JOURNAL ARTICLE
Quantifying trends in and potential drivers of mycobacteriosis in Atlantic Striped Bass in Maryland waters of the Chesapeake Bay.
Published In: Transactions of the American Fisheries Society, 2025, v. 154, n. 1. P. 35 1 of 3
Database: Environment Complete 2 of 3
Authored By: Jesse, Jerelle; Nesslage, Geneviève; Matsche, Mark; Townsend, Howard; Shen, Chunqi; Testa, Jeremy M; Wilberg, Michael J 3 of 3
Abstract
This article focuses on quantifying trends and potential environmental and nutritional drivers of mycobacteriosis, a chronic bacterial disease, in Atlantic Striped Bass (Morone saxatilis) within Maryland waters of the Chesapeake Bay from 1998 to 2017. Using long-term fish health monitoring data and coupled hydrodynamic–biogeochemical modeling, the study found that disease prevalence in young Striped Bass increased with higher summer water temperatures and greater hypoxic (low oxygen) volume, while disease severity increased with age and was higher in males. Contrary to expectations, severe disease occurrence decreased with worsening water quality, which the authors interpret as likely reflecting increased mortality of severely diseased fish under stressful environmental conditions. Fish condition, measured by Fulton's condition factor, was related to disease progression but appeared more as a symptom than a cause of mycobacteriosis. The findings suggest that poor water quality and climate-related stressors contribute to widespread mycobacteriosis in Maryland's Chesapeake Bay Striped Bass population, with implications for survival and fisheries management.
Additional Information
- Source:Transactions of the American Fisheries Society. 2025/01, Vol. 154, Issue 1, p35
- Document Type:Article
- Subject Area:Environmental Sciences
- Publication Date:2025
- ISSN:0002-8487
- DOI:10.1093/tafafs/vnae003
- Accession Number:185452422
- Copyright Statement:Copyright of Transactions of the American Fisheries Society is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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