Fish Bioacoustics
Many fishes make sounds. This fact allows our Fish Acoustics Research Team (comprised of Associate Professor Mark Sprague in Physics, the late Professor Hal J. Daniel III, former and current graduate students Stephen Johnson, Chris Pullinger, Todd Jenkins, Marcie Hutchinson, and Cecilia Krahforst) to use the passive acoustic approach to determine spawning areas used by fishes in the family Sciaenidae (drums, weakfish, and seatrouts), which are both commercially and recreationally valuable in North Carolina. These fishes make species-specific sounds using their swim bladders and sonic muscles during spawning activities; in most cases, males make the sounds as an advertisement call to attract females. By recording sounds of captive specimens of each of five species of Sciaenidae fishes (silver perch, Bairdiella chrysoura, weakfish, Cynoscion regalis, spotted seatrout, C. nebulosus, Atlantic croaker, Micropogonias undulatus, and red drum, Sciaenops ocellatus), Luczkovich and his colleagues can identify the species making calls by simply by listening to recordings and analyzing them spectrographically. The team makes recordings of fish sounds, analyzes their spectral properties, correlates the sounds with plankton net, trawl, and gill net samples, and produces spawning area maps for each species. An initial publication from this study revealed a direct relationship between sound pressure levels (from male weakfish) and egg production (from females) at spawning aggregations in Pamlico Sound (Luczkovich et al., 1999). Luczkovich and the team also discovered that silver perch became acoustically inactive when bottlenose dolphins (Tursiops truncatus) were in the spawning areas indicating that these fishes can hear and respond to a predator’s sounds (Luczkovich et al., 2000). A common sound heard in Pamlico Sound is called “the chatter”; previous researchers had identified it as being produced by weakfish, but the ECU team determined that it was produced instead by striped cusk-eels (Ophididon marginatum)(Sprague & Luczkovich, 2001). A study using a Remotely Operated Vehicle (ROV) was conducted at one of the spawning areas in the Ocracoke Inlet; this ROV was fitted with a calibrated hydrophone and was positioned near a calling silver perch, allowing for a sound source level measurement (Sprague & Luczkovich, 2004). An analysis of an autonomous sonobuoy survey of Pamlico Sound was published in the Transactions of the American Fisheries Society (Luczkovich et al., 2008). A recent summary of the work by Luczkovich and colleagues in soniferous estuarine fish over twenty years was presented at the Underwater Noise meeting in Berlin (Luczkovich & Sprague, 2023). Finally, the effect of hypoxia (low dissolved oxygen) suppresses fish sound production in Pamlico Sound and the Neuse River was published (Luczkovich et al., 2024). This recent study demonstrates how the problem of worsening dissolved oxygen concentrations in estuaries due to water pollution and eutrophication is leading to less habitat availability for spawning in commercially and recreationally important fish like weakfish and red drum.
More recently, a Liquid Robotics Wave Glider with a passive acoustic recorder for ocean soundscape studies was obtained under a grant from the National Science Foundation by Dr. Luczkovich and his collaborators Sprague (ECU Physics), Roger Rulifson (ECU Biology) and J. P Walsh (ECU Geological Sciences, now at University of Rhode Island) (Luczkovich et al., 2019). A study using this mobile wave-powered instrument (Luczkovich & Sprague, 2022) was published in Frontiers in Marine Science, in which ocean soundscapes and calls of sound-producing species were identified and mapped along a path followed by the wave glider in the Atlantic Ocean off North Carolina. This is an innovative use of a wave-powered and silent glider to travel along the coast and record the changing soundscapes produced by fishes, marine mammals, and invertebrates through space and time; normally most hydrophone surveys are done at a fixed location, so only temporal changes can be studied. One of the key findings was that there were many known species (red drum, Atlantic croaker, black drum, striped cusk-eels, and oyster toadfish) using open sand, natural reefs, and artificial reefs offshore, some of which also use estuarine habitats for spawning. In addition, several unknown sounds were recorded including possible sounds from sea robins and groupers, the “unknown buzz” hypothesized to be made by Atlantic midshipmen fish, Porichthyes plectrodon in a study from the Atlantic Ocean off Florida (Iafrate et al., 2023), and the “unknown grunt” (possibly made by the banded drum Larimus fasciatus Sciaenidae) which is known to spawn near the wave glider’s track in that time of year (August). A similar spectrogram was recorded from the unknown grunt in North Carolina and the related Larimus breviceps in the Atlantic Ocean off Brazil, leading to this hypothesized species identity. The wave glider with passive acoustic hydrophones has confirmed the offshore habitat use by fish species and revealed new sounds made by species not known to produce sounds in this region. Thus, new soniferous species have been found to use offshore habitats and contribute to the ocean soundscape.
More recently, a Liquid Robotics Wave Glider with a passive acoustic recorder for ocean soundscape studies was obtained under a grant from the National Science Foundation by Dr. Luczkovich and his collaborators Sprague (ECU Physics), Roger Rulifson (ECU Biology) and J. P Walsh (ECU Geological Sciences, now at University of Rhode Island) (Luczkovich et al., 2019). A study using this mobile wave-powered instrument (Luczkovich & Sprague, 2022) was published in Frontiers in Marine Science, in which ocean soundscapes and calls of sound-producing species were identified and mapped along a path followed by the wave glider in the Atlantic Ocean off North Carolina. This is an innovative use of a wave-powered and silent glider to travel along the coast and record the changing soundscapes produced by fishes, marine mammals, and invertebrates through space and time; normally most hydrophone surveys are done at a fixed location, so only temporal changes can be studied. One of the key findings was that there were many known species (red drum, Atlantic croaker, black drum, striped cusk-eels, and oyster toadfish) using open sand, natural reefs, and artificial reefs offshore, some of which also use estuarine habitats for spawning. In addition, several unknown sounds were recorded including possible sounds from sea robins and groupers, the “unknown buzz” hypothesized to be made by Atlantic midshipmen fish, Porichthyes plectrodon in a study from the Atlantic Ocean off Florida (Iafrate et al., 2023), and the “unknown grunt” (possibly made by the banded drum Larimus fasciatus Sciaenidae) which is known to spawn near the wave glider’s track in that time of year (August). A similar spectrogram was recorded from the unknown grunt in North Carolina and the related Larimus breviceps in the Atlantic Ocean off Brazil, leading to this hypothesized species identity. The wave glider with passive acoustic hydrophones has confirmed the offshore habitat use by fish species and revealed new sounds made by species not known to produce sounds in this region. Thus, new soniferous species have been found to use offshore habitats and contribute to the ocean soundscape.
Food Web Network Models
In food web network modeling, a matrix of food web interactions (who eats whom) is used to describe the flow of energy, carbon, or other materials through a series of species or compartments in an ecosystem. Flow rates are based on dietary data, production rate, consumption rate, and respiration rate estimates. These network models, when applied to marine food webs, offer quantitative perspectives of the entire ecosystem. Luczkovich has been working in collaboration with biologists, sociologists, anthropologists, and mathematical modelers (Dan Baird of Stellenbosch University in South Africa, Steve Borgatti at the University of Kentucky, Robert Christian of ECU Biology Department, Jeffrey C. Johnson formerly at ECU and now at the University of Florida, and Martin Everett of the University of Westminster in England, Lisa Clough formerly in ECU Biology and now at the National Science Foundation, David Griffith of ECU Anthropology/Department of Coastal Sciences, and Brian Cheuvront, NC Division of Marine Fisheries) to describe both food web interactions in marine ecosystems and interactions in human social systems (Luczkovich et al., 2021a). These models can be used to study the human social networks of the fishers and how they change when management regulations change,
The ecological network models to which the social network models are linked can be used to study the impact of fishery harvests under changing regulatory scenarios (proposed trawling and gill net bans), the effective trophic levels (between integer levels) of any group of organisms, the cycling of nutrients, the description of the extended diets of individual species (i.e., what prey they consume and depend upon indirectly), and prediction of their trophic impacts on other species. Trophic network models have been constructed for a seagrass ecosystem at St. Marks, Florida (Luczkovich et al. 2003), a coral reef ecosystem at Calabash Caye, Belize (Deehr et al. 2008), and an estuarine ecosystem inside and outside of closed trawling areas in Core Sound (Deehr et al., 2014). Graduate and undergraduate students and their thesis and dissertation projects are involved in data gathering to parameterize these models (Deehr, 2012; Deehr et al., 2007; Luczkovich et al., 2018, 2021). Finally, the trophic role (or niche) of any species can now be measured and their position in the food web visualized using modeling software, allowing one to view and explore the complex interactions of such food webs (Christian et al., 2005; Luczkovich et al., 2002, 2003). These network modeling approaches can now be applied to characterize food webs at various time scales and in diverse ecosystems. Luczkovich and colleagues have constructed these ecosystem network models to represent a temporal sequence of trophic network development using continuous-time Markov chains (Johnson et al., 2009). Luczkovich and his collaborators have received much attention for their work in this area (McMahon et al., 2001), having been invited to present their models at the Santa Fe Institute, New Mexico, the Russian Academy of Sciences in Academgorodok, Novosibirsk, Siberia, Russia, at the Central European University in Budapest Hungary, and at the Institute for Advanced Study, Collegium Budapest. One of these papers (Luczkovich et al. 2003) was awarded the 2006 Helms Award from the Sigma Xi Research Society at ECU. More recently, the impacts of shrimp trawling and gill netting on the whole ecosystem of Core Sound, NC, and its important fisheries, have been examined with network models (Luczkovich et al., 2018, 2021b). Studies underway now and a dissertation recently completed (Raab, 2020) and funded by Puerto Rico Sea Grant (and a pending proposal to NOAA) are applying this network modeling approach to model bioaccumulation of a biotoxin produced by dinoflagellates in the genus Gambierdiscus and the human health issue of ciguatera fish poisoning in tropical reef fisheries (Raab et al., 2021). In the future, human interactions and human social systems can be included as part of these food web network models, and we hope to be able to predict the impact of humans on ecosystems.
The ecological network models to which the social network models are linked can be used to study the impact of fishery harvests under changing regulatory scenarios (proposed trawling and gill net bans), the effective trophic levels (between integer levels) of any group of organisms, the cycling of nutrients, the description of the extended diets of individual species (i.e., what prey they consume and depend upon indirectly), and prediction of their trophic impacts on other species. Trophic network models have been constructed for a seagrass ecosystem at St. Marks, Florida (Luczkovich et al. 2003), a coral reef ecosystem at Calabash Caye, Belize (Deehr et al. 2008), and an estuarine ecosystem inside and outside of closed trawling areas in Core Sound (Deehr et al., 2014). Graduate and undergraduate students and their thesis and dissertation projects are involved in data gathering to parameterize these models (Deehr, 2012; Deehr et al., 2007; Luczkovich et al., 2018, 2021). Finally, the trophic role (or niche) of any species can now be measured and their position in the food web visualized using modeling software, allowing one to view and explore the complex interactions of such food webs (Christian et al., 2005; Luczkovich et al., 2002, 2003). These network modeling approaches can now be applied to characterize food webs at various time scales and in diverse ecosystems. Luczkovich and colleagues have constructed these ecosystem network models to represent a temporal sequence of trophic network development using continuous-time Markov chains (Johnson et al., 2009). Luczkovich and his collaborators have received much attention for their work in this area (McMahon et al., 2001), having been invited to present their models at the Santa Fe Institute, New Mexico, the Russian Academy of Sciences in Academgorodok, Novosibirsk, Siberia, Russia, at the Central European University in Budapest Hungary, and at the Institute for Advanced Study, Collegium Budapest. One of these papers (Luczkovich et al. 2003) was awarded the 2006 Helms Award from the Sigma Xi Research Society at ECU. More recently, the impacts of shrimp trawling and gill netting on the whole ecosystem of Core Sound, NC, and its important fisheries, have been examined with network models (Luczkovich et al., 2018, 2021b). Studies underway now and a dissertation recently completed (Raab, 2020) and funded by Puerto Rico Sea Grant (and a pending proposal to NOAA) are applying this network modeling approach to model bioaccumulation of a biotoxin produced by dinoflagellates in the genus Gambierdiscus and the human health issue of ciguatera fish poisoning in tropical reef fisheries (Raab et al., 2021). In the future, human interactions and human social systems can be included as part of these food web network models, and we hope to be able to predict the impact of humans on ecosystems.
References
Christian, R. R., Baird, D., Luczkovich, J., Johnson, J. C., Scharler, U. M., & Ulanowicz, R. E. (2005). Role of network analysis in comparative ecosystem ecology of estuaries. Aquatic Food Webs. Oxford University Press, Oxford, 25–40.
Deehr, R. A. (2012). Measuring the ecosystem impacts of commercial shrimp trawling and other fishing gear in Core Sound, North Carolina, using ecological network analysis [East Carolina University]. In Dissertation for the Coastal Resources Management PhD Program, East Carolina University. http://hdl.handle.net/10342/3994
Deehr, R. a, Barry, D. B., Chagaris, D. D., & Luczkovich, J. J. (2007). Using SCUBA and Snorkeling Methods to Obtain Model Parameters for an Ecopath Network Model for Calabash Caye, Belize, Central America. Proceedings of the American Academy of Underwater Sciences 26th Symposium, 51–67.
Deehr, R. a., Luczkovich, J. J., Hart, K. J., Clough, L. M., Johnson, B. J., & Johnson, J. C. (2014). Using stable isotope analysis to validate effective trophic levels from Ecopath models of areas closed and open to shrimp trawling in Core Sound, NC, USA. Ecological Modelling, 282, 1–17. https://doi.org/10.1016/j.ecolmodel.2014.03.005
Iafrate, J., Reyier, E., Ahr, B., Carroll, A., Rice, A. N., Dossot, G., Watwood, S. L., & Murie, D. (2023). Evidence of Atlantic midshipman ( Porichthys plectrodon) vocalizations from an unmanned surface vehicle in the U.S. South Atlantic . The Journal of the Acoustical Society of America, 154(5), 2928–2936. https://doi.org/10.1121/10.0022328
Johnson, J. C., Luczkovich, J. J., Borgatti, S. P., & Snijders, T. A. B. (2009). Using social network analysis tools in ecology: Markov process transition models applied to the seasonal trophic network dynamics of the Chesapeake Bay. Ecological Modelling, 220(22), 3133–3140.
Luczkovich, J. J., Borgatti, S. P., Johnson, J. C., & Everett, M. G. (2003). Defining and measuring trophic role similarity in food webs using regular equivalence. Journal of Theoretical Biology, 220, 303–321.
Luczkovich, J. J., Daniel III, H. J., Hutchinson, M., Jenkins, T., Johnson, S. E., Pullinger, R. C., & Sprague, M. W. (2000). Sounds of sex and death in the sea: bottlenose dolphin whistles suppress mating choruses of silver perch. Bioacoustics, 10, 323–334.
Luczkovich, J. J., Deehr, R. A., Hart, K. J., Clough, L. M., & Johnson, J. C. (2018). Cascading Effects of Shrimp Trawling: Increased Benthic Biomass and Increase in Net Primary Production. BioRxiv, 298323. https://doi.org/10.1101/298323
Luczkovich, J. J., Johnson, J. C., Deehr, R. A., Hart, K. J., Clough, L., & Griffith, D. C. (2021a). Linking Fishing Behavior and Ecosystem Dynamics Using Social and Ecological Network Models. Frontiers in Ecology and Evolution, 9. https://doi.org/10.3389/fevo.2021.662412
Luczkovich, J. J., Johnson, J. C., Deehr, R. A., Hart, K. J., Clough, L., & Griffith, D. C. (2021b). Linking Fishing Behavior and Ecosystem Dynamics Using Social and Ecological Network Models . In Frontiers in Ecology and Evolution (Vol. 9, p. 359). https://www.frontiersin.org/article/10.3389/fevo.2021.662412
Luczkovich, J. J., Pullinger, R. C., Johnson, S. E., & Sprague, M. W. (2008). Identifying sciaenid critical spawning habitats by the use of passive acoustics. Transactions of the American Fisheries Society, 137(2), 576–605.
Luczkovich, J. J., Rulifson, R. A., & Sprague, M. W. (2019). Listening to Ocean Life: Monitoring Fish, Marine Mammal Sounds with Wave Glider. Sea Technology, May 2019, 16--20.
Luczkovich, J. J., & Sprague, M. W. (2022). Soundscape Maps of Soniferous Fishes Observed From a Mobile Glider. Frontiers in Marine Science, 9(779540), 1–25. https://doi.org/10.3389/fmars.2022.779540
Luczkovich, J. J., & Sprague, M. W. (2023). Analyzing Long-Term Changes in Soundscapes Using Power Spectral Band Sums. In A. N. Popper, J. Sisneros, A. D. Hawkins, & F. Thomsen (Eds.), The Effects of Noise on Aquatic Life: Principles and Practical Considerations (pp. 1–22). Springer International Publishing. https://doi.org/10.1007/978-3-031-10417-6_95-1
Luczkovich, J. J., Sprague, M. W., Johnson, S. E., & Pullinger, R. C. (1999). Delimiting spawning areas of weakfish Cynoscion regalis (Family Sciaenidae) in Pamlico Sound, North Carolina Using Passive Hydroacoustic Surveys. Bioacoustics, 10(2–3), 143–160. https://doi.org/10.1080/09524622.1999.9753427
Luczkovich, J. J., Sprague, M. W., & Paerl, H. W. (2024). Bottom water hypoxia suppresses fish chorusing in estuaries. The Journal of the Acoustical Society of America, 155(3), 2014–2024. https://doi.org/10.1121/10.0025289
Luczkovich, J. J., Ward, G. P., Johnson, J. C., Christian, R. R., Baird, D., Neckles, H., & Rizzo, W. M. (2002). Determining the trophic guilds of fishes and macroinvertebrates in a seagrass food web. Estuaries, 25(6), 1143–1163.
McMahon, S. M., Miller, K. H., & Drake, J. (2001). Social science and ecology: Networking tips for social scientists and ecologists. Science, 293(5535), 1604–1605. https://doi.org/10.1126/science.1062026
Raab, H., Luczkovich, J., Pozo, M. Del, Griffith, D., Grace-McCaskey, C., & Litaker, W. (2021). Confirmation of fishers’ local ecological knowledge of ciguatoxic fish species and ciguatera-prone hotspot areas in Puerto Rico using harmful benthic algae surveys and fish toxicity testing. BioRxiv, 2021.10.10.463731. https://doi.org/10.1101/2021.10.10.463731
Raab, H. R. (2020). Fishers ’ Perceptions of Ciguatoxin Fish Poisoning and Modeling Biomagnification of Ciguatoxin in the Trophic Dynamics of Caribbean Coral Reef Ecosystems by [Ph.D. Disseration]. East Carolina University.
Sprague, M. W., & Luczkovich, J. J. (2001). Do striped cusk-eels Ophidion marginatum (Ophidiidae) produce the “chatter” sound attributed to weakfish Cynoscion regalis (Sciaenidae)? Copeia, 3. https://doi.org/10.1643/0045-8511(2001)001[0854:DSCEOM]2.0.CO;2
Sprague, M. W., & Luczkovich, J. J. (2004). Measurement of an individual silver perch Bairdiella chrysoura sound pressure level in a field recording. The Journal of the Acoustical Society of America, 116(5), 3186–3191.
Deehr, R. A. (2012). Measuring the ecosystem impacts of commercial shrimp trawling and other fishing gear in Core Sound, North Carolina, using ecological network analysis [East Carolina University]. In Dissertation for the Coastal Resources Management PhD Program, East Carolina University. http://hdl.handle.net/10342/3994
Deehr, R. a, Barry, D. B., Chagaris, D. D., & Luczkovich, J. J. (2007). Using SCUBA and Snorkeling Methods to Obtain Model Parameters for an Ecopath Network Model for Calabash Caye, Belize, Central America. Proceedings of the American Academy of Underwater Sciences 26th Symposium, 51–67.
Deehr, R. a., Luczkovich, J. J., Hart, K. J., Clough, L. M., Johnson, B. J., & Johnson, J. C. (2014). Using stable isotope analysis to validate effective trophic levels from Ecopath models of areas closed and open to shrimp trawling in Core Sound, NC, USA. Ecological Modelling, 282, 1–17. https://doi.org/10.1016/j.ecolmodel.2014.03.005
Iafrate, J., Reyier, E., Ahr, B., Carroll, A., Rice, A. N., Dossot, G., Watwood, S. L., & Murie, D. (2023). Evidence of Atlantic midshipman ( Porichthys plectrodon) vocalizations from an unmanned surface vehicle in the U.S. South Atlantic . The Journal of the Acoustical Society of America, 154(5), 2928–2936. https://doi.org/10.1121/10.0022328
Johnson, J. C., Luczkovich, J. J., Borgatti, S. P., & Snijders, T. A. B. (2009). Using social network analysis tools in ecology: Markov process transition models applied to the seasonal trophic network dynamics of the Chesapeake Bay. Ecological Modelling, 220(22), 3133–3140.
Luczkovich, J. J., Borgatti, S. P., Johnson, J. C., & Everett, M. G. (2003). Defining and measuring trophic role similarity in food webs using regular equivalence. Journal of Theoretical Biology, 220, 303–321.
Luczkovich, J. J., Daniel III, H. J., Hutchinson, M., Jenkins, T., Johnson, S. E., Pullinger, R. C., & Sprague, M. W. (2000). Sounds of sex and death in the sea: bottlenose dolphin whistles suppress mating choruses of silver perch. Bioacoustics, 10, 323–334.
Luczkovich, J. J., Deehr, R. A., Hart, K. J., Clough, L. M., & Johnson, J. C. (2018). Cascading Effects of Shrimp Trawling: Increased Benthic Biomass and Increase in Net Primary Production. BioRxiv, 298323. https://doi.org/10.1101/298323
Luczkovich, J. J., Johnson, J. C., Deehr, R. A., Hart, K. J., Clough, L., & Griffith, D. C. (2021a). Linking Fishing Behavior and Ecosystem Dynamics Using Social and Ecological Network Models. Frontiers in Ecology and Evolution, 9. https://doi.org/10.3389/fevo.2021.662412
Luczkovich, J. J., Johnson, J. C., Deehr, R. A., Hart, K. J., Clough, L., & Griffith, D. C. (2021b). Linking Fishing Behavior and Ecosystem Dynamics Using Social and Ecological Network Models . In Frontiers in Ecology and Evolution (Vol. 9, p. 359). https://www.frontiersin.org/article/10.3389/fevo.2021.662412
Luczkovich, J. J., Pullinger, R. C., Johnson, S. E., & Sprague, M. W. (2008). Identifying sciaenid critical spawning habitats by the use of passive acoustics. Transactions of the American Fisheries Society, 137(2), 576–605.
Luczkovich, J. J., Rulifson, R. A., & Sprague, M. W. (2019). Listening to Ocean Life: Monitoring Fish, Marine Mammal Sounds with Wave Glider. Sea Technology, May 2019, 16--20.
Luczkovich, J. J., & Sprague, M. W. (2022). Soundscape Maps of Soniferous Fishes Observed From a Mobile Glider. Frontiers in Marine Science, 9(779540), 1–25. https://doi.org/10.3389/fmars.2022.779540
Luczkovich, J. J., & Sprague, M. W. (2023). Analyzing Long-Term Changes in Soundscapes Using Power Spectral Band Sums. In A. N. Popper, J. Sisneros, A. D. Hawkins, & F. Thomsen (Eds.), The Effects of Noise on Aquatic Life: Principles and Practical Considerations (pp. 1–22). Springer International Publishing. https://doi.org/10.1007/978-3-031-10417-6_95-1
Luczkovich, J. J., Sprague, M. W., Johnson, S. E., & Pullinger, R. C. (1999). Delimiting spawning areas of weakfish Cynoscion regalis (Family Sciaenidae) in Pamlico Sound, North Carolina Using Passive Hydroacoustic Surveys. Bioacoustics, 10(2–3), 143–160. https://doi.org/10.1080/09524622.1999.9753427
Luczkovich, J. J., Sprague, M. W., & Paerl, H. W. (2024). Bottom water hypoxia suppresses fish chorusing in estuaries. The Journal of the Acoustical Society of America, 155(3), 2014–2024. https://doi.org/10.1121/10.0025289
Luczkovich, J. J., Ward, G. P., Johnson, J. C., Christian, R. R., Baird, D., Neckles, H., & Rizzo, W. M. (2002). Determining the trophic guilds of fishes and macroinvertebrates in a seagrass food web. Estuaries, 25(6), 1143–1163.
McMahon, S. M., Miller, K. H., & Drake, J. (2001). Social science and ecology: Networking tips for social scientists and ecologists. Science, 293(5535), 1604–1605. https://doi.org/10.1126/science.1062026
Raab, H., Luczkovich, J., Pozo, M. Del, Griffith, D., Grace-McCaskey, C., & Litaker, W. (2021). Confirmation of fishers’ local ecological knowledge of ciguatoxic fish species and ciguatera-prone hotspot areas in Puerto Rico using harmful benthic algae surveys and fish toxicity testing. BioRxiv, 2021.10.10.463731. https://doi.org/10.1101/2021.10.10.463731
Raab, H. R. (2020). Fishers ’ Perceptions of Ciguatoxin Fish Poisoning and Modeling Biomagnification of Ciguatoxin in the Trophic Dynamics of Caribbean Coral Reef Ecosystems by [Ph.D. Disseration]. East Carolina University.
Sprague, M. W., & Luczkovich, J. J. (2001). Do striped cusk-eels Ophidion marginatum (Ophidiidae) produce the “chatter” sound attributed to weakfish Cynoscion regalis (Sciaenidae)? Copeia, 3. https://doi.org/10.1643/0045-8511(2001)001[0854:DSCEOM]2.0.CO;2
Sprague, M. W., & Luczkovich, J. J. (2004). Measurement of an individual silver perch Bairdiella chrysoura sound pressure level in a field recording. The Journal of the Acoustical Society of America, 116(5), 3186–3191.