundscape Recording System (SRS) that combines a four‐channel, discrete microphone system with a quadraphonic playback system for surveying bird communities. We compared the effectiveness of SRS and point counts for estimating species abundance, richness, and composition of riparian breeding birds in California by comparing data collected simultaneously using both methods. We used the temporal‐removal method to estimate individual bird detection probabilities and species abundances using the program MARK. Akaike's Information Criterion provided strong evidence that detection probabilities differed between the two survey methods and among the 10 most common species. The probability of detecting birds was higher when listening to SRS recordings in the laboratory than during the field survey. Additionally, SRS data demonstrated a better fit to the temporal‐removal model assumptions and yielded more reliable estimates of detection probability and abundance than point‐count data. Our results demonstrate how the perceptual constraints of observers can affect temporal detection patterns during point counts and thus influence abundance estimates derived from time‐of‐detection approaches. We used a closed‐population capture–recapture approach to calculate jackknife estimates of species richness and average species detection probabilities for SRS and point counts using the program CAPTURE. SRS and point counts had similar species richness and detection probabilities. However, the methods differed in the composition of species detected based on Jaccard's similarity index. Most individuals (83%) detected during point counts vocalized at least once during the survey period and were available for detection using a purely acoustic technique, such as SRS. SRS provides an effective method for surveying bird communities, particularly when most species are detected by sound. SRS can eliminate or minimize observer biases, produce permanent records of surveys, and resolve problems associated with the limited availability of expert field observers.     

Measuring gas vesicle dimensions by electron microscopy

Gas vesicles (GVs) are cylindrical or spindle‐shaped protein nanostructures filled with air and used for flotation by various cyanobacteria, heterotrophic bacteria, and Archaea. Recently, GVs have gained interest in biotechnology applications due to their ability to serve as imaging agents and actuators for ultrasound, magnetic resonance and several optical techniques. The diameter of GVs is a crucial parameter contributing to their mechanical stability, buoyancy function and evolution in host cells, as well as their properties in imaging applications. Despite its importance, reported diameters for the same types of GV differ depending on the method used for its assessment. Here, we provide an explanation for these discrepancies and utilize electron microscopy (EM) techniques to accurately estimate the diameter of the most commonly studied types of GVs. We show that during air drying on the EM grid, GVs flatten, leading to a ~1.5‐fold increase in their apparent diameter. We demonstrate that GVs'' diameter can be accurately determined by direct measurements from cryo‐EM samples or alternatively indirectly derived from widths of flat collapsed and negatively stained GVs. Our findings help explain the inconsistency in previously reported data and provide accurate methods to measure GVs dimensions.     

A simple and low‐cost method to estimate spatial positions of shorebirds: the Telescope‐Mounted Angulator

ABSTRACT Estimating the spatial position of birds in open habitats like intertidal mudflats is important for many studies, for example, detailed density estimates or linking predation pressure to resource availability. To date, several methods have been used to estimate the positions of birds, including density counts in predetermined plots, range finders, photography, and tracking individuals tagged with GPS‐equipped transmitters, and each method has advantages and shortcomings. Counts in premarked plots are possible over relatively long distances, but small‐scale information is lost due to within‐plot averaging. Other methods accurately determine the position of individuals, but can only be used at relatively short distances or involve capturing birds. We describe a simple and low‐cost method to estimate the spatial position of individual birds in open habitats using a telescope‐mounted instrument that measures the scope's viewing angle. Using this Telescope‐Mounted Angulator (TMA), the distance to focal birds can be calculated by simple trigonometry, requiring only the viewing angle and mounting height of the telescope. Laboratory tests revealed that the TMA was most accurate when calibrated for individual observers. Field experiments performed on a 4‐m high observation platform showed that the TMA can estimate the position of shorebirds with an accuracy of 18 to 36 m up to a distance of 500 m. By also including the direction, determined with a compass, the spatial position of birds can be reliably estimated. The TMA can be a valuable tool for estimating the spatial position of animals in various flat landscapes, providing detailed measurements in a relatively short period of time.     

On path restoration for censored outcomes

Summary Dimension reduction, model and variable selection are ubiquitous concepts in modern statistical science and deriving new methods beyond the scope of current methodology is noteworthy. This article briefly reviews existing regularization methods for penalized least squares and likelihood for survival data and their extension to a certain class of penalized estimating function. We show that if one's goal is to estimate the entire regularized coefficient path using the observed survival data, then all current strategies fail for the Buckley–James estimating function. We propose a novel two‐stage method to estimate and restore the entire Dantzig‐regularized coefficient path for censored outcomes in a least‐squares framework. We apply our methods to a microarray study of lung andenocarcinoma with sample size n = 200 and p = 1036 gene predictors and find 10 genes that are consistently selected across different criteria and an additional 14 genes that merit further investigation. In simulation studies, we found that the proposed path restoration and variable selection technique has the potential to perform as well as existing methods that begin with a proper convex loss function at the outset.     

Demographic and genetic estimates of effective population size (Ne) reveals genetic compensation in steelhead trout

Estimates of effective population size (Ne) are required to predict the impacts of genetic drift and inbreeding on the evolutionary dynamics of populations. How the ratio of Ne to the number of sexually mature adults (N) varies in natural vertebrate populations has not been addressed. We examined the sensitivity of Ne/N to fluctuations of N and determined the major variables responsible for changing the ratio over a period of 17 years in a population of steelhead trout (Oncorhynchus mykiss) from Washington State. Demographic and genetic methods were used to estimate Ne. Genetic estimates of Ne were gained via temporal and linkage disequilibrium methods using data from eight microsatellite loci. DNA for genetic analysis was amplified from archived smolt scales. The Ne/N from 1977 to 1994, estimated using the temporal method, was 0.73 and the comprehensive demographic estimate of Ne/N over the same time period was 0.53. Demographic estimates of Ne indicated that variance in reproductive success had the most substantial impact on reducing Ne in this population, followed by fluctuations in population size. We found increased Ne/N ratios at low N, which we identified as genetic compensation. Combining the information from the demographic and genetic methods of estimating Ne allowed us to determine that a reduction in variance in reproductive success must be responsible for this compensation effect. Understanding genetic compensation in natural populations will be valuable for predicting the effects of changes in N (i.e. periods of high population density and bottlenecks) on the fitness and genetic variation of natural populations.     

Turning the analysis of obesity–mortality associations upside down: Modeling years of life lost through conditional distributions

Objective:

We demonstrate the utility of parametric survival analysis. The analysis of longevity as a function of risk factors such as body mass index (BMI; kg/m²), activity levels, and dietary factors is a mainstay of obesity research. Modeling survival through hazard functions, relative risks, or odds of dying with methods such as Cox proportional hazards or logistic regression are the most common approaches and have many advantages. However, they also have disadvantages in terms of the ease of interpretability, especially for non‐statisticians; the need for additional data to convert parameter estimates to estimates of years of life lost (YLL); debates about the appropriate time scale in the model; and an inability to estimate median survival time when the censoring rate is too high.

Design and Methods:

We will conduct parametric survival analyses with multiple distributions, including distributions that are known to be poor fits (Gaussian), as well as a newly discovered “Compressed Gaussian”'' distribution.

Results:

Parametric survival analysis models were able to accurately estimate median survival times in a population‐based data set of 15,703 individuals, even for distributions that were not good fits and the censoring rate was high, due to the central limit theorem.

Conclusions:

Parametric survival models are able to provide more direct answers, and in our analysis of an obesity‐related data set, gave consistent YLL estimates regardless of the distribution used. We recommend increased consideration of parametric survival models in chronic disease and risk factor epidemiology.     

Quantification of avian parental behavior: what are the minimum necessary sample times?

Methods used to study parental behavior are largely idiosyncratic and are rarely tested to verify that they yield reliable data. In particular, the minimum number and duration of observations used to describe behavior accurately is rarely, if ever, justified. Using data on parental behavior of Eastern Kingbirds (Tyrannus tyrannus) collected by video in Oregon, we evaluated three questions regarding sampling methods: (1) Is within‐pair behavior sufficiently consistent among days so that observations from a single session are representative of parental behavior? (2) Does a 1‐h sampling window fairly represent parental behavior or is a longer period needed to accurately describe behavior? (3) Assuming that a 1‐h period is sufficient, does the first hour immediately after disturbance to start recordings yield reliable data? We found that among‐pair differences in parental behavior were consistent over different days and that a single hour of observation was representative of parental behavior over a longer (2–3 h) period of observation. However, our data also suggested that the first hour yielded less representative data than the remaining 2–3 h; nonetheless, consistent among‐pair differences were still detectable. The shortcoming of data collected in the first hour appeared to be due to a lingering effect of human disturbance from setting up recording devices rather than a time‐of‐day effect. We suggest that researchers test the appropriateness of their methods, but our kingbird data suggest that observations over relatively brief periods can yield useful and reliable data.     

A novel cost function to estimate parameters of oscillatory biochemical systems

Oscillatory pathways are among the most important classes of biochemical systems with examples ranging from circadian rhythms and cell cycle maintenance. Mathematical modeling of these highly interconnected biochemical networks is needed to meet numerous objectives such as investigating, predicting and controlling the dynamics of these systems. Identifying the kinetic rate parameters is essential for fully modeling these and other biological processes. These kinetic parameters, however, are not usually available from measurements and most of them have to be estimated by parameter fitting techniques. One of the issues with estimating kinetic parameters in oscillatory systems is the irregularities in the least square (LS) cost function surface used to estimate these parameters, which is caused by the periodicity of the measurements. These irregularities result in numerous local minima, which limit the performance of even some of the most robust global optimization algorithms. We proposed a parameter estimation framework to address these issues that integrates temporal information with periodic information embedded in the measurements used to estimate these parameters. This periodic information is used to build a proposed cost function with better surface properties leading to fewer local minima and better performance of global optimization algorithms. We verified for three oscillatory biochemical systems that our proposed cost function results in an increased ability to estimate accurate kinetic parameters as compared to the traditional LS cost function. We combine this cost function with an improved noise removal approach that leverages periodic characteristics embedded in the measurements to effectively reduce noise. The results provide strong evidence on the efficacy of this noise removal approach over the previous commonly used wavelet hard-thresholding noise removal methods. This proposed optimization framework results in more accurate kinetic parameters that will eventually lead to biochemical models that are more precise, predictable, and controllable.     

Fast and accurate fitting of relaxation dispersion data using the flexible software package GLOVE

Relaxation dispersion spectroscopy is one of the most widely used techniques for the analysis of protein dynamics. To obtain a detailed understanding of the protein function from the view point of dynamics, it is essential to fit relaxation dispersion data accurately. The grid search method is commonly used for relaxation dispersion curve fits, but it does not always find the global minimum that provides the best-fit parameter set. Also, the fitting quality does not always improve with increase of the grid size although the computational time becomes longer. This is because relaxation dispersion curve fitting suffers from a local minimum problem, which is a general problem in non-linear least squares curve fitting. Therefore, in order to fit relaxation dispersion data rapidly and accurately, we developed a new fitting program called GLOVE that minimizes global and local parameters alternately, and incorporates a Monte-Carlo minimization method that enables fitting parameters to pass through local minima with low computational cost. GLOVE also implements a random search method, which sets up initial parameter values randomly within user-defined ranges. We demonstrate here that the combined use of the three methods can find the global minimum more rapidly and more accurately than grid search alone.     

Adjusting count period strategies to improve the accuracy of forest bird abundance estimates from point transect distance sampling surveys

Although point transect distance sampling methods have become widely used in surveys of forest birds, there has been no attempt to tailor field methods to maximize the accuracy of abundance estimates by minimizing the effects of violations of the method's critical assumptions, which are: (1) birds at distance 0 m are detected with certainty, (2) birds are detected at their initial location and (3) distances to objects are measured accurately. We investigate the effects on abundance estimates for Philippine forest birds of varying the count period from 2 to 10 min, and of including and excluding a pre‐count settling down period. Encounter rates were highly sensitive to count period length but density estimates from 10‐min count periods were, on average, only 13% higher than those from 2‐min periods, and in several cases were actually lower than those from periods of 6–8 min. This was because birds tended to be recorded at greater distances from the recorder as the count period went on, thus ‘stretching out’ detection functions while having little effect on detection rates close to the recorder. For some bird groups, including canopy frugivores and upperstorey gleaning insectivores, density estimates were more than twice as high without than with a settling down period. We suggest that movement away from the recorder is more common than attraction to the recorder, and that unless pilot studies show otherwise, similar studies should not use a settling down period for surveying many species. Count periods that maximized probability of bird detection close to the central point while minimizing the unwanted effects of bird movement during the count period were: 4 min for omnivores, 6 min for nectarivores and upperstorey gleaning insectivores, 8 min for understorey insectivores and canopy frugivores, and a full 10 min for sallying insectivores, ground‐dwellers, carnivores and coucals/koels. We use the results to suggest ‘group‐specific’ count period regimes that could help maximize the accuracy of density estimates from similar studies of tropical forest birds.     

Are reclamo hunting seasons for the Spanish red-legged partridge off the mark?

The red-legged partridge (Alectoris rufa) is abundant in a number of regions in Spain and one of the most commonly hunted small game species in the country. Partridge hunting generates substantial income in rural areas where agriculture is less profitable. A traditional hunting method, reclamo hunting, is currently under revision by the European Commission's (EC) Birds Directive because hunting may fall within the reproduction period of the species. So far, only limited data on the reproductive phenology of the species exist to inform a policy change. In this study, we present reproduction data for red-legged partridges from 9 hunting estates in Andalusia during 1 year, and over 3 consecutive seasons from a control estate. We used direct nest and partridge chick covey observations to estimate 165 egg-laying dates. We found significant differences between sites related to altitude during reproduction periods. Using our pooled data, we showed that reproduction occurred between the last 10 days in January and the middle of February; beyond 31 January we observed an exponential increase in birds reproduction. According to these data and current EC legislation, reclamo hunting should not extend beyond 31 January. © 2012 The Wildlife Society.     

Estimation of Parameters in the Two-Compartment Model for Exhaled Nitric Oxide

The fractional concentration of exhaled nitric oxide (FeNO) is a biomarker of airway inflammation that is being increasingly considered in clinical, occupational, and epidemiological applications ranging from asthma management to the detection of air pollution health effects. FeNO depends strongly on exhalation flow rate. This dependency has allowed for the development of mathematical models whose parameters quantify airway and alveolar compartment contributions to FeNO. Numerous methods have been proposed to estimate these parameters using FeNO measured at multiple flow rates. These methods—which allow for non-invasive assessment of localized airway inflammation—have the potential to provide important insights on inflammatory mechanisms. However, different estimation methods produce different results and a serious barrier to progress in this field is the lack of a single recommended method. With the goal of resolving this methodological problem, we have developed a unifying framework in which to present a comprehensive set of existing and novel statistical methods for estimating parameters in the simple two-compartment model. We compared statistical properties of the estimators in simulation studies and investigated model fit and parameter estimate sensitivity across methods using data from 1507 schoolchildren from the Southern California Children''s Health Study, one of the largest multiple flow FeNO studies to date. We recommend a novel nonlinear least squares model with natural log transformation on both sides that produced estimators with good properties, satisfied model assumptions, and fit the Children''s Health Study data well.     

Quick methods for evaluating survival of age-characterizable long-lived territorial birds

Survival is a key life-history trait in animals. However, most methods of survival estimation require substantial human and economic investment in the long term, particularly in species occurring in low densities, the case of most endangered species. An alternative to traditional recapture (CR) methods is estimation of adult survival based indirectly on either age ratios (AGR) or turnover rates (TOR) in territorial species. These 2 methods are applicable to bird species in which recruited individuals enter into the breeding population whilst still exhibiting the external traits that distinguish those animals from experienced adults. The main advantages of these methods are that survival can be easily estimated for all monitored individuals after just 1 or 2 breeding seasons and that disturbance to the species is minimized. The main constraints of indirect methods are that the assumptions are more restrictive than in CR methods, and survival estimates, although comparable between sites and years, may be biased. We used data from a long-term monitoring survey of 2 populations of the endangered Bonelli's eagle (Aquila fasciata), one in Catalonia (NE Spain) and the other in Provence and Languedoc-Roussillon (SE France). We evaluated survival estimates using the AGR and TOR methods and compared them with CR methods and provide suitable corrections for refining survival estimates based on indirect methods. In Catalonia (2002–2008), survival was estimated at 0.84 by CR methods (SE = 0.047; n = 25 radio tagged eagles), at 0.86 by the corrected AGR method (SE = 0.011; n = 558 bird * year), and at 0.86 by the corrected TOR method (SE = 0.022; n = 547 bird * year). In France (1999–2008), survival was estimated at 0.88 by CR methods (SE = 0.040; n = 45 darvic banded eagles), at 0.87 by the corrected AGR method (SE = 0.015; n = 443 bird * year), and at 0.87 by the corrected TOR method (SE = 0.015; n = 438 bird * year). All analyses suggest that females survive better than males and that individuals from the French population survive better than individuals from the Catalan population. We conclude that indirect methods, which should not be regarded as a substitute of CR methods, will allow wildlife managers and researchers to estimate accurately adult survival in a territorial species over a short period of time and to monitor survival across populations over large geographic ranges and over time. © 2011 The Wildlife Society.     

A novel tool for individual haplotype inference using mixed data

Background

In many studies, researchers may recruit samples consisting of independent trios and unrelated individuals. However, most of the currently available haplotype inference methods do not cope well with these kinds of mixed data sets.

Methods

We propose a general and simple methodology using a mixture of weighted multinomial (MIXMUL) approach that combines separate haplotype information from unrelated individuals and independent trios for haplotype inference to the individual level.

Results

The new MIXMUL procedure improves over existing methods in that it can accurately estimate haplotype frequencies from mixed data sets and output probable haplotype pairs in optimized reconstruction outcomes for all subjects that have contributed to estimation. Simulation results showed that this new MIXMUL procedure competes well with the EM-based method, i.e. FAMHAP, under a few assumed scenarios.

Conclusion

The results showed that MIXMUL can provide accurate estimates similar to those haplotype frequencies obtained from FAMHAP and output the probable haplotype pairs in the most optimal reconstruction outcome for all subjects that have contributed to estimation. If available data consist of combinations of unrelated individuals and independent trios, the MIXMUL procedure can be used to estimate the haplotype frequencies accurately and output the most likely reconstructed haplotype pairs of each subject in the estimation.