Necropsy-based wild fish health assessment

Journal of Visualized Experiments
By: , and 

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Abstract

Anthropogenic influences from increased nutrients and chemical contaminants, to habitat alterations and climate change, can have significant effects on fish populations. Adverse effects monitoring, utilizing biomarkers from the organismal to the molecular level, can be used to assess the cumulative effects on fishes and other organisms. Fish health has been used worldwide as an indicator of aquatic ecosystem health. The necropsy-based fish health assessment provides data on visible abnormalities and lesions, parasites, condition and organosomatic indices. These can be compared by site, season and sex, as well as temporally, to document change over time. Severity ratings can be assigned to various observations to calculate a fish health index for more quantitative assessment. A drawback of the necropsy-based assessment is that it is based on visual observations and condition factors, which are not as sensitive as tissue and subcellular biomarkers for sublethal effects. Additionally, it is rarely possible to identify causes or risk factors associated with observed abnormalities. So, for instance a raised lesion or "tumor" on the fins, lips or body surface may be a neoplasm. However, it could also be a response to a parasite, chronic inflammation or hyperplasia of normal cells in response to an irritant. Conversely, neoplasms, certain parasites, other infectious agents and many tissue changes are not visible and so may be underestimated. However, during the necropsy-based assessment, blood (plasma), tissues for histopathology (microscopic pathology), genomics and other molecular analyses, and otoliths for aging can be collected. These downstream analyses, together with geospatial analyses, habitat assessments, water quality and contaminant analyses can all be important in comprehensive ecosystem evaluations.

Publication type Article
Publication Subtype Journal Article
Title Necropsy-based wild fish health assessment
Series title Journal of Visualized Experiments
DOI 10.3791/57946
Volume 139
Year Published 2018
Language English
Publisher JOVE
Contributing office(s) Leetown Science Center
Description e57946, 11 p.
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