Return to search

Modeling the Effects of Hypoxia on Fish Movement in the Gulf of Mexico Hypoxic Zone

The Louisiana-Texas coast is one of the largest areas of seasonal, coastal hypoxia. The hypoxic zone has increased in size since the 1900s and has significantly increased in thickness since 1985. Hypoxia can negatively affect fish through direct mortality, reduced fecundity, and reduced preyavailability. Movement algorithms were used to model fish movement and avoidance of hypoxia in 2-D and 3-D with static and dynamic environmental fields. Output from a 3-D, coupled, hydrodynamic-water quality model was used for the environmental conditions of the model. A particle tracking module for the hydrodynamic model was used to track fish movement. Movement algorithms were added to the tracking module to allow for active movement. Three movement algorithms for use outside of hypoxic conditions were compared in static 2-D scenarios. There was not a large difference in hypoxia exposure for the three algorithms, but there was a difference in sinuosity (amount of wiggle in the fish track). Comparing static and dynamic environmental fields in 2-D resulted in higher exposures for dynamic conditions. There was also an unexpected effect from a narrow region of normoxic water surrounded by hypoxic water. The presence of this thin area resulted in more outliers in hypoxia exposure. Three algorithms for hypoxia avoidance were compared in dynamic conditions. Two of the algorithms were found to be similar, but a third that used both dissolved oxygen and temperature as inputs had much higher exposures. Balancing the two environmental cues resulted in poor hypoxia avoidance. Comparing 2-D and 3-D scenarios resulted in lower exposure for fish in 3-D scenarios. Two different methods of perception ranges were used and found to result in similar hypoxia exposures. The research highlighted the need to include 3-D movement in fish models for the Gulf of Mexico hypoxia region. Also, high-resolution field data need to be collected to calibrate and validate such models and facilitate selection of appropriate movement algorithms.

Identiferoai:union.ndltd.org:LSU/oai:etd.lsu.edu:etd-11092016-124939
Date08 December 2016
CreatorsLaBone, Elizabeth Dawn
ContributorsJustic, Dubravko, Rose, Kenneth, Huang, Haosheng, Leonard, Billy Rogers
PublisherLSU
Source SetsLouisiana State University
LanguageEnglish
Detected LanguageEnglish
Typetext
Formatapplication/pdf
Sourcehttp://etd.lsu.edu/docs/available/etd-11092016-124939/
Rightsrestricted, I hereby certify that, if appropriate, I have obtained and attached herein a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to LSU or its agents the non-exclusive license to archive and make accessible, under the conditions specified below and in appropriate University policies, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report.

Page generated in 0.0021 seconds