Bayesian modeling and simulation methods for fish movements

Bayesian methods have been popular in modelling complex ecological data collected using modern animal tracking technologies such as acoustic telemetry for multiple reasons, including their extreme flexibility, ability to incorporate prior knowledge and better precision. Acoustic telemetry systems te...

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Bibliographic Details
Main Author: Munaweera Arachchilage, Inesh Prabuddha
Other Authors: Aleeza, Gerstein (Statistics), Kevin, Fraser (Biological sciences), Veronica, Berrocal (University of California, Irvine), Saman, Muthukumarana, Darren, Gillis
Format: Doctoral or Postdoctoral Thesis
Language:English
Published: 2023
Subjects:
Online Access:http://hdl.handle.net/1993/37211
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spelling ftunivmanitoba:oai:mspace.lib.umanitoba.ca:1993/37211 2023-08-27T04:07:46+02:00 Bayesian modeling and simulation methods for fish movements Munaweera Arachchilage, Inesh Prabuddha Aleeza, Gerstein (Statistics) Kevin, Fraser (Biological sciences) Veronica, Berrocal (University of California, Irvine) Saman, Muthukumarana Darren, Gillis 2023-03-20T20:22:23Z application/pdf http://hdl.handle.net/1993/37211 eng eng http://hdl.handle.net/1993/37211 open access Acoustic Telemetry Bayesian Inference State-space Models Mark-recapture models doctoral thesis 2023 ftunivmanitoba 2023-08-06T17:37:16Z Bayesian methods have been popular in modelling complex ecological data collected using modern animal tracking technologies such as acoustic telemetry for multiple reasons, including their extreme flexibility, ability to incorporate prior knowledge and better precision. Acoustic telemetry systems technology has been increasingly used to study fish movement patterns and habitat use and estimate demographic parameters, including survival probabilities and population size. However, the data generated using omnidirectional acoustic telemetry studies are complex, with multiple sources of variability. In this thesis, I develop methods to effectively analyze data generated with omnidirectional acoustic telemetry systems. The thesis consists of four manuscripts with three different Bayesian models in the first three manuscripts: (1) Bayesian state-space modelling approach to estimate the hidden fish movement paths of walleye in lake Winnipeg, (2) Bayesian multi-state mark-recapture models to estimate survival of Arctic char living in multiple habitats of the Cambridge bay region of Nunavut, and (3) Bayesian hierarchical modelling to understand the biological and environmental drivers behind the survival of Cambridge bay Arctic char. In the fourth manuscript, we develop a novel set of fishery metrics to further understand the vulnerability of walleye to fishing activities in lake Winnipeg. Furthermore, the thesis provides practical tools for many challenges that will arise from the planning stage of the study to the data analysis stage of acoustic telemetry studies. In addition, the finding of each study provides valuable and influential information for fishery managers to make effective fish management and conservation decisions that will affect the future of the aquatic species in those regions. May 2023 Doctoral or Postdoctoral Thesis Arctic Cambridge Bay Nunavut MSpace at the University of Manitoba Arctic Nunavut Cambridge Bay ENVELOPE(-105.130,-105.130,69.037,69.037)
institution Open Polar
collection MSpace at the University of Manitoba
op_collection_id ftunivmanitoba
language English
topic Acoustic Telemetry
Bayesian Inference
State-space Models
Mark-recapture models
spellingShingle Acoustic Telemetry
Bayesian Inference
State-space Models
Mark-recapture models
Munaweera Arachchilage, Inesh Prabuddha
Bayesian modeling and simulation methods for fish movements
topic_facet Acoustic Telemetry
Bayesian Inference
State-space Models
Mark-recapture models
description Bayesian methods have been popular in modelling complex ecological data collected using modern animal tracking technologies such as acoustic telemetry for multiple reasons, including their extreme flexibility, ability to incorporate prior knowledge and better precision. Acoustic telemetry systems technology has been increasingly used to study fish movement patterns and habitat use and estimate demographic parameters, including survival probabilities and population size. However, the data generated using omnidirectional acoustic telemetry studies are complex, with multiple sources of variability. In this thesis, I develop methods to effectively analyze data generated with omnidirectional acoustic telemetry systems. The thesis consists of four manuscripts with three different Bayesian models in the first three manuscripts: (1) Bayesian state-space modelling approach to estimate the hidden fish movement paths of walleye in lake Winnipeg, (2) Bayesian multi-state mark-recapture models to estimate survival of Arctic char living in multiple habitats of the Cambridge bay region of Nunavut, and (3) Bayesian hierarchical modelling to understand the biological and environmental drivers behind the survival of Cambridge bay Arctic char. In the fourth manuscript, we develop a novel set of fishery metrics to further understand the vulnerability of walleye to fishing activities in lake Winnipeg. Furthermore, the thesis provides practical tools for many challenges that will arise from the planning stage of the study to the data analysis stage of acoustic telemetry studies. In addition, the finding of each study provides valuable and influential information for fishery managers to make effective fish management and conservation decisions that will affect the future of the aquatic species in those regions. May 2023
author2 Aleeza, Gerstein (Statistics)
Kevin, Fraser (Biological sciences)
Veronica, Berrocal (University of California, Irvine)
Saman, Muthukumarana
Darren, Gillis
format Doctoral or Postdoctoral Thesis
author Munaweera Arachchilage, Inesh Prabuddha
author_facet Munaweera Arachchilage, Inesh Prabuddha
author_sort Munaweera Arachchilage, Inesh Prabuddha
title Bayesian modeling and simulation methods for fish movements
title_short Bayesian modeling and simulation methods for fish movements
title_full Bayesian modeling and simulation methods for fish movements
title_fullStr Bayesian modeling and simulation methods for fish movements
title_full_unstemmed Bayesian modeling and simulation methods for fish movements
title_sort bayesian modeling and simulation methods for fish movements
publishDate 2023
url http://hdl.handle.net/1993/37211
long_lat ENVELOPE(-105.130,-105.130,69.037,69.037)
geographic Arctic
Nunavut
Cambridge Bay
geographic_facet Arctic
Nunavut
Cambridge Bay
genre Arctic
Cambridge Bay
Nunavut
genre_facet Arctic
Cambridge Bay
Nunavut
op_relation http://hdl.handle.net/1993/37211
op_rights open access
_version_ 1775348481250033664