Census and Population Estimation

This paper evaluates SCR survey designs for multiple populations, showing systematic layouts perform well despite group differences.

This paper examines how data augmentation affects uncertainty estimates in ecological models by analyzing the impact of a fixed superpopulation size on variance constraints.

This paper introduces an efficient Bayesian model for estimating natal dispersal and spatially varying demographic parameters using capture-recapture data, applied to white stork populations across 101 spatial units.

The paper develops a space-for-time mark-recapture model that incorporates age, time, and individual covariates to estimate survival in migrating animals.

The paper estimates chronological age without known-age individuals by modeling half-sibling pair occurrence rates and capture times using a pseudo-likelihood framework.

The paper introduces the R-package Jsmm for analysing mark-recapture data using Bayesian joint species movement modelling to estimate movement behaviours and population parameters.

The paper shows that low between/within area resighting ratios in mark-recapture studies can result from restricted sampling, not population isolation, and highlights the need for methods accounting for space-time fidelity.

This paper introduces a Bayesian spatially explicit integrated population model to estimate and predict spatio-temporal demographic rates across large geographic areas, showing it provides unbiased and precise estimates even with data misalignment and spatial autocorrelation.

The paper integrates UAS-based spatial surveys and bio-logging tracking to improve population size estimation by combining individual behavior data with colony-level counts.

This paper applies spatially explicit capture-recapture models to acoustic telemetry data in river networks to estimate habitat use parameters of Arctic grayling based on temperature distributions.