Acoustic monitoring indicates a positive relationship between calling frequency and spawning in captive spotted seatrout (Cynoscion nebulosus)

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1 Department of Natural Sciences, University of South Carolina Beaufort, Bluffton, SC, USA
2 Department of Mathematics and Computational Science, University of South Carolina Beaufort, Bluffton, South Carolina, United States
3 South Carolina Department of Natural Resources, Marine Resources Research Institute, Charleston, South Carolina, USA
DOI
10.7287/peerj.preprints.1656v1
Published
Accepted
Subject Areas
Animal Behavior, Aquaculture, Fisheries and Fish Science, Marine Biology
Keywords
Cynoscion nebulosus, spotted seatrout, spawning, sound production, reproduction, Sciaenidae
Copyright
© 2016 Montie et al.
Licence
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ PrePrints) and either DOI or URL of the article must be cited.
Cite this article
Montie EW, Hoover M, Kehrer C, Yost J, Brenkert K, O'Donnell T, Denson MR. 2016. Acoustic monitoring indicates a positive relationship between calling frequency and spawning in captive spotted seatrout (Cynoscion nebulosus) PeerJ PrePrints 4:e1656v1

Abstract

Background: Fish sound production is widespread throughout many families. Agonistic and courtship behaviors are the most common reasons for fish sound production. Yet, there is still some debate on how sound production and spawning are correlated in many soniferous fish species. In the present study, our aim was to determine if a quantitative relationship exists between calling and egg deposition in captive spotted seatrout (Cynoscion nebulosus). This type of data is essential if scientists and managers plan to use acoustic metrics to identify spawning aggregations over large spatial scales and monitor reproductive activity over annual and decadal timeframes.Methods: Wild caught spotted seatrout were held in three laboratory tanks equipped with long-term acoustic loggers (i.e., DSG-Oceans) to record underwater sound throughout an entire, simulated reproductive season. Acoustic monitoring occurred from April 13 to December 19, 2012 for Tank 1 and from April 13 to November 21, 2012 for Tanks 2 and 3. DSG-Oceans were scheduled to record sound for 2 min every 20 min. We enumerated the number of calls, calculated the received sound pressure level (SPL in dB re 1 µPa; between 50 and 2000 Hz) of each 2 min ‘wav file’, and counted the number of eggs every morning in each tank.Results: Spotted seatrout produced three distinct call types characterized as “drums”, “grunts”, and “staccatos”. Spotted seatrout calling increased as the light cycle shifted from 13.5 to 14.5 h of light, and the temperature increased to 27.7oC. Calling began to decrease once the temperature fell below 27.7 oC, and the light cycle shifted to 12 h of light. These captive settings are similar to the amount of daylight and water temperatures observed during the summer, which is the primary spawning period of spotted seatrout. Spotted seatrout exhibited daily patterns of calling. Sound production began once the lights turned off, and calling reached maximum activity approximately 3 h later. Spawning occurred only on evenings in which spotted seatrout were calling. Significantly more calling and higher mean SPLs occurred on evenings in which spawning occurred as compared to evenings in which spawning did not occur. Spawning was more productive when spotted seatrout produced more calls. For all tanks, more calling and higher SPLs were associated with more eggs released by females.Discussion: The fact that more calling and higher SPLs were associated with spawns that were more productive indicates that acoustic metrics can provide quantitative information on spotted seatrout spawning in the wild. These findings will help us to identify spawning aggregations over large spatial scales and monitor the effects of noise pollution, water quality, and climatic changes on reproductive activity using acoustic technology.

Author Comment

This is a submission to PeerJ for review.

Supplemental Information

Raw data of fish lengths and weights

Dataset 1. Raw data that contains the sex, length, and weights of all fish in tanks 1, 2, and 3.

DOI: 10.7287/peerj.preprints.1656v1/supp-1

Raw data of water quality

Dataset 2. Raw data that contains the water temperature, dissolved oxygen, conductivity, and salinity over the entire study period for each tank.

DOI: 10.7287/peerj.preprints.1656v1/supp-2

Raw data of number of calls and SPL for tank 1

Dataset 3. Raw data of the number of drums, grunts, trains, total calls, and SPL for tank 1.

DOI: 10.7287/peerj.preprints.1656v1/supp-3

Raw data of number of calls and SPL for tank 2

Dataset 4. Raw data of the number of drums, grunts, trains, total calls, and SPL for tank 2.

DOI: 10.7287/peerj.preprints.1656v1/supp-4

Raw data for number of calls and SPL for tank 3

Dataset 5. Raw data of the number of drums, grunts, trains, total calls, and SPL for tank 3.

DOI: 10.7287/peerj.preprints.1656v1/supp-5

Raw data number of calls, SPL, and eggs per day

Dataset 6. Raw calling, SPL, and egg data for each tank.

DOI: 10.7287/peerj.preprints.1656v1/supp-6