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Closed Population (closed + population)
Selected AbstractsApplications and Extensions of Chao's Moment Estimator for the Size of a Closed PopulationBIOMETRICS, Issue 4 2007Louis-Paul Rivest Summary This article revisits Chao's (1989, Biometrics45, 427,438) lower bound estimator for the size of a closed population in a mark,recapture experiment where the capture probabilities vary between animals (model Mh). First, an extension of the lower bound to models featuring a time effect and heterogeneity in capture probabilities (Mth) is proposed. The biases of these lower bounds are shown to be a function of the heterogeneity parameter for several loglinear models for Mth. Small-sample bias reduction techniques for Chao's lower bound estimator are also derived. The application of the loglinear model underlying Chao's estimator when heterogeneity has been detected in the primary periods of a robust design is then investigated. A test for the null hypothesis that Chao's loglinear model provides unbiased abundance estimators is provided. The strategy of systematically using Chao's loglinear model in the primary periods of a robust design where heterogeneity has been detected is investigated in a Monte Carlo experiment. Its impact on the estimation of the population sizes and of the survival rates is evaluated in a Monte Carlo experiment. [source] EFFECTIVE POPULATION SIZES AND TEMPORAL STABILITY OF GENETIC STRUCTURE IN RANA PIPIENS, THE NORTHERN LEOPARD FROGEVOLUTION, Issue 11 2004Eric A. Hoffman Abstract Although studies of population genetic structure are very common, whether genetic structure is stable over time has been assessed for very few taxa. The question of stability over time is particularly interesting for frogs because it is not clear to what extent frogs exist in dynamic metapopulations with frequent extinction and recolonization, or in stable patches at equilibrium between drift and gene flow. In this study we collected tissue samples from the same five populations of leopard frogs, Rana pipens, over a 22,30 year time interval (11,15 generations). Genetic structure among the populations was very stable, suggesting that these population were not undergoing frequent extinction and colonization. We also estimated the effective size of each population from the change in allele frequencies over time. There exist few estimates of effective size for frog populations, but the data available suggest that ranid frogs may have much larger ratios of effective size (Ne) to census size (Nc) that toads (bufonidae). Our results indicate that R. pipiens populations have effective sizes on the order of hundreds to at most a few thousand frogs, and Nee/Nc ratios in the range of 0.1,1.0. These estimates of Ne/Nc are consistent with those estimated for other Rana species. Finally, we compared the results of three temporal methods for estimating Ne. Moment and pseudolikelihood methods that assume a closed population gave the most similar point estimates, although the moment estimates were consistently two to four times larger. Wang and Whitlock's new method that jointly estimates Ne and the rate of immigration into a population (m) gave much smaller estimates of Ne and implausibly large estimates of m. This method requires knowing allele frequencies in the source of immigrants, but was thought to be insensitive to inexact estimates. In our case the method may have failed because we did not know the true source of immigrants for each population. The method may be more sensitive to choice of source frequencies than was previously appreciated, and so should be used with caution if the most likely source of immigrants cannot be identified clearly. [source] A mark,recapture study of the caecilian amphibian Gegeneophis ramaswamii (Amphibia: Gymnophiona: Caeciliidae) in southern IndiaJOURNAL OF ZOOLOGY, Issue 2 2003G. John Measey Abstract The potentially important ecology of subterranean predators of soil ecosystem engineers is poorly understood. This is especially true of caecilian amphibians (Gymnophiona) for which there are virtually no quantitative data. Results of the first field trials of permanent marking in caecilians are presented. A preliminary assessment is made of the efficacy of mark,recapture studies for estimating population size of Gegeneophis ramaswamii Taylor in 100 m2 of low intensity agriculture in Kerala, India. Over three sampling occasions spanning 58 days of the monsoon season, 114 individuals were captured, 104 marked and released, and 21 recaptured. Models estimate an open population of 60 individuals (95% confidence interval of 45.2 to 151.3), and a closed population of 236 (95% confidence interval of 174 to 351). A census interpretation of the raw capture data gives densities of about 0.31 to 0.48 m,2. Results suggest large movement in and out of the sampled area during the study. Despite caveats associated with these data, progress is made in identifying potential limitations and improvements in the methods used. This study highlights the paucity of knowledge of caecilian ecology, and the need for long-term studies to elucidate further ecological information and to monitor populations. [source] Improved log-linear model estimators of abundance in capture-recapture experimentsTHE CANADIAN JOURNAL OF STATISTICS, Issue 4 2001Louis-Paul Rivest Abstract The authors review log-linear models for estimating the size of a closed population and propose a new log-linear estimator for experiments having between animal heterogeneity and a behavioral response. They give a general formula for evaluating the asymptotic biases of estimators of abundance derived from log-linear models. They propose simple frequency modifications for reducing these asymptotic biases and investigate the modifications in a Monte Carlo experiment which reveals that they reduce both the bias and the mean squared error of abundance estimators. [source] A Multilevel Model for Continuous Time Population EstimationBIOMETRICS, Issue 3 2009Jason M. Sutherland Summary Statistical methods have been developed and applied to estimating populations that are difficult or too costly to enumerate. Known as multilist methods in epidemiological settings, individuals are matched across lists and estimation of population size proceeds by modeling counts in incomplete multidimensional contingency tables (based on patterns of presence/absence on lists). As multilist methods typically assume that lists are compiled instantaneously, there are few options available for estimating the unknown size of a closed population based on continuously (longitudinally) compiled lists. However, in epidemiological settings, continuous time lists are a routine byproduct of administrative functions. Existing methods are based on time-to-event analyses with a second step of estimating population size. We propose an alternative approach to address the twofold epidemiological problem of estimating population size and of identifying patient factors related to duration (in days) between visits to a health care facility. A Bayesian framework is proposed to model interval lengths because, for many patients, the data are sparse; many patients were observed only once or twice. The proposed method is applied to the motivating data to illustrate the methods' applicability. Then, a small simulation study explores the performance of the estimator under a variety of conditions. Finally, a small discussion section suggests opportunities for continued methodological development for continuous time population estimation. [source] Applications and Extensions of Chao's Moment Estimator for the Size of a Closed PopulationBIOMETRICS, Issue 4 2007Louis-Paul Rivest Summary This article revisits Chao's (1989, Biometrics45, 427,438) lower bound estimator for the size of a closed population in a mark,recapture experiment where the capture probabilities vary between animals (model Mh). First, an extension of the lower bound to models featuring a time effect and heterogeneity in capture probabilities (Mth) is proposed. The biases of these lower bounds are shown to be a function of the heterogeneity parameter for several loglinear models for Mth. Small-sample bias reduction techniques for Chao's lower bound estimator are also derived. The application of the loglinear model underlying Chao's estimator when heterogeneity has been detected in the primary periods of a robust design is then investigated. A test for the null hypothesis that Chao's loglinear model provides unbiased abundance estimators is provided. The strategy of systematically using Chao's loglinear model in the primary periods of a robust design where heterogeneity has been detected is investigated in a Monte Carlo experiment. Its impact on the estimation of the population sizes and of the survival rates is evaluated in a Monte Carlo experiment. [source] Estimating Population Size for a Continuous Time Frailty Model with Covariates in a Capture,Recapture StudyBIOMETRICS, Issue 3 2007Ying Xu Summary A continuous time frailty capture,recapture model is proposed for estimating population size of a closed population with the use of observed covariates to explain individuals' heterogeneity in presence of a random effect. A conditional likelihood approach is used to derive the estimate of parameters, and the Horvitz,Thompson estimator is adopted to estimate the unknown population size. Asymptotic normality of the estimates is obtained. Simulation results and a real example show that the proposed method works satisfactorily. [source] Using Mixtures to Model Heterogeneity in Ecological Capture-Recapture StudiesBIOMETRICAL JOURNAL, Issue 6 2008Shirley Pledger Abstract Modelling heterogeneity of capture is an important problem in estimating animal abundance from capturerecapture data, with underestimation of abundance occurring if different animals have intrinsically high or low capture probabilities. Mixture models are useful in many cases to model the heterogeneity. We summarise mixture model results for closed populations, using a skink data set for illustration. New mixture models for heterogeneous open populations are discussed, and a closed population model is shown to have new and potentially effective applications in community analysis. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [source] | |||||||||||||