Fishery-independent observations of Atlantic menhaden abundance in the coastal waters south of New York

Fisheries Research 218 (2019) 229–236

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Fishery-independent observations of Atlantic menhaden abundance in the coastal waters south of New York

T

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Brandyn M. Lucca, Joseph D. Warren

School of Marine and Atmospheric Sciences, Stony Brook University, 239 Montauk Highway, Southampton, NY 11968, United States

A R T I C LE I N FO

A B S T R A C T

Handled by George A. Rose

Atlantic menhaden (Brevoortia tyrannus) is a migratory forage fish whose geographic range extends from the Gulf of Maine to Florida. Despite the ecological and commercial importance of menhaden, few fishery-independent surveys have been conducted to quantify their distributions of abundance and biomass. Active acoustic surveys of menhaden schools were conducted using 38, 120, and 200 kHz scientific echosounders in two regions on the continental shelf south of Long Island, New York during the summer of 2014 and spring, summer, and fall of 2015. Spatial distributions of menhaden schools were considered to be clustered across all surveys where three or more schools were observed. Estimates of school volume were highly variable, ranging from 30 to 48,000 m3. Menhaden aggregations were absent in the spring (April, May, and June) and present in the summer and fall (July, August, and September) surveys. Target strength measurements at 120 kHz during the summer and fall surveys were consistent with predicted values for adult Atlantic menhaden, suggesting that fish size did not change substantially during this time. Peak menhaden abundance was observed during August 2015 (approximately 157,000 fish km−2 with a wet weight biomass density of 35,000 kg km−2). Multifrequency acoustic surveys can provide an efficient and fishery-independent method for quantifying menhaden abundance and distribution in coastal habitats.

Keywords: Atlantic menhaden Forage fish Target strength Abundance Acoustics New York

1. Introduction Atlantic menhaden (Brevoortia tyrannus Latrobe 1802) is an estuarine-dependent planktivorous fish abundant along the entire eastern coast of the United States, particularly from North Carolina to Massachusetts (Ahrenholz, 1991). During the early spring, adult menhaden make coastwide migrations away from the coastal waters of North Carolina with larger, older individuals moving further than their smaller, younger counterparts (Liljestrand et al., 2019; Simpson et al., 2017). During the late-fall, the geographic range of these fish contracts with most adults migrating back towards Cape Hatteras; however, some may overwinter in the coastal bays and estuaries along their migratory path (Ahrenholz, 1991; Liljestrand et al., 2019). Climate variability (i.e., Atlantic Multidecadal Oscillation) also has a significant effect on the spatial distribution of recruitment throughout their geographic range, thereby impacting the coastal abundances of juveniles (Simpson et al., 2016). Similar to other shoaling clupeids, these fish are known for their size-segregated schools that can span hundreds of meters across, contain millions of individuals, and be found in both shallow estuarine and relatively-deeper coastal waters (Ahrenholz, 1991). Menhaden is an important prey item for many piscivores such as

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striped bass (Morone saxatalis), bluefish, (Pomatomus saltarix), weakfish (Cynoscion regali), seabirds, sharks, and marine mammals (Ahrenholz, 1991). Consequently, menhaden serve as an important forage species that trophically links primary producers and their direct grazers with upper-trophic predators. Despite historical overfishing during the 19th and 20th centuries, which had a substantial effect on the menhaden stock (McHugh, 1972), the stock is not considered to be currently overfished or experiencing overfishing (ASMFC, 2017). However, with no regional or local estimates of menhaden abundances it is difficult to assess the impact of various ecosystem processes such as: habitat shifts due to climate change (Buchheister et al., 2017), natural mortality events (i.e., fish kills, Lucca and Warren, 2018), and increased populations of predators such as humpback whales (Brown et al., 2018). As other forage fish stocks decline (Essington et al., 2015), there is an increased need to inform the current single-species stock assessment and validate future ecosystem-based estimates of menhaden abundance and biomass. The current comprehensive menhaden stock assessment generated by the Atlantic States Marine Fisheries Commission (ASMFC) primarily use fishery landings, port samples, and daily logbooks from regional fisheries to generate a model that estimates abundance, fishing

Corresponding author. E-mail address: [email protected] (J.D. Warren).

https://doi.org/10.1016/j.fishres.2019.05.016 Received 25 January 2019; Received in revised form 21 May 2019; Accepted 29 May 2019 Available online 12 June 2019 0165-7836/ © 2019 Elsevier B.V. All rights reserved.

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B.M. Lucca and J.D. Warren

in the coastal waters of New York (such as Atlantic herring, Clupea harengus), we did not observe any non-menhaden schools. One limitation of this study is that direct net sampling was not possible from our research vessel. Anecdotal observations from local fisherman and boat captains in the survey areas and times also reported that schools were menhaden and not other species of fish. Hydroacoustic observations were recorded using single- and splitbeam echosounders (Simrad ES60 at 38, 120, and 200 kHz) (Table 1). Transducers were mounted on a tow-body deployed at an approximate depth of 0.5 m off the starboard side of the R/V Paumanok (13.4 m length) and towed at an approximate speed of 2.5 m/s. Echosounders were calibrated using a 38.1 mm tungsten carbide sphere at an approximate depth of 10.5 m on 10 September 2015 (Foote et al., 1987). Hydrographic profiles of the water column were measured at each site on each sampling date from vertical CTD (Seabird 19+) casts. Divercollected video was used to estimate the packing density of in situ menhaden schools using the length relationship described in Pitcher and Partridge (1979) for Atlantic herring. This analysis measured the distances between fish and estimates of fish lengths to determine the relative density (fish m−3) of individuals.

mortality, biomass, fecundity, and other proxies that represent stock status (ASMFC, 2017). For example, the model used to quantify stock size estimated that the biomass of the entire stock was approximately 1.1 billion kg, which comprised 14 billion fish. However, the current stock assessment relies on survey data that are either fishery-dependent port sampling data or utilizes sampling methods that do not adequately target menhaden schools (ASMFC, 2017). Consequently, estimates of regional absolute abundance and biomass of menhaden are unavailable for the majority of their geographic range. Therefore, the development and implementation of new sampling techniques that are specifically designed for menhaden is crucial to track spatiotemporal changes in stock abundance and biomass. Active acoustic surveys are a primary assessment tool for many forage fish species (Demer et al., 2013) and have been previously used to study estuarine schools of menhaden (Lucca and Warren, 2018). This technique can provide spatial data with fine resolution in space and time for offshore fish schools that cannot be resolved by traditional sampling methods, such as net trawls and underwater video (Simmonds and MacLennan, 2005). Acoustic trawl surveys can provide a multi-year stock biomass/abundance index (Trenkel et al., 2011) and also be used to complement other sampling methods (Handegard et al., 2013), especially for data-poor fisheries. Similar to Gulf menhaden (Brevoortia patronus, Boswell et al., 2007) and Pacific sardines (Sardinops sagax, Demer et al., 2013), estimates of schooling and life history characteristics of individual fish can be inferred from the remote observations provided by active acoustics (Simmonds and MacLennan, 2005). Acoustic survey data can then be converted from acoustic backscatter to relative indices or direct estimates of abundance (# fish) and biomass (kg) (Simmonds and MacLennan, 2005). In the context of monitoring stock status, acoustic data can quantify spatial and temporal shifts in stock abundance and biomass that can be used to both complement and inform single-species and ecosystem-based models (Garrison et al., 2010; Trenkel et al., 2011; Buchheister et al., 2017). Better estimates of menhaden abundance and biomass in coastal habitats are crucial for improved management of both menhaden and its predators. We conducted a series of boat-based surveys of two offshore regions south of Long Island, New York in 2014 and 2015 to determine if a hydroacoustic sampling approach was feasible for surveying Atlantic menhaden. This study provides a quantitative estimate of menhaden abundance and biomass at these two sites and demonstrates the utility of fishery acoustics methods to assess menhaden in continental shelf habitats.

2.2. Data analysis Hydroacoustic data were pre-processed to correct the ES60 triangle wave error (Keith et al., 2005) and then further processed using Echoview 7.1 (Myriax, 2016) and R 3.3.1 (R Development Core Team, 2016; Wickham, 2016). A surface exclusion line set was at 1.5 m to account for the near-field and surface noise (i.e., bubble intrusion). It is possible that this excluded some near-surface fish; however, no schools were observed at the surface directly underneath the vessel and it was assumed most schools were at depths greater than 1.5 m (Churnside et al., 2011). This observation is likely the result of vessel avoidance by the fish due to vessel noise or vessel presence (Mitson and Knudsen, 2003; Mann et al., 2001). Acoustic backscatter data from the 120 kHz echograms were used to calculate mean volume backscattering strength (SV, dB re. m−1), target strength (TS, dB re. 1 m2), and nautical acoustic area scattering coefficient (NASC, m2 nmi−2). Background noise was filtered out based on signal-to-noise ratios based on recommendations by De Robertis and Higginbottom (2007). The 120 kHz echosounder was the only split-beam system used in the survey so it was necessary to use this frequency in order to collect both TS and Sv data (Ona and Barange, 1999). NASC, which represents the vertically integrated acoustic backscatter averaged over a square nautical mile, is often used as a proxy for numeric fish density or biomass (Simmonds and MacLennan, 2005). TS is another acoustic measurement that has been used as a proxy index (Trenkel et al., 2011) for changes in population size class composition since TS is, in many cases, a function of fish size for a given species (Love, 1971; Simmonds and MacLennan, 2005; Lucca and Warren, 2018). Ping times for all three frequencies were matched to account for spacing of the echosounders on the towfish. A 3 × 3 median filter was applied to all three frequencies to remove intermittent background noise. Transect lines were then divided into 50 m evenly spaced elementary distance sampling units (EDSUs) to measure the fine-scale distribution of NASC (Lucca and Warren, 2018). Once smoothed, minimum SV-thresholds were set at −60, −70, and −70 dB at 38, 120, and 200 kHz respectively (Jech and Michaels, 2006). All acoustic backscatter data collected while not on transect (i.e. the north-south between transect lines) were not included in these analyses. Menhaden schools were defined using a modified school detection algorithm adapted from Fernandes (2009) and then visually inspected to remove scattering from other sources (e.g. zooplankton) (Fig. 2A–B). The smoothed SV from all three frequencies were summed and total values less than −160 dB were removed, which filtered out non-school backscatter (Fernandes, 2009). This mask was then applied to the 120 kHz echogram resulting in the isolation of aggregations; schools

2. Methods 2.1. Survey design Twenty four acoustic surveys were conducted at two regions (12 surveys for each area) approximately 6 km south of Long Island, New York. The Atlantic Beach region was centered at approximately 40° 31.884′ N, 73° 43.445′ W with a survey area of 1.67 km2. The Hempstead region was centered at 40° 31.250′ N, -73° 32.595 with a survey area of 3.01 km2 (Fig. 1A). Both locations had average depths of approximately 20 m. Surveys were conducted on 15–18 August 2014, 16–17 April 2015, 19–20 May 2015, 12 and 16 June 2015, 13–14 July 2015, 12–13 August 2015, and 10 September 2015 typically between 08:00 and 17:00 Eastern Standard Time (EST). With the exceptions of April, May, and September 2015, two surveys were conducted within each region each month. Only one survey was conducted at Hempstead during April and September 2015 and at Atlantic Beach during May and September 2015. The survey vessel ran multiple, roughly-parallel eastwest transect lines that varied in length at each site (Fig. 1B–C). The heading of transects were reversed depending on wind direction and sea state. The presence of menhaden schools was ground-truthed within the sampling regions using underwater video and visual observations of surface schools. While there are other fish species that occur in schools 230

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Fig. 1. Acoustic surveys were conducted off the southern coast of Long Island (A) approximately 6 km offshore at two sites: Atlantic Beach (circle) and Hempstead (triangle). Example survey track-lines from 10 September 2015 at Atlantic Beach (B) and Hempstead (C) comprised semi-parallel transects. Water depths ranged from 16 to 20 m and from 14 to 22 m at Atlantic Beach and Hempstead, respectively.

step, and a minimum TS threshold of -60 dB were rejected. An additional algorithm was adapted using the Sawada Index (NV) which represents the number fish per reverberation volume (Sawada et al., 1993). All single target TS values in cells with NV > 0.10 were rejected (Fig. 2C).

Table 1 Instrument and calibration settings for each echosounder used in the survey.

Manufacturer Beam Pattern Pulse Length (ms) Ping Interval (s) Transmit Power (W) Half-power Beam Width (Degrees) Equivalent Beam Width (dB re 1 str) Transducer Gain (dB) Absorption Coefficient (dB/m)

38 kHz

120 kHz

200 kHz

Simrad Single-beam 0.256 0.500 1000 15.20 −14.00 17.50 0.010

Simrad Split-beam 0.256 0.500 1000 7.00 −21.00 27.00 0.038

Simrad Single-beam 0.256 0.500 1000 7.20 −20.50 26.30 0.053

2.3. Abundance and biomass estimation A multi-step approach was used to estimate menhaden abundance and biomass based on acoustic measurements. Mean NASC for each sampling month was calculated using a method for stratified analysis of multiple strata adapted from Jolly and Hampton (1990). Each survey was split into approximately longitudinal (i.e., eastward and westward) transect segments (N = 228 across all surveys). NASC from menhaden schools along each transect were weighted based on their school-totransect length ratio and then averaged. The first and second strata were the daily and monthly mean NASC at each site respectively. Daily mean NASC was estimated by taking a weighted-mean via:

were then hand-drawn for additional measurements. For comparisons between schools, all energetic (i.e., NASC, TS) and positional (i.e., longitude, latitude, distance from bottom, vertical position in water column or depth) descriptors were exported from the filtered 120 kHz echogram. We assumed that each school detection was an independent measurement (i.e. fish schools were not moving between transect lines and being repeatedly detected) due to our vessel survey speed and distance of and between transect lines (1–4 km). The Echoview single-target detection method 2 algorithm was used for single target analysis. Parameters used to filter out single targets were relaxed from recommended settings (Ona and Barange, 1999) due to the observed patchiness of schools and number of single targets per bin. Single targets outside a maximum beam compensation of 3 dB, normalized pulse length between 0.60 and 1.50, phase deviation of 1

NASCds = wtds =

n 1 ∑ ds wtds NASCtds ni d=1

Ltds nds 1 ∑ n ds t=1

Ltds

(1)

(2)

where NASCds is the mean NASC for day d at site s, nd is total number of transects for day d, wtds is the weight applied to transect t, L is the along-track distance (m) of each transect line. The monthly mean (NASCms) was estimated using a slightly modified form of Eq. (1) where: Fig. 2. Echograms (120 kHz) of a relatively dense menhaden school at Hempstead on 15 August 2014 before (A) and after (B) applying the school detection algorithm. A single target detector algorithm was used to produce measurements of individual fish TS (C). The bottom-exclusion line (thick black line) was set 0.5 m above the sea floor. Panels A and B are SV echograms while panel C is an echogram of in situ single target TS measurements.

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NASCms =

n 1 ∑ ms wtms NASCtms. nm d=1

u (σbs ∨ Lm) =

(3)

∑s Sm NASCms ∑s Sm

2.4. Statistical analysis

(4)

where Si is the total survey length at site s during month m. Monthly mean σbs (the acoustic backscattering cross-section [m2] which is the linear transform of TS), was calculated by weighting daily site σbs means by their respective survey length. The areal fish numerical density (ρA, fish m−2) was then estimated via:

ρA =

NASCm 4πσbs (1852)2

The spatial structure of menhaden schools were characterized using a cluster coefficient which was estimated by:

Cdr =

(5)

3.1. Spatial distribution of schools

(6)

Schools of menhaden were observed throughout both survey regions with no consistent pattern in school location or fish density (fish m−2) (Fig. 3). School NASC ranged from 1000 to 400,000 m2 nmi−2 and was highly variable (CV = 1.6; Fig. 5), which coincided with significant differences in mean transect NASC among survey months (F6,144 = 3.47, p = 0.01, ANOVA), between regions among survey months (F6,144 = 7.98, p < 0.01), but not between regions (F6,144 = 0.02, p = 0.89). There was a moderately strong correlation between school NASC and thickness (ρ(85) = 0.50, p < 0.01; Fig. S1) whereas the relationship between NASC and school length was relatively weak (ρ(85) = 0.32, p < 0.01). Aspect ratios of fish schools (length/thickness) were quite variable, ranging from 0.96 (roughly symmetrical) to 20.70 (horizontally-long, vertically-compressed), and were independent of depth (ρ(85) = −0.14, p = 0.22; Fig. S2). However, there was no significant correlation between these school aspect ratios and their respective NASC (ρ(85) = 0.02, p = 0.82). Overall, the relative range between the minimum (NND = 50 m, Cdr = 0.06) and maximum (NND = 550 m, Cdr = 0.49) NND and Cdr values, respectively, suggests that there was evidence of clustering among schools during all surveys at the spatial scale of our analysis (Fig. S3). This spatial clustering was also reflected in how schools were distributed among transect lines. A total of 85 individual transects (out of 190) contained schools with 22 transect lines containing two or more schools. A maximum of six schools per single transect was observed on 12 August 2015 at Atlantic Beach compared to the overall mean of 0.5 schools per transect (CV = 0.2). Although there was evidence of strong spatial clustering among schools, there was no significant correlation between mean transect NASC and Cdr (ρ(9) = −0.45, p = 0.22) or the number of observed schools (ρ(9) = −0.42, p = 0.26) which suggests that the observed differences in inter-school NASC were controlled, in part, by other factors.

(7)

where W is mean weight in grams and TLmm is the mean TS-derived fish total length (mm). It was assumed that this weight-length relationship was the same for all encountered fish. Biomass (kg) was estimated by first converting W into kilograms and then multiplying by abundance: B=NWkg . Trends in abundance and biomass were examined within each region (Eq. 1) and as an aggregate (Eq. 4). The monthly coefficient of variation (CV) for NASC (Jolly and Hampton, 1990) was calculated using:

CV=

Var(NASCm) NASCm

(8)

Total uncertainty, or the combined standard uncertainty (CSU), for extrapolated monthly abundance and biomass estimates was calculated using the ‘root sum squared’ (RSS) method (Taylor and Kuyatt, 1994):

u (Nm ∨ Bm) =

u (NASCm ) u (σbs ) u (Lm ) + + NASCm σbs Lm

(9)

where terms in the numerator and denominator represent the standard uncertainty and mean for the mth month respectively. A Type A evaluation of uncertainty (Taylor and Kuyatt, 1994) was used to estimate standard uncertainties for each term:

u (NASCm) =

u (NASCm ) nm

(12)

3. Results

where TLcm is the fish total length (cm). The resulting length from Eq. (6) was then used to convert TS into biomass by producing a body length estimate and using the average regression coefficients calculated from the annual empirical weight-length relationships specific to Atlantic menhaden using landing data (ASMFC, 2017):

ln(W ) = −11.396 + 3.08ln(TL mm)

NND MND

where Cdr is the daily cluster coefficient, NND is the mean nearest neighbor haversine distance, and MND is the mean neighbor haversine distance between all schools (Hijmans, 2016). This Cdr index has a standardized range from 0 to 1 which represents if schools tend to be more closely associated with each other (i.e., Cdr < 0.5) or are evenly distributed (i.e., Cdr > 0.5) in space, respectively. The Cdr was calculated daily for each region where more than two schools were encountered. A type II analysis of variance (ANOVA, α = 0.05) was used to test for significant differences in the mean TS (in the linear domain) and log10-transformed NASC (Fox and Weisberg, 2014). A post hoc Tukey’s Honest Significance Test (Tukey HSD, α = 0.05) was used for pairwise comparisons among survey months and between sites. Lastly, descriptive statistics (i.e., mean, medians, measures of dispersion) were used on a school-by-school basis to examine school NASC (m2 nmi−2), length (m), thickness (m), and mean depth (m). A Spearman (ρ, α = 0.05) correlation coefficient test was used to describe any significant relationships between school parameters.

Numeric menhaden abundance was calculated via N=ρA A (Simmonds and MacLennan, 2005) where N is the monthly abundance (# fish) and A is the total site area (km2). In order to calculate biomass, monthly mean σbs was transformed to TS and converted into a comparable standard fish length (cm) using a TS-length model (described below). Acoustic-derived packing densities were compared to theoretical maximum values using the relationship for Atlantic herring described by Pitcher and Partridge (1979): 0.7BL−3, where BL is the fish body length in m. Due to the absence of a dorsal TS-length model specific to Atlantic menhaden, several published models for clupeids were considered (Appenzeller and Leggett, 1992; Brandt et al., 1991; Degnbol et al., 1985; Lassen and Stæhr, 1985; Love, 1971; Lucca and Warren, 2018; Nakken and Olsen, 1977; Thomas et al., 2002) in reference to the expected range of length estimates provided by landings for adult fish (ASMFC, 2010, 2017) and an average of the a and b coefficients were used:

TS=20.40log10 (TL cm) − 68.88

(11)

where σ is the standard deviation and n is the number of samples for each term. All CSU estimates are expressed as percentages.

now represents the mean daily NASC at site s during month m. The third and final stratum consisted of estimating the mean between both sites:

NASCm =

σm nm

(10) 232

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Fig. 3. Spatial distribution of all fish schools at Atlantic Beach (left) and Hempstead (right) measured during each sampling month. Color of each point is scaled to acoustically-estimated areal fish density (fish m−2) for each school. Gray lines represent a sample cruisetrack from each month and site as multiple surveys were conducted during most months.

school TS (variance: 21.1 to 14.5 dB2). Therefore, schools with sufficient sample sizes (n > 25) had similar in situ TS measurements for single targets (i.e. individual fish).

3.2. In-situ target strength Significant differences in the mean linear-transformed single target TS were detected among survey months (F6,2783 = 1884.36, p < 0.01; ANOVA; Figure S4), between each site (F1, 2783 = 5.33, p = 0.02), and between each site among months (F6,2783 = 5.33, p < 0.01). These significant differences were likely driven by the presence of large, dense schools observed during August 2014 at Atlantic Beach (mean TS = −32.8 dB, n = 68) and during July 2015 at Hempstead (mean TS = −35.7 dB, n = 57). These dense schools were often characterized as having a “cloud” of weak acoustic backscatter (SV < −60 dB, TS < −60 dB) directly below them (Fig. 4), likely the result of multiple scattering effects (Sawada et al., 1993). Across all schools, the inter-quartile range (IQR) of single target TS values per school ranged from 0.2 to 25.1 dB (mean =5.7 dB); however, both the mean and IQR of single target TS within schools were heavily influenced by their respective sample sizes. This effect whereby both the IQR and mean school TS estimates varied significantly among schools became more constrained once the sample size exceeded 25 single targets. Likewise, the TS distributions with and without these smaller samples were significantly different (Kolmogorov-Smirnov test, D = 0.184, p < 0.01). Once removed, variability decreased substantially in both inter-school IQR (variance: 11.3 to 1.1 dB2) and mean

3.3. Abundance and biomass distributions Using commercial landings data between 2000 and 2016 (ASMFC, 2017), age-1+ fish lengths ranged from 130 to 360 mm. These lengths correspond to a theoretical packing density range of 10–290 fish m−3. Comparatively, fish observed in video screenshots were spaced approximately 0.25 body lengths apart from one another (Fig. 5). Using acoustically-derived monthly mean fish lengths (220 to 290 mm) we estimated maximum theoretical packing densities which ranged from 20 to 50 fish m−3. The weighted mean volumetric fish density among schools was 4.2 fish m−3 with very few schools having densities on the same order of magnitude as the estimated maximum theoretical packing densities (ρV > 10 fish m−3, n = 4). When only schools with more than 25 single targets and a mean TS values within the overall IQR (−45.1 to −39.6 dB, or 160 to 280 mm) are analyzed, the weighted mean acoustic-derived volumetric density is similar, 4 fish m−3, with a range of 1–7 fish m−3. Aside from a single school in April, there was a clear temporal trend whereby menhaden were only present from mid-summer to fall (Table 2). Between the two sites, biomass and abundance were highest

Fig. 5. Video observations of a menhaden school in the coastal waters of Long Island during September 2015 were used to estimate fish packing density. Spacing between fish was approximately 0.25 body lengths. Assuming a single fish falls within the observed length ranges for adult fish from commercial landings data (130–360 mm), the estimated maximum packing density of this school ranged from 10 to 40 fish m−3. Screen capture from a video provided by Dr. Mark Bond.

Fig. 4. Menhaden schools varied widely both in school size, density of fish within the school (1.5 and 3.1 fish m−3) and fish abundance as measured by school NASC (20,000 and 397,000 m2nmi−2). Values provided are for the left and right panels respectively. 233

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is poorly represented in the literature, it is difficult to infer any significant spatial patterns along the coast. Menhaden schools were first observed in summer months with the exception of a single school measured in April 2015. Similar acoustic fish densities between sampling sites suggest that the influx of menhaden biomass into the survey regions during the mid-summer is constant. Likewise, the number of fish schools and inter-school clustering may have contributed to the peak densities observed in August 2015, with the exception of August 2014. Although increasing abundance and biomass of menhaden from spring to fall is consistent with previous observations (Ahrenholz, 1991; McHugh, 1972), the total area of our survey regions (4.68 km2) represents an extremely small proportion of the fish habitat in the coastal waters of New York. Therefore, the scalability of our abundance and biomass estimates are limited for three reasons: sampling small areas will likely result in missed schools (e.g., menhaden can be observed upwards of 50 km offshore, Quinlan et al., 1999), high variability in school abundance and spatial distribution, and our survey uncertainty is amplified with extrapolation. However, the estimates of peak abundance and biomass in this study correspond to 2% and 11% of the estimated U.S. total stock respectively (ASMFC, 2017), so the use of acoustic methods to measure Atlantic menhaden produces realistic values. The use of a stratified survey design reduces bias in both abundance variance/error estimates (Simmonds and Fryer, 1996), thereby allowing data-poor environments to be sampled with relatively high statistical rigor (Jolly and Hampton, 1990). For example, weighting in situ TS and NASC contributions from schools by the number of single target detections and school-to-transect length ratio helps to reduce the relative influence of extremely dense schools that drove the observed significant differences in TS between regions and among survey months. This is critical since even small changes in mean TS can contribute to large changes in TS-derived fish lengths and ultimately biomass. Using the weighted TS value results (−41.4 to −39.0 dB, or fish lengths between 220 and 290 mm) in an approximate doubling of estimated fish abundance while also producing reasonable volumetric densities that fall below theoretical maximum packing densities. Therefore, to produce more accurate estimates of fish biomass, it is important to avoid using a single TS value for an “average” fish to convert backscatter measurements to estimates of biomass. The monthly mean TS values not only remained relatively consistent, but also fell within body length ranges consistent with age-1+ fish (ASMFC, 2017) that would be expected to be found offshore. Since the growth rate of adult menhaden is significantly slower than that of age-0 fish (Reintjes, 1969), it would be expected that the overall TS distribution would not undergo large shifts due to a relatively consistent age class of similar size ranges. Likewise, non-significant differences in mean TS (when excluding the abnormally-dense schools which likely had biased TS estimates due to multiple scattering, Sawada et al., 1993) between survey regions suggests that there was no spatial age class separation either. Conversely, TS-derived volumetric fish densities within schools were substantially smaller than what would be normally predicted for other clupeids and what was observed using video analysis; however, the lack of packing density models specific to menhaden and video analysis of only one school limits what can be conferred from these comparisons. Moreover, the lack of net sampling to validate species composition and size-at-age distributions of schools introduces additional uncertainty into both TS and biomass estimates. Improving the methods used to estimate menhaden abundance and biomass to allow for broader spatiotemporal sampling is important for quantifying the absolute magnitude of changes in stock abundance and biomass of fish in situ instead of relying on data from trawled animals. The relative uncertainties among TS-length models used to convert abundance to biomass and the change in size classes over time reflect the need for an adaptive conversion factor as opposed to the use of a single value. Previous observations of time-varying growth for

Table 2 Extrapolated abundance (# fish km−2), biomass (kg km−2), and combined standard uncertainty (CSU, %) for Atlantic Beach and Hempstead survey regions during each sampling month. CSU represents the weighted mean output from multiple surveys at both Atlantic Beach and Hempstead using Eq. (3). Atlantic Beach and Hempstead survey areas were 1.67 and 3.01 km2 respectively. Atlantic Beach Survey Month

N (fish km−2)

B (kg km

Aug-2014 Apr-2015 May-2015 Jun-2015 Jul-2015 Aug-2015 Sep-2015

74,000 < 1000 0 0 21,000 157,000 25,000

33,000 < 1000 0 0 6000 35,000 4000

Hempstead −2

)

CSU (%)

N (fish km−2)

B (kg km−2)

CSU (%)

16 14 0 0 21 14 24

141,000 0 0 0 22,000 11,000 93,000

51,000 0 0 0 1000 3000 14,000

19 0 0 0 19 22 28

at Atlantic Beach during August 2015 and at Hempstead during August 2014, respectively. When both regions are grouped (Eq 3), the overall and 2015 peak biomass densities were observed during August 2014 (41,000 kg km−2) and 2015 (18,000 kg km−2), respectively. The aggregate abundance and biomass estimates produced relatively more conservative estimates than the region-specific values with the exception of April 2015. When abundance and biomass estimates were partitioned out by region, the peak monthly region-specific biomass (6000–51,000 kg km−2) eclipsed the aggregated estimates (4000–41,000 kg km-2) between July and September 2015. As a way to check the feasibility of these numbers and assuming the aggregated monthly biomass densities were representative of the overall coastal distribution of menhaden along Long Island (a region approximately ˜15 km cross-shore, ˜194 km along-shore), total biomass would range from 490,000 to 120,610,000 kg, or roughly up to 11% of the total stock in 2015. There was relatively high uncertainty in these abundance and biomass estimates (14–28% and 12–19% for the region-specific and aggregated, respectively). Cruisetrack length, TS, and NASC all contributed relatively similar uncertainty to the abundance and biomass estimates (1–12%, 8–17%, and 5–17% respectively). When these uncertainty estimates were incorporated, the peak abundance and biomass along the coast of Long Island ranged from 228,000,000 to 308,000,000 fish and from 103,000,000 to 139,000,000 kg, respectively. 4. Discussion Similar to the relative patchiness of other schooling fish species such as Pacific sardines (Demer et al., 2013) and estuarine menhaden (Lucca and Warren, 2018), offshore menhaden schools were not uniformly distributed throughout the survey and had varying along-track lengths and thicknesses. The clustering patterns in the observed menhaden schools differed from spatial trends observed in other forage fish such as consistent inter-school distances and a strong relationship between the number of schools and clustering (Petitgas et al., 2001); however, it is unclear how observed clustering patterns in this study reflect standard spatial heterogeneity of menhaden schools due to the relatively high degree of variability. Otherwise, clustering did not appear to coincide with changes in school presence over the course of the summer from July to September. Vessel avoidance behavior may have also influenced schools’ vertical position in the water column, spatial clustering, and relative areal fish densities (fish m−2) (De Robertis and Handegard, 2013). Qualitatively, menhaden schools were most abundant in August 2015 which coincided with peak abundance, biomass, and school clustering among all surveys in 2015. However, since the explicit spatial and temporal distributions of menhaden in New York coastal waters 234

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menhaden (Schueller and Williams, 2017), supports the use of an adaptive length-weight regression relationship. Likewise, although aerial surveys can identify the spatial extent of schools (Churnside et al., 2011), they are not able to provide reliable estimates of fish numerical densities except when done in conjunction with purse seine fishers. The combination of aerial sampling, net trawls, and active acoustic surveys can provide a more precise estimate of stock abundance and biomass. Improvements to future acoustic trawl survey designs can reduce uncertainty in acoustic estimates of abundance and biomass by incorporating data quantifying how menhaden interact with survey vessels (De Robertis and Handegard, 2013) and developing menhaden-specific TS models (Simmonds and Maclennan, 2005). The incorporation of acoustic surveys (including trawl ground-truthing) will help better inform multispecies and ecosystem-level models used in the northwest Atlantic that include menhaden distributions as a key ecological component for the stocks of higher trophic species such as bluefin tuna (Butler et al., 2010), striped bass (Sanchirico et al., 2008), weakfish, and bluefish (e.g., MSVPA-X, Garrison et al., 2010). Although the menhaden stock is currently classified as healthy, the population collapse in the 1950s (ASMFC, 2017; McHugh, 1972), the general depletion of other forage fish (Essington et al., 2015), and expansion of industrial fishing pressures into new areas raise concerns for the recovery of higher trophic species. Acoustic estimates of menhaden abundance and biomass can be used to validate the numbers provided by the current single-species stock assessment (ASMFC, 2017) and to measure the abundance of these fish in local (Lucca and Warren, 2018), regional, or larger spatial habitats as part of ecosystem process studies.

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5. Conclusion This study demonstrates that active acoustics is capable of providing fishery-independent estimates of abundance, biomass, and spatiotemporal distributions of menhaden in coastal waters. This method produced reasonable values of fish abundance and biomass, which are necessary to better understand the coastal ecosystem and effects of local processes such as commercial fishing and natural mortality. Moreover, acoustic survey data can be used to assess changes in stock abundance and biomass that can be useful for validating assessment results. Acknowledgments We would like to thank Captain Brian Gagliardi for assisting in logistics and operations aboard the R/V Paumanok. Samuel Urmy, Hannah Blair, Julie Cossavela, and Alfredo Esposito assisted with the collection of acoustic and CTD data. Bradley Peterson, Stephen Heck, Amanda Tinoco, Gina Clementi, and Amber Stubler assisted with set up and deployment of equipment. We also thank Kevin Boswell, Bradley Peterson, and Justin Bopp for their valuable comments on early drafts of this manuscript. Mark Bond provided underwater video footage of offshore menhaden schools. Data were collected during surveys funded by the State of New York Department of Environmental Conservation to assess the role of artificial reefs in the coastal ecosystem of Long Island. The opinions, findings, and interpretations of the data contained herein are solely those of the authors and do not necessarily represent the opinions, interpretations, or policy of the Department of Environmental Conservation or the State of New York. Appendix A. Supplementary data Supplementary material related to this article can be found, in the online version, at doi:https://doi.org/10.1016/j.fishres.2019.05.016. References Ahrenholz, D.W., 1991. Population biology and life history of the North American menhadens, Brevoortia spp. Mar. Fish. Rev. 53, 3–19. https://doi.org/10.1111/bjd.

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