scholarly journals A Simulation Study on Increasing Capture Periods in Bayesian Closed Population Capture-Recapture Models with Heterogeneity

2020 ◽  
Vol 18 (1) ◽  
pp. 2-23
Author(s):  
Ross M. Gosky ◽  
Joel Sanqui
Keyword(s):  
Population Size ◽  
Simulation Study ◽  
Simulated Data ◽  
Population Models ◽  
Data Set ◽  
Closed Population ◽  
Population Sizes ◽  
Capture Recapture

Capture-Recapture models are useful in estimating unknown population sizes. A common modeling challenge for closed population models involves modeling unequal animal catchability in each capture period, referred to as animal heterogeneity. Inference about population size N is dependent on the assumed distribution of animal capture probabilities in the population, and that different models can fit a data set equally well but provide contradictory inferences about N. Three common Bayesian Capture-Recapture heterogeneity models are studied with simulated data to study the prevalence of contradictory inferences is in different population sizes with relatively low capture probabilities, specifically at different numbers of capture periods in the study.

scholarly journals Estimation of a closed population size of tadpoles in temporary pond

2017 ◽  
Vol 78 (2) ◽  
pp. 328-336
Author(s):  
M. S. C. S. Lima ◽  
J. Pederassi ◽  
C. A. S. Souza
Keyword(s):  
Population Size ◽  
Bayes Theorem ◽  
Venn Diagram ◽  
Temporary Pond ◽  
Larval Phase ◽  
Closed Population ◽  
Lotic Environment ◽  
Capture Recapture ◽  
Kolmogorov Smirnov ◽  
Smirnov Test

Abstract The practice of capture-recapture to estimate the diversity is well known to many animal groups, however this practice in the larval phase of anuran amphibians is incipient. We aimed at evaluating the Lincoln estimator, Venn diagram and Bayes theorem in the inference of population size of a larval phase anurocenose from lotic environment. The adherence of results was evaluated using the Kolmogorov-Smirnov test. The marking of tadpoles for later recapture and methods measurement was made with eosin methylene blue. When comparing the results of Lincoln-Petersen estimator corresponding to the Venn diagram and Bayes theorem, we detected percentage differences per sampling, i.e., the proportion of sampled anuran genera is kept among the three methods, although the values are numerically different. By submitting these results to the Kolmogorov-Smirnov test we have found no significant differences. Therefore, no matter the estimator, the measured value is adherent and estimates the total population. Together with the marking methodology, which did not change the behavior of tadpoles, the present study helps to fill the need of more studies on larval phase of amphibians in Brazil, especially in semi-arid northeast.

scholarly journals Variational inference using approximate likelihood under the coalescent with recombination

2021 ◽  
pp. gr.273631.120
Author(s):  
Xinhao Liu ◽  
Huw A Ogilvie ◽  
Luay Nakhleh
Keyword(s):  
Simulated Data ◽  
Variational Inference ◽  
Divide And Conquer ◽  
Data Sets ◽  
Transition Rates ◽  
Data Set ◽  
Population Sizes ◽  
Novel Method ◽  
Approximate Likelihood ◽  
Promising Avenue

Coalescent methods are proven and powerful tools for population genetics, phylogenetics, epidemiology, and other fields. A promising avenue for the analysis of large genomic alignments, which are increasingly common, are coalescent hidden Markov model (coalHMM) methods, but these methods have lacked general usability and flexibility. We introduce a novel method for automatically learning a coalHMM and inferring the posterior distributions of evolutionary parameters using black-box variational inference, with the transition rates between local genealogies derived empirically by simulation. This derivation enables our method to work directly with three or four taxa and through a divide-and-conquer approach with more taxa. Using a simulated data set resembling a human-chimp-gorilla scenario, we show that our method has comparable or better accuracy to previous coalHMM methods. Both species divergence times and population sizes were accurately inferred. The method also infers local genealogies and we report on their accuracy. Furthermore, we discuss a potential direction for scaling the method to larger data sets through a divide-and-conquer approach. This accuracy means our method is useful now, and by deriving transition rates by simulation it is flexible enough to enable future implementations of all kinds of population models.

What are the main drivers of survival and recruitment in tropical forest marsupials? A 16-year study

2020 ◽  
Vol 101 (2) ◽  
pp. 515-525
Author(s):  
Mariana Silva Ferreira ◽  
Rui Cerqueira ◽  
Marcus Vinícius Vieira
Keyword(s):  
Tropical Forest ◽  
Density Dependence ◽  
Population Size ◽  
Litter Size ◽  
Survival Rates ◽  
Data Set ◽  
Population Sizes ◽  
Reproductive Females ◽  
Didelphis Aurita ◽  
Metachirus Nudicaudatus

Abstract Tropical forest marsupials exhibit large interannual variation in population sizes, with direct negative density dependence capturing the essential features of their dynamics. However, the demographic mechanisms underlying population growth rate and driving both survival and reproduction are still unclear. We used a 16-year capture-mark-recapture data set for five tropical forest marsupials to test for seasonal and interannual density dependence in survival and recruitment. Hypotheses regarding the effects of exogenous (rainfall and minimum temperature) factors on survival, recruitment, and reproductive parameters (fecundity, litter size, and proportion of reproductive females) were also tested. Population size negatively affected survival in three of five species. High population sizes in a given year reduced survival rates in the following year, with strong detrimental effects on males. Recruitment and proportion of reproductive females were highly dependent on weather variables, and were not affected by previous population sizes (except for Metachirus nudicaudatus). Fecundity (number of female offspring/female) was related negatively to population size only in the black-eared opossum (Didelphis aurita), while litter size was a relatively conservative parameter, largely independent of external conditions. Our analyses indicate that density-dependent survival is the mechanism that regulates population size of tropical forest marsupials, either through a reduction in survival or an increase in emigration rates. This general regulatory mechanism may be common to other marsupials in the Atlantic Forest and other tropical forests. Marsupiais de florestas tropicais exibem grande variação interanual nos tamanhos populacionais, com dependência negativa e direta da densidade capturando a essência de sua dinâmica populacional. No entanto, os mecanismos demográficos subjacentes à taxa de crescimento populacional e determinantes da sobrevivência e reprodução ainda são incertos. Nós usamos 16 anos de dados de captura-marcação-recaptura de cinco espécies de marsupiais de florestas tropicais para avaliar a dependência de densidade sazonal e interanual na sobrevivência e recrutamento. Hipóteses sobre efeitos de fatores exógenos (pluviosidade e temperatura mínima) na sobrevivência, recrutamento e parâmetros reprodutivos (fecundidade, tamanho da ninhada e proporção de fêmeas reprodutivas) também foram testadas. O tamanho da população afetou negativamente a sobrevivência em três das cinco espécies. O tamanho populacional elevado em um ano reduziu as taxas de sobrevivência no ano seguinte, com efeitos mais negativos nos machos. Recrutamento e proporção de fêmeas reprodutivas foram dependentes das variáveis climáticas e não foram afetados pelos tamanhos populacionais anteriores (com exceção de Metachirus nudicaudatus). A fecundidade (número de filhotes fêmea/fêmea) foi relacionada negativamente ao tamanho da população do gambá-de-orelha-preta (Didelphis aurita), enquanto o tamanho da ninhada foi um parâmetro relativamente conservador e independente das condições externas. Nossas análises indicam que a sobrevivência dependente da densidade regula as populações de marsupiais em florestas tropicais, seja através da redução na sobrevivência ou no aumento da emigração. Esse mecanismo regulatório pode ser comum a outros marsupiais na Mata Atlântica e outras florestas tropicais.

scholarly journals Bayesian Estimation of Population Size Changes by Sampling Tajima’s Trees

2019 ◽  
Author(s):  
Julia A. Palacios ◽  
Amandine Véber ◽  
Lorenzo Cappello ◽  
Zhangyuan Wang ◽  
John Wakeley ◽  
...  
Keyword(s):  
State Space ◽  
Bayesian Estimation ◽  
Population Size ◽  
Simulated Data ◽  
Effective Population ◽  
Large State Space ◽  
Population Sizes ◽  
Efficient Alternative ◽  
Inference Methods ◽  
Kingman’S Coalescent

AbstractThe large state space of gene genealogies is a major hurdle for inference methods based on Kingman’s coalescent. Here, we present a new Bayesian approach for inferring past population sizes which relies on a lower resolution coalescent process we refer to as “Tajima’s coalescent”. Tajima’s coalescent has a drastically smaller state space, and hence it is a computationally more efficient model, than the standard Kingman coalescent. We provide a new algorithm for efficient and exact likelihood calculations for data without recombination, which exploits a directed acyclic graph and a correspondingly tailored Markov Chain Monte Carlo method. We compare the performance of our Bayesian Estimation of population size changes by Sampling Tajima’s Trees (BESTT) with a popular implementation of coalescent-based inference in BEAST using simulated data and human data. We empirically demonstrate that BESTT can accurately infer effective population sizes, and it further provides an efficient alternative to the Kingman’s coalescent. The algorithms described here are implemented in the R package phylodyn, which is available for download at https://github.com/JuliaPalacios/phylodyn.

Population-size estimators and unequal catchability in painted turtles

1998 ◽  
Vol 76 (3) ◽  
pp. 458-465 ◽  
Author(s):  
Nicola Koper ◽  
Ronald J Brooks
Keyword(s):  
Population Size ◽  
Sampling Methods ◽  
Ecological Research ◽  
Closed Population ◽  
Painted Turtles ◽  
Population Size Estimates ◽  
Population Sizes ◽  
Almost All ◽  
Size Estimates ◽  
True Population

Most methods of estimating population size from mark-recapture data assume equal catchability. Failure to meet this assumption may have profound effects on population-size estimates. We used 3 sampling methods to compare population-size estimates derived from Petersen, Schumacher and Eschmeyer, and Jolly-Seber models with the true size of a closed population of painted turtles (Chrysemys picta) in Algonquin Park, Ontario. We found significant variation in capture probabilities, and almost all population-size estimates were far below the true population size. To try to improve the accuracy of the estimates, we applied 4 techniques commonly recommended for reducing bias when catchability is unequal: (i) changing sampling methods, (ii) using several sampling methods simultaneously, (iii) dividing the population by sex, and (iv) calculating population sizes using the computer program CAPTURE. None of the 4 methods reduced the error that resulted from unequal catchability in any of the estimates sufficiently for these methods to be suitable for management of populations or for ecological research.

scholarly journals Using visual encounter data to improve capture-recapture abundance estimates

2020 ◽  
Author(s):  
Maxwell B. Joseph ◽  
Roland A. Knapp
Keyword(s):  
Population Size ◽  
Lower Bounds ◽  
Bayesian Approach ◽  
Individual Identification ◽  
Hierarchical Bayesian ◽  
Sampling Occasion ◽  
Demographic Rates ◽  
Abundance Estimates ◽  
Population Sizes ◽  
Capture Recapture

AbstractCapture-recapture studies are widely used in ecology to estimate population sizes and demographic rates. In some capture-recapture studies, individuals may be visually encountered but not identified. For example, if individual identification is only possible upon capture and individuals escape capture, visual encounters can result in failed captures where individual identities are unknown. In such cases, the data consist of capture histories with known individual identities, and counts of failed captures for individuals with unknown identities. These failed captures are ignored in traditional capture-recapture analyses that require known individual identities. Here we show that if animals can be encountered at most once per sampling occasion, failed captures provide lower bounds on population size that can increase the precision of abundance estimates. Analytical results and simulations indicate that visual encounter data improve abundance estimates when capture probabilities are low, and when there are few repeat surveys. We present a hierarchical Bayesian approach for integrating failed captures and auxiliary encounter data in statistical capture-recapture models. This approach can be integrated with existing capture-recapture models, and may prove particularly useful for hard to capture species in data-limited settings.

Likelihood and Bayes Estimation of Ancestral Population Sizes in Hominoids Using Data From Multiple Loci

Genetics ◽  
2002 ◽  
Vol 162 (4) ◽  
pp. 1811-1823 ◽  
Author(s):  
Ziheng Yang
Keyword(s):  
Population Size ◽  
Gene Tree ◽  
Bayes Estimation ◽  
Joint Estimation ◽  
Ancestral Population ◽  
Human Populations ◽  
Data Set ◽  
Bayes Methods ◽  
Multiple Loci ◽  
Population Sizes

AbstractPolymorphisms in an ancestral population can cause conflicts between gene trees and the species tree. Such conflicts can be used to estimate ancestral population sizes when data from multiple loci are available. In this article I extend previous work for estimating ancestral population sizes to analyze sequence data from three species under a finite-site nucleotide substitution model. Both maximum-likelihood (ML) and Bayes methods are implemented for joint estimation of the two speciation dates and the two population size parameters. Both methods account for uncertainties in the gene tree due to few informative sites at each locus and make an efficient use of information in the data. The Bayes algorithm using Markov chain Monte Carlo (MCMC) enjoys a computational advantage over ML and also provides a framework for incorporating prior information about the parameters. The methods are applied to a data set of 53 nuclear noncoding contigs from human, chimpanzee, and gorilla published by Chen and Li. Estimates of the effective population size for the common ancestor of humans and chimpanzees by both ML and Bayes methods are ∼12,000-21,000, comparable to estimates for modern humans, and do not support the notion of a dramatic size reduction in early human populations. Estimates published previously from the same data are several times larger and appear to be biased due to methodological deficiency. The divergence between humans and chimpanzees is dated at ∼5.2 million years ago and the gorilla divergence 1.1-1.7 million years earlier. The analysis suggests that typical data sets contain useful information about the ancestral population sizes and that it is advantageous to analyze data of several species simultaneously.

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