Mark loss can strongly bias estimates of demographic rates in multi-state models: a case study with simulated and empirical datasets

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-...

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Main Authors: Touzalin, Frédéric, Petit, Eric J., Cam, Emmanuelle, Stagier, Claire, Teeling, Emma C., Puechmaille, Sébastien J.
Format: Article
Language:English
Published: Peer Community In 2023-12-01
Series:Peer Community Journal
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Online Access:https://peercommunityjournal.org/articles/10.24072/pcjournal.348/
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author Touzalin, Frédéric
Petit, Eric J.
Cam, Emmanuelle
Stagier, Claire
Teeling, Emma C.
Puechmaille, Sébastien J.
author_facet Touzalin, Frédéric
Petit, Eric J.
Cam, Emmanuelle
Stagier, Claire
Teeling, Emma C.
Puechmaille, Sébastien J.
author_sort Touzalin, Frédéric
collection DOAJ
description 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. 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'. 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. 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. 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.
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institution Kabale University
issn 2804-3871
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publishDate 2023-12-01
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series Peer Community Journal
spelling doaj-art-8c9a577acc4746aaa34fe97253211fbd2025-02-07T10:16:48ZengPeer Community InPeer Community Journal2804-38712023-12-01310.24072/pcjournal.34810.24072/pcjournal.348Mark loss can strongly bias estimates of demographic rates in multi-state models: a case study with simulated and empirical datasets Touzalin, Frédéric0https://orcid.org/0000-0002-3042-8986Petit, Eric J.1https://orcid.org/0000-0001-5058-5826Cam, Emmanuelle2https://orcid.org/0000-0001-7324-6958Stagier, Claire3Teeling, Emma C.4https://orcid.org/0000-0002-3309-1346Puechmaille, Sébastien J.5https://orcid.org/0000-0001-9517-5775School of Biology and Environmental Science, Science Centre West, University College Dublin, Dublin, Ireland; Bretagne Vivante-SEPNB, Brest, FranceDECOD (Ecosystem Dynamics and Sustainability), INRAE, Institut Agro, Ifremer, Rennes, FranceUniversité de Bretagne occidentale, Brest, LEMAR, CNRS, IRD, Ifremer, F-29280 Plouzane, FranceSchool of Biology and Environmental Science, Science Centre West, University College Dublin, Dublin, IrelandSchool of Biology and Environmental Science, Science Centre West, University College Dublin, Dublin, IrelandZoological Institute and Museum, University of Greifswald, Greifswald, Germany; ISEM, Univ Montpellier, CNRS, IRD, Montpellier, France; Institut Universitaire de France, Paris, France1. 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. 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'. 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. 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. 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. https://peercommunityjournal.org/articles/10.24072/pcjournal.348/Arnason-Schwarz model; Bayesian; bats; capture-mark-recapture; mark retention; Myotis myotis; multi-state; surgical glue
spellingShingle Touzalin, Frédéric
Petit, Eric J.
Cam, Emmanuelle
Stagier, Claire
Teeling, Emma C.
Puechmaille, Sébastien J.
Mark loss can strongly bias estimates of demographic rates in multi-state models: a case study with simulated and empirical datasets
Peer Community Journal
Arnason-Schwarz model; Bayesian; bats; capture-mark-recapture; mark retention; Myotis myotis; multi-state; surgical glue
title Mark loss can strongly bias estimates of demographic rates in multi-state models: a case study with simulated and empirical datasets
title_full Mark loss can strongly bias estimates of demographic rates in multi-state models: a case study with simulated and empirical datasets
title_fullStr Mark loss can strongly bias estimates of demographic rates in multi-state models: a case study with simulated and empirical datasets
title_full_unstemmed Mark loss can strongly bias estimates of demographic rates in multi-state models: a case study with simulated and empirical datasets
title_short Mark loss can strongly bias estimates of demographic rates in multi-state models: a case study with simulated and empirical datasets
title_sort mark loss can strongly bias estimates of demographic rates in multi state models a case study with simulated and empirical datasets
topic Arnason-Schwarz model; Bayesian; bats; capture-mark-recapture; mark retention; Myotis myotis; multi-state; surgical glue
url https://peercommunityjournal.org/articles/10.24072/pcjournal.348/
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