Evaluation of a Mark–Recapture Method for Estimating Mortality and Migration Rates of Stratified Populations

1991 ◽  
Vol 48 (2) ◽  
pp. 254-260 ◽  
Author(s):  
Robert M. Dorazio ◽  
Paul J. Rago
Keyword(s):  
Maximum Likelihood ◽  
Sockeye Salmon ◽  
Maximum Likelihood Estimates ◽  
Fishing Mortality ◽  
Mark Recapture ◽  
Sampling Variability ◽  
Migration Rates ◽  
Tag Loss ◽  
And Migration ◽  
Biased Estimates

We simulated mark–recapture experiments to evaluate a method for estimating fishing mortality and migration rates of populations stratified at release and recovery. When fish released in two or more strata were recovered from different recapture strata in nearly the same proportions, conditional recapture probabilities were estimated outside the [0, 1] interval. The maximum likelihood estimates tended to be biased and imprecise when the patterns of recaptures produced extremely "flat" likelihood surfaces. Absence of bias was not guaranteed, however, in experiments where recapture rates could be estimated within the [0, 1] interval. Inadequate numbers of tag releases and recoveries also produced biased estimates, although the bias was easily detected by the high sampling variability of the estimates. A stratified tag–recapture experiment with sockeye salmon (Oncorhynchus nerka) was used to demonstrate procedures for analyzing data that produce biased estimates of recapture probabilities. An estimator was derived to examine the sensitivity of recapture rate estimates to assumed differences in natural and tagging mortality, tag loss, and incomplete reporting of tag recoveries.

Maximum-likelihood estimates of the mortality and migration rates of the infective larvae of Ostertagia ostertagi and Cooperia oncophora

Parasitology ◽  
1986 ◽  
Vol 92 (3) ◽  
pp. 643-652 ◽  
Author(s):  
B. T. Grenfell ◽  
G. Smith ◽  
R. M. Anderson
Keyword(s):  
Maximum Likelihood ◽  
Larval Mortality ◽  
Maximum Likelihood Estimates ◽  
Laboratory Studies ◽  
Migration Rates ◽  
Cooperia Oncophora ◽  
Northern European ◽  
Rate Processes ◽  
And Migration ◽  
Good Agreement

SUMMARYWe present an analysis of the survival and migration rates of the infective (L3) stages of Oslertagia ostertagi and Cooperia oncophora. Although the majority of laboratory studies show that the survival of the L3 stage depends upon temperature, moisture and the age of the larvae, a simple mathematical model of larval demography, in which their mortality and migration rates are held constant, provides as good agreement between observed and predicted larval counts as models in which these rate processes are made explicit functions of larval age and microclimate. Maximum-likelihood estimates of larval mortality rates in the faeces and on the herbage are 0·0284/day and 0·00887/day respectively. The average migration rate from faeces to herbage under temperate Northern European conditions is estimated as 0·00884/day. Finally, we discuss the probable scale of L3 larval losses due to desiccation and lavage (active or passsive migration into the soil).

Bias and Loss of Precision Due to Tag Loss in Jolly–Seber Estimates for Mark–Recapture Experiments

1981 ◽  
Vol 38 (9) ◽  
pp. 1077-1095 ◽  
Author(s):  
A. N. Arnason ◽  
K. H. Mills
Keyword(s):  
Loss Rate ◽  
Full Model ◽  
Coregonus Clupeaformis ◽  
Lake Whitefish ◽  
Mark Recapture ◽  
Tag Retention ◽  
Tag Loss ◽  
Capture Recapture ◽  
Biased Estimates ◽  
Theoretical Analyses

A crucial, though often ignored, assumption of mark–recapture experiments is that animals do not lose their marks (tags). We present results of theoretical analyses of the effects of tag loss on estimates of population size ([Formula: see text]), survival ([Formula: see text]), births or new entries ([Formula: see text]), and on their standard errors (SE()), for the Jolly–Seber (full) model allowing birth and death. We show that[Formula: see text], SE([Formula: see text]) and SE([Formula: see text]) are not biased by tag loss, while [Formula: see text], [Formula: see text], and SE([Formula: see text]) are biased. A similar analysis for the Jolly–Seber (death-only) model where births are known not to occur shows that [Formula: see text], [Formula: see text], and SE([Formula: see text]) are strongly biased by tag loss while only SE([Formula: see text]) is unbiased. Moreover, for both models, tag loss causes a loss in precision in all estimates (i.e. an increase in the standard error of the estimate, leading to wider confidence intervals). Throughout the paper, we assume that tag loss is homogeneous among animals; that is, it is the same for all marked animals regardless of age, sex, or tag-retention time, although the rate per unit time may change over time (e.g. over years or seasons within years).We develop analytic formulae for both models that allow calculation of the expected bias and SE in an estimate at given tag loss rates in a population of given size, subject to specified sampling, survival, and birth rates. The analytic formulae are large sample approximations, but are shown, by simulations, to be adequate provided marked captures (mi) and subsequent recoveries (ri) are no lower than around 5.We discuss how these calculations can be used in practical situations to plan experiments that will yield adequately precise estimates and to determine whether corrections to compensate for tag loss are necessary. In general, corrections are unnecessary if bias is slight or precision is poor. Otherwise, they should be corrected. The biased estimates from the full model ([Formula: see text], SE([Formula: see text]), and [Formula: see text]) are correctable only if an estimate of tag-loss rate is available. The death-only model estimates can all be corrected to eliminate bias due to tag loss both with and without knowledge of the tag-loss, rate. Knowledge of the tag-loss rate will usually give higher precision of the corrected estimates over those corrected without knowing the tag-loss rate.The Robson–Regier method of estimating tag loss can be used in experiments with double tagging where one tag is a permanent batch mark and where all recaptured animals are removed. We extend this method to allow for the multiple mark–recapture case where recaptures may be returned to the population. An example of the methods of estimating tag loss and then correcting the death-only model estimates is presented for some lake whitefish (Coregonus clupeaformis) data. Without the corrections, the estimates for these data would have been in serious error. The example provides some evidence that the correction may work even when the tag loss is not homogeneous across all animals.Recommendations are presented for planning mark–recapture experiments to minimize the problems created by tag loss.Key words: marking methods, tag loss, bias of estimates, capture–recapture, Jolly–Seber estimates, population estimates, survival, mortality, lake whitefish

scholarly journals ESTIMATES OF INBREEDING IN A NATURAL POPULATION: A COMPARISON OF SAMPLING PROPERTIES

Genetics ◽  
1982 ◽  
Vol 100 (2) ◽  
pp. 339-358 ◽  
Author(s):  
Martin Curie-Cohen
Keyword(s):  
Maximum Likelihood ◽  
Natural Population ◽  
Inbreeding Coefficient ◽  
Single Locus ◽  
Maximum Likelihood Estimates ◽  
Gene Frequencies ◽  
Chi Square ◽  
Inbreeding Coefficients ◽  
Good For ◽  
Biased Estimates

ABSTRACT The average inbreeding coefficient f of a population can be estimated in several different ways based solely on the genotypic frequencies at a single locus. The means and variances of four different estimates have been compared. While the four estimates are equivalent when there are two alleles, the best estimates when there are three or more alleles are based upon total heterozygosity (see PDF) where x and y are the expected and observed number of heterozygotes) and the proportion of alleles that are homozygous (see PDF) where k = the number of alleles, aii = the number of AiAi homozygotes, and 2aij = the number of AiAj heterozygotes). Both are minimally biased estimates of f and have identical sampling variances when all alleles are equally frequent. However, when alleles have different frequencies, the choice between these two estimates depends on the gene frequencies and the true inbreeding coefficient of a population; f  2 is the best estimate when the true average inbreeding coefficient is suspected to be low or f = 0, while f  1 is best in populations with large average inbreeding coefficients. Approximate sampling variances of these two estimates are given for any f and any number of alleles with arbitrary gene frequencies; these approximations are accurate for samples as small as n = 100. The chi-square and maximum likelihood estimates of f are not as good for realistic sample sizes.

Mark-recapture estimation of mortality and migration rates for sea trout (Salmo trutta) in the northern Baltic sea

2016 ◽  
Vol 74 (1) ◽  
pp. 286-300 ◽  
Author(s):  
Rebecca E. Whitlock ◽  
Juho Kopra ◽  
Tapani Pakarinen ◽  
Eero Jutila ◽  
Adrian W. Leach ◽  
...  
Keyword(s):  
Baltic Sea ◽  
Salmo Trutta ◽  
Mortality Rates ◽  
Fish Population ◽  
Fishing Mortality ◽  
Recreational Fisheries ◽  
Sources Of Information ◽  
Mark Recapture ◽  
Sea Trout ◽  
And Migration

Knowledge of current fishing mortality rates is an important prerequisite for formulating management plans for the recovery of threatened stocks. We present a method for estimating migration and fishing mortality rates for anadromous fishes that combines tag return data from commercial and recreational fisheries with expert opinion in a Bayesian framework. By integrating diverse sources of information and allowing for missing data, this approach may be particularly applicable in data-limited situations.Wild populations of anadromous sea trout (Salmo trutta) in the northern Baltic Sea have undergone severe declines, with the loss of many populations. The contribution of fisheries to this decline has not been quantified, but is thought to be significant. We apply the Bayesian mark-recapture model to two reared sea trout stocks from the Finnish Isojoki and Lestijoki Rivers. Over the study period (1987–2012), the total harvest rate was estimated to average 0.82 y–1 for the Isojoki River stock and 0.74 y−1 for the Lestijoki River stock. Recreational gillnet fishing at sea was estimated to be the most important source of fishing mortality for both stocks, particularly during the 1980s and 1990s. Our results indicate a high probability of unsustainable levels of fishing mortality for both stocks, and illustrate the importance of considering the effect of recreational fisheries on fish population dynamics.

Estimating reference fishing mortality rates from noisy spawner–recruit data

2004 ◽  
Vol 61 (9) ◽  
pp. 1771-1783 ◽  
Author(s):  
A Jamie F Gibson ◽  
Ransom A Myers
Keyword(s):  
Maximum Likelihood ◽  
Mortality Rate ◽  
Mortality Rates ◽  
Maximum Sustainable Yield ◽  
Maximum Likelihood Estimates ◽  
Organizational Level ◽  
Likelihood Method ◽  
Parameter Estimates ◽  
Fishing Mortality ◽  
Over Exploitation

We review and evaluate methods of estimating reference fishing mortality rates from spawner–recruit (SR) data to obtain maximum sustainable yield. Using Monte Carlo simulations, we found that a reference fishing mortality rate derived from the maximum likelihood estimates of the SR parameters was less biased than reference fishing mortality rates obtained using the mode of the marginal probability distribution for the maximum rate that spawners produce recruits or by finding the fishing mortality rate that maximizes the expected yield. However, the maximum likelihood method produced the most variable estimates, at times leading to substantial under- or over-exploitation of the population. In contrast, the decision theoretic method of maximizing the expected yield exhibited less variability, produced higher yields, and substantially reduced the risk of overexploiting the population. We show how these methods can be extended to include information from other populations. Bayesian priors for the SR parameters, obtained through meta-analyses of population dynamics at some higher organizational level (e.g., the species), may be used to assess the plausibility of parameter estimates obtained for a single population or combined with the data for the population of interest. Reference fishing mortality rates are then estimated from the resulting joint posterior distribution.

Using mark-recapture to estimate the numbers of a migrating stage-structured population

1997 ◽  
Vol 54 (9) ◽  
pp. 2097-2104 ◽  
Author(s):  
R A Myers ◽  
M O Hammill ◽  
G B Stenson
Keyword(s):  
Continuous Distribution ◽  
Structured Data ◽  
Joint Analysis ◽  
Halichoerus Grypus ◽  
Birth Rates ◽  
Mark Recapture ◽  
Migration Rates ◽  
Structured Population ◽  
Age Structured ◽  
And Migration

A model is presented for the joint analysis of mark-recapture data and stage- or age-structured data that allows the population abundance, birth rates, and migration rates to be estimated in situations where standard methods may be unreliable. The model assumes that birth rates follow a continuous distribution and that migration can be described by a simple Markov process. Application of the model is illustrated using mark-recapture and stage-structured data for grey seal (Halichoerus grypus) pup production in the Gulf of St. Lawrence and resulted in estimates of 9800 and 10 500 pups produced in 1989 and 1990, respectively.

MAXIMUM LIKELIHOOD ESTIMATES OF TAG LOSS IN LEATHERBACK SEA TURTLES

2005 ◽  
Vol 69 (2) ◽  
pp. 540-548 ◽  
Author(s):  
PHILIPPE RIVALAN ◽  
MATTHEW H. GODFREY ◽  
ANNE-CAROLINE PRÉVOT-JULLIARD ◽  
MARC GIRONDOT
Keyword(s):  
Maximum Likelihood ◽  
Sea Turtles ◽  
Maximum Likelihood Estimates ◽  
Tag Loss ◽  
Leatherback Sea Turtles

scholarly journals Directional Selection and the Site-Frequency Spectrum

Genetics ◽  
2001 ◽  
Vol 159 (4) ◽  
pp. 1779-1788 ◽  
Author(s):  
Carlos D Bustamante ◽  
John Wakeley ◽  
Stanley Sawyer ◽  
Daniel L Hartl
Keyword(s):  
Maximum Likelihood ◽  
High Power ◽  
Negative Selection ◽  
Likelihood Estimation ◽  
Directional Selection ◽  
Likelihood Ratio Tests ◽  
Maximum Likelihood Estimates ◽  
Likelihood Methods ◽  
Ancestral States ◽  
Asymptotic Variances

Abstract In this article we explore statistical properties of the maximum-likelihood estimates (MLEs) of the selection and mutation parameters in a Poisson random field population genetics model of directional selection at DNA sites. We derive the asymptotic variances and covariance of the MLEs and explore the power of the likelihood ratio tests (LRT) of neutrality for varying levels of mutation and selection as well as the robustness of the LRT to deviations from the assumption of free recombination among sites. We also discuss the coverage of confidence intervals on the basis of two standard-likelihood methods. We find that the LRT has high power to detect deviations from neutrality and that the maximum-likelihood estimation performs very well when the ancestral states of all mutations in the sample are known. When the ancestral states are not known, the test has high power to detect deviations from neutrality for negative selection but not for positive selection. We also find that the LRT is not robust to deviations from the assumption of independence among sites.

scholarly journals Spatial and space-time correlations in systems of subpopulations with genetic drift and migration.

Genetics ◽  
1993 ◽  
Vol 133 (3) ◽  
pp. 711-727
Author(s):  
B K Epperson
Keyword(s):  
Population Genetics ◽  
Time Correlation ◽  
Space Time ◽  
Spatial Correlations ◽  
Gene Frequencies ◽  
Migration Patterns ◽  
Migration Rates ◽  
Space And Time ◽  
Time Correlations ◽  
And Migration

Abstract The geographic distribution of genetic variation is an important theoretical and experimental component of population genetics. Previous characterizations of genetic structure of populations have used measures of spatial variance and spatial correlations. Yet a full understanding of the causes and consequences of spatial structure requires complete characterization of the underlying space-time system. This paper examines important interactions between processes and spatial structure in systems of subpopulations with migration and drift, by analyzing correlations of gene frequencies over space and time. We develop methods for studying important features of the complete set of space-time correlations of gene frequencies for the first time in population genetics. These methods also provide a new alternative for studying the purely spatial correlations and the variance, for models with general spatial dimensionalities and migration patterns. These results are obtained by employing theorems, previously unused in population genetics, for space-time autoregressive (STAR) stochastic spatial time series. We include results on systems with subpopulation interactions that have time delay lags (temporal orders) greater than one. We use the space-time correlation structure to develop novel estimators for migration rates that are based on space-time data (samples collected over space and time) rather than on purely spatial data, for real systems. We examine the space-time and spatial correlations for some specific stepping stone migration models. One focus is on the effects of anisotropic migration rates. Partial space-time correlation coefficients can be used for identifying migration patterns. Using STAR models, the spatial, space-time, and partial space-time correlations together provide a framework with an unprecedented level of detail for characterizing, predicting and contrasting space-time theoretical distributions of gene frequencies, and for identifying features such as the pattern of migration and estimating migration rates in experimental studies of genetic variation over space and time.

Sign in / Sign up

Export Citation Format

Share Document