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Sampling effort and its allocation in the Lincoln-Petersen experiment: a hierarchical approach

Sampling effort and its allocation in the Lincoln-Petersen experiment: a hierarchical approach
Sampling effort and its allocation in the Lincoln-Petersen experiment: a hierarchical approach

Capture-recapture methods are widely used for estimating population sizes in ecological and epidemiological studies, yet the optimal allocation of sampling effort often remains underexplored. This study explores sampling efforts in a hierarchical framework that subdivides each capture occasion in a Lincoln–Petersen experiment into multiple sub-occasions, allowing for flexible resource allocation. When detection probabilities are equal across occasions, an even split minimizes variance; when probabilities differ, maximizing the joint detection probability is essential. A pseudo-Bayesian approach is also proposed to address scenarios with unknown catchabilities. Detailed simulation studies validate the theoretical findings and demonstrate the framework's robustness. The resulting guidelines offer practical insights for designing more efficient capture-recapture experiments and improving population size estimates.

Capture-recapture, Lincoln–Petersen estimator, Population size, Sampling effort, Variance estimation
0378-3758
Chin, Su Na
c55163ba-6ad6-42f5-ad6d-b784c664c716
Overstall, Antony
c1d6c8bd-1c5f-49ee-a845-ec9ec7b20910
Böhning, Dankmar
1df635d4-e3dc-44d0-b61d-5fd11f6434e1
Chin, Su Na
c55163ba-6ad6-42f5-ad6d-b784c664c716
Overstall, Antony
c1d6c8bd-1c5f-49ee-a845-ec9ec7b20910
Böhning, Dankmar
1df635d4-e3dc-44d0-b61d-5fd11f6434e1

Chin, Su Na, Overstall, Antony and Böhning, Dankmar (2025) Sampling effort and its allocation in the Lincoln-Petersen experiment: a hierarchical approach. Journal of Statistical Planning and Inference, 241, [106330]. (doi:10.1016/j.jspi.2025.106330).

Record type: Article

Abstract

Capture-recapture methods are widely used for estimating population sizes in ecological and epidemiological studies, yet the optimal allocation of sampling effort often remains underexplored. This study explores sampling efforts in a hierarchical framework that subdivides each capture occasion in a Lincoln–Petersen experiment into multiple sub-occasions, allowing for flexible resource allocation. When detection probabilities are equal across occasions, an even split minimizes variance; when probabilities differ, maximizing the joint detection probability is essential. A pseudo-Bayesian approach is also proposed to address scenarios with unknown catchabilities. Detailed simulation studies validate the theoretical findings and demonstrate the framework's robustness. The resulting guidelines offer practical insights for designing more efficient capture-recapture experiments and improving population size estimates.

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Accepted/In Press date: 24 July 2025
e-pub ahead of print date: 5 August 2025
Published date: 7 August 2025
Keywords: Capture-recapture, Lincoln–Petersen estimator, Population size, Sampling effort, Variance estimation

Identifiers

Local EPrints ID: 504678
URI: http://eprints.soton.ac.uk/id/eprint/504678
ISSN: 0378-3758
PURE UUID: d3fcb6b7-376b-40b1-a811-42bdb9ae2f90
ORCID for Su Na Chin: ORCID iD orcid.org/0000-0002-6826-266X
ORCID for Antony Overstall: ORCID iD orcid.org/0000-0003-0638-8635
ORCID for Dankmar Böhning: ORCID iD orcid.org/0000-0003-0638-7106

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Date deposited: 17 Sep 2025 16:52
Last modified: 18 Sep 2025 02:05

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Contributors

Author: Su Na Chin ORCID iD

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