Knowl. Manag. Aquat. Ecosyst.
Number 424, 2023
Management of habitats and populations/communities
|Number of page(s)||13|
|Published online||23 February 2023|
ABC model for estimating sea lamprey local population size using a simple nest count during the spawning season
Université de Pau et des Pays de l'Adour, E2S UPPA, INRAE, ECOBIOP, Saint-Pée-sur-Nivelle, France
2 Pôle Gestion des Migrateurs Amphihalins dans leur Environnement, OFB, INRAE, Agrocampus Ouest, Univ Pau & Pays Adour/ E2S UPPA, Pau, France
3 Department of Plant Biology and Ecology, University of the Basque Country (UPV/EHU), Bilbao, Spain
* Corresponding author: firstname.lastname@example.org
Accepted: 12 January 2023
Population estimation implies considering the biology of the species, but also the constraints of logistic aspects such as cost. While common methods based on individual counts can provide precise estimates, they require an extensive sampling effort. An alternative to these methods is using cues linked to the species abundance. In that case, producing absolute estimates requires assessing the relationship between the individuals and these cues. In this paper, we propose a model based on data on spawning behaviour and Approximate Bayesian Computation to estimate the number of sea lamprey spawners using nest counts data. By counting the daily number of occupied nests and using parameters from a behavioural study, we set up a model simulating a spawning season and returning a population estimate by comparison with field data. Our model gives realistic estimates and we discuss the parameters on which to prioritize data collection with a sensitivity analysis, and show that halving the sample size provides a still satisfactory accuracy. We made an easily parametrizable application to run the model for any people interested in sea lamprey population estimation, and believe this framework to be a good way to increase data collection for both endangered and invasive sea lamprey.
Key words: Management / anadromous species / endangered species / nesting behaviour / mechanistic model
© M. Dhamelincourt et al., Published by EDP Sciences 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License CC-BY-ND (https://creativecommons.org/licenses/by-nd/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. If you remix, transform, or build upon the material, you may not distribute the modified material.
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