Tropical Storm Debby: Soundscape and fish sound production in Tampa Bay and the Gulf of Mexico

Anjali D Boyd; Shannon Gowans; David A Mann; Peter Simard

doi:10.1371/journal.pone.0254614

. 2021 Jul 13;16(7):e0254614. doi: 10.1371/journal.pone.0254614

Tropical Storm Debby: Soundscape and fish sound production in Tampa Bay and the Gulf of Mexico

Anjali D Boyd ^1,^¤,^*,^#, Shannon Gowans ^1,^2,^‡, David A Mann ^3,^‡, Peter Simard ^4,^#

Editor: Dennis M Higgs⁵

PMCID: PMC8277075 PMID: 34255792

Abstract

Tropical cyclones have large effects on marine ecosystems through direct (e.g., storm surge) and indirect (e.g., nutrient runoff) effects. Given their intensity, understanding their effects on the marine environment is an important goal for conservation and resource management. In June 2012, Tropical Storm Debby impacted coastal Florida including Tampa Bay. Acoustic recorders were deployed prior to the storm at a shallow water location inside Tampa Bay and a deeper water location in the Gulf of Mexico. Ambient noise levels were significantly higher during the storm, and the highest increases were observed at lower frequencies (≤ 500 Hz). Although the storm did not directly hit the area, mean ambient noise levels were as high as 13.5 dB RMS above levels in non-storm conditions. At both the shallow water and the deep water station, the rate of fish calls showed a variety of patterns over the study period, with some rates decreasing during the storm and others showing no apparent reaction. The rates of fish calls were frequently correlated with storm conditions (storm surge, water temperature), but also with lunar cycle. Reactions to the storm were generally stronger in the inshore station, although fish sounds increased quickly after the storm’s passage. Although this was not a major tropical cyclone nor a direct hit on the area, the storm did appear to elicit a behavioral response from the fish community, and ambient noise levels likely limited the abilities of marine species to use sound for activities such as communication. Given the increases in intensity and rainfall predicted for tropical cyclones due to climate change, further studies of the ecological effects of tropical cyclones are needed.

Introduction

Tropical cyclones (e.g., tropical storms, hurricanes) can have ruinous effects on coastal ecosystems, including flooding and enhanced erosion, as well as detrimental effects on benthic and pelagic marine communities. The biological effects of tropical cyclones have been documented in a variety of taxa and habitats, including benthic communities (especially coral reefs [1] and fish [2]). However, the effects of tropical cyclones on marine communities are not well understood and appear to be dependent on a variety of factors including the intensity of the storm and the specifics of the habitat (e.g., coral reef habitat vs. seagrass beds), the timescale considered (e.g., whether observations were conducted days vs. months after the storm) and the methodology (e.g., visual surveys vs. acoustic monitoring).

Many studies have examined the effects of tropical cyclones on fish using traditional survey methods such as net sampling or visual counts. While traditional visual based survey techniques have advantages, they are difficult to implement immediately before, during or after tropical cyclones. Therefore, passive methodologies–where data are collected remotely–can be a useful tool. For example, acoustic telemetry tags have been used to document the distribution changes in red snapper (Lutjanus campechanus) and several species of shark in response to tropical storms [3–5]. Passive acoustic monitoring (PAM) devices can operate for long periods of time and in environmental conditions that make many other techniques difficult or impossible, such as during major storms [6]. For example, PAM technology was used to monitor fish sounds in Charlotte Harbor, Florida during Hurricane Charley, a category 4 hurricane [7]. The authors found that the hurricane did not inhibit fish sound production, despite the fact that the recorder was located in only 3.5 m of water.

An additional advantage of PAM is the ability to conduct soundscape analysis. Soundscape analysis is the characterization and quantification of natural and anthropogenic sounds in a given environment [8]. The study of soundscapes can involve both spatial and temporal analysis of sounds to assess natural non-biological conditions (the “geophony”: e.g., wind-driven waves, earthquakes), biological conditions (the “biophony”: e.g., species-specific sounds, biodiversity), and anthropogenic noise (the “anthrophony”: e.g., boat noise, marine construction; [8]). Furthermore, soundscapes can provide insight into the structure of biological communities, and how natural and anthropogenic disturbances effect community structure [8, 9].

In 2012, Tropical Storm Debby formed in the Gulf of Mexico and impacted Tampa Bay, Florida, from June 24^th -27^th [10]. In the Tampa Bay area, the storm was characterized by a storm surge, inundating rainfall, and sustained winds of over 54 km h^-1. At the time of this storm, two bottom-mounted autonomous acoustic recorders were operating in the Tampa Bay area. As most previous studies investigating biological responses to tropical cyclones suffer from undersampling due to the inability to collect data at high-frequency intervals, especially during and immediately after the storm, PAM is an ideal methodology to examine the biological responses to and the recovery after these weather systems. As the frequency and severity of these storms is likely to increase with global climate change [11–13], our understanding of biological responses to these storms is increasingly important. Using the data from these acoustic recorders, the aims of this study were (a) to investigate the underwater soundscape associated with this tropical storm, and (b) to investigate changes in fish sound production over the duration of the storm. Based on the results from previous studies, we hypothesized that Tropical Storm Debby would cause an increase in ambient noise, and given the variability in the literature, we hypothesized a variety of species-specific patterns in fish vocalization rates.

Materials and methods

Sampling sites

Acoustic recorders were deployed throughout the duration of Tropical Storm Debby at two sites: (1) station Boca 3, an inshore, shallow-water (approximately 3 m) sparse seagrass bed in Boca Ciega, Tampa Bay, and (2) station Gulf 1, an offshore, deeper water (approximately 9 m) sandy bottom site in the open Gulf of Mexico (approximately 10 km from shore, Fig 1). Both of these sites were approximately 175 km south of the storm track, although well within the ≥34 knot wind swath of the storm (Fig 1). Acoustic recorders were bottom-mounted, shackled to 1.2 m augers screwed into the sediment. These deployments were part of a longer-term study involving acoustic recorder deployments in a variety of locations in Tampa Bay and the Gulf of Mexico to monitor bottlenose dolphins (Tursiops truncatus) under National Marine Fisheries Service General Authorization for Scientific Research 1077–19540 & 1077–1794 and were not specifically deployed for the tropical storm. However, due both to the deployment areas and the species considered in this study (i.e., passively monitoring non-protected species in non-protected areas), no permits were required to deploy the recorders at these sites or to carry out our analysis.

Fig 1 — Top panel: track of the center of Hurricane Debby from June 24 (00:00) to June 27 (00:00) shown by red line (date-time coding of positions YYYYMMDDHH). Yellow polygon shows the NOAA working best track wind swath between June 23 and June 26 (≥34 knots). Red polygon shows the NOAA working best track wind swath between June 24 and June 25 (≥50 knots). Bottom panel: study area, showing the locations of the acoustic recorder stations, Boca 3 (inshore, ≈3 m depth) and Gulf 1 (offshore, ≈9 m depth), station Boca 2 (temperature data only, ≈3 m depth), and NOAA weather station St. Petersburg. Landform and bathymetry data from the Florida Fish and Wildlife Conservation Commission [14]; storm track and wind swath data from the NOAA National Hurricane Center / National Weather Service [15].

The acoustic recorders were Digital SpectroGram [DSG] recorders (Loggerhead Instruments, Sarasota, FL, USA) with HTI-96-MIN hydrophones (-170 dB/V, High-Tech Inc., Long Beach, MS, USA). Recorders operated on a duty cycle of 10 seconds per 10 minutes, at a 50 kHz sample rate and 16-bit resolution, and data were stored on 32 GB SD cards.

In-situ water temperature data were collected using Hobo UA-002-64 temperature loggers (ONSET Corporation, Bourne, MA, USA). While a temperature logger was operational at the offshore station Gulf 1, one was not operational at the inshore station Boca 3. However, the nearby inshore station Boca 2 (approximately 4 km to the north, Fig 1) did have an operational temperature logger, although it did not have an operational DSG recorder during the time of the tropical storm. Therefore, temperature data from station Boca 2 was used in this study as a proxy for the temperature conditions at the acoustic recorder Boca 3. Temperature loggers recorded every 10 minutes and were located approximately 0.5 m above the sea floor.

Additional environmental data

In addition to the in-situ water temperature data collected in this study, wind speed, water level, and barometric pressure were obtained from the US National Oceanic and Atmospheric Administration [16–18]. These data were recorded at the NOAA St. Petersburg Station 8726520, approximately 15 km to the north-northeast from Boca 3 (inshore) and approximately 20 km to the east-northeast from Gulf 1 (offshore). Moon phase data for the study period were obtained from the National Aeronautics and Space Administration [19] as a number of fish species have shown lunar periodicity in their call rates [20, 21].

Analysis

In order to quantify the effects of the tropical storm during its passage through the study area, three time periods were defined: before, during and after the storm. Dates were selected based on the water level anomaly (storm surge), as this environmental variable indicated when tropical storm Debby had its greatest impact on our field sites. Water level anomaly was calculated by subtracting the observed water levels from the predicted water levels [16, 17]. Five days during the storm’s passage over the study area were characterized by having a water level anomaly above 0.5 m (June 22–26), while the five days before and after this period had water level anomalies below 0.5 m (June 17–21 and June 27-July 1, respectively).

Acoustic recordings from June 17th—July 1st were analyzed via (a) soundscape analysis using third-octave bands [22], and (b) spectrogram analysis of fish sounds [20]. Third-octave soundscape analysis was conducted in MATLAB 2009b (Mathworks, Natick MA, USA) and was used to characterize band-specific changes in ambient noise levels over the course of the storm. Individual sound files were band-pass filtered at standardized third-octave center frequencies established by the United Nations Economic Commission for Europe [23]. The mean root-mean-square (RMS) sound pressure level was calculated for each 24-hour period in each third-octave band, using the sensitivity of the recorder (0.1 V full-scale) and the hydrophone (-170 dBV re 1 μPa). Fish sounds were identified by manually inspecting 1024-point spectrograms in Raven Pro 1.5 (Cornell Lab of Ornithology, Ithaca, NY). The number of fish sounds were counted in each 10-second file, identified to species whenever possible. Published species-specific vocalization patterns from FishBase [24] and DOSITS’ Discovery of Sound in the Sea Audio Gallery [25] were used to identify fish species vocalization patterns.

Statistical analysis was conducted in RStudio (Version 1.3.1073, PBC). Repeated measures ANOVA tests with Tukey post-hoc comparisons were used to determine if differences in RMS sound pressure levels in individual files existed in each third-octave band before, during and after Tropical Storm Debby at both stations. Comparisons of the number of fish calls detected (total calls and species-specific calls) per individual file at each station between the three time periods (before, during and after the passage of Tropical Storm Debby) were also tested using repeated measures ANOVA tests with Tukey post-hoc comparisons. Spearman’s correlations were calculated between the total number of fish calls and species-specific calls for each 24-hour period of the study period at each station and the mean bottom temperature for each 24-hour period (collected at station Boca 2 for the inshore recorder), the mean sea level anomaly for each 24-hour period (i.e., storm surge, collected at the NOAA St. Petersburg weather station, [16, 17]) and the daily lunar cycle [19]. In addition, Spearman’s correlations were calculated between the total number of fish calls and species-specific calls for each 24-hour period and the mean RMS noise level at the 500 Hz third-octave band for each 24-hour period. This frequency band was chosen as it falls within the frequency band of most fish sound production (50–1000 Hz: e.g., [20, 26]), allowing us to better determine both if ambient noise levels were affecting fish sound production, and if acoustic masking by ambient noise was affecting our detection rates.

Results

Tropical Storm Debby conditions

At the NOAA St. Petersburg weather station, Tropical Storm Debby was characterized by a storm surge as high as 1.17 m above predicted levels ([16, 17] Fig 2A), a decrease in barometric pressure to 1002.2 mb ([18] Fig 2B), and wind speeds up to 15.0 m sec^-1 ([19] Fig 2C). During this time period, the moon was waxing and increased from approximately 5% visible at the beginning of the study period to 93% visible at the end of the study period ([19] Fig 2D). At both stations Boca 2 (inshore) and Gulf 1 (offshore), water temperature generally decreased as the storm approached the study area (Fig 2E). At station Boca 2 the water temperatures ranged between 26.1°C and 30.8°C (range = 4.7°C). Water temperatures at this station had noticeable (approximately 2°C) diel fluctuations before and after the storm’s passage; however, these fluctuations were mostly absent during the storm. Water temperature increased rapidly after the passage of Tropical Storm Debby (increasing by approximately 4°C in five days). At station Gulf 1, the temperature range was less (27.0°C to 29.2°C, range = 2.2°C) and little diel temperature fluctuation was observed. The temperature increase after the passage of the storm at station Gulf 1 was minimal (Fig 2E).

Fig 2 — Environmental conditions before, during and after the passage of Tropical Storm Debby (bars show the first day of the “during storm” period, and “after storm” period). (a) Observed and predicted water level (m), (b) atmospheric pressure (mbar), and (c) wind speed (m/sec) from the NOAA St. Petersburg station (data from [16–18]). (d) Percent of moon visible (data from [19]). (e) Temperature data collected at the acoustic recorder stations Boca 2 (inshore) and Gulf 1 (offshore).

Soundscape analysis

At station Boca 3 (inshore), all third-octave bands with center frequencies up to and including 500 Hz noticeably increased in amplitude during the storm (Figs 3 and 4). Mean RMS sound pressure levels during the storm were as high as 12.3 dB above mean levels before and after the storm (63 Hz center frequency). The highest mean value was 103.9 dB re 1 μPa (500 Hz center frequency during the storm), and the highest single measured RMS sound pressure level was 126.4 dB re 1 μPa (500 Hz center frequency, June 24 18:10 hrs). In the 5000 Hz and 20000 Hz bands, the maximum mean values did not occur during the storm, but instead occurred after the storm (Figs 3 and 4). These bands also showed considerably less variability in their mean sound pressure levels than was observed in lower frequency bands. Repeated measures ANOVA indicated that significant differences occurred in the RMS sound pressure levels before, during and after the passage of Tropical Storm Debby at station Boca 3 (Table 2). Post-hoc analysis indicated that sound pressure levels before and during the storm were significantly different in all bands except 5000 Hz, and that sound pressure levels during and after the storm were significantly different in all frequency bands except 20000 Hz. Sound pressure levels before and after the storm were also significantly different for all bands except 250 Hz (Table 1).

Fig 3 — Daily mean RMS sound pressure levels at station Boca 3 (inshore) for third-octave bands centered at 63 Hz, 125 Hz, 250 Hz, 500 Hz, 5000 Hz, and 20,000 Hz third-octave bands. Dark bars indicate the first day of the “during storm” period, and the first day of the “after storm” period. Error bars ± 1 SD. Note that the scale of the y-axes for the top four panels are not the same as the bottom two panels.

Fig 4 — Mean RMS sound pressure level at station Boca 3 (inshore) third-octave bands for before, during and after the passage of Tropical Storm Debby. Error bars ± 1 SD.

Table 2. Repeated measures ANOVA and post-hoc test for Gulf 1 sound pressure levels.

Repeated Measures ANOVA
Effect	DFn	DFd	F	p
Time Period	2	14644	1613.177	p<0.001^*
Frequency	5	14644	572.298	p<0.001^*
Post-hoc Test
Band (Hz)	Before storm–during storm		During storm–after storm	Before storm–after storm
63	p<0.001^*		p<0.001^*	p = 0.473
125	p<0.001^*		p<0.001^*	p<0.001^*
250	p<0.001^*		p<0.001^*	p<0.001^*
500	p<0.001^*		p<0.001^*	p<0.001^*
5000	p<0.068		p = 0.809	p<0.080
20000	p = 0.001^*		p<0.001^*	p<0.001^*

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Repeated measures ANOVA and Tukey post-hoc test results for mean RMS sound pressure levels (dB re 1 μPa) before, during and after Tropical Storm Debby at site Gulf 1.

*Indicates significant results (p < 0.05).

Table 1. Boca 3 repeated measures ANOVA and post-hoc test on sound pressure levels.

Repeated Measures ANOVA
Effect	DFn	DFd	F	p
Time Period	2	14644	501.483	p<0.001^*
Frequency	5	14644	609.135	p<0.001^*
Post-hoc Test
Band (Hz)	Before storm–during storm		During storm–after storm	Before storm–after storm
63	p<0.001^*		p<0.001^*	p<0.001^*
125	p<0.001^*		p<0.001^*	p<0.001^*
250	p<0.001^*		p<0.001^*	p = 0.004
500	p<0.001^*		p<0.001^*	p = 0.001^*
5000	p = 0.007		p<0.001^*	p = 0.001^*
20000	p<0.001^*		p = 0.211	p<0.001^*

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Repeated measures ANOVA and Tukey post-hoc test results for mean RMS sound pressure levels (dB re 1 μPa) before, during and after the Tropical Storm Debby at station Boca 3.

*Indicates significant results (p < 0.05).

At station Gulf 1 (offshore), all third-octave bands with center frequencies up to and including 500 Hz also noticeably increased in amplitude during the storm (Figs 5 and 6). Mean RMS sound pressure levels during the storm were as high as 13.5 dB above levels before and after the storm (125 Hz center frequency). The highest mean value was 113.7 dB re 1 μPa (63 Hz center frequency), and the highest measured RMS sound pressure level was 127.2 dB re 1 μPa (63 Hz center frequency, June 24, 15:20 hrs). While no clear trend was seen in the 5000 Hz band, RMS sound pressure levels appeared to decrease over the study period in the 20000 Hz band (Figs 5 and 6). Results from the repeated measures ANOVA tests indicated there were significant differences in RMS sound pressure levels before, during and after the passage of Tropical Storm Debby at the offshore station Gulf 1. Post-hoc analysis indicated that sound pressure levels for before and during the storm, and for during and after the storm were significantly different in all bands except 5000 Hz (Table 2). Significant differences in sound pressure levels were also found for before and after the storm for all bands except 63 Hz and 5000 Hz (Table 2).

Fig 5 — Daily mean RMS sound pressure levels at station Gulf 1 (offshore) for third-octave bands centered at 63 Hz, 125 Hz, 250 Hz, 500 Hz, 5000 Hz, and 20000 Hz third-octave bands. Dark bars indicate the first day of the “during storm” period, and the first day of the “after storm” period. Error bars ± 1 SD. Note that the scale of the y-axes for the top four panels are not the same as the bottom two panels.

Fig 6 — Mean RMS sound pressure level at station Gulf 1 (offshore) third-octave bands for before, during and after the passage of Tropical Storm Debby. Error bars ± 1 SD.

Fish calls

Six types of fish sounds were identified to species or family level: gulf toadfish (Opsanus beta) silver perch (Bairdiella chrysoura), sand seatrout (Cynoscion arenarius), spotted seatrout (Cynoscion nebulosus), red drum (Sciaenops ocellatus), and grunts (Haemulidae). Fish calls were overall approximately twice as abundant at station Boca 3 (inshore) than at station Gulf 1 (offshore, Table 3), and at times approximately five times more abundant at station Boca 3 than at station Gulf 1 (Figs 7A and 8A). All identified calls were found at both stations Boca 3 and Gulf 1; however, spotted seatrout and red drum were only occasionally heard (Table 3).

Table 3. List of fish species detected at Boca 3 and Gulf 1.

Species	Boca 3	Gulf 1
Gulf toadfish (Opsanus beta)	7150	1635
Silver perch (Bairdiella chrysoura)	3437	3821
Sand seatrout (Cynoscion arenarius)	23399	10710
Spotted seatrout (Cynoscion nebulosus)	5	6
Red drum (Sciaenops ocellatus)	1	16
Grunt (Haemulidae spp.)	906	152
Total	34898	16340

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List of species detected and the total number of calls at both sites during the duration of the study period.

Fig 7 — Number of fish calls per file per 24-hour period before, during and after the passage of Tropical Storm Debby at station Boca 3 (inshore); (a) total fish calls (all species), sand seatrout calls and gulf toadfish calls, (b) silver perch, unknown grunt, (c) spotted seatrout, red drum. Dark bars indicate the first day of the “during storm” period, and the first day of the “after storm” period.

Fig 8 — Mean number of fish calls detected per acoustic file before, during and after the passage of Tropical Storm Debby at station Boca 3 (inshore); (a) total fish calls (all species), sand seatrout calls and gulf toadfish calls, (b) silver perch, unknown grunt, (c) spotted seatrout, red drum. Bars beneath plots indicate significant differences in post-hoc tests (p < 0.05). Note in (c) that spotted seatrout calls were only observed before the storm, and a single red drum call was observed after the storm.

At station Boca 3 (inshore), total fish calls (all species) per 24-hour period decreased prior to the storm but increased again before the storm affected the study area, then decreased to their lowest values during the peak of the storm (June 24, Fig 7A). Total fish calls per 24-hour period then increased to their highest values after the storm (Fig 7A). Similar patterns were also observed for sand seatrout and silver perch (Fig 7A and 7B). Gulf toadfish and grunts also had a minimum in call detections during the peak of the storm; however, this decrease was not as dramatic and unusual as seen with other species or total fish calls (Fig 7A and 7B). The calls of spotted seatrout were only detected in low numbers for two days before the storm, while a single red drum call was detected after the storm (Fig 7C). Mean fish calls per acoustic file for total fish calls (all species) and sand seatrout decreased to their lowest value during the storm and increased to their highest value after the storm (Fig 8A). However, the mean number of gulf toadfish calls decreased over the study period (Fig 8A), and the mean number of silver perch and grunt calls increased over the study period (Fig 8B). Spotted seatrout and red drum had low mean detection rates reflecting the low number of calls detected (Fig 8C)

The repeated measures ANOVA indicated that the total number of fish calls (all species combined) detected per file before, during and after Tropical Storm Debby at station Boca 3 were significantly different (Table 4). Post-hoc tests also indicated that significant differences existed between during the storm and after the storm, and before the storm and after the storm, but not before and during the storm (Table 4, Fig 8).

Table 4. Repeated measures ANOVA and post-hoc test on total fish detections for stations Boca 3 and Gulf 1.

Repeated Measures ANOVA
Effect	DFn	DFd	F	p
Boca	2	2439	11.945	p<0.001^*
Gulf	2	2439	59.865	p<0.001^*
Post-hoc Tests
Station	Before storm–during storm		During storm–after storm	Before storm–after storm
Boca 3	p<0.069		p<0.001^*	p<0.001^*
Gulf 1	p<0.001^*		p<0.001^*	p<0.001^*

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Repeated measures ANOVA and Tukey post-hoc test results comparing total fish detections (all species) per file before, during and after Tropical Storm Debby.

*Indicates significant results (p < 0.05).

The repeated measures ANOVA indicated significant differences between species/family-specific fish calls per file for all groups except spotted seatrout and red drum (Table 5). Post-hoc tests indicated that for gulf toadfish, silver perch and sand seatrout, there were significant differences between all pairwise comparisons (before–during the storm, during–after the storm, and before–after the storm, Table 5, Fig 8). For grunt, significant differences were found between during and after the storm, and before and after the storm, but not between before and during the storm (Table 5, Fig 8).

Table 5. Repeated measures ANOVA and post-hoc test on species/family-specific fish detections for station Boca 3.

Repeated Measures ANOVA
Effect	DFn	DFd	F	p
Gulf Toadfish	2	2439	39.856	p<0.001^*
Silver Perch	2	2439	25.936	p<0.001^*
Spotted Seatrout	2	2439	1.781	p = 0.169
Sand Seatrout	2	2439	38.193	p<0.001^*
Grunt	2	2439	17.839	p<0.001^*
Red Drum	2	2439	0.711	p = 0.491
Post-hoc Tests
Species	Before storm–during storm		During storm–after storm	Before storm–after storm
Gulf Toadfish	p<0.001^*		p<0.001^*	p<0.001^*
Silver Perch	p<0.001^*		p<0.008^*	p<0.001^*
Spotted Seatrout	p = 0.112		p = 1.000	p = 0.086
Sand Seatrout	p = 0.012^*		p<0.001^*	p<0.001^*
Grunt	p = 0.155		p<0.001^*	p<0.001^*
Red Drum	p = 1.000		p = 0315	p = 0.316

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Repeated measures ANOVA and Tukey post-hoc test results comparing fish species detections per file before, during and after Tropical Storm Debby at station Boca 3.

*Indicates significant results (p < 0.05).

At station Gulf 1 (offshore), total fish calls (all species) per 24-hour period increased prior to the storm, decreased slightly during the arrival of the storm, then increased steadily through the storm’s passage and after the storm when it peaked and declined at the end of the study period (Fig 9A). Sand seatrout calls showed a similar pattern but without a decrease during the arrival of the storm (Fig 9A). Gulf toadfish calls per 24-hour period declined to their lowest levels during storm conditions and remained relatively low after the storm (Fig 9B). Silver perch calls were highly variable throughout the study period (Fig 9B). Grunts were also highly variable but were only found at low levels during the approach of the storm (i.e., the first half of the “during” period), and red drum and spotted seatrout calls were uncommon and only found during and after the storm, or only during the storm, respectively (Fig 9C).

Fig 9 — Number of fish calls per file per 24-hour period before, during and after the passage of Tropical Storm Debby at station Gulf 1 (offshore); (a) total fish calls (all species), sand seatrout calls (b) silver perch and gulf toadfish calls, (c) unknown grunt, spotted seatrout and red drum calls. Dark bars indicate the first day of the “during storm” period, and the first day of the “after storm” period.

At station Gulf 1, mean fish calls per acoustic file for total fish calls (all species), sand seatrout and silver perch all increased throughout the study period (Fig 10A). Gulf toadfish were found at their lowest mean value during the storm, and increased slightly after the storm (Fig 10B). Grunts also were found at their lowest mean values during the storm, but increased to their highest levels after the storm. Mean fish calls per file for red drum and spotted seatrout were low (Fig 10C).

Fig 10 — Mean number of fish calls detected per file per acoustic file before, during and after the passage of Tropical Storm Debby at station Gulf 1 (offshore); (a) total fish calls (all species) and sand seatrout calls (b) silver perch and gulf toadfish calls, (c) unknown grunt, red drum and spotted seatrout calls. Bars beneath plots indicate significant relationships in post-hoc tests (p < 0.05).

Results of the repeated measures ANOVA indicated that the number of total fish calls (all species) detected per file was significantly different before, during and after the storm at station Gulf 1 (Table 4). Post-hoc tests indicated significant differences in the number of total fish call detections between all time periods (before, during and after the storm; Table 4, Fig 10). Repeated measure ANOVAs indicated significant differences between the time periods for all species except spotted seatrout (Table 6). Post-hoc tests for species/family-specific differences found significant differences in the mean number of calls per file between all three time periods for sand seatrout (Table 6, Fig 10). For gulf toadfish, significant differences were found between before and during the storm, and between before and after the storm. Significant differences were found for silver perch between during and after the storm, and before and after the storm. For red drum, significant differences were found between before and during the storm, and between during and after the storm, while for grunt the only significant difference was for between during and after the storm (Table 6, Fig 10).

Table 6. Gulf 1 repeated measures ANOVA and post-hoc test on fish species detections.

Repeated Measures ANOVA
Effect	DFn	DFd	F	p
Gulf Toadfish	2	2439	207.043	p<0.001^*
Silver Perch	2	2439	18.348	p<0.001^*
Spotted Seatrout	2	2439	1.196	p = 0.303
Sand Seatrout	2	2439	116.511	p<0.001^*
Grunt	2	2439	3.836	p = 0.022^*
Red Drum	2	2439	3.036	p = 0.048^*
Post-hoc Tests
Species	Before storm–during storm		During storm–after storm	Before storm–after storm
Gulf Toadfish	p<0.001^*		p = 0.750	p<0.001^*
Silver Perch	p = 0.402		p<0.008^*	p<0.001^*
Spotted Seatrout	p = 0.1940		p = 0.160	p = 1.000
Sand Seatrout	p<0.001^*		p<0.001^*	p<0.001^*
Grunt	p = 0.291		p = 0.006^*	p = 0.114
Red Drum	p = 0.025^*		p = 0.041^*	p = 0.687

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Repeated measures ANOVA and Tukey post-hoc test results comparing fish species detections per file before, during and after Tropical Storm Debby at site Gulf.

*Indicates significant results (p < 0.05).

Correlations

In inshore waters, several statistically significant correlations were found between environmental variables (Table 7). A negative correlation was found between water level anomaly data from the NOAA St. Petersburg weather station and in situ water temperature collected at the inshore station Boca 2 (as water level increased, water temperature decreased). In addition, a positive correlation was found between RMS sound pressure level in the 500 Hz third-octave band from station Boca 3 and the lunar cycle (as the % of the moon visible increased, sound pressure level increased). Several statistically significant correlations between fish calls recorded at station Boca 3 and environmental variables were also found (Table 7). Negative correlations were observed between total fish calls (all species), sand seatrout calls and silver perch calls and NOAA water level anomaly data (as water level anomaly increased, fish calls decreased), while positive correlations were observed between total fish calls, sand seatrout calls and sliver perch calls and bottom temperature collected at the nearby station Boca 2 (as water temperature decreased, fish calls decreased). Total fish calls, sand seatrout calls and silver perch calls were positively correlated to the lunar cycle (fish calls increased as the % of the moon visible increased), while a negative relationship was found with gulf toadfish and spotted seatrout (fish calls decreased as the % of the moon visible increased). No fish calls were correlated with ambient noise (RMS sound pressure level in the 500 Hz third-octave band).

Table 7. Spearman’s rho correlations for station Boca 3.

	Water level anomaly	Temperature (station Boca 2)	Lunar cycle	SPL 500 Hz third-octave band (station Boca 3)
Total fish calls	-0.650, p = 0.009^*	0.707, p = 0.003^*	0.581, p = 0.023^*	-0.232, p = 0.405
Sand seatrout	-0.682, p = 0.005^*	0.846, p<0.001^*	0.574, p = 0.025^*	-0.346, p = 0.206
Gulf toadfish	-0.025, p = 0.930	-0.150, p = 0.594	-0.695, p = 0.004^*	-0.389, p = 0.152
Silver perch	-0.561, p = 0.030^*	0.561, p = 0.030^*	0.878, p<0.001^*	-0.107, p = 0.704
Unknown grunt	-0.146, p = 0.603	0.457, p = 0.087	0.390, p = 0.151	-0.300, p = 0.277
Spotted seatrout	-0.278, p = 0.316	0.139, p = 0.622	-0.517, p = 0.049^*	-0.290, p-0.295
Red drum	-0.371, p = 0.173	0.186, p = 0.508	0.248, p = 0.373	0.062, p = 0.827
SPL 500 Hz third-octave band (station Boca 3)	0.246, p = 0.361	-0.318, p = 0.248	0.270, p = 0.023^*	-
Lunar cycle	-0.379, p = 0.164	0.409, p = 0.130	-	-
Temperature (station Boca 2)	-0.750, p = 0.001^*	-	-	-

Open in a new tab

Spearman’s rho correlation results for fish calls per 24-hour time period at station Boca 3 (inshore) and environmental variables. SPL is RMS sound pressure level. All test results 2-tailed, n = 15.

*Indicates significant results (p < 0.05).

At the offshore station Gulf 1, bottom temperature was significantly and negatively correlated with both lunar cycle and the RMS sound pressure level in the 500 Hz third-octave band (as bottom temperature decreased, the % of the moon visible increased, and RMS sound pressure level increased, Table 8). The calls of grunts were negatively correlated with water level anomaly (as water level anomaly increased, fish calls decreased). Total fish calls and the calls of sand seatrout and red drum were negatively correlated with water temperature (as temperature decreased, fish calls increased), while gulf toadfish calls were positively correlated with temperature (as temperature decreased, fish calls decreased). There were positive correlations between total fish calls and sand seatrout calls and the lunar cycle (as the % of the moon visible increased, fish calls increased), however a negative correlation was found between gulf toadfish calls and the lunar cycle (as the % of the moon visible increased, fish calls decreased). Detections of gulf toadfish calls was negatively correlated with ambient noise (RMS sound pressure level in the 500 Hz third-octave band), while detections of red drum calls were positively correlated with ambient noise.

Table 8. Spearman’s rho correlations for station Gulf 1.

	Water level anomaly	Temperature (station Gulf 1)	Lunar cycle	SPL 500 Hz third-octave band (station Gulf 1)
Total fish calls	-0.429, p = 0.111	-0.518, p = 0.048^*	0.765, p = 0.001^*	0.225, p = 0.420
Sand seatrout	-0.368, p = 0.177	-0.593, p = 0.020^*	0.808, p<0.001^*	0.329, p = 0.232
Gulf toadfish	0.023, p = 0.934	0.885, p<0.001^*	-0.733, p = 0.002^*	-0.810, p<0.001^*
Silver perch	-0.018, p = 0.950	-0.171, p = 0.541	0.375, p = 0.168	0.054, p = 0.850
Unknown grunt	-0.630, p = 0.012^*	0.005, p = 0.985	0.252, p = 0.366	-0.320, p = 0.245
Spotted seatrout	0.433, p = 0.107	-0.247, p = 0.374	0.000, p = 1.000	0.309, p-0.262
Red drum	0.107, p = 0.704	-0.684, p = 0.005^*	0.225, p = 0.420	0.666, p = 0.007^*
SPL 500 Hz third-octave band (station Gulf 1)	0.389, p = 0.152	-0.857, p<0.001^*	0.450, p = 0.092	-
Lunar cycle	-0.379, p = 0.164	-0.692, p = 0.004^*	-	-
Temperature (station Gulf 1)	-0.007, p = 0.980	-	-	-

Open in a new tab

Spearman’s rho correlation results for fish calls per 24-hour at station Gulf 1 (offshore) and environmental variables. SPL is RMS sound pressure level. All test results 2-tailed, n = 15. Note that the test between lunar cycle and water level anomaly is the same test as in Table 7 as only one dataset for each of these variables was available.

*Indicates significant results (p < 0.05).

Discussion

While Tropical Storm Debby did not make landfall in the direct vicinity of Tampa Bay (landfall was approximately 175 km to the north), the storm was spatially large ([10]; Fig 1) and resulted in high amounts of rain, wind, and storm surge in the area [17, 18]. We detected decreases in water temperature and increases in ambient noise at both stations (Figs 2–6), and significant variations in the call rates of some species which were correlated with storm conditions.

Water temperature near the sea floor at the inshore station Boca 2 decreased and reached minimum temperatures on June 20 (just before the storm arrived) and on June 25 and 26 (during the storm); while bottom temperature at the offshore station Gulf 1 reached a minimum value on June 27, just after the passage of the storm. After the storm passed, water temperature increased rapidly at station Boca 2, however this trend was not observed at station Gulf 1. As station Boca 2 was located in shallower, more inshore water, it is not unexpected that bottom temperatures returned to pre-storm conditions more rapidly than in deeper waters further offshore at station Gulf 1. The mechanism leading to earlier bottom cooling of inshore waters is beyond the scope of this study, but as the bathymetry of the region is very complex, it is possible that this complicated the dynamics of any upwelling of deeper water that occurred.

At both the inshore station Boca 3 and the offshore station Gulf 1, high levels of ambient noise occurred during the passage of Tropical Storm Debby that could be attributed to natural, non-biological sources (the geophony). Most of the increase in ambient noise was observed in lower frequencies (63 Hz, 125 Hz and 500 Hz third-octave bands; Figs 3 and 5), and qualitative review of these files suggested that the noise was caused by surface wind-driven waves and rain. Increases in low frequency underwater ambient noise are characteristic of large storms. Raffenberg [27], for example, reported increased ambient noise in frequencies below 10000 Hz during four hurricanes in the Bahamas, and reported that lower frequencies increased the most. Tropical storm Debby also produced heavy rain in the area, which can contribute to underwater broadband ambient noise from frequencies below 1000 Hz to above 20000 Hz [28, 29].

In addition to detecting changes in environmental conditions, acoustic monitoring is a valuable approach to detecting species and biological responses such as alterations in vocalization rates of fishes. At both station Boca 3 and Gulf 1, significant differences were found in the number of calls detected per file between the time periods before, during and after the storm for all fish species combined and for all species/group-specific calls except spotted seatrout and red drum (which were only rarely detected). However, the patterns of call production levels, and the degree of correlation between the number of calls and environmental variables, was species specific.

One pattern observed was the decrease in call numbers during the passage of the storm, followed by an increase in call numbers after the storm. This was only observed strongly with sand seatrout calls at station Boca 3 (inshore), although sand seatrout at the offshore station increased throughout the study. At Boca 3, calls were detected in high numbers before the storm, decreased to their lowest level during the storm, and increased to their highest levels after the storm. Correlations with environmental variables suggest that this was likely due to the storm conditions, as sand seatrout calls at station Boca 3 were correlated with both water level anomaly (the negative storm surge) and water temperature (which decreased during the storm). In several other cases, minimums in the mean number of fish calls were observed during the storm, but the overall pattern was only partially significant. For example, the minimum mean number of total fish calls (all species/groups) per file at station Boca 3 also occurred during the storm, but no significant difference was found between call detections before and during the storm. Similarly, gulf toadfish and grunt calls at station Gulf 1 (offshore) decreased during the storm period, however significant differences were only found between the before and during storm periods and before and after storm periods for gulf toadfish, and between the during and after storm time periods for grunt. Correlations with water level anomaly (total calls at Boca 3, grunt at Gulf 1) and water temperature (total calls at Boca 3, gulf toadfish at Gulf 1) suggest that differences in call rates were partially due to conditions associated with the storm, but other factors were likely important. As total fish calls were made up largely of sand seatrout calls, but other species also contributed and exhibited different temporal patterns, the weaker relationship with total fish calls was not surprising.

Raffenberg [27] investigated fish vocalizations (all species combined) during four hurricanes in a marine sinkhole in the Bahamas and found that vocalizations significantly decreased in the three stronger storms but not in the weaker, distant storm. However, Locascio and Mann [7] investigated fish vocalizations in the path of a category 4 hurricane (Hurricane Charlie) over a nearby area with a similar species assemblage (Charlotte Harbor, Florida). In that study, the authors found that the storm had little effect on spawning fish vocalizations (in fact, sound levels increased during and after the storm) [7]. While the study by Locascio and Mann [7] was on all fish calls combined, calls were primarily from sand seatrout. Despite the similar environments between station Boca 3 (this study) and that investigated by Locascio and Mann [7], we found that sand seatrout calls were significantly lower during Tropical Storm Debby. However, in this study and the study by Raffenburg [27], fish vocalizations were individually identified by manual inspection of spectrograms, while in Locascio and Mann [7] fish vocalizations were quantified by identifying chorusing events through spectral analysis, so the methodologies are not directly comparable.

Several types of fish calls in this study were correlated with water temperature, which at both stations appeared to decrease with the passage of the storm. At station Boca 3, total fish calls and sand seatrout calls decreased with decreasing water temperature (recorded at the nearby station Boca 2). While there has been little research done on the effect of tropical cyclones on fish vocalizations, the production rate of fish calls has been correlated with water temperature. Monczak and colleagues [30] found that negative temperature anomalies decreased the calling rates of oyster toadfish (O. tau), silver perch and spotted seatrout in the May River estuary. Mann and Grothues [31] documented declines in call rates for Atlantic croaker (Micropogonias undualtus) and weakfish (Cynoscion regalis) in response to episodic cold-water upwelling events, and a recent review by Ladich [32] indicated a general trend toward decreases in fish vocalizations in colder temperatures. This suggests that the changes in call rates observed in this study may be linked to the influx of cold water associated with Tropical Storm Debby. After the storm passed, both water temperatures and some call rates increased rapidly at station Boca 3 (the call rates possibly in conjunction with the lunar cycle). However, at station Gulf 1, temperature was not observed to increase after the storm, yet most correlations between fish calls and temperature were negative (total fish calls, sand seatrout and red drum). Therefore, fish calls increased with decreasing temperature. Only gulf toadfish had a positive correlation where the decrease in water temperature was associated with a decrease in calls. Along with a high correlation to the lunar cycle (see below), these results suggest a weaker relationship between fish call rates and the observed temperature fluctuation and a stronger relationship with lunar cycle.

As the effects of Tropical Storm Debby were severe but not extreme (e.g., wind speeds up to 15 m sec^-1 [18]), the decreases in fish calls observed were likely due to non-lethal effects such as behavioral and distribution changes. The appearance and disappearance of species, as well as major shifts in distribution appear to be common biological reactions of fish to tropical cyclones (e.g., [3, 4, 33]). In the Gulf of Mexico, normal seasonal migrations between the Gulf of Mexico and estuaries, such as Tampa Bay, by various fish species are common (including sound producing species, e.g., sand seatrout: [34]), therefore shifts in distribution during storm events may be a common behavioral reaction.

Alternately, a reduction in the detection of fish calls during the storm could reflect a true reduction in call production by individuals. Several studies have documented reductions in sound production by fish when exposed to increased ambient noise. For example, Atlantic croaker decreased their call rates when a loud ferry passed nearby, especially during the peak calling season; [35]). Reduced fish call rates during periods of increased ambient noise have also been shown in experimental settings for gobys (Gobiusculus flavescens and Pomatoschistus pictus) which led to a decrease in spawning success [36]. However, our study found little correlation between fish calls and ambient noise, with gulf toadfish showing a strong negative correlation and red drum showing a weaker positive correlation at station Gulf 1. Higgs & Humphrey [37] also detected no correlation between ambient noise and the call rate of the goby Neogobius melanstromus. Although little is currently known about how free-living fish respond acoustically to increases in ambient noise levels, increases in background noise associated with tropical cyclones could potentially have profound biological consequences in terms of reductions in communication distances and other masking-related issues. For example, many fish use vocalizations in courtship and can use “eavesdropping” for activities such as foraging and avoiding predators [38–40]. If the passage of tropical storms coincides with prime spawning periods (e.g., full moon periods with certain species), the impacts of these storms could be exacerbated, especially if masking reduced the probability of finding a suitable spawning partner. The effects of ambient noise on the masking of communication signals, predator-prey relationships and reproductive efficiency of fish are considered serious and are currently areas of active investigation (e.g., see [41, 42] for reviews).

A more common temporal pattern was a consistent increase in call production over the study period. This pattern was observed strongly in silver perch at station Boca 3, and total fish calls and sand seatrout calls at station Gulf 1 (all pairwise differences significant). In these cases, weaker correlations were found between call rates and conditions associated with the storm (r < 0.60, water level anomaly and/or water temperature), but strong correlations were found with the lunar cycle (r > 0.75). This suggests that in these cases, call rates increased with the waxing moon (as the moon approached full, July 3) and that environmental conditions associated with the storm had less effect. Grunt calls at station Boca 3 and silver perch calls at station Gulf 1 appear to have been consistent before and during the storm, however, a significant increase in call rate was observed after the storm for both species. This suggests that for grunt (Boca 3) and silver perch (Gulf 1) there was an overall increase in call production with the waxing moon that was interrupted or delayed by the passage of Tropical Storm Debby. However, an increase in calls with lunar cycle could also be more sudden in these cases (i.e., call rates increase closer to the full moon), and conclusions are confounded by having no significant correlations with environmental conditions, including the lunar cycle. Gulf toadfish at station Boca 3 were the only case showing a consistent decrease in call production over the study period and were only correlated with the lunar cycle, suggesting that this species decreases its call production with the waxing moon. We expect that this was also the case with gulf toadfish at station Gulf 1, but at this location the storm conditions prematurely decreased call rates. This is supported by the strong correlation found between gulf toadfish calls and both water temperature and lunar cycle at station Gulf 1. In previous studies, the calls of spotted seatrout [43] and oyster toadfish [30, 44] have been associated with the full and/or new moons, which was attributed to the times of increased tidal flow. However, our results should be interpreted with caution. Wall and colleagues [20] found that toadfish calls (combined calls from gulf toadfish and another closely related species, the leopard toadfish, O. pardus) on the West Florida Shelf were not associated with the lunar cycle [20]. In a nearby estuary, sand seatrout were also not found to have a lunar periodicity in sound production [45]. As our study took place during a single phase of the lunar cycle, we can only suggest the relationship between fish calls and the lunar cycle as a possibility, and studies over multiple lunar cycles are needed to confirm this pattern.

Overall, the changes in fish calling rates appear to be partly due to storm conditions but are likely also the result of other factors including the lunar cycle. The call rates of sand seatrout suggest that the effects of the storm on the fish community were more severe at station Boca 3. For sand seatrout, call rates were significantly lower during the storm at station Boca 3, while at Gulf 1 calls increased throughout the study despite the storm and were strongly correlated with lunar cycle. Station Boca 3 was located close to shore and in shallow water (3 m), and therefore was likely exposed to a more significant storm surge, a greater freshwater input with the accompanying chemical and solid waste pollution associated with major storm events, and more water motion from surface waves and currents. Station Gulf 1, on the other hand, was in approximately 9 m of water and approximately 10 km from shore. Although it was more exposed to ocean swell due to its location in the Gulf of Mexico, at 9 m depth the conditions may have been less severe, which could mean the fish community may have been less impacted by the storm. Greater impacts on the fish community from tropical cyclones in shallow water environments is a pattern that has been reported previously [46]. This difference in depth may also change the acoustic field surrounding the stations, and therefore could also affect fish call detections.

Most or all species appeared to recover very quickly from this tropical storm. Rapid recovery of fish communities after tropical cyclones have also been documented in other areas (e.g., in the Indian River Lagoon, Florida, USA after Hurricanes Frances and Jeanne [47]). Increases in call detections at the end of the study period can be explained by immigration of individuals into the area, or by an increase in sound production by the individual fish already present (e.g., an increase in call rate due to the lunar cycle). Despite the apparent resistance and resilience to Tropical Storm Debby in this study, given the other evidence for effects of tropical cyclones on fish communities (e.g., [46, 48]) further research should be conducted in this area.

While acoustic masking of fish calls by the noise of the storm may contribute to the decrease in call detections in this study, we believe that this effect is low. For several species, the rate in fish call detections increased steadily throughout the study (e.g., sand seatrout at station Gulf 1) or decreased steadily through the study (gulf toadfish at station Boca 3) despite significant increases in ambient noise during the storm. If significant masking were taking place, we would not expect call rates to be higher than in a storm-free period (i.e., before or after). In addition, while the rate of fish calls were significantly correlated to other factors (e.g., water temperature), fish calls were only correlated with ambient noise for gulf toadfish at station Gulf 1. Therefore, while signal masking may be a factor in our results, we believe this bias does not completely explain the observed patterns in fish detections. Masking by anthropogenic sounds (mostly from boats) could potentially occur as well, it would occur mainly outside the period of the storm’s passage, especially before. Therefore this would bias our results to decreased call detections before and after the storm. We cannot rule out this possibility, however as the highest levels of ambient noise were ubiquitously during the storm, we believe that this effect is minimal.

Conclusion

This study is one of only a few studies to examine the soundscape of a tropical storm. We found significantly higher ambient noise levels during Tropical Storm Debby, and noise levels increased most significantly at lower frequencies (up to the 500 Hz third-octave band). These noise levels, as high as 127.2 dB_RMS re 1 μPa and up to 13.5 dB above mean background noise levels, are expected to have a significant impact on marine life that uses sound for foraging, communication and predator avoidance. This study is also only the third study that we are aware of to investigate fish sound production immediately before, during, and immediately after a tropical cyclone, and the first to do so with species/group specific sounds. The use of PAM technology allowed us to observe the biological effects of a tropical storm at a far higher temporal resolution than possible using many other methodologies. In both the inshore lagoon ecosystem of Boca Ciega Bay and the deeper water Gulf of Mexico ecosystem, the detection rates for some fish calls appeared to have a biological reaction to the passage of Tropical Storm Debby in that fish sound production decreased, but as fish sound production recovered quickly this ecosystem showed both resistance and resilience to this disturbance. However, other species’ call rates did not appear to be strongly affected by the storm, and fish calls were highly correlated with lunar cycle. It is important to remember that this rapid recovery and lack of response in some species would potentially not apply to a direct impact from a major tropical cyclone. Within a 200 km radius, the Tampa Bay area had 21 tropical cyclones between 2001 and 2020, and 121 tropical cyclones (including 16 category 3–5 hurricanes, [49]). While this rate is similar to other areas experiencing tropical cyclones (e.g., Miami, USA and Nassau, Bahamas), the area has been exposed to fewer major hurricanes (category 3–5) during those times [49]. Studies investigating major hurricanes have reported fish mortality, loss of diversity and decreased sound production [27, 47]. However, recovery of the fish community after a major hurricane can be observed in days to weeks after the passage of the storm [27, 47]. Therefore, our results and the results of previous studies indicate that fish communities generally have high levels of resistance and resilience to tropical cyclones. The cumulative and synergistic effects of tropical storms also need to be considered as coastal ecosystems are also besieged by climate change, overfishing, pollution and other threats. In addition, there is compelling evidence that global climate change is increasing the frequency and intensity of tropical cyclones [11–13]. Therefore, it is increasingly important to understand how marine (and other) ecosystems respond to and recover from these storms.

Supporting information

S1 File. Raw data.

The spreadsheet contains the fish vocalization raw count data per file throughout the study period.

(XLSX)

Click here for additional data file.^{(680.3KB, xlsx)}

Acknowledgments

We would like to thank Kyla Foley for assistance in acoustic analysis, and all those who assisted with the deployment and retrieval of the recorders. Additionally, we would like to thank the Eckerd College Marine Science Department for their logistical support and assistance. This recorder deployment was part of the Eckerd College Dolphin Project. Neither Eckerd College Marine Science nor the Eckerd College Dolphin Project provided funding for this project.

Data Availability

All relevant data are within the manuscript and its S1 File.

Funding Statement

The work was supported by NOAA Ernest F. Hollings Undergraduate Scholarship (awarded to A.D.B. | https://www.noaa.gov/office-education/hollings-scholarship). Development and construction of the Digital SpectroGram recorders built in this study was supported by a grant (awarded to P.S.) from the National Oceanographic Partnership Program (OCE-0741705 | https://www.nopp.org). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The funder, Loggerhead Instruments (Sarasota, Florida, United States of America), provided support in the form of salaries for authors D.M., but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section.

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PLoS One. doi: 10.1371/journal.pone.0254614.r001

Decision Letter 0

Dennis M Higgs

6 May 2021

PONE-D-21-10011

Tropical Storm Debby: soundscape and fish sound production in Tampa Bay and the Gulf of Mexico

PLOS ONE

Dear Dr. Boyd,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

As noted in my response, please pay careful attention to the reviewers comments and also tighten up the writing for more focus on the interesting biophony aspects.

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Additional Editor Comments:

As you can see both reviewers, both of whom are expert in the field, find much positive to say about the data collected in the current study but both request major changes and after my own review I find I agree with all their recommendations. The fact that recorders were placed before a major storm event did result in an interesting natural experiment but the limitations of this being an unreplicated observation should be addressed. Both reviewers also find the manuscript would be significantly strengthened with less focus on the geophony and more on the biophony. Please address all reviewers comments carefully.

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Reviewers' comments:

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Reviewer #2: Yes

**********

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #2: Yes

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5. Review Comments to the Author

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Reviewer #1: I like the topic of the paper, and the idea of taking opportunistic data and finding something novel in the biological effects. Unfortunately, your main points and interesting take home messages felt a little lost in the main body of text. It felt like you were trying to put too many ideas into what should be a fairly simple paper (i.e. a storm event causing fish vocalizations to decrease due to masking/ silencing effects). I suggest you try to condense your writing and focus on the biophony aspect. I hope some of my specific comments help with this.

While reading the manuscript I also had a couple major questions:

1) How often storm events occur in the area? What are the knock on effects of lots of storm events versus one or two each year?

2) You mention Tropical Storm Debby was not a major tropical cyclone. Therefore, how often do different intensity storm events occur and what are your predictions for the relationship to sound? For example, the category 4 hurricane Charley did not inhibit fish production (line 78) but not reference the category for Debby thus making comparisons difficult.

Specific comments

Introduction

Line 60: this sentence repeats itself, suggest you omit.

Lines 66 – 76: this section is very repetitive, and I suggest could be condensed.

Line 99: The authors make it seem like these recorders were placed in Tampa Bay to record the storm. However, I suspect it was serendipitous that the storm occurred, and they could look back and see the effects on noise in the area. I think the authors should be forthcoming about this as (at least in my opinion) this is a major advantage of PAM that you never truly know what you will record!

Methods

Line 152: why was a level of 0.5m chosen as the pivotal value?

Line 164: how were fish sounds identified to species? And are the sounds published? If not these should be included in the methodology as example spectrograms.

Table 1 is not needed as these values are well known in the acoustics literature

Results

Figures 4 and 6: I suggest clustering the bar plot as frequencies, with before, during and after in different colours, as I think that would better show your differences.

It would also be worth knowing how far away each of the stations was from the ‘epicentre’ of the storm event as it passed and maybe making some predictions of source levels.

Line 280: Again, I wonder how you distinguished these call types and if able to separate species could you not separate in Figure 7? Perhaps one species effected more than another? Why did you group all fish calls together?

Discussion

The description of environmental change with Debby at that start of the discussion although useful seems irrelevant if not linked to your main aim of investigating the effect of the storm on fish acoustic activity.

At the moment the increase in sound levels during a storm event doesn’t seem to be particularly novel, I think any acoustician would expect this in the low frequencies due to wind/rain noise. What is novel is linking it to fish sounds.

At the beginning of the biophony section you talk about dolphins, this seems irrelevant and I suggest you omit as your focus is fish in your results.

Could you split fish species and make discussions about how the storm effects different species differently?

Could fish habituate to the sound of storm events if happens regularly? I would expand on depth effects and how fish could move to deeper locations to seek acoustic refuge.

Lines 420 – 431: you compare your study to others on storm events. However, you do not mention if similar species were present or even fish groups. Furthermore, were the storms during comparable times of the year? Besides methodological differences, these differences would also effect comparing results between studies.

At the end of the discussion you deviate into talking about anthropogenic noise, I don’t think this is a needed topic in this paper.

Overall, the discussion is too long with too many ideas and little focus or direction. I suggest removing the information on geophony/anthrophony and really homing in on the biophony (both in the results and discussion) as this is the really interesting stuff!

Reviewer #2: This study explores the effect of a storm on the local soundscape and the number of fish calls in an area. The article is well structured and easy to read. However, it suffers mainly from pseudoreplication: the authors recorded the soundscape in only one area (although 2 sites) affected by the storm before, during and after. There are no proper controls, it is therefore impossible to draw robust conclusions from the study. I believe that the study should still be published (as studies in the field are rare and a replicated study is very difficult to conduct), but this problem needs to be clearly stated in the abstract and in the discussion.

More specific comments:

- In the introduction, the authors state that PAM is ideal methodology to examine the biological responses to and recovery after storms… Their results however attract more questions than answers (did the fish stop calling, did they leave the area, did they die?). Although PAM can be a useful tool, in this case, it only gives us some limited information on what exactly is happening. It would be worth discussing this point made in the introduction back in the discussion.

- It would be good to have some hypothesis in the introduction on to what the investigators are expecting as results, based on existing literature

- Methods: fish calls were counted for each 24-hour period: fish calls usually vary a lot during the day, did you try to calculate the fish calls per smaller amount of time, e.g. dawn/dusk, night/day ? Do you think it could bring up other important trends?

- L 186: please explain how exactly you could determine if masking was affecting your rates, it is unclear

- Fig. 7: how is it possible to get a negative mean number? I think this data should be presented as boxplots rather than histograms.

- L378: avoid double negative ‘not unexpected’

- L 382 – 393: could the change of water depth during the storm also have altered the ambient noise propagation?

- L. 196 – 502: How can you be sure that anthropogenic noise did not mask fish calls significantly during your study?

**********

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Reviewer #2: Yes: Lucille Chapuis

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PLoS One. 2021 Jul 13;16(7):e0254614. doi: 10.1371/journal.pone.0254614.r002

Author response to Decision Letter 0

27 Jun 2021

Editor’s Comments:

Comment 1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at:

Reply: We have rechecked the revised manuscript’s format to ensure it meets the PLOS ONE style requirement.

Comment 2. We note that one or more of the authors are employed by a commercial company: Loggerhead Instruments, Sarasota, Florida, United States of America. Please provide an amended Funding Statement declaring this commercial affiliation, as well as a statement regarding the Role of Funders in your study. If the funding organization did not play a role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript and only provided financial support in the form of authors' salaries and/or research materials, please review your statements relating to the author contributions, and ensure you have specifically and accurately indicated the role(s) that these authors had in your study. You can update author roles in the Author Contributions section of the online submission form.

Please also include the following statement within your amended Funding Statement.

If your commercial affiliation did play a role in your study, please state and explain this role within your updated Funding Statement.

Reply: Amended funding statement:

Comment 3. Please also provide an updated Competing Interests Statement declaring this commercial affiliation along with any other relevant declarations relating to employment, consultancy, patents, products in development, or marketed products, etc. Within your Competing Interests Statement, please confirm that this commercial affiliation does not alter your adherence to all PLOS ONE policies on sharing data and materials by including the following statement: "This does not alter our adherence to PLOS ONE policies on sharing data and materials.” (as detailed online in our guide for authors http://journals.plos.org/plosone/s/competing-interests) . If this adherence statement is not accurate and there are restrictions on sharing of data and/or materials, please state these. Please note that we cannot proceed with consideration of your article until this information has been declared. Please include both an updated Funding Statement and Competing Interests Statement in your cover letter. We will change the online submission form on your behalf.

Reply: Updated Competing Interests Statement:

M.D. is affiliated with a commercial company, Loggerhead Instruments, Sarasota, Florida, United States of America, as the company's President. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Comment 4. Thank you for stating the following in the Acknowledgments Section of your manuscript:

[ Additionally, we would like to thank the Eckerd College Marine Science Department for their support and assistance. This recorder deployment was part of the Eckerd College Dolphin Project.]

Please remove any funding-related text from the manuscript and let us know how you would like to update your Funding Statement. Currently, your Funding Statement reads as follows:

Please include your amended statements within your cover letter; we will change the online submission form on your behalf.

Reply: We have updated the acknowledgements section to read as follows:

Comment 5. We note that Figure 1 in your submission contains map images which may be copyrighted. All PLOS content is published under the Creative Commons Attribution License (CC BY 4.0), which means that the manuscript, images, and Supporting Information files will be freely available online, and any third party is permitted to access, download, copy, distribute, and use these materials in any way, even commercially, with proper attribution. For these reasons, we cannot publish previously copyrighted maps or satellite images created using proprietary data, such as Google software (Google Maps, Street View, and Earth). For more information, see our copyright guidelines: http://journals.plos.org/plosone/s/licenses-and-copyright. We require you to either (1) present written permission from the copyright holder to publish these figures specifically under the CC BY 4.0 license, or (2) remove the figures from your submission:

Reply: Figure 1 was made from data downloaded from government agencies and made in ArcGIS Pro by one of the authors (PS). To be certain we are able to use this data we reached out to the appropriate agencies.

We have received email confirmation from the National Hurricane Center (6/2/21) and the Florida Fish and Wildlife Conservation Commission (6/3/21) that the data we use is public domain and we are free to use it in the figure. We also confirmed that the data used in the manuscript from the NOAA St. Petersburg weather and tide station are also public domain and available for use (confirmed via email 6/3/21). Please let me know if you need additional details.

Comment 6. In your Methods section, please provide additional information regarding the permits you obtained for the work. Please ensure you have included the full name of the authority that approved the field site access and, if no permits were required, a brief statement explaining why.

Reply: See line 106 to end of paragraph. We have also included a bit about the fact that recorders were not specifically deployed to monitor the storm, and edited the sentence to make it shorter and more readable.

Comment 7. Please include captions for your Supporting Information files at the end of your manuscript, and update any in-text citations to match accordingly. Please see our Supporting Information guidelines for more information: http://journals.plos.org/plosone/s/supporting-information.

Reply: A caption for the supporting information file have been added to the end of the manuscript and in-text citations have been updated.

Reviewer 1:

Comment 1. I like the topic of the paper, and the idea of taking opportunistic data and finding something novel in the biological effects. Unfortunately, your main points and interesting take home messages felt a little lost in the main body of text. It felt like you were trying to put too many ideas into what should be a fairly simple paper (i.e. a storm event causing fish vocalizations to decrease due to masking/ silencing effects). I suggest you try to condense your writing and focus on the biophony aspect. I hope some of my specific comments help with this.

Reply: We appreciate this comment from Reviewer 1 and have gone through and revised the writing (specifically the Results and Discussion sections) to focus solely on the third-octave data and the fish volication data. We have completely rewritten the discussion to focus mostly on the new species-specific vocalization data that was added to the manuscript.

Comment 2. While reading the manuscript I also had a couple major questions: 1) How often storm events occur in the area? What are the knock-on effects of lots of storm events versus one or two each year? and 2) You mention Tropical Storm Debby was not a major tropical cyclone. Therefore, how often do different intensity storm events occur and what are your predictions for the relationship to sound? For example, the category 4 hurricane Charley did not inhibit fish production (line 78) but not reference the category for Debby thus making comparisons difficult.

Reply: Q1)This information and a better interpretation of the general effects of these storms are now presented in the conclusion, starting on line 664 Q2) Debby was categorized as a tropical storm, not a hurricane (category 1-5 possible with the latter). Therefore it was one category weaker than a category 1 hurricane. There are no category numbers associated with tropical storms.

Comment 3. Line 60: this sentence repeats itself, suggest you omit.

Reply: We have omitted the line.

Comment 4. Lines 66 – 76: this section is very repetitive, and I suggest could be condensed.

Reply: We have condensed this section.

Comment 5. Line 99: The authors make it seem like these recorders were placed in Tampa Bay to record the storm. However, I suspect it was serendipitous that the storm occurred, and they could look back and see the effects on noise in the area. I think the authors should be forthcoming about this as (at least in my opinion) this is a major advantage of PAM that you never truly know what you will record!

Reply: We have made it more clear that the recorders had already been deployed at our field sites for a different research project, when Tropical Storm Debby hit the area (Line 103).

Comment 6. Line 152: why was a level of 0.5m chosen as the pivotal value?

Reply: We have explained our reasoning for the 0.5m cut-off for the During the storm time period (Line 150).

Comment 7. Line 164: how were fish sounds identified to species? And are the sounds published? If not these should be included in the methodology as example spectrograms.

Reply: We have added additional information to the methods section to explain how the fish sounds were identified and added the database sources to the references (Line 166).

Comment 8. Figures 4 and 6: I suggest clustering the bar plot as frequencies, with before, during and after in different colours, as I think that would better show your differences.

Reply: Figures have been changed as suggested and we agree that they show the differences much more clearly.

Comment 9. It would also be worth knowing how far away each of the stations was from the ‘epicentre’ of the storm event as it passed and maybe making some predictions of source levels.

Reply: The methods section has been updated to include the distance to the track line of the storm (line 103). It is also mentioned in the first paragraph of the discussion.

We are not quite sure what the reviewer means by “source levels”. In this case the source level would be the ambient noise at the surface, so therefore is a function of the distance to the water surface where the waves are being generated and rain is impacting the water surface. However we suspect the reviewer was referring to the ambient noise levels where the storm was at its maximum. This is largely a function of the relationships between wind speed / surface agitation and sound pressure level, and of rainfall and sound pressure level, at the source. We feel that attempting to estimate the sound pressure level of the storm at its maximum wind speed and rainfall is interesting but beyond the scope of this paper. Although we know of one study where a category 1 hurricane was detected acoustically 800 km away, we also feel that attempting to calculate sound pressure levels at the source is not feasible, as that signal on our recordings would be highly masked by the received levels of the local conditions.

Comment 10. Line 280: Again, I wonder how you distinguished these call types and if able to separate species could you not separate in Figure 7? Perhaps one species effected more than another? Why did you group all fish calls together?

Reply: We added the species-specific call data to the results section and refocused the discussion section on the new data added (Figures 7-10).

Comment 11. The description of environmental change with Debby at the start of the discussion although useful seems irrelevant if not linked to your main aim of investigating the effect of the storm on fish acoustic activity.

Reply: With the new addition of the species-specific data, we feel this section of the discussion is more relevant and have made it more clear how the environmental changes as a result of Debby may be responsible for some of the trends detected throughout the study.

Comment 12. At the moment the increase in sound levels during a storm event doesn’t seem to be particularly novel, I think any acoustician would expect this in the low frequencies due to wind/rain noise. What is novel is linking it to fish sounds.

Reply: We have condensed this section of the manuscript and focused more on the fish vocalization trends discovered throughout our study.

Comment 13. Could you split fish species and make discussions about how the storm affects different species differently?

Reply: We have added species-specific data to the manuscript.

Comment 14. Could fish habituate to the sound of storm events if it happens regularly? I would expand on depth effects and how fish could move to deeper locations to seek acoustic refuge.

Reply: We expended on this topic in the discussion, starting at line 620,

Comment 15. Lines 420 – 431: you compare your study to others on storm events. However, you do not mention if similar species were present or even fish groups. Furthermore, were the storms during comparable times of the year? Besides methodological differences, these differences would also effect comparing results between studies.

Reply: We have added additional information (line 522) to compare and contrast the methodologies and results of similar studies to the methodologies and results from our study.

Comment 16. At the end of the discussion you deviate into talking about anthropogenic noise, I don’t think this is a needed topic in this paper.

Reply: We have omitted this section from the manuscript.

Comment 17. Overall, the discussion is too long with too many ideas and little focus or direction. I suggest removing the information on geophony/anthrophony and really homing in on the biophony (both in the results and discussion) as this is the really interesting stuff!

Reply: We have restructured and rewritten the discussion to focus mostly on the species-specific trends we discovered throughout the study and omitted other information on the geophony, anthrophony, and how the storm affects other organisms (i.e. dolphins, shrimp, etc.)

Reviewer 2:

Comment 1. In the introduction, the authors state that PAM is ideal methodology to examine the biological responses to & recovery after storm. Their results however attract more questions than answers (did the fish stop calling, did they leave the area, did they die?). Although PAM can be a useful tool, in this case, it only gives us some limited information on what exactly is happening. It would be worth discussing this point made in the introduction back in the discussion.

Reply: We have expanded on this point significantly throughout our results and discussion section and discussed some of the limitations (i.e. masking) of PAM (see line 639).

Comment 2. It would be good to have some hypothesis in the introduction on to what the investigators are expecting as results, based on existing literature

Reply: We have added a line to the introduction section about our hypothesis at the beginning of this study to address this comment (Line 91).

Comment 3. Fish calls were counted for each 24-hour period: fish calls usually vary a lot during the day, did you try to calculate the fish calls per smaller amount of time, e.g. dawn/dusk, night/day? Do you think it could bring up other important trends?

Reply: We believe this is beyond the scope of this study and decided to omit this analysis. While we did perform the analysis we felt it did not add anything of substance to the study.

Comment 4. L 186: please explain how exactly you could determine if masking was affecting your rates, it is unclear

Reply: The discussion of why masking is thought to be a factor but a minor one has been elaborated on to hopefully be clearer (starting on line 636).

Comment 5. Fig. 7: how is it possible to get a negative mean number? I think this data should be presented as boxplots rather than histograms

Reply: We added new results to the results section and conducted new analysis, the old Fig 7 was replaced by Figures 8 and 10.

Comment 6. L 378: avoid double negative ‘not unexpected’

Reply: This has been fixed.

Comment 7. L 382 – 393: could the change of water depth during the storm also have altered the ambient noise propagation?

Reply: Yes, this is now acknowledged in the discussion (starting on line 627).

Comment 8. L 196 – 502: How can you be sure that anthropogenic noise did not mask fish calls significantly during your study?

Reply: This is now discussed starting on line 647.

Attachment

Submitted filename: FINAL_Response_Letter_Soundscape_Manuscript.docx.pdf

Click here for additional data file.^{(281.2KB, pdf)}

PLoS One. doi: 10.1371/journal.pone.0254614.r003

Decision Letter 1

Dennis M Higgs

30 Jun 2021

Tropical Storm Debby: soundscape and fish sound production in Tampa Bay and the Gulf of Mexico

PONE-D-21-10011R1

Dear Dr. Boyd,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Reviewers' comments:

PLoS One. doi: 10.1371/journal.pone.0254614.r004

Acceptance letter

Dennis M Higgs

5 Jul 2021

PONE-D-21-10011R1

Tropical Storm Debby: soundscape and fish sound production in Tampa Bay and the Gulf of Mexico

Dear Dr. Boyd:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

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Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

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on behalf of

Dr. Dennis M. Higgs

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 File. Raw data.

The spreadsheet contains the fish vocalization raw count data per file throughout the study period.

(XLSX)

Click here for additional data file.^{(680.3KB, xlsx)}

Attachment

Submitted filename: FINAL_Response_Letter_Soundscape_Manuscript.docx.pdf

Click here for additional data file.^{(281.2KB, pdf)}

Data Availability Statement

All relevant data are within the manuscript and its S1 File.

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Tropical Storm Debby: Soundscape and fish sound production in Tampa Bay and the Gulf of Mexico

Anjali D Boyd

Shannon Gowans

David A Mann

Peter Simard

Roles

Abstract

Introduction

Materials and methods

Sampling sites

Fig 1. Tropical Storm Debby path.

Additional environmental data

Analysis

Results

Tropical Storm Debby conditions

Fig 2. Tropical Storm Debby environmental conditions.

Soundscape analysis

Fig 3. Boca 3 sound pressure levels during Tropical Storm Debby.

Fig 4. Boca 3 mean RMS sound pressure levels.

Table 2. Repeated measures ANOVA and post-hoc test for Gulf 1 sound pressure levels.

Table 1. Boca 3 repeated measures ANOVA and post-hoc test on sound pressure levels.

Fig 5. Gulf 1 sound pressure levels during Tropical Storm Debby.

Fig 6. Gulf 1 mean RMS sound pressure levels.

Fish calls

Table 3. List of fish species detected at Boca 3 and Gulf 1.

Fig 7. Fish detections at station Boca 3 during Tropical Storm Debby.

Fig 8. Mean fish detections per file at station Boca 3 during Tropical Storm Debby.

Table 4. Repeated measures ANOVA and post-hoc test on total fish detections for stations Boca 3 and Gulf 1.

Table 5. Repeated measures ANOVA and post-hoc test on species/family-specific fish detections for station Boca 3.

Fig 9. Fish detections at station Gulf 1 during Tropical Storm Debby.

Fig 10. Mean fish detections per file at station Gulf 1 during Tropical Storm Debby.

Table 6. Gulf 1 repeated measures ANOVA and post-hoc test on fish species detections.

Correlations

Table 7. Spearman’s rho correlations for station Boca 3.

Table 8. Spearman’s rho correlations for station Gulf 1.

Discussion

Conclusion

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Dennis M Higgs

Roles

Author response to Decision Letter 0

Decision Letter 1

Dennis M Higgs

Roles

Acceptance letter

Dennis M Higgs

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

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