Submit a preprint

416

Mark loss can strongly bias estimates of demographic rates in multi-state models: a case study with simulated and empirical datasetsuse asterix (*) to get italics
Frédéric Touzalin, Eric J. Petit, Emmanuelle Cam, Claire Stagier, Emma C. Teeling, Sébastien J. PuechmaillePlease use the format "First name initials family name" as in "Marie S. Curie, Niels H. D. Bohr, Albert Einstein, John R. R. Tolkien, Donna T. Strickland"
2023
<p style="text-align: justify;">1. The development of methods for individual identification in wild species and the refinement of Capture-Mark-Recapture (CMR) models over the past few decades have greatly improved the assessment of population demographic rates to address ecological and conservation questions. In particular, multi-state models, which offer flexibility in analysing complex study systems, have gained popularity within the ecological community. In this study, we focus on the issue of mark loss and the associated recycling of remarked individuals, which requires further exploration given the increasing use of these models.</p> <p style="text-align: justify;">2. To fill this knowledge gap, we employed a wide range of simulation scenarios that reflect commonly encountered real case studies, drawing inspiration from the survival rates of 700 vertebrate species. Using a multi-state, Arnason-Schwartz (AS) modelling framework, we estimated the effects of mark loss and recycled individuals on parameter estimates. We assessed parameter bias by simulating a metapopulation system with varying capture and survival rates. Additionally, we demonstrated how mark loss can be easily estimated and accounted for using a 10-year empirical CMR dataset of bats. The bats were individually identified using Passive Integrated Transponder (PIT) tag technology as potentially lost marks and multi-locus genotypes as 'permanent marks'.</p> <p style="text-align: justify;">3. Our simulation results revealed that the occurrence of bias and the affected parameters were highly dependent on the study system, making it difficult to establish general rules to predict bias a priori. The model structure and the interdependency among parameters pose challenges in predicting the impact of bias on estimates.</p> <p style="text-align: justify;">4. Our findings underscore the importance of assessing the effect of mark loss when using AS models. Ignoring such violations of model assumptions can have significant implications for ecological inferences and conservation policies. In general, the use of permanent marks, such as genotypes, should always be preferred when modelling population dynamics. If that is not feasible, an alternative is to combine two independent types of temporary marks, such as PIT tags and bands.</p> <p style="text-align: justify;">5. Analysis of our empirical dataset on Myotis myotis bats revealed that tag loss is higher in juveniles than in adults during the first year after tagging. The use of surgical glue to close the injection hole reduces tag loss rate from 28% to 19% in juveniles, while it has no effect on the tag loss rate in adults (~10%). The main bias observed in our metapopulation system appears in the survival rate, with up to a 20% underestimation if tag loss is not accounted for.</p>
https://doi.org/10.5281/zenodo.6453953You should fill this box only if you chose 'All or part of the results presented in this preprint are based on data'. URL must start with http:// or https://
https://doi.org/10.5281/zenodo.6453953You should fill this box only if you chose 'Scripts were used to obtain or analyze the results'. URL must start with http:// or https://
You should fill this box only if you chose 'Codes have been used in this study'. URL must start with http:// or https://
Arnason-Schwarz model, Bayesian, bats, capture-mark-recapture, mark retention, Myotis myotis, multi-state, surgical glue
NonePlease indicate the methods that may require specialised expertise during the peer review process (use a comma to separate various required expertises).
Conservation biology, Demography
Paul Acker, [paul.acker@ntnu.no], Stephanie Jenouvrier, [sjenouvrier@whoi.edu], Aurélien BESNARD, [aurelien.besnard@cefe.cnrs.fr], Christophe Barbrau, [christophe.barbraud@cebc.cnrs.fr], Marie Nevoux, [marie.nevoux@inrae.fr] No need for them to be recommenders of PCIEcology. Please do not suggest reviewers for whom there might be a conflict of interest. Reviewers are not allowed to review preprints written by close colleagues (with whom they have published in the last four years, with whom they have received joint funding in the last four years, or with whom they are currently writing a manuscript, or submitting a grant proposal), or by family members, friends, or anyone for whom bias might affect the nature of the review - see the code of conduct
e.g. John Doe [john@doe.com]
2022-04-12 18:49:34
Sylvain Billiard