Estimating Reproductive Parameters of a Newly Discovered Weather Loach Population

ABSTRACT Aquatic invasive species have negative impacts on native biodiversity and pose a significant threat to overall ecosystem health. Successfully established non‐native species possess life history traits that are advantageous for colonization and expansion into novel environments. The reproductive traits and strategies of fish are often good predictors of invasion success. Thus, understanding reproductive dynamics of non‐native species in their introduced environments is an important component for predicting expansion and effectively managing invasive populations. The Weather Loach Misgurnus anguillicaudatus is a recently discovered introduced species in Georgia, USA, and little is known about its life history attributes where it is not native. Thus, the objectives of this study were to: (1) estimate mean batch fecundity of female Weather Loach; (2) determine timing and periodicity of spawning; and (3) evaluate whether the gonadosomatic index (GSI) is a reliable indicator of reproductive status in this species. Based on observed peaks in eggs larger than 500 µm, we identified the presumed spawning season for Weather Loach to be occurring from April through August. The highest average fecundity observed was during July (10,539 eggs) and the lowest average fecundity observed was during April (3083 eggs). The GSI was a strong predictor of fecundity and tracked the number of mature eggs present in each month of the year. Our estimates of batch fecundity and determination of the annual spawning season can help managers better understand reproductive dynamics and develop predictive population models aimed at evaluating management activities.

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Publication Details

Journal
Aquaculture Fish and Fisheries
Published
2025-09-12
DOI
https://doi.org/10.1002/aff2.70117
Primary Topic
Fish Ecology and Management Studies
Type
article
Field-Weighted Citation Impact
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article

Estimating Reproductive Parameters of a Newly Discovered Weather Loach Population

T.P. Faherty, Peter D. Hazelton, Martin J. Hamel, Andrew Lyons et al.
Aquaculture Fish and Fisheries
Fish Ecology and Management Studies
article

Estimating Reproductive Parameters of a Newly Discovered Weather Loach Population

T.P. Faherty, Peter D. Hazelton, Martin J. Hamel, Andrew Lyons, Joseph Dahlen, Molly A. Martin, Alan M. Bond, Wesley Gerrin, James L. Shelton, Michael A. Baker, Sarah F. McNair, Katherine Fincher, Zachary Schumber
article en

Abstract

ABSTRACT Aquatic invasive species have negative impacts on native biodiversity and pose a significant threat to overall ecosystem health. Successfully established non‐native species possess life history traits that are advantageous for colonization and expansion into novel environments. The reproductive traits and strategies of fish are often good predictors of invasion success. Thus, understanding reproductive dynamics of non‐native species in their introduced environments is an important component for predicting expansion and effectively managing invasive populations. The Weather Loach Misgurnus anguillicaudatus is a recently discovered introduced species in Georgia, USA, and little is known about its life history attributes where it is not native. Thus, the objectives of this study were to: (1) estimate mean batch fecundity of female Weather Loach; (2) determine timing and periodicity of spawning; and (3) evaluate whether the gonadosomatic index (GSI) is a reliable indicator of reproductive status in this species. Based on observed peaks in eggs larger than 500 µm, we identified the presumed spawning season for Weather Loach to be occurring from April through August. The highest average fecundity observed was during July (10,539 eggs) and the lowest average fecundity observed was during April (3083 eggs). The GSI was a strong predictor of fecundity and tracked the number of mature eggs present in each month of the year. Our estimates of batch fecundity and determination of the annual spawning season can help managers better understand reproductive dynamics and develop predictive population models aimed at evaluating management activities.

Aquaculture Fish and FisheriesVol. 5(5)
University of Georgia (US)
Openalex Percentile: Top 73%
Fish Ecology and Management Studies
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