Vertical distribution of alewife in the Lake Ontario offshore: Implications for resource use

JGLR-01240; No. of pages: 15; 4C: Journal of Great Lakes Research xxx (2017) xxx–xxx

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Vertical distribution of alewife in the Lake Ontario offshore: Implications for resource use Milan Riha a,f, Maureen G. Walsh b,⁎, Michael J. Connerton c, Jeremy Holden d, Brian C. Weidel b, Patrick J. Sullivan e, Toby J. Holda a, Lars G. Rudstam a a

Cornell Biological Field Station, Department of Natural Resources, Cornell University, Bridgeport, NY, USA USGS Great Lakes Science Center, Lake Ontario Biological Station, Oswego, NY, USA New York Department of Environmental Conservation, Lake Ontario Research Unit, Cape Vincent, NY, USA d Ontario Ministry of Natural Resources and Forestry, Lake Ontario Management Unit, Glenora Fisheries Station, 41 Hatchery Lane, Picton, ON, Canada e Department of Natural Resources, Cornell University, Ithaca, NY, USA f Biology Centre CAS, Institute of Hydrobiology, Ceske Budejovice, Czech Republic b c

a r t i c l e

i n f o

Article history: Received 26 September 2016 Received in revised form 14 July 2017 Accepted 20 July 2017 Available online xxxx Keywords: Diel vertical migration Deep chlorophyll layer Zooplankton Mysids Alewife Hydroacoustics

a b s t r a c t Oligotrophication of Lake Ontario has led to increased water clarity and an increased proportion of zooplankton residing in the metalimnion during the day, which may affect the utilization of different depth regions for planktivorous fish. We investigated day and night distributions of fish using hydroacoustics and suspended vertical gillnets during the summer of 2013 when a deep chlorophyll layer (DCL) was established. We related fish distributions to concurrent measures of temperature and prey (zooplankton) density. Alewife dominated in vertical gill net catches, indicating that most acoustic targets were alewife. Alewife schooled during the day in the bottom of the mixed layer, and at dusk alewife schools broke up and fish moved towards the surface. We hypothesize this movement followed migrating zooplankton to allow feeding at night; alewife sampled from vertical gillnets fed on cyclopoid copepods and cladocerans, prey groups that migrate into the epilimnion at night. Some alewife remained at the bottom of the mixed layer at night and these fish ate deep-water calanoid copepods such as Limnocalanus. Vertical distributions were best predicted by temperature and the interaction between temperature and zooplankton density. We include uplooking acoustics data to complement our downlooking datasets, which provided evidence for potential bias in downlooking acoustic assessments of alewife due to high proportions of alewife found in the surface exclusion zone. Our approach combining several datasets provides a new perspective to understand summer diel distribution of alewife and the factors driving their distribution. Published by Elsevier B.V. on behalf of International Association for Great Lakes Research.

Introduction Oligotrophication associated with decreasing nutrient loading and dreissenid mussel invasion has occurred in the Laurentian Great Lakes in the last several decades (Barbiero et al., 2014, 2012; Bunnell et al., 2014), and has contributed to varying ecological change depending on the species present in each Great Lake. In Lake Ontario, nutrient loading stabilized around 1995 and in-lake total phosphorus concentration has ranged between 5 and 10 μg/L since that time (Dove and Chapra, 2015; Holeck et al., 2015). The Lake Ontario fish community has a high proportion of non-native species at all trophic levels. Most prominent in the system are Pacific salmon (primarily Chinook salmon Oncorhynchus tshawytscha) and their dominant prey, the alewife Alosa pseudoharengus ⁎ Corresponding author at: USFWS Panama City Field Office, 1601 Balboa Ave, Panama City, FL 32405, USA. E-mail address: [email protected] (M.G. Walsh).

(Mills et al., 2003). Alewives have been present in Lake Ontario since the 1860s (Smith, 1970), and they are important drivers of lake ecology through intensive pelagic predation that both structures zooplankton communities (Johannsson et al., 1991) and impacts native fishes (Madenjian et al., 2008). Alewife consume a variety of pelagic prey items, including the native Mysis diluviana, native and invasive cladocerans, and copepods (Stewart et al., 2009). In the mid-2000s, decreases in primary production and zooplankton in Lake Ontario was counterintuitive to the consistently high alewife biomass and condition in the Lake (Walsh et al., 2016). Alewife are the main prey fish for the salmonids, especially Chinook salmon (Mills et al., 2003). Subsequent research led to an increased understanding of changes in the vertical structure and distribution of primary production and zooplankton. Epilimnetic zooplankton abundance in Lake Ontario declined almost an order of magnitude in the mid-2000s; however, this decline in epilimnetic zooplankton was not associated with a decline in the biomass of zooplankton in the whole water column due to

http://dx.doi.org/10.1016/j.jglr.2017.07.007 0380-1330/Published by Elsevier B.V. on behalf of International Association for Great Lakes Research.

Please cite this article as: Riha, M., et al., Vertical distribution of alewife in the Lake Ontario offshore: Implications for resource use, J. Great Lakes Res. (2017), http://dx.doi.org/10.1016/j.jglr.2017.07.007

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M. Riha et al. / Journal of Great Lakes Research xxx (2017) xxx–xxx

increases in larger, cold-water calanoid copepods (Limnocalanus macrurus and Leptodiaptomus sicilis) (Barbiero et al., 2014; Rudstam et al., 2015). During the summer of 2008, over 90% of the zooplankton biomass was found below the thermocline during daytime (Rudstam et al., 2015). The proportion of primary production associated with the phytoplankton in the deep chlorophyll layer (DCL) may have increased (Twiss et al., 2012; Watkins et al., 2015) and more of the lower trophic level production may now occur in deeper water, at least in the summer months. Given that the decline in epilimnetic zooplankton was not associated with declines in alewife growth rate or condition (O'Gorman et al., 2008; Walsh et al., 2016), we questioned the assumptions that alewife in Lake Ontario are mainly using epilimnetic zooplankton resources. Understanding how alewife use the lower trophic levels is important if we are to couple observed and future changes in nutrient loading, primary production and secondary production with the future of the valuable salmonid fishery in the lake. Understanding how and when alewife feed on zooplankton and mysids requires an understanding of their vertical distribution. Alewife diet analyses from Lake Ontario in the 2000s showed an increase in use of mysids (Boscarino et al., 2010; Stewart et al., 2009), calanoid copepods and Bythotrephes (O'Gorman et al., 2008). This suggests a shift in the vertical distribution of alewife from being mainly epilimnetic in the 1980s (Olson et al., 1988; Urban and Brandt, 1993) to using deeper water and therefore colder temperatures. However, the literature suggests that alewife select temperatures from 15 to 20 °C for adults and 17 to 26 °C for age-0 (Brandt et al., 1980; Kellogg, 1982; McCauley and Binkowski, 1982; Otto et al., 1976; Simonin et al., 2012), and both age groups should avoid temperatures below 10 °C during summer (Brandt et al., 1980; Brandt, 1980). Therefore, alewives should have a difficult time accessing mysids and Limnocalanus which generally reside below the thermocline (Barbiero et al., 2014; Boscarino et al., 2010; Rudstam et al., 2015). In other lakes, alewife avoid cold meta- and hypolimnion water during summer (Dahlberg, 1981; Simonin et al., 2012). However, alewives have been found close to the thermocline feeding on mysids in Lake Ontario (Boscarino et al., 2010). Brandt et al. (1980) found adult alewife concentrated at or below the thermocline in Lake Michigan during the day and migrated to the epilimnion at night. Such results suggest higher plasticity of alewife vertical distribution and an ability to occupy a broader range of temperatures than suggested by temperature preference experiments, and therefore they may have the potential to feed on zooplankton concentrated below the thermocline in Lake Ontario. Vertical migration and distribution models typically include temperature, prey availability, foraging efficiency and predation risk (e.g. Gilliam and Fraser, 1987; Mehner et al., 2007; Jensen et al., 2011; Ahrenstorff et al., 2011). We did not have data on light intensity or predator presence or density, so we did not attempt to include these parameters. Instead we focused on understanding alewife vertical distribution in relation to temperature and spatial overlap between alewife and their zooplankton prey. It is likely that temperature and prey availability determine the trophic profitability of different depth strata for zooplanktivorous fish including alewife, so we hypothesized these two important variables would be the primary drivers of alewife resource use during summer months. As for most fish species, alewife growth and consumption rates are affected by temperature (Stewart and Binkowski, 1986) with the maximum consumption rate occurring at temperatures close to the preferred temperature (Coutant, 1977) that can also be used to predict vertical distributions (Rudstam and Magnuson, 1985). Martin et al. (2011) found temperature as the most important factor structuring larval fish distribution in Lake Michigan, and Simonin et al. (2012) found most support for predicting the vertical distribution of age-0 alewife in Lake Champlain using a model with temperature and light. We only included light indirectly by evaluating the effect of temperature and zooplankton prey on alewife distributions separately for night and day conditions.

In Lake Ontario, a summer hydroacoustic survey occurs annually (Connerton and Holden, 2015), but data are only collected at night, so there is only limited historical information on the diel changes in fish vertical distribution in Lake Ontario. A focus of the multi-agency Cooperative Science and Monitoring Initiative (CSMI) field year in 2013 for Lake Ontario was understanding the vertical restructuring of all trophic levels (nutrients, algae, zooplankton and fish) as a result of the oligotrophication of the lake. As part of that program, we investigated diel patterns in alewife vertical distribution to try to better understand the potential use of zooplankton resources in the DCL by alewife, and how prey distribution and temperature relate to alewife distribution. Our objectives were (1) to describe and compare vertical distribution of alewife during day and night in the Lake Ontario offshore, including a period when a DCL was established in the lake, and (2) to explore relationships between night alewife distribution and temperature and prey density during stratified conditions. Materials and methods Description of acoustic datasets We investigated relationships between vertical fish distribution (we investigated only fish of age-1 and older as data about age-0 fish were not available) and potential environmental drivers using two primary datasets collected during 2013. The first dataset (herein referred to as Oswego) was collected by the United States Geological Survey's (USGS) Great Lakes Science Center (GLSC) and contains paired day and night data obtained along one transect (bottom depth 5–200 m) located near Oswego (NY, USA; Fig. 1) sampled once in July, August and September. Acoustic data were collected with a 120 kHz down-looking transducer (BioSonics DtX) deployed through the hull of the USGS R/V Kaho (Table 1). Environmental variables (temperature and zooplankton vertical distributions) were also collected for this dataset and fish diet and vertical distribution were sampled using vertical gillnets (description below). The second dataset (Lakewide) was collected from the United States Environmental Protection Agency's (USEPA) R/V Lake Guardian (bottom depth 60–230 m) and contains data from four open lake transects in July and September (Fig. 1, Table 1). Similar to Oswego, acoustic data were collected both day and night with a 120 kHz downlooking transducer (BioSonics DtX; and environmental variables (temperature, chlorophyll, and zooplankton vertical distributions) were measured. We included a third complementary dataset (Uplooking) to investigate distribution of alewife near surface in the epilimnion. Standard down-looking acoustic sampling (as applied for data gathering in Oswego and Lakewide datasets) does not provide information about fish close to the surface (from 0 to ~5 m, due to tow depth and near field dynamics, Parker-Stetter et al., 2009), often referred to as the surface blind zone. This habitat is important to alewife at night (Simonin et al., 2012; Connerton and Holden, 2015), therefore, alewife density estimated using downlooking acoustics can be biased if fish are present in surface waters not sampled by downlooking acoustics. To investigate fish occurrence close to the surface during the night, we used acoustic data collected by the New York State Department of Environmental Conservation (NYSDEC) and the Ontario Ministry of Natural Resources and Forestry (OMNRF) using a BioSonics DTX SUB 120 kHz transducer that is towed at depth and looks upward (Table 1). The echosounder and transducer were mounted in a tow-body and attached to a trawl door towed at about 40 m depth with the transducer facing towards the surface. The trawl door acted as a depressor for the towfish and pulled it off to the port side of the vessel approximately 75 m to avoid surface-noise and bubbles generated by the vessel wake. Acoustic sampling was performed at three transects (8–24 km long spanning 40 m to 120 m bottom depth) along the southern shore of the lake during July 2013 and was accompanied by vertical gillnet sampling at location 3, the farthest east of the three sites (Fig. 1).

Please cite this article as: Riha, M., et al., Vertical distribution of alewife in the Lake Ontario offshore: Implications for resource use, J. Great Lakes Res. (2017), http://dx.doi.org/10.1016/j.jglr.2017.07.007

M. Riha et al. / Journal of Great Lakes Research xxx (2017) xxx–xxx

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Fig. 1. Map of acoustic sampling conducted during the 2013 Cooperative Science and Monitoring Initiative (CSMI), including one transect off Oswego, NY sampled by the USGS with the R/V Kaho (Oswego dataset, OG-1), four lakewide transects sampled by the USEPA and Cornell University with the R/V Lake Guardian (Lakewide dataset, LW), and three locations where uplooking acoustics were used by the NYSDEC and OMNRF (Uplooking dataset, UL).

All transducers were calibrated prior to sampling using standard tungsten carbide calibration spheres. Data acquisition of the Oswego and Lakewide datasets were conducted during day and night on every date, with day surveys ending at least 1 h prior to sunset and night surveys starting at least 1 h after civil sunset. The Uplooking dataset was only collected during night. For all datasets, the threshold used during acoustic data collections was lower than − 100 dB, as per the Great Lakes standard procedures (Parker-Stetter et al., 2009). Analysis of acoustic data: fish distribution during the nighttime For the night-collected data in the Oswego and Lakewide datasets, we processed hydroacoustic data using Echoview version 5.4 (Myriax Software Pty Ltd.) following the standard operating procedures for hydroacoustic surveys in the Great Lakes (Parker-Stetter et al., 2009; Rudstam et al., 2009) with some modifications described below. We defined analysis regions vertically in the water column based on visual examination of the echograms and TS histograms such that resulting analysis regions were layers with homogenous TS distribution of fish echoes. The surface layer was defined by identifying the presence of Mysis diluviana in a layer, and setting the boundary just above this “mysid layer”. This boundary was generally between 5 and 20 m below surface and roughly corresponded to the epilimnion. The two deeper layers ranged mostly from 20 to 40 m and N40 m, respectively. Again, boundaries between these two deeper vertical layers were placed after examining histograms of TS distribution such that each of

Table 1 Details of hydroacoustic instruments (transducers) and survey parameters for all datasets used in the study. The uplooking transducer was used in single beam mode because of a phase detection problem in the split mode. Transducer and survey parameters

Frequency (kHz) Beam type Pulse duration (ms) Pulse interval (s) Deployment Beaming direction Transducer depth (m) Cruise speed (m/s) Vessel Date of surveys

Oswego USGS

Lakewide USEPA

Fish

Zoop

120 Split 0.4 1 In hull

430 Single 0.4 1 In hull

Fish

Uplooking NYSDEC/OMNRF Zoop

123 430 Split Single 0.4 0.4 1 1 Towed Towed body body Down Down Down Down 1.3–1.5 1.3–1.5 1.6–2.2 1.6–2.2 2 2 2.5 2.5 Kaho Kaho Guardian Guardian July 11–12 July 18–22 August 6–7 September 30 September 9–13

Fish 121 Single 0.4 1 Towed body Up 40 3.0 Seth Green July 16–18

the three layers represented a homogenous TS distribution within the layer as suggested in the Great Lakes Standard Operating Procedure (Parker-Stetter et al., 2009). We considered targets larger than −55 dB to be age-1 and older fish, primarily alewife (see below). This threshold is based on observation of Parker-Stetter et al. (2006) and Rudstam et al. (2009). They documented that the majority of targets of adult alewife and rainbow smelt (Osmerus mordax) were above −55 dB at 120 kHz. To calculate density of adult fish, we first calculated fish density based on all targets that could be considered fish (TS larger than −70 dB in July, −65 dB in August and −60 dB in September and for all seasons in the metalimnion and hypolimnion). Smaller fish targets are rare below the thermocline in the Great Lakes (Kocovsky et al., 2013). This increase in the TS threshold reflect the occurrence of age-0 fish in the epilimnion and the growth of these fish through the season (Parker-Stetter et al., 2006; Simonin et al., 2012; Kocovsky et al., 2013). A − 60 dB threshold excludes most mysid targets and is a commonly used lower threshold for alewife in inland lakes (Rudstam et al., 2008a, 2011). Density of targets larger than − 55 dB was then calculated at the proportion of these larger targets (out of all targets larger than the minimum threshold) multiplied by the total fish density. To get a finer resolution of fish vertical distribution, volume backscattering coefficients were calculated for cells of the dimensions 200 m of length and 1 m of height. Fish density in each cell (number/ m3) was calculated using mean in-situ TS for the depth zone and layer (see above) and cell-specific volume backscattering coefficients (sv). Sawada's index (Nv, the average number of fish per pulse volume) was calculated for the cells with highest fish density. None of these cells had Nv values N0.10, the value used to indicate a bias in in situ target strength estimates (Parker-Stetter et al., 2009). Total fish density in a cell was divided into different age groups based on the ratio between number of age-0 (b−55 dB) and adult (N− 55 dB) single echoes. The ratio was calculated separately for each depth zone, depth layer and 200 m long interval with at least 30 echoes. If this interval contained b30 echoes, we used echoes from adjacent interval (from the same depth zone and layer) to get at least 30 echoes for the ratio calculation. In the Uplooking dataset, in situ fish target strength measures were not available due a malfunctioning phase detection chip in the transducer, so only sv was calculated. sv indicates relative fish density and fish biomass assuming no change in fish size structure, but absolute fish density requires an assumption or measure of target strength. The minimal threshold was set to −70 dB (TS domain) to include all fish with a TS larger than −64 dB without bias (Parker-Stetter et al., 2009). We calculated vertical distribution of sv with 1 m depth increment at each sampled locality. We checked for occasional larger targets perhaps from salmonids that may bias the results using a smaller grid size of

Please cite this article as: Riha, M., et al., Vertical distribution of alewife in the Lake Ontario offshore: Implications for resource use, J. Great Lakes Res. (2017), http://dx.doi.org/10.1016/j.jglr.2017.07.007

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50 m × 1 m. We detected several outlier sv cells (with sv values over 5 10−6) that would indicate the presence of a larger target and removed those cells from the analysis. Surface noise was evident and variable between transects. This was removed by excluding the affected data close to the surface (upper 2 m).

zooplankton data below 50 m depth because variation in noise levels led to some areas with inflated volume backscattering and therefore erroneous zooplankton densities. This procedure was applied to both diel periods for the Oswego and Lakewide datasets. Vertical gillnet sampling

Analysis of acoustic data: fish distribution during the daytime We observed that the majority of fish targets were found in dense schools during the daytime, rather than dispersed as they are at night, so we were not able to use the same analytical methods that we used for night distribution. Schools were relatively rare, so we did not use sv by depth, instead, we used the school detection module of Echoview to identify schools and calculate school distribution descriptors. School dimensions for detections were set as follows: minimum total school length = 2 m, minimum total school height = 0.75 m, minimum candidate length = 0.5 m, minimum candidate height = 0.5 m, maximum vertical linking distance = 0.5 m, maximum horizontal linking distance = 6 m. To avoid inclusion of zooplankton aggregations, detected schools were filtered and only schools with corrected mean Sv ≥ −65 dB, length ≥ 2 m and height ≥ 1 m were considered fish schools. This step may have filtered out aggregations of smaller fish; we therefore consider our description of day distributions to primarily represent adult fish. To describe the vertical distribution of the schools within the water column, we used four position descriptors. Mean school depth (MSD) and school height (SH, height is defined as the height of a box bounding the region representing a school in an echogram) were calculated using Echoview school detection module. These descriptors were corrected by the Echoview correction algorithm for beam pattern and pulse length (based on Diner, 2001). Further, two additional position descriptors were derived from MSD and SH: the upper depth of the school (herein referred as Depth UP) and the lower depth of the school (Depth DOWN). These were calculated as: Depth UP ¼ MSD−

SH 2

and Depth DOWN ¼ MSD þ

SH 2

We chose to use multiple descriptors of schools because school sizes and vertical distribution varied, and we calculated temperature and acoustic zooplankton biomass at all school descriptors to best investigate relationships of schools with those environmental parameters. Using MSD only to evaluate school structure in relationship to environmental variables could bias results. However, for comparing between day and night distribution (details below) we did consider MSD to be our best available descriptor for this analysis because it was a coarser level of analysis. Analysis of acoustic data: zooplankton distribution Acoustic zooplankton biomass (AZB) which includes mysids was expressed as volume backscattering strength Sv at 430 kHz and was calculated for each acoustic cell (200 m × 1 m) using the same post-processing as described for fish above. Fish targets were excluded from the acoustic records using a procedure for mysid density estimate developed by Rudstam et al. (2008b). First, targets with TS higher than −70 dB were dilated using the 3 × 3 dilation filter on the TS echogram. Second, a mask was created to remove all dilated targets. Third, noise backscattering was removed using the Echoview Noise Removal algorithm (based on De Robertis and Higginbottom, 2007) with settings maximum noise removal = − 125 dB, minimum signal to noise ratio (SNR) = 5 dB. Fourth, volume backscattering coefficients were calculated for each cell from 5 m to 50 m depth. We excluded acoustic

The purpose of using vertical gillnets was to ground-truth acoustic fish targets at depth, evaluate the proportion and species of fish present in the surface area not sampled by downlooking acoustics, and to obtain fish at specific depth layers for diet analysis. Vertical gillnets were deployed in association with the acoustics sampling events at the Oswego, NY transect sampled by USGS in July, August, and September 2013 (Oswego), with nets deployed prior to the start of acoustic sampling and pulled approximately 6 h later after acoustic sampling was completed. An individual vertical gill net consisted of 6 or 12 panels tied together vertically, all of the same sized mesh, with each panel 3.3 m long by 1.6 m deep. The number of panels deployed was dictated by station water depth, as vertical net distance could not exceed water depth. The panels were arranged vertically, with 1.8 m of space between each panel such that the 6 panel net stretched from the surface to 18.6 m and the 12 panel net from the surface to 39.0 m. The purpose of the spaces between panels vertically was to reduce drag on the mesh and therefore reduce the chance that the often strong subsurface currents would twist the nets. Spreader bars at the surface, bottom and between panels maintained the net shape. We used three stretch mesh sizes, 18.4, 25.4 and 38.1 mm. These mesh sizes will catch alewife from 85 to 245 mm total length (range of length with at least 30% efficiencies based on alewife net selectivity curves by Warner et al., 2002), which matches the size distribution of alewife age-1 and older in Lake Ontario (Walsh and Connerton, 2014). In July and August we deployed all three mesh size nets at 20, 50, and 100 m water depth stations. In September we deployed all three mesh sizes at the 20 and 50 m station. Nets set at the stations N20 m in water depth were drifted, and relocated using an attached GPS device on each net, and nets set at the 20 m station were anchored so they did not drift into shore. For each sampling occasion, fish collected were sorted by net (mesh size) and panel (which represented the depth below surface). Fish catches were identified to the species level, measured to the nearest mm (total length, TL) and weighed (nearest g). Gillnets of the same design and deployment procedure were set at one location during acoustic up-looking sampling (Uplooking Station 3, Fig. 1). Alewife from a given gill net sampling site (date and bottom depth), net (mesh size), and panel (depth below surface) were divided into 20-mm length bins (0– 20 mm TL, 21–40 mm-TL, etc.). Once fish were separated into length bins, five fish were randomly subsampled from the total number of fish per bin, or all fish were pooled if the total b 5 fish. Due to high density and diversity of prey items in alewife stomachs, we subsampled and pooled individuals for diet analysis to expedite processing. For each individual fish diet sample within a pooled sample, we noted fish length and weight, and weighed stomach contents to the nearest 1 mg before combining stomach contents into the pooled sample. All combined stomach contents were rinsed into a beaker and diluted with water to evenly distribute prey items. To enumerate larger diet items we passed the sample through a 600-μm sieve to homogenize the contents then randomly subsampled by weight. We measured diet item lengths to the nearest 1 μm on up to 10 items from each taxon. From the portion of the sample that had passed through the 600-μm sieve, we diluted it to allow subsampling using a Henson-Stemple pipette (1 ml). We identified and counted approximately 200 diet items in the subsample. For both larger and smaller diet items, the subsample counts and lengths were multiplied by the appropriate expansion factor and the two components summed for the final record of stomach contents. For the purpose of reporting, diet results from fish caught from the same depth, locality and season were pooled and the numerical proportion of each diet item was calculated.

Please cite this article as: Riha, M., et al., Vertical distribution of alewife in the Lake Ontario offshore: Implications for resource use, J. Great Lakes Res. (2017), http://dx.doi.org/10.1016/j.jglr.2017.07.007

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Environmental data To evaluate the relationship between alewife school distribution and environmental variables we quantified vertical temperature and zooplankton biomass distribution. Temperature was measured at 0.5 m depth intervals using a SBE-911 CTD profiler. Profiles were collected at five stations that spanned the entire Oswego transect (5, 20, 50, 100 and 200-m water depths). Between 3 and 6 profiles were completed for each of the four Lakewide transects. Fish and zooplankton acoustic data were collected at a finer horizontal spatial scale than temperature profiles. To obtain temperature estimates for each acoustic cell, average weighted gridding was applied using the Ocean Data View software (Schlitzer, 2016). Grid-spacing along the X and Y directions varied according to data density. High resolution (small grid-spacing) was provided in regions with high data density, whereas in areas of sparse sampling a coarser grid with reduced resolution was used. This approach of spatially varying length-scales allows resolving small-scale features in areas of dense data coverage and at the same time provides smooth and stable fields in other regions with sparse data coverage (Schlitzer, 2016). This gridding method of vertical distribution of temperature on both vertical and horizontal axes is appropriate here as it considers both the strong vertical changes and the gradual horizontal changes in temperature stratification typical of Lake Ontario in the summer and fall. We also measured and present chlorophyll-a data to understanding fish and zooplankton relative to the DCL, but we did not explicitly evaluate the relationships of fish distribution relative to chlorophyll-a

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profiles. Continuous profiles of in situ fluorescence were collected with a Seapoint chlorophyll-a fluorometer (Seapoint Sensors, Inc., Exeter, NH) in conjunction with water temperature profiles. Statistical analysis of fish distribution and environmental variables We quantified the relationships between fish distribution in the water column and the temperature and zooplankton density separately for daytime and nighttime periods. Differences in fish behavior and distribution between night (dispersed) and day (schooling) required that we analyze the data differently for each time period. The distribution of abundance relative to environmental factors at night was tested using a generalized additive mixed model (GAMM). The GAMM was used to quantify fish distribution as a smoothed response to temperature and zooplankton biomass at depth. For daytime observations, we related the depth descriptors of school distribution (mean depth, Depth UP, Depth DOWN, described above) to environmental variables predicted at those positions. We tested for differences in environmental conditions among school positions using ANOVA. This approach provided a detailed description of school position relative to environmental variables during the day. We then tested for differences between day and night fish distribution by comparing depth, temperature and AZB between the two time periods. First, we calculated the average depth, temperature and AZB encountered by an adult alewife by weighting these values with acoustic fish density in each depth layer over each 200 m interval. These weighted night data reflected depth, temperature and AZB where fish

Fig. 2. Vertical profiles of temperature, chlorophyll-a, day and night acoustic zooplankton biomass (AZB) and night acoustic fish densities (AFD) from the standard vertical down-looking beaming in Oswego (OG) and Lakewide (LW) datasets. Line patterns depict different sampling month for the Oswego dataset (top row of panels), and depict different transects for the Lakewide dataset (middle and bottom row of panels). Only data from parts of the transects with bottom depth N50 m were used (both datasets).

Please cite this article as: Riha, M., et al., Vertical distribution of alewife in the Lake Ontario offshore: Implications for resource use, J. Great Lakes Res. (2017), http://dx.doi.org/10.1016/j.jglr.2017.07.007

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Fig. 3. Vertical distribution of alewife (gn-fish) from gillnets (Oswego) in three sampling months (July — a, August — b, September — c) pooled over all sampling sites. Vertical distribution of fish acoustic densities (ac-fish) in 6 adjacent intervals of each gillnet sampling site.

had the highest concentration at night. These night values were compared (using ANOVA) with depth, temperature and AZB at middle school position observed during the day. This allowed us to test for diel differences in fish distribution with respect to environmental factors. Finally, to ground truth our night fish acoustic data, we tested the relationship between abundance of alewife in gillnets with the abundance of fish detected by acoustic methods. Detailed descriptions of all applied analyses follow. A GAMM fits nonparametric smoothed functions to data that can be used when data are correlated or the study design includes clustered or spatially-explicit sampling (Wood, 2006). A GAMM will account for correlation among observations under random effects and nested designs, and uses nonparametric regression to fit the flexible functional dependence of a variable to one or more covariates (Lin and Zhang, 1999; Wood, 2006). These models were applied to each dataset and month separately. The Oswego dataset contains one sampling month (August) that was not available for the Lakewide dataset. The response variable (the square root of average fish density) was assumed normally distributed and the explanatory variables included latitude, bottom depth, temperature, and AZB. These data were observed for every acoustic interval (200 m long) in which temperature, AZB, and average fish density were given in 1 m depth bins through the water column. The fixed effects independent components of the GAMM model were latitude, bottom depth, temperature and AZB. Random effects used in all models were acoustic interval (200 m long segment, see above) in the Oswego dataset and transect and interval in the Lakewide dataset where interval

was nested within transect (randomize interval only within certain transects). Thus, the full model is: pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi fish abundance ¼ β0 þ f 1 ðlatitudei Þ þ f 2 ðbottom depthi Þ þ f 3 ðtemperaturei Þ þ f 4 ðAZBi Þ þ f 5 ðtemperaturei ; AZBi Þ þ ζi where fish abundance is a function of an intercept term (β0) and a smoothed function of the explanatory variables using cubic splines applied individually to each of the set of predictors (latitude, bottom depth, temperature, AZB), the interaction of temperature and AZB, and a random effect ζi. The model that included only latitude and bottom depth was used as a null model and all possible models with the two parameters (temperature and AZB) tested and compared using Akaike's

Table 3 Weighted means of depth (m), temperature (w_mean; °C) and range of available temperatures (range_min, range_max; °C) at night. Mean value for each variable was first calculated for every acoustic interval, and fish density was used to weight the mean. Then mean weighted values for every month (Oswego) and every transect and month (Lakewide) were calculated to describe how these variables related to fish density. Transect (Tr.) locations are noted in Fig. 1. Depth (m)

Oswego Table 2 Percentage of fish acoustic biomass (volume backscattering coefficient — sv) in 5-m depth bins obtained by vertical uplooking acoustics. Sampling locations are noted in Fig. 1. Surface bin is 2-5 m for transect L3. Location

2–5

5–10

10–15

15–20

20–25

25–30

UL-L1 UL-L2 UL-L3

10.5 41.5 70.7

67.2 49.4 14.9

21.9 8.1 11.2

0.2 0.4 1.3

0.1 0.2 0.8

0.0 0.2 0.9

Lakewide July

Lakewide Sept.

July August Sept. Tr.1 Tr.2 Tr.3 Tr.4 Tr.1 Tr.2 Tr.3 Tr.4

10.9 13.7 12.9 8.5 12.9 12.5 13.2 12.5 14.9 19.0 10.9

Temperature (°C) w_mean

range_min

range_max

18.1 20.3 17.6 20.5 14.5 20.0 16.9 14.6 15.2 19.3 18.1

6.3 6.2 6.6 4.3 4.4 4.8 4.9 4.2 4.5 6.4 6.3

21.8 21.9 18.8 23.3 20.0 22.8 21.9 18.4 19.7 20.6 21.8

Please cite this article as: Riha, M., et al., Vertical distribution of alewife in the Lake Ontario offshore: Implications for resource use, J. Great Lakes Res. (2017), http://dx.doi.org/10.1016/j.jglr.2017.07.007

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Fig. 4. Vertical distribution of night total fish acoustic densities (colors) in relation to temperature (contours) during each sampling month of Oswego only. Numbers beside contours are temperature in °C. Note differences in density scale among panels. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Information Criterion, a metric used to quantify parsimony and evidence in support of a model, given the data (AIC, Anderson, 2008). Differences in depth, height, temperature and acoustic zooplankton biomass at each school position (dependent variables) were tested among seasons (Oswego) and transects (Lakewide) using analysis of variance (ANOVA) with month (Oswego) or transect (Lakewide) as

explanatory variables. Datasets were tested separately. The Lakewide dataset was tested separately for each sampling season because not all transects were sampled during the daytime. Transects 1, 2, 3 were sampled in July and 1, 2, 4 in September. As discussed for the GAMM analyses above, a square root transformation was applied to the fish density response variables.

Table 4 Generalized additive mixed models relating temperature (Temp) and acoustic zooplankton biomass (AZB) to fish vertical distribution. Difference between given model in Akaike's Information Criterion when model ranked highest (value of 0; ΔAIC) and R2. Null model included factors latitude and bottom depth associated with each acoustic interval. Model

Oswego

Lakewide

July

Null Null + Temp Null + AZB Null + Temp + AZB Null + Temp ∗ AZB Null + Temp + Temp ∗ AZB

August

September

July

September

ΔAIC

R2

ΔAIC

R2

ΔAIC

R2

ΔAIC

R2

ΔAIC

R2

633 186 249 43 13 0

0.05 0.23 0.21 0.29 0.30 0.31

376 84 325 46 0 2

0.04 0.14 0.06 0.16 0.17 0.17

456 79 386 42 48 0

0.04 0.20 0.07 0.21 0.22 0.23

6019 776 5417 543 12 0

−0.04 0.20 0.00 0.21 0.24 0.24

5524 1069 5216 649 127 0

0.02 0.24 0.02 0.27 0.29 0.28

Please cite this article as: Riha, M., et al., Vertical distribution of alewife in the Lake Ontario offshore: Implications for resource use, J. Great Lakes Res. (2017), http://dx.doi.org/10.1016/j.jglr.2017.07.007

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M. Riha et al. / Journal of Great Lakes Research xxx (2017) xxx–xxx

Differences between these square root-transformed night/day values were tested using ANOVA, with diel period and season (Oswego) or transect (Lakewide) as explanatory variables. In these analyses, all data were limited to the depth range from 5 to 50 m because AZB was calculated only to 50 m, and acoustic data could not be collected above 5 m because of the surface blind zone (see above). The relationship between the number of alewife collected in vertical gillnets and acoustic fish densities were tested by comparing the sum of fish densities from 6 acoustic intervals (3 in front of a gillnet site and 3 after a gillnets site) with sum of alewife from the corresponding gillnet site. Relationship was tested using Pearson correlation with logarithmic transformation of input data. All statistical analyses were developed using the statistical program R (R Core Team, 2016), and GAMM models were developed using mgcv package (Wood, 2006). Vertical distribution of acoustic fish biomass (Sv) calculated for the Uplooking dataset was not used in the above mentioned analysis because of more limited spatial and temporal coverage in the Uplooking dataset. Instead, we used these data to calculate the proportion of fish in the near surface region out of all fish observed from 30 m depth to the surface. We used Sv values in 5-m depth bins in this analysis (5 m is height of surface blind zone for vertical down-looking beaming in the Oswego and Lakewide datasets).

Results Environmental variables Lake Ontario was thermally stratified during all field collections of this study. Among seasons and transects, temperatures in the epilimnion ranged from 17 °C to 23.2 °C (Fig. 2). The depth of the thermocline increased from July through September and from the west to the east end of the lake (Fig. 2). Acoustic zooplankton biomass distribution was bimodal during night with one peak in the metalimnion and one in the epilimnion (Fig. 2). During the daytime bimodality of ABZ was less prominent during August and September in which ABZ had the main peak near surface (Fig. 2). A well-defined DCL was developed during July sampling in both Oswego and Lakewide datasets (Scofield et al., in this issue). The DCL was weak in the Oswego transect in August. In September, peaks in metalimnetic chlorophyll-a were only present in the western-most transect of Lakewide (Fig. 2). Fish distribution: night Vertical night gillnet sampling and comparison of gillnet and acoustic densities In total, 560 fish were captured in vertical gillnets deployed at night on the Oswego transect in July, August, and September 2013. Alewife

Fig. 5. Vertical distribution of acoustic fish density (red line) and temperature (mean temperature indicated by circles, minimal and maximal temperature in a transect by dashed lines) for Transect 1 (east end of lake, see Fig. 1) and Transect 4 (west end of lake, see Fig. 1) of the Lakewide in July (a, b) and September (c, d). GAMM models representing effect of temperature on total fish acoustic density (e, f) for Lakewide (model: Null + Temp, see Table 4). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Please cite this article as: Riha, M., et al., Vertical distribution of alewife in the Lake Ontario offshore: Implications for resource use, J. Great Lakes Res. (2017), http://dx.doi.org/10.1016/j.jglr.2017.07.007

M. Riha et al. / Journal of Great Lakes Research xxx (2017) xxx–xxx

(length range from 60 to 209 mm TL) strongly dominated catches in all sites, and represented 97.1% of overall catch. Other species collected were seven round goby (Neogobius melanostomus), five emerald shiner (Notropis atherinoides), two Chinook salmon, one rainbow smelt and one smallmouth bass (Micropterus dolomieu). Vertical distribution of alewife was similar in all months (Fig. 3). Alewife vertical distribution was multimodal at night with several peaks in each sampling month. In all months one peak was near surface in depth layers from 0 to 6.8 m and the second peak was in depths between 10 and 20 m. In August alewives were detected even deeper with the third peak in depths between 27 and 31 m. Numbers of alewife from gillnets showed significant positive correlation with acoustic densities from nearby acoustic intervals (p = 0.026; r = 0.769 with R2 = 0.59). Vertical patterns between gillnets and adjacent acoustic intervals showed peaks of fish acoustic densities in the same depths or slightly shallower than in gillnets (Fig. 3). Uplooking acoustics We detected the highest fish acoustic biomass in the near surface layer (1–5 m) at one (Station Uplooking-3) of the three sampling locations (Table 2). That was the day with the least surface noise and calm condition. At Uplooking-1 and Uplooking-2, the highest biomass was in the 5–10 m depth layer although the difference between 2–5 m and 5–10 m was small in Uplooking-2. Echograms revealed alewife layers close to the surface in Uplooking-3, two layers in Uplooking-2 and only one slightly deeper layer in Uplooking-1. We believe these differences reflect sea state and possible associated zooplankton distributions, but

9

more detailed analyses of this kind of data is needed. Less than 3% of fish acoustic biomass was detected below 15 m in all sampling locations. Vertical gillnets deployed at Uplooking-3 (the farthest east of the sites, near Oswego) captured 83 fish, of which 80 were alewife and 3 were rainbow smelt. Downlooking acoustics: Oswego and Lakewide Fish vertical distribution differed between seasons in Lakewide data as fish were deeper in September than in July along each transect (Fig. 2, Table 3). Average depth of fish (depth weighted by acoustic fish density) ranged from 8.6 to 13.2 m in July and from 12.5 to 18.5 m in September, respectively (Table 3). In both July and September, fish were shallower in the west than in the middle and the east part of the lake. However, there were no monthly or spatial trends in the average temperature occupied. This temperature ranged from around 14 to 20 °C. Fish were dispersed almost exclusively in the epilimnion during all sampling months. The seasonal increase in epilimnion thickness changed alewife depth distribution, but not their distribution in terms of temperature (Fig. 4). Temperature was a better single predictor of night vertical fish distribution than AZB in both datasets and all seasons as demonstrated by lower AIC of the temperature models when a single predictor was used (Table 4). Temperature preference models assume single peak temperature optimum, but visualization of GAMM results showed that fish had two peaks in the distribution within the epilimnion (Lakewide, Fig. 5): one peak near the surface in temperatures above 20 °C and a second peak near the bottom of the thermocline in temperatures of 13–16 °C.

Fig. 6. Vertical distribution of acoustic fish density (red line) and acoustic zooplankton biomass (mean AZB biomass is indicated by circles, minimal and maximal AZB in a transect by dashed lines) in two transects (the most east and west transects) of the Lakewide in July (a, b) and September (c, d). GAMM models representing effect of interaction between acoustic zooplankton and temperature to total fish acoustic density (e, f) for Lakewide (model: Null + Temp + Temp ∗ AZB, see Table 4). Range of covered temperatures and AZB is indicated at x and y axes. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Please cite this article as: Riha, M., et al., Vertical distribution of alewife in the Lake Ontario offshore: Implications for resource use, J. Great Lakes Res. (2017), http://dx.doi.org/10.1016/j.jglr.2017.07.007

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M. Riha et al. / Journal of Great Lakes Research xxx (2017) xxx–xxx

The pattern was similar for both the Oswego and Lakewide datasets, but the relative importance of the two peaks differed among transects as fish were only in the shallowest part of the epilimnion in some transects (e.g. Transect 1 in July and Transect 4 in September, Fig. 5a, d) and mainly in or near the thermocline in other transects (e.g. Transect 1 in September or Transect 4 in July, Fig. 5b, c). When fish have a bimodal distribution along a temperature gradient, the distribution cannot be a simple response to a preferred temperature. Indeed, the prediction of fish density by the temperature model was improved when including interaction of temperature and AZB as these models had the lowest AIC values (Table 4). Highest acoustic fish densities were concentrated in regions of the epilimnion where AZB was higher than − 75 dB, but fish were not found at temperatures below 10 °C even when AZB was high (Fig. 6). This indicates that the alewife distribution within the water column is affected by both temperature and zooplankton biomass.

Alewife diet In total, 265 alewife individuals (Oswego) were examined for diet analysis (Table 7). Their diet varied among depths and seasons (Fig. 9). In July, cyclopoid copepods (primarily Diacyclops thomasi) dominated in the diet except in the deepest layers (24–27 m) in which cladocerans and Cercopagis pengoi were found in higher proportions. In August, cladocerans (primarily Bosminidae) dominated in depths down to 10 m. In deeper water, cyclopoids and calanoid copepods were the most important diet items, and the larger calanoid Limnocalanus macrurus appeared in alewife caught in the deepest set nets. Similar patterns were found in September. In that month, cladocerans were the dominant diet items in the upper and middle part of the water column; and Limnocalanus dominated in fish caught in 20– 24 m depth and in the deepest nets. However, Limnocalanus was detected in the diet of some fish caught in near surface layers in both August and September. Mysids were consumed by b5% of the alewives, primarily in fish caught in deep water at night.

Fish distribution: day Thirty-six fish schools were detected in the Oswego dataset and 314 schools in the Lakewide dataset (Table 5). Mean depth of these schools ranged from 18.8 to 23.2 m and school height ranged from 2.7 to 4.6 m. Mean depth differed significantly among seasons (Oswego) and transects (Lakewide; Table 5). Similar to night distributions, schools were deeper later in the season (Oswego, Fig. 7) and deeper in the eastern than in western part of the lake (Lakewide, Fig. 7). Differences were found in temperature and AZB among school positions in Lakewide. Fish in Depth UP position were exposed to significantly higher temperatures than fish in Depth DOWN position in both July and September in the Lakewide dataset (Fig. 7, Table 5), but not in the Oswego dataset. Acoustic zooplankton biomass differed between UP and DOWN position only in the case of Lakewide in July when fish in UP position were found with lower AZB than fish in DOWN position (Fig. 7, Table 5).

Diel difference in fish vertical distribution In both the Oswego and Lakewide datasets and all months, the day/ night period had a significant effect on the depth of fish and AZB at mean school position/average fish depth (Table 6). Mean school depth during the day was deeper than average depth of fish at night and occupied temperature was lower during the day than at night (Lakewide, Fig. 8). Day/night period also had an effect on the occupied temperature in Oswego, but the significance of this difference varied among sampling months (Table 6, Fig. 8). Acoustic zooplankton biomass at mean school position during the daytime was lower than weighted mean acoustic zooplankton biomass at night (Fig. 8).

Discussion By combining several datasets on fish distribution collected in 2013, we advanced the understanding of summer diel distribution of alewife in Lake Ontario and the factors driving their distribution. Acoustic sampling revealed that in day and night fish were concentrated in the epilimnion or close to the epi-/metalimnion boundary. However, vertical distribution within the upper part of the water column differed between day and night as fish were deeper, in lower temperatures and exposed to lower densities of zooplankton during the daytime. Alewife schooled during the day in the lower epilimnion with the lower part of the school residing in the metalimnion. In July when the deep chlorophyll layer was developed, the lower parts of a school were associated with higher daytime zooplankton concentrations that occurred in the DCL (see also Watkins et al., in this issue). At dusk, a majority of the alewives migrate with their zooplankton prey towards the surface, but some remain in the metalimnion at night. The proportion of the alewife population that move into the top 5 m of the water column can be high (over 70%), but varies between nights and/or stations. In the summer and fall of 2013, night-caught alewife fed primarily on small cyclopoid copepods (Diacyclops thomasi), a zooplankton species that migrated from the metaliminion to the epilimnion during the night (Watkins et al., in this issue). The larger metalimnetic copepod Limnocalanus macrurus was consumed by the fish remaining in deeper water during the night. This two-layered distribution during the night was best predicted by the interaction between temperature and zooplankton biomass.

Table 5 Number of detected schools, mean values of school descriptors, depth (m), school height (m), temperature (°C) and acoustic zooplankton biomass (AZB, dB), and significance (p-value) of each tested factor (school position and month (Oswego) or transect (Lakewide)). Values in bold font are considered significant. No. of detected schools

Oswego

36

Lakewide July

86

Lakewide September

228

Parameters

Depth Height Temperature AZB Parameters Depth Height Temperature AZB Depth Height Temperature AZB

School position Up

Middle

Down

17.47 – 17.00 −79.19 Up 17.20 – 17.65 −78.37 21.69 – 14.67 −81.08

18.82 2.72 16.58 −79.74 Middle 19.48 4.56 14.85 −77.24 23.24 3.11 13.02 −81.44

20.18 – 16.08 −80.14 Down 21.76 – 12.43 −76.68 24.80 – 11.64 −81.02

p (Position)

p (Month)

p (Pos. ∗ Month)

– – 0.685 0.478 p (Position) – – N0.001 N0.001 – – N0.001 0.306

0.018 0.558 N0.001 N0.001 p (Transect) N0.001 0.014 0.246 N0.001 N0.001 0.001 N0.001 N0.001

– – 1.000 0.560 p (Pos. ∗ Transect) – – 0.898 0.299 – – 0.018 0.333

Please cite this article as: Riha, M., et al., Vertical distribution of alewife in the Lake Ontario offshore: Implications for resource use, J. Great Lakes Res. (2017), http://dx.doi.org/10.1016/j.jglr.2017.07.007

M. Riha et al. / Journal of Great Lakes Research xxx (2017) xxx–xxx

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Fig. 7. Locations of school positions (up, middle, down) in relation to depth, temperature and acoustic zooplankton biomass in Oswego (OG; a) and Lakewide (LW; b — July, c — September). Boxes show upper (75%), lower (25%) quantiles and median, whiskers show maximal and minimal values without outliers (dots).

Methodological considerations This interpretation of our data is contingent on our assumption that the observed acoustic targets were alewife. Hydroacoustic techniques alone cannot distinguish fish species, but our previous knowledge of fish distribution during summer acoustic surveys (Connerton and Holden, 2015; Boscarino et al., 2010) and vertical gillnet catches when deployed confirmed that the majority of acoustically detected fish were alewife. The vertical gillnets and the Uplooking dataset also added considerable insight to patterns in alewife vertical distribution in the surface waters that fall in the acoustic blind zone of downlooking acoustics. Although we did not catch daytime fish targets, observations of the break-up of schools (Fig. 11) and subsequent catch of these fish in gillnets confirmed that the schools observed during the day were alewife. Adult alewives are known to school during the day (Olson et al., 1988; Dunlop et al., 2010). Further, alewife was the most abundant fish species in

Lake Ontario in 2013 and has been so for some time, particularly in the epilimnion (Olson et al., 1988; Walsh and Connerton, 2014; Weidel and Connerton, 2013). We therefore considered all our epiand metalimnetic acoustic targets to be alewife. Hydroacoustic measurement of smaller zooplankton has been used for some time (McNaught, 1969; Megard et al., 1997; Hembre and Megard, 2003; Holbrook et al., 2006) but should also be interpreted with caution due to the non-linear effect of animal size on acoustic backscattering (Stanton and Chu, 2000) as well as ambient noise from bubbles and interference from larger targets. In our study, the increase in acoustic metalimnetic backscattering during the day was consistent with depth stratified net tows done concurrently with the Lakewide and Oswego datasets and with laser optical plankton counter data collected with the Lakewide dataset (Watkins et al., in this issue). During the night, the strong scattering layer in the metalimnion is comprised of mysid shrimps that migrate from the bottom of the lake at dusk and return at dawn (Janssen and

Table 6 Effect of diel period (day versus night, D/N) on the distribution of fish in relation to depth, temperature and acoustic zooplankton biomass (AZB). Significance (p-value) of each tested factor (diel period and month(Oswego)/transect(Lakewide)) for parameters in both datasets. Significant (≤ 0.005) results are bolded. More information on day vs night vertical distribution that will show magnitude and direction of difference is in Fig. 8. Parameter

Depth Temperature AZB

Lakewide — July

Oswego

Lakewide — September

D/N

Month

D/N ∗ Mon

D/N

Transect

Per ∗ Tr

D/N

Transect

D/N ∗ Tr

b0.001 b0.001 b0.001

b0.001 b0.001 0.005

0.002 b0.001 b0.001

b0.001 b0.001 b0.001

b0.001 0.965 b0.001

b0.001 0.382 0.343

b0.001 b0.001 b0.001

b0.001 b0.001 b0.001

0.001 0.235 0.171

Please cite this article as: Riha, M., et al., Vertical distribution of alewife in the Lake Ontario offshore: Implications for resource use, J. Great Lakes Res. (2017), http://dx.doi.org/10.1016/j.jglr.2017.07.007

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Fig. 8. Comparison of day and night fish distribution in relation to depth, temperature and acoustic zooplankton biomass. Depth, temperature and acoustic zooplankton biomass for mean school depth were used for daytime and depth, temperature and acoustic zooplankton biomass weighted by fish density were used for nighttime. Boxes show upper (75%), lower (25%) quantiles and median, whiskers show maximal and minimal values without outliers (dots).

Brandt, 1980; Rudstam et al., 2008b), which was also confirmed with mysid net tows. However, our data also showed a high backscattering near surface in both diel periods that may be explained by presence of other small targets such as air bubbles induced by wave activity (Simmonds and MacLennan, 2008). Periods of stronger wind and higher wave activity are present in all datasets, and these air bubbles likely cause us to overestimate zooplankton density in the top 10 m of the water column. A relatively large proportion of alewife were found to be in the near surface depths during the night (13–62% of alewife captured by near surface gillnets in Oswego and 12–28% of the total acoustic biomass in Uplooking). Alewives are commonly caught near surface at night in smaller lakes (Rudstam et al., 2011; Simonin et al., 2012). Near-surface water layers may be an important night habitat for adult alewife. This also indicates that standard downlooking acoustic surveys as used in the Oswego and Lakewide datasets underestimate alewife abundance in Lake Ontario (Connerton and Holden, 2015). This will affect depth, temperature and zooplankton biomass preferences as more fish are

Table 7 Numbers of dissected fish from all gillnet sampling sites and seasons. Month

July August September

Depth of gillnets (m) 0

4

7

10

14

17

21

24

27

30 10 12

32 6 7

28 1 3

18 2 4

19 9 13

16 7 17

5 – 4

1 3 5

1 5 1

31

34

38

Sum

2 1

– – 1

– 1 1

150 46 69

actually at higher temperatures and in unknown zooplankton densities close to the surface than indicated by data from below 5 m depth. This limitation of our dataset affect only the results obtained during night sampling as we have no indication that alewife concentrate near the surface during the day. Visual inspection of echograms showed no schools in the top water layers surveyed and observations during the dawn period showed schools forming and moving down to the bottom of the epilimnion, locations were these schools were observed during the day (Fig. 10). GAMMs have been successfully applied to relate fish distribution to environmental factors (e.g. Simonin et al., 2012; Parra et al. in press; Fulton et al., 2016) as they provide a flexible way to model nonlinear relationships between response data and continuous variables and include both fixed and random effects of the variables included (Wood, 2006). The GAMMs also allow us to include bimodal effects of temperature. Our application of GAMMs demonstrate the importance of temperature and zooplankton, including the interaction between these variables, in predicting alewife distribution. However, a large portion of variability remained as the best models explained only 17 to 31% of the variability in alewife distributions. This remaining variability could be due to alewife response to additional variables such as light intensity and predators, as well as to response to the distribution of specific, perhaps preferred, zooplankton species and issues with measuring alewife distribution in the surface layers. More detailed analysis of the correlations between nets, LOPC and zooplankton acoustics is needed and is planned using data collected by the authors' agencies during 2013, but they are beyond the scope of the current paper.

Please cite this article as: Riha, M., et al., Vertical distribution of alewife in the Lake Ontario offshore: Implications for resource use, J. Great Lakes Res. (2017), http://dx.doi.org/10.1016/j.jglr.2017.07.007

M. Riha et al. / Journal of Great Lakes Research xxx (2017) xxx–xxx

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Fig. 9. Percentage diet composition (in abundance) of alewife captured by vertical gillnets (all depths combined) set at the Oswego transect (see Fig. 1) in different sampling months (a–c).

Alewife distribution and implications for resource use We found alewife throughout the epilimnion at night and at the epi/ metalimnetic boundary during the day which corroborates previous studies in Lake Ontario (Olson et al., 1988; Urban and Brandt, 1993) and reflects the known temperature preference of alewife (Brandt, 1980; McCauley and Binkowski, 1982; Otto et al., 1976). Depth distribution varied with the seasonal and spatial changes in the thickness of the epilimnion (Fig. 2), but alewife distribution in relation to temperature was more consistent across the lake and across seasons. However, alewives were deeper during the day than at night indicating short-scale vertical migration of alewife in Lake Ontario from the lower part of the epilimnion and metalimnion during the day to the upper epilimnion at night. These diel depth changes had consequences for the exposure of alewife to different temperature regimes between day and night. Temperature of maximal alewife density was above 15 °C, and fish density declined sharply at temperatures below 14 °C during night. During the day, mean temperatures at the middle school position were similar, in the range of 13–17 °C but mean temperatures at the lower depth of the schools was lower, especially in the Lakewide dataset (11.6 °C).

Reported temperature preferences of alewife are above 15 °C (McCauley and Binkowski, 1982; Otto et al., 1976), and lower temperatures likely decrease their growth rates (Stewart and Binkowski, 1986). Thus, alewife in the lower part of schools may experience suboptimal temperatures for growth during the day. These suboptimal temperatures may be offset by higher daytime zooplankton abundance at these deeper depths. Diel short-scale vertical migration and occurrence of alewife in suboptimal temperatures during the day could be associated with diel changes in predation pressure and prey availability (Mehner, 2012). Alewives are active during the day (Brandt, 1980; Richkus and Winn, 1979) and capable of feeding even under low light intensity (Janssen, 1978; Boscarino et al., 2010). High light levels near surface increase the potential of being detected by a predator; and therefore increases predation risk (Clark and Levy, 1988). Light intensity decreases exponentially with depth and even a relatively minor depth change could modify predation risk when a limiting light intensity threshold is exceeded (Mazur and Beauchamp, 2003). Predators in the Lake Ontario offshore are represented mostly by salmonids, in particular Chinook salmon. According to Mazur and Beauchamp (2003) reaction distances of salmonids (two of which, rainbow trout Oncorhynchus mykiss and

Fig. 10. Example of change in fish dispersion (dots) and position in the water column between day and night as visually detected on the 120 kHz echogram recorded on 11 September 2013 (sunrise time 0618 EST) during Lakewide sampling. It illustrates that fish were dispersed in the water column during the night (time 0240 EST) and around 0540 EST started to concentrated around a depth of 20 m below the surface. Schools subsequently become more organized, and around one and half hour later schools were fully formed (time 0725 EST).

Please cite this article as: Riha, M., et al., Vertical distribution of alewife in the Lake Ontario offshore: Implications for resource use, J. Great Lakes Res. (2017), http://dx.doi.org/10.1016/j.jglr.2017.07.007

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lake trout Salvelinus namaycush are present in Lake Ontario and prey on alewife) to their prey decreased below light intensity of 20 lx. Such light intensity was reached at depths from 20 to 30 m in the Lake Ontario offshore during the day in the summer of 2013. We found schools at such depths in the eastern part of the lake where the thermocline was deeper. Therefore, predation risk should decrease at those depths also during the day, and this may be the reason for downward movement of alewife at dawn. However, prey availability was also higher at the thermocline during the day in 2013 and alewife may be descending with their prey during the dawn migration (Fig. 10). Therefore, it would be advantageous for alewife to reside near the thermocline during the day both to decrease predation risk and to increase feeding rates on zooplankton. Alewives are generally considered more difficult to sample during the day due to gear avoidance (Lindenberg, 1976; Suuronen et al., 1997), and we do not have daytime diets available for this study to confirm on what prey they are feeding during the day. Therefore, we cannot distinguish between the effect of predation risk and prey availability towards explanations for diel changes of alewife vertical distribution; both are likely to be important. Gillnets and to some degree acoustic results showed bimodal alewife distribution with one peak in shallower depths and a second peak near the thermocline at night. Alewife diet analysis revealed evidence for vertical structure in their night diet as well as dynamic vertical movement. Limnocalanus macrurus is a cold water calanoid which was found exclusively in meta/hypolimnion of Lake Ontario during summer (Rudstam et al., 2015; Watkins et al., in this issue). Alewife from the deepest sampled layers in August and September preyed on L. macrurus. While this was only two individual fish, it is a notable result. However, alewife with L. macrurus present in the diet were also collected in gillnets in the middle of the epilimnion or near the surface. These results indicate that most alewife migrated towards near surface layers at dusk feeding on migrating zooplankton but that some individuals remained near the thermocline feeding on L. macrurus. Depths occupied by individual fish may be more varied and include multiple vertical movements during the night. Intensity of these vertical movements and proportions of alewife performing such movements cannot be deduced from our data. In Cayuga Lake, New York, targets assumed to be alewife have been observed to move between the upper and lower epilimnion at night over short periods of time (minutes) using stationary acoustics (Rudstam, pers. obs.). Other fish were more stationary at depth. Mysids (Mysis diluviana) are reported as an important prey for alewife in Lake Ontario (Boscarino et al., 2010; Stewart et al., 2009), but they represented only a negligible proportion of alewife diet in the Oswego transect in 2013when mysids were found in at most 13 out of the 265 individuals examined (exact number not known due to diet pooling). These fish were caught in the depths from 10 to 39 m. However, night vertical distribution of acoustically detected fish and zooplankton from the other transects (Lakewide) suggests potential overlap between some proportion of alewife and the high metalimnetic zooplankton peak represented mainly by mysids. According to Boscarino et al. (2010), low light intensity reduces alewife feeding on mysids during the new moon phase. They suggested that alewives feed on mysids mainly when the moonlight is high enough for alewives to detect mysids at the upper edge of the mysid layer. Dates of Oswego sampling were very close to the new moon phase (moon illumination 0–19%) while dates for sampling of Lakewide were around the full moon in July (moon illumination 80–100%) and the half-moon phase in September (moon illumination 20–64%). This suggests that light intensity was low for alewife feeding on mysids when gillnetting was performed, and it might explain low representation of mysids in alewife diet. A higher moon illumination could enhance alewife-mysid interactions and the utilization of the epi/ metalimnetic boundary. Lack of direct fish sampling in the Lakewide dataset may affect our perception of the importance of the mysids for alewife in this dataset. Our data suggest that alewives use a larger portion of the zooplankton population present in the lake than what is revealed by daytime sampling of the epilimnion. This is likely the reason why alewife

growth rates have not declined following the documented decline in epilimnetic daytime zooplankton in the late 1990s and again in the mid 2005 (Walsh et al., 2016; Holeck et al., 2008; Rudstam et al., 2015). Although the spatial overlap between alewife and zooplankton concentrated below the thermocline in the DCL was low, alewives were present at the upper edge of the DCL during the night in July. In addition, alewife schools were distributed in close vicinity of zooplankton concentrated in meta/hypolimnion during the daytime, and some fish stayed near the thermocline at night, presumably to feed on large calanoids and perhaps mysids. In addition, alewives have access to the zooplankton that migrate from the metalimnion to the epilimnion during the night. This study provides a more complete picture of the diel patterns in alewife spatial distribution in the offshore of Lake Ontario during the summer period than has been available to date. The study highlighted several important topics which should be addressed by future research. Alewife near surface night distribution is a problem for standard acoustic surveys because a significant part of the alewife biomass is not detected (Connerton and Holden, 2015). The dynamics of alewife diel distribution and the split to groups feeding in different parts of the water column represent a partial migration recently documented for many fish species (Chapman et al., 2012). This pattern should be better understood because it can enhance our understanding of fish impact to part of lower trophic levels and the resiliency of the alewife population to ecological changes occurring in the lake. This behavioral plasticity needs to be incorporated in ecological models (bioenergetics and population model) that are used to predict future changes in the lake. Additionally, the daytime evaluation of fish behavior in schools, and the approach of using complementary acoustic datasets to explore fish behavior are novel approaches that may have wide-reaching applications in fish ecology and distribution studies. Acknowledgements This study was supported by grants for the Great Lakes Fishery Commission (2013-RUD-44029), a Great Lakes Restoration Initiative grant from the Environmental Protection Agency (Cooperative Agreement GL 00E01184-0) and funds from the USGS Ecosystems Mission Area. Dr. Riha was supported by fellowships from the Fulbright Scholar program and the PPLZ program of the Czech Academy of Sciences and the program COST-CZ under contract number MSMT-LD15021. Additional support was provided by the New York State Department of Environmental Conservation through funding from Federal Aid in Sportfish Restoration and Ontario Ministry of Natural Resources and Forestry and the Canada-Ontario Agreement on Great Lakes Water Quality and Ecosystem Health. We are grateful to the vessel crews and biological staff of the R/V Lake Guardian, R/V Kaho, R/V Seth Green and R/V Lake Ontario Explorer, and to the technicians and graduate students at USGS and Cornell that contributed to the data presented in this paper. Use of product names does not indicate endorsement by the U.S. government. References Ahrenstorff, T.D., Hrabik, T.R., Stockwell, J.D., Yule, D.L., Sass, G.G., 2011. Seasonally dynamic diel vertical migrations of Mysis diluviana, coregonine fishes, and Siscowet Lake trout in the pelagia of western Lake Superior. Trans. Am. Fish. Soc. 140, 1504–1520. Anderson, D.R., 2008. Model Based Inference in the Life Sciences: A Primer on Evidence. Springer, New York, NY. Barbiero, R.P., Lesht, B.M., Warren, G.J., 2012. Convergence of trophic state and the lower food web in Lakes Huron, Michigan and Superior. J. Great Lakes Res. 38, 368–380. Barbiero, R.P., Lesht, B.M., Warren, G.J., 2014. Recent changes in the offshore crustacean zooplankton community of Lake Ontario. J. Great Lakes Res. 40, 898–910. Boscarino, B.T., Rudstam, L.G., Tirabassi, J., Janssen, J., Loew, E.R., 2010. Light effects on alewife-mysid interactions in Lake Ontario: a combined sensory physiology, behavioral, and spatial approach. Limnol. Oceanogr. 55, 2061–2072. Brandt, S.B., 1980. Spatial segregation of adult and young-of-the-year alewives across a thermocline in Lake Michigan. Trans. Am. Fish. Soc. 109, 469–478. Brandt, S., Magnuson, J.J., Crowder, L.B., 1980. Thermal habitat partitioning by fishes in Lake Michigan. Can. J. Fish. Aquat. Sci. 37, 1557–1564. Bunnell, D.B., Barbiero, R.P., Ludsin, S.a., Madenjian, C.P., Warren, G.J., Dolan, D.M., Brenden, T.O., Briland, R., Gorman, O.T., He, J.X., Johengen, T.H., Lantry, B.F., Lesht,

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Please cite this article as: Riha, M., et al., Vertical distribution of alewife in the Lake Ontario offshore: Implications for resource use, J. Great Lakes Res. (2017), http://dx.doi.org/10.1016/j.jglr.2017.07.007