A new method of estimating the pollen dispersal curve independently of effective density

We introduce a novel indirect method of estimating the pollen dispersal curve from mother-offspring genotypic data. Unlike an earlier indirect approach (TwoGener), this method is based on a normalized measure of correlated paternity between female pairs whose expectation does not explicitly depend on the unknown effective male population density (d(e)). We investigate the statistical properties of the new method, by comparison with those of TwoGener, considering the sensitivity to reductions of d(e), relative to census density, resulting from unequal male fecundity and asynchronous flowering. Our main results are: (i) it is possible to obtain reliable estimates of the average distance of pollen dispersal, delta, from indirect methods, even under nonuniform male fecundity and variable flowering phenology; (ii) the new method yields more accurate and more precise delta-estimates than TwoGener under a wide range of sampling and flowering scenarios; and (iii) TwoGener can be used to obtain approximate d(e) estimates, if needed for other purposes. Our results also show that accurately estimating the shape of the tail of the pollen dispersal function by means of indirect methods remains a very difficult challenge.     

MCMC estimation of Markov models for ion channels

Ion channels are characterized by inherently stochastic behavior which can be represented by continuous-time Markov models (CTMM). Although methods for collecting data from single ion channels are available, translating a time series of open and closed channels to a CTMM remains a challenge. Bayesian statistics combined with Markov chain Monte Carlo (MCMC) sampling provide means for estimating the rate constants of a CTMM directly from single channel data. In this article, different approaches for the MCMC sampling of Markov models are combined. This method, new to our knowledge, detects overparameterizations and gives more accurate results than existing MCMC methods. It shows similar performance as QuB-MIL, which indicates that it also compares well with maximum likelihood estimators. Data collected from an inositol trisphosphate receptor is used to demonstrate how the best model for a given data set can be found in practice.     

A new approach for calibrating dental caries frequency of skeletal remains

It is a fact that researchers make use of various calibration methods for calculating and correcting dental caries frequency. The lack of standardization and accuracy of such methods has made it difficult for the researchers to draw reliable and differentiated conclusions from caries frequencies. Besides, the number of studies on how far the calculation methods reflect the "real" caries frequency is very limited. In this study, various methods for calculating caries frequency in skeletal samples are discussed and a new calculation method is proposed for estimating "real" caries frequency. The Hardwick's correction, which is one of the methods discussed in this study, is not successful in estimating "real" caries frequency as it proposes standard values for different life styles and dietary habits. The decayed and missing index is also considered inefficient as it assumes that all antemortem tooth loss is due to caries. The caries correction factor, proposed by Lukacs, achieves more successful results by considering factors other than caries in antemortem tooth loss, but because it does not differentiate between the anterior and posterior tooth groups during calculation, the results to be obtained therefrom may deviate from actual figures. In order to correct any such deviation, the caries correction factor must be applied separately for the anterior and posterior teeth groups since the resistance of each group to cariogenic factors is different. All the methods outlined above do not consider the effects of postmortem tooth loss on caries frequency. As a result, these methods are still far from reflecting a reliable caries frequency. The application of a proportional correction factor--as a technique newly introduced here--corrects the deviation caused by postmortem tooth loss and achieves more realistic results.     

Estimating recombination rates from population genetic data.

We introduce a new method for estimating recombination rates from population genetic data. The method uses a computationally intensive statistical procedure (importance sampling) to calculate the likelihood under a coalescent-based model. Detailed comparisons of the new algorithm with two existing methods (the importance sampling method of Griffiths and Marjoram and the MCMC method of Kuhner and colleagues) show it to be substantially more efficient. (The improvement over the existing importance sampling scheme is typically by four orders of magnitude.) The existing approaches not infrequently led to misleading results on the problems we investigated. We also performed a simulation study to look at the properties of the maximum-likelihood estimator of the recombination rate and its robustness to misspecification of the demographic model.     

Quantifying the multiple facets of isotopic diversity: New metrics for stable isotope ecology

Stable isotope analyses have emerged as an insightful tool for ecologists, with quantitative methods being developed to analyse data at the population, community and food web levels. In parallel, functional ecologists have developed metrics to quantify the multiple facets of functional diversity in a n-dimensional space based on functional traits. Here, we transferred and adapted metrics developed by functional ecologists into a set of four isotopic diversity metrics (isotopic divergence, dispersion, evenness and uniqueness) complementary to the existing metrics. Specifically, these new metrics are mathematically independent of the number of organisms analysed and account for the abundance of organisms. They can also be calculated with more than two stable isotopes. In addition, we also provide a procedure for calculating the levels of isotopic overlap (similarity and turnover) between two groups of organisms. These metrics have been implemented into new functions in R made freely available to users and we illustrated their application using stable isotope values from a freshwater fish community. Transferring the framework developed initially for measuring functional diversity to stable isotope ecology will allow more efficient assessments of changes in the multiple facets of isotopic diversity following anthropogenic disturbances.     

A new specially designed needle significantly increases sample yield during fine needle aspiration of breast lesions

A large and increasing number of women in the western world will at some point during their life be investigated morphologically for breast cancer. Fine needle aspiration (FNA) is one morphological method which is considered to be the fastest, cheapest and the most patient-friendly approach. Nevertheless, the technique has not gained major clinical success outside of Scandinavia, mainly because of a high frequency of insufficient samples. With this in mind it is quite peculiar that standard needles which are mainly configured for blood sampling and infusion therapy, comprising large quantities of residual spaces, are used. In this study we have developed and tested a new needle dedicated for FNA, which is intended to abate this drawback by increasing the sampling yield by changing the tip angle, the cannula wall-thickness and the storage compartment. In total, 499 consecutive aspiration procedures of palpable breast lesions were performed to compare the new needle (outer diameter 0.6 mm) with standard needles (outer diameters 0.6 mm and 0.7 mm). The new needle provided three times more material than did standard needles of the same diameter. Surprisingly, the new needle also provided more material than the standard 0.7 mm needle, which increased up to almost twice the material in cases with no material in the syringe. The frequency of tests with sparse harvested material (<4 mg) was less with the new needle (9%) compared to its standard counterpart (35%). The presented results were obtained by a very skilled sampling operator. Thus for the average sampling operator who probably obtains more samples in the spare range, the new dedicated FNA needle should have even more added value.     

生物群落多样性的测度方法VI：与多样性测度中有关的统计问题

物种多样性测度是(群落的)总体参数,它们常常是未知的,需要通过抽样将它们估计出来,因此,必须了解估计量的抽样性质。本文对与一些多样性测度的均值、方差的估计和假设检验以及大、小样本分布等有关的问题作了综述。可以看出大多数多样性测度的抽样性质还不清楚,有些甚至根本就没有研究过。Pielou的合并样方法和刀切法是两个比较通用的方法,用它们可以解决其中的一些问题。但相比之下,刀切法更实用。     

Focusing modelling on the tracheid development period – An alternative method for treatment of xylogenesis intra-annual data

Intra-annual repeated micro-sampling of the developing tree ring is getting more and more applied in xylogenesis studies. Variability in growth magnitude, notably due to different sampling positions on the stem, encouraged application of standardization and modelling techniques. Among these, methods using Gompertz equation had become widely spread, but tests made with black spruce revealed a frequent occurrence of crossovers between the cumulative number of cells in enlargement and the cumulative number of cells in wall thickening. This was due to a localized problem in the fitting for values close to the asymptote and was a major problem for estimating the timing of each individual cell development phases, which is an interesting application of these data. In this paper, a new method, based on a different approach, has been developed in order to avoid that problem and applied to intra-annual growth curves from four sites in Quebec (Canada). Since tracheid development analysis allows discriminating between active and inactive period of a phase, modelling can be restricted on the active period alone. The new method did not cause crossovers between the fitted curves. Therefore, it has been considered appropriate for estimating the timing for each individual cell in the whole range of data. Since resulting functions are polynomials from degree 1 to 3, possible studies concerning general tendency should be easy to lead. Also, the method has been tested with different sampling frequencies. To do this, number of observations from weekly samplings has been halved to simulate a semi-monthly sampling frequency and a comparison of the results from the new method applied on each version of the datasets has been tested. Generally, the simulated semi-monthly sampled dataset did not give significantly different results from the original weekly sampled dataset, in terms of general tendency and predicted intercept time in the extremities of the data range. This is very encouraging for situations when only semi-monthly sampling is available.     

Estimation of segregation and linkage parameters in simulated data. II. Simultaneous estimation with one linked marker.

This study examined the method of simultaneous estimation of recombination frequency and parameters for a qualitative trait locus and compared the results with those of standard methods of linkage analysis. With both approaches we were able to detect linkage of an incompletely penetrant qualitative trait to highly polymorphic markers with recombination frequencies in the range of .00-.05. Our results suggest that detecting linkage at larger recombination frequencies may require larger data sets or large high-density families. When applied to all families without regard to informativeness of the family structure for linkage, analyses of simulated data could detect no advantage of simultaneous estimation over more traditional and much less time-consuming methods, either in detecting linkage, estimating frequency, refining estimates of parameters for the qualitative trait locus, or avoiding false evidence for linkage. However, the method of sampling affected results.     

Hts1 Encodes Both the Cytoplasmic and Mitochondrial Histidyl-Trna Synthetase of Saccharomyces Cerevisiae: Mutations Alter the Specificity of Compartmentation

Wright's method of estimating the number of genes contributing to the difference in a quantitative character between two populations involves observing the means and variances of the two parental populations and their hybrid populations. Although simple, Wright's method provides seriously biased estimates, largely due to linkage and unequal effects of alleles. A method is suggested to evaluate the bias of Wright's estimate, which relies on estimation of the mean recombination frequency between a pair of loci and a composite parameter of variability of allelic effects and frequencies among loci. Assuming that the loci are uniformly distributed in the genome, the mean recombination frequency can be calculated for some organisms. Theoretical analysis and an analysis of the Drosophila data on distributions of effects of P element inserts on bristle numbers indicate that the value of the composite parameter is likely to be about three or larger for many quantitative characters. There are, however, some serious problems with the current method, such as the irregular behavior of the statistic and large sampling variances of estimates. Because of that, the method is generally not recommended for use unless several favorable conditions are met. These conditions are: the two parental populations are many phenotypic standard deviations apart, linkage is not tight, and the sample size is very large. An example is given on the fruit weight of tomato from a cross with parental populations differing in means by more than 14 phenotypic standard deviations. It is estimated that the number of loci which account for 95% of the genic variance in the F2 population is 16, with a 95% confidence interval of 7-28, and the effect of the leading locus is 13% of the parental difference, with 95% confidence interval 8.5-25.7%.     

The efficacy of sampling strategies for estimating scabies prevalence

BackgroundEstimating community level scabies prevalence is crucial for targeting interventions to areas of greatest need. The World Health Organisation recommends sampling at the unit of households or schools, but there is presently no standardised approach to scabies prevalence assessment. Consequently, a wide range of sampling sizes and methods have been used. As both prevalence and drivers of transmission vary across populations, there is a need to understand how sampling strategies for estimating scabies prevalence interact with local epidemiology to affect the accuracy of prevalence estimates.MethodsWe used a simulation-based approach to compare the efficacy of different scabies sampling strategies. First, we generated synthetic populations broadly representative of remote Australian Indigenous communities and assigned a scabies status to individuals to achieve a specified prevalence using different assumptions about scabies epidemiology. Second, we calculated an observed prevalence for different sampling methods and sizes.ResultsThe distribution of prevalence in subpopulation groups can vary substantially when the underlying scabies assignment method changes. Across all of the scabies assignment methods combined, the simple random sampling method produces the narrowest 95% confidence interval for all sample sizes. The household sampling method introduces higher variance compared to simple random sampling when the assignment of scabies includes a household-specific component. The school sampling method overestimates community prevalence when the assignment of scabies includes an age-specific component.DiscussionOur results indicate that there are interactions between transmission assumptions and surveillance strategies, emphasizing the need for understanding scabies transmission dynamics. We suggest using the simple random sampling method for estimating scabies prevalence. Our approach can be adapted to various populations and diseases.     

Improving marginal likelihood estimation for Bayesian phylogenetic model selection

The marginal likelihood is commonly used for comparing different evolutionary models in Bayesian phylogenetics and is the central quantity used in computing Bayes Factors for comparing model fit. A popular method for estimating marginal likelihoods, the harmonic mean (HM) method, can be easily computed from the output of a Markov chain Monte Carlo analysis but often greatly overestimates the marginal likelihood. The thermodynamic integration (TI) method is much more accurate than the HM method but requires more computation. In this paper, we introduce a new method, steppingstone sampling (SS), which uses importance sampling to estimate each ratio in a series (the "stepping stones") bridging the posterior and prior distributions. We compare the performance of the SS approach to the TI and HM methods in simulation and using real data. We conclude that the greatly increased accuracy of the SS and TI methods argues for their use instead of the HM method, despite the extra computation needed.     

相机陷阱法在潮间带底栖蟹类群落生态学中的应用研究

潮间带大型底栖动物调查是滨海湿地生物多样性监测的重要环节。目前普遍应用的传统侵入性调查方法（挖掘法、手捕法和陷阱诱捕法）存在干扰强、耗时久和劳动密集等问题,无法客观反映活动性较强的蟹类等重要功能类群的群落结构和物种多样性。对陆地野生动物研究中常用的相机陷阱法进行了符合潮间带应用条件的便携式设计,并以红树林蟹类为例,通过与3种传统侵入性调查方法进行对比,探讨相机陷阱法在潮间带底栖蟹类群落生态学研究中的应用。结果表明：（1）相机陷阱法在种群密度测定方面比挖掘法提高2.1倍,比手捕法提高10.3倍,比陷阱诱捕法提高16.3倍;（2）相机陷阱法在调查物种数方面均高于3种传统侵入性调查方法,适用于沙蟹科（Ocypodidae）和方蟹科（Grapsidae）蟹类调查;（3）相机陷阱法对个体大小选择性弱,采样更加全面;（4）相机陷阱法在群落alpha多样性（Shannon-Wiener指数）、beta多样性（样方-多度矩阵总方差Var （Y））和功能多样性（Rao二次熵和功能离散度）调查方面整体不弱于侵入性调查方法。此外,相较于侵入性调查方法,相机陷阱法对沉积物结构破坏小、不干扰蟹类群落结构,在兼顾数据丰富性的同时又具有高效性。然而,由于相机陷阱法基于蟹类底表活动性,无法适用于冬季调查、夜行性蟹类和游泳型蟹类调查。未来,相机陷阱法的发展将与基于深度学习的图像处理技术结合以满足数据处理需求。研究揭示了相机陷阱法在潮间带底栖蟹类群落中的应用优越性与局限性,为潮间带大型底栖动物群落生态学的研究提供技术支撑。     

南亚热带森林种群分布格局取样技术研究

森林群落中植物种群分布格局测定和分析的结果,密切依赖于野外取样的技术手段及资料的可靠性。本文通过鼎湖山自然保护区三个不同森林群落类型的取样,比较了随机样方、相邻格子样方、中心点四分法、最近相邻法和最近个体法在野外操作、数据整理以及种群分布格局测定分析中的效用,对各方法在南亚热带森林群落中进行种群分布格局研究中的适用性予以客观评价。研究表明,同一样地中不同取样方法和测定方法会导致不同结果。随机样方取样数据的测定结果受样方大小影响,而几种无样地方法在种类复杂的群落中,应用受到限制。相邻格子样方适用于各群落类型中种群分布格局的测定与分析。     

A Bayesian method for jointly estimating allele age and selection intensity.

The problem of jointly estimating the intensity of past selection affecting an allele and the allele's age is formulated in a Bayesian framework. The prior distribution of allele age given its frequency is obtained from existing population genetics theory. The prior distribution of selection intensity is assumed to reflect the fact that positive selection on a new mutant is more likely to be weak than strong. The general approach is illustrated by the development of an importance sampling method applicable to low-frequency alleles. This method can be used either when the haplotypes of closely linked marker loci are known or when the lengths of linked ancestral chromosomal segments can be inferred. The method is illustrated with an application to the A-allele of G6PD in Africa. Because changes in allele frequency and recombination are both intrinsically stochastic, there are limits to the accuracy achievable with any method.     

Testing the impact of Remotely Operated Vehicle (ROVs) camera angle on community metrics of temperate mesophotic organisms: A 3D model-based approach

While Remotely Operated Vehicle (ROV) technologies have rapidly increased our understanding of deeper water mesophotic ecosystems, there are some inherent problems in their use when estimating the abundance of sessile benthic organisms. Specifically, for rocky and coral reefs there has been recent debate about the importance of the angle of the ROV camera to the substrate, which is difficult to standardise, and how variation in this angle might impact abundance estimates and therefore our ability to detect change in mesophotic ecosystems. Here we simulated a series of 3D rocky temperate mesophotic communities based on real data with three different levels of habitat complexity (high, medium, and low). We ‘sampled’ these communities in a virtual space varying the angle of the camera to the substrate, to assess the influence of camera angle on percent cover estimates and overall benthic community composition. We found that increases in the ROV to substrate angle overestimated the percent cover (per degree of camera angle) of gorgonians (large: R² = 0.16; small: R² = 0.18), tubular sponges (R² = 0.11), and ascidians (R² = 0.05–0.13), and underestimated the abundance of Crustose Coraline Algae (R² = 0.1, likely due to shading) in the most complex habitats. While we also found some significant differences in the overall benthic community and data dispersion for the more complex habitats, angle explained only a small amount of total variation (<6%) and significant dispersion was only found between 0- and 50-degree angles in high and medium complexity habitats. We conclude that while ROV to surface angle should be a consideration when sampling deep water reefs, its influence on standard measurements that we estimate with photography is likely to be low, and restricted to errors in the abundance of organisms with a high ratio of height to planar projection area (e.g., gorgonians).     

How accurately can retention of benthic macrofauna by a particular mesh size be predicted from body size of organisms?

Size of organisms is frequently the prime criterion in selecting a mesh size to sample benthic assemblages. This study quantified the accuracy in estimating the sampling efficiency of screens from body size of macrozoobenthos in the upper, sandy, reaches of a small, shallow estuary, where the community consisted primarily of peracarid crustaceans and polychaetes. Body size of organisms retained by a 0.25, 0.5 and 1.0 mm screen was used to predict the retention efficiency of each gear by multiple discriminant analysis (MDA), or by simply assuming that an animal of known size will be retained by a screen of the same aperture size (‘body aperture match’). MDA-models classified about 70% of all cases correctly, whereas matching of body-to screen-size gave at best spurious, and often seriously wrong estimates of retention efficiency for all tested mesh sizes. Regardless of the method employed, body size was found to be an extremely poor predictor of mesh retention. Consequently, sampling performance of each mesh size in a particular habitat × community combination should be determined experimentally and not from body size measurements obtained during pilot studies.     

A Generalized Approach for Estimating Effective Population Size from Temporal Changes in Allele Frequency

The temporal method for estimating effective population size (Ne) from the standardized variance in allele frequency change (F) is presented in a generalized form. Whereas previous treatments of this method have adopted rather limiting assumptions, the present analysis shows that the temporal method is generally applicable to a wide variety of organisms. Use of a revised model of gene sampling permits a more generalized interpretation of Ne than that used by some other authors studying this method. It is shown that two sampling plans (individuals for genetic analysis taken before or after reproduction) whose differences have been stressed by previous authors can be treated in a uniform way. Computer simulations using a wide variety of initial conditions show that different formulas for computing F have much less effect on Ne than do sample size (S), number of generations between samples (t), or the number of loci studied (L). Simulation results also indicate that (1) bias of F is small unless alleles with very low frequency are used; (2) precision is typically increased by about the same amount with a doubling of S, t, or L; (3) confidence intervals for Ne computed using a chi 2 approximation are accurate and unbiased under most conditions; (4) the temporal method is best suited for use with organisms having high juvenile mortality and, perhaps, a limited effective population size.     

A model for dispersion experiments

Summary A new model is proposed for the dispersion of animals and other organisms and its use is discussed for the analysis of the data from experiments on dispersion. The model is a generalisation of the random walk model, but because of its flexibility it should be much more widely applicable than the random walk model.The new model has been found to fit the results of many dispersion experiments and examples are given of its use with data for millipedes and Drosophila.