Modelling Heron Survival Using Weather Data

North, Philip M.; Morgan, Byron J. T.

doi:10.2307/2530260

Cited by 93 publications

(65 citation statements)

References 11 publications

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“…where α and β are the regression parameters (see for example North and Morgan 1979;King et al 2009). The set of model parameters is θ = { p, λ, α, β}, since the survival probabilities are a deterministic function of α and β.…”

Section: Modelmentioning

confidence: 99%

Analysing Mark–Recapture–Recovery Data in the Presence of Missing Covariate Data Via Multiple Imputation

Worthington

King

Buckland

2014

JABES

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We consider mark-recapture-recovery data with additional individual time-varying continuous covariate data. For such data it is common to specify the model parameters, and in particular the survival probabilities, as a function of these covariates to incorporate individual heterogeneity. However, an issue arises in relation to missing covariate values, for (at least) the times when an individual is not observed, leading to an analytically intractable likelihood. We propose a two-step multiple imputation approach to obtain estimates of the demographic parameters. Firstly, a model is fitted to only the observed covariate values. Conditional on the fitted covariate model, multiple "complete" datasets are generated (i.e. all missing covariate values are imputed). Secondly, for each complete dataset, a closed form complete data likelihood can be maximised to obtain estimates of the model parameters which are subsequently combined to obtain an overall estimate of the parameters. Associated standard errors and 95 % confidence intervals are obtained using a non-parametric bootstrap. A simulation study is undertaken to assess the performance of the proposed twostep approach. We apply the method to data collected on a well-studied population of Soay sheep and compare the results with a Bayesian data augmentation approach.Supplementary materials accompanying this paper appear on-line.

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Section: Modelmentioning

confidence: 99%

Analysing Mark–Recapture–Recovery Data in the Presence of Missing Covariate Data Via Multiple Imputation

Worthington

King

Buckland

2014

JABES

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“…A special mention should be given to the model of North & Morgan (1979) which allows parameter reduction and provides meaningful biological information by relating survival to external variables as a regression built into the model (see also Cave 1983).…”

Section: Introductionmentioning

confidence: 99%

“…(1985). In a line similar to that of North & Morgan (1979) for recoveries, Clobert & Lebreton (1985) developed a model with built in regression of survival on environmental variables. In both cases, the parsimony implies iterative fitting by computer.…”

Section: Introductionmentioning

confidence: 99%

A General Approach to Survival Rate Estimation by Recaptures or Resightings of Marked Birds

Clobert¹,

Lebreton

Allainé

2002

Ardea

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“…Thus we adopt the common practice of ignoring temporal variation and assume that the probability a dead bird is recovered remains constant within each cohort. Therefore, the conditional probability of recovery in year t from cohort i is given by the probability of a bird dying in year t divided by the complement of the probability of its still being alive at the end of the recovery period (North and Morgan, 1979). The likelihood for the ring-recovery data, which is simply a product of Multinomials for both juvenile and adult recoveries, is given by…”

Section: Ring-recovery Datamentioning

confidence: 99%

An Integrated Population Model From Constant Effort Bird-Ringing Data

Cave

King

Freeman

2010

JABES

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Data from annual bird-ringing programmes, in which catch effort is standardised, are routinely used to index abundance, productivity and adult survival. Efficient models have been developed for each. Such monitoring schemes, based on ringing across a number of sites, are perhaps unique in providing this combination of demographic information and make the data particularly amenable to an integrated approach to population modelling. We develop a Bayesian approach and a deterministic population model uniting abundance, productivity and survival.The method is applied to Sedge Warbler Acrocephalus schoenobaenus data from the British Trust for Ornithology's Constant Effort Site scheme. The possibility of "transient" birds needs to be incorporated within this analysis. We demonstrate how current methodology can efficiently be extended to use additional data from multiple within-year recaptures when controlling for transience.

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Modelling Heron Survival Using Weather Data

Cited by 93 publications

References 11 publications

Analysing Mark–Recapture–Recovery Data in the Presence of Missing Covariate Data Via Multiple Imputation

Analysing Mark–Recapture–Recovery Data in the Presence of Missing Covariate Data Via Multiple Imputation

A General Approach to Survival Rate Estimation by Recaptures or Resightings of Marked Birds

An Integrated Population Model From Constant Effort Bird-Ringing Data

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