Int. J. Lim.
Volume 60, 2024
Special issue - Biology and Management of Coregonid Fishes - 2023
Article Number 8
Number of page(s) 16
Published online 04 July 2024

© C.M. Ryther et al., published by EDP Sciences, 2024

Licence Creative CommonsThis is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

1 Introduction

Spawning behaviour is a crucial component in the life history of fishes and can be used to help predict reproductive resilience in populations (Biggs et al., 2021). Relating spatiotemporal aspects of spawning, such as where, when, and for how long a population spawns, can provide insights into the population’s vulnerability to harvest or other stressors during periods of population decline (Sadovy De Mitcheson and Erisman, 2012; Biggs et al., 2021). Additionally, characteristics of spawning populations, such as sex ratios and the number of spawning individuals, can be important for quantifying reproductive potential and aiding in stock assessments (Methot Jr and Wetzel, 2013). At a finer scale, quantifying the sex-specific movement and activity rates of fish can also help us understand the energetic costs of spawning behaviour, which can be used in bioenergetics models (Rudstam et al., 1994). More broadly, describing the migratory behaviour of spawning stocks, including when fish arrive and leave spawning areas, is important in formulating harvest strategies (Ebener et al., 2008; Li et al., 2014).

Lake whitefish (Coregonus clupeaformis Mitchill 1818; dikameg in Anishnaabemowin) are a cold-water, benthic fish that is widely distributed throughout freshwaters across the northern region of North America (Scott and Crossman, 1973). The species are a valued part of the diet and culture of many Indigenous communities, are an important ecological linkage between nearshore and offshore food webs, and support valuable recreational and commercial fisheries (Rennie et al., 2009; Almack et al., 2023). In many regions of the Laurentian Great Lakes, lake whitefish abundance and commercial fishery yield has undergone significant declines over the past 25 years, raising concerns from commercial harvesters, Indigenous communities, and fisheries management agencies about the sustainability of these populations (Brenden et al., 2010; Cottrill et al., 2020; Gobin et al., 2023). In addition to declines in abundance and harvest, lake whitefish in the Great Lakes have also undergone reductions in growth, condition, and recruitment and there have been large changes in the species diet and distribution (Rennie et al., 2009; Herbst et al., 2013; Fera et al., 2015; Gobin et al., 2015; Ebener et al., 2021). These changes to lake whitefish are closely associated with the invasion of dreissenid mussels, including the zebra mussel Dreissena polymorpha (Pallas 1771) and quagga mussel D. bugensis (Andrusov 1897). Dreissenid mussels have altered nutrient cycling and food webs in the many lakes they have invaded across North America and Europe, including the Laurentian Great Lakes (Karatayev et al., 1997; Higgins and Vander Zanden, 2010; Burlakova et al., 2012). Through their ability to filter large volumes of water, dreissenid mussels are associated with reduced phytoplankton biovolume and zooplankton biomass. In Lake Huron where ecosystem productivity is currently very low, changes to lower trophic levels are thought to have reduced the amount of zooplankton prey available to larval lake whitefish, leading to declines in the survival of young life stages (Ebener et al., 2021; Cunningham and Dunlop, 2023). Another concern is that dreissenid mussels, together with excessive growth of filamentous algae (Cladophora spp.) may also be diminishing the quality of spawning habitat and reducing survival of embryonic life stages (Ebener et al., 2021; Gobin et al., 2023; Weidel et al., 2023). Currently, there is little information quantifying lake whitefish spawning habitat characteristics or what the range of spawning habitat requirements are for the species (Ebener et al., 2021). We are also lacking knowledge of whether dreissenid mussels have adversely impacted the functionality of spawning habitat for lake whitefish in the Great Lakes and other systems with these invaders. A more complete understanding of lake whitefish reproductive ecology, including examining behaviour and habitat usage during spawning, may provide insights about factors affecting lake whitefish recruitment.

Despite the importance of lake whitefish, there is surprisingly little documented about the spawning behaviour of this species in the scientific literature. Most literature on lake whitefish spawning originates from historical studies, where sex-specific details of behaviour are generally not alluded to. Lake whitefish are broadcast spawners that spawn between late October to early December, depending on temperature and site (Scott and Crossman, 1973; Goodyear et al., 1982; Ford et al., 1995). Spawning typically occurs in shallow water (5–10 m), over rocky and cobble shoals that can include honeycomb-shaped rock (Hart, 1930; Scott and Crossman, 1973; Goodyear et al., 1982; Bodaly, 1986). Genetic and mark-recapture studies of lake whitefish in lakes Huron and Michigan have indicated spawning site fidelity in some populations, with at least some fish returning to the same spawning shoals in subsequent years (VanDeHey et al., 2009; Ebener et al., 2010; Ebener et al., 2021). Published descriptions of other Coregonus spp. spawning behaviours are also available (Eckmann, 1991). For example, European vendace (C. albula Linnaeus 1758) and Siberian Coregonus spp. (i.e.C. peled Gmelin 1789, C. pidschian Gmelin 1789, C. muksun Pallas 1814, C. tugun Pallas 1814, and C. migratorius Georgi 1775) have been observed under laboratory conditions to display pair and communal spawning where, in some cases, one or two males participated in a spawning event with a female (Karjalainen and Marjomäki, 2018; Semenchenko and Smeshlivaya, 2021). Additionally, Gatch et al. (2023) found evidence of spawning site fidelity of cisco (Coregonus artedi Lesueur 1818) in Lake Ontario using a fine-scale acoustic telemetry system. Studies that describe finer-scale movements of spawning lake whitefish are restricted to small inland lakes (∼16–1206 ha; Bégout Anras et al., 1999; Gorsky et al., 2012; Whitaker and Wood, 2021). For example, Bégout Anras et al. (1999) found lake whitefish swimming speed and distance travelled decreased until a peak in activity during spawning, although sex-specific comparisons were not available. To our knowledge, fine-scale sex-specific information like biometrics, movement rates, and spatial activity before, during, and after spawning, has not been published for lake whitefish in a large system like Lake Huron (∼5.96 million ha) and is generally lacking for most coregonines.

The purpose of this study was to use fine-scale acoustic telemetry to quantify sex-specific movement patterns of lake whitefish during spawning at a shoal in Georgian Bay (Lake Huron), named the Little Port Elgin shoal. The spawning shoal is of significance to two local First Nations collectively known as the Saugeen Ojibway Nation (SON), who have been harvesting lake whitefish for thousands of years for food, economy, and cultural purposes (Almack et al., 2023; Duncan et al., 2023; Gobin et al., 2023). The research was motivated by declining lake whitefish abundance in SON’s traditional territory, which threatens the Nation’s food sovereignty and economy. In 2020, 50 lake whitefish were tagged at the Little Port Elgin shoal, and a VEMCO Positioning System (VPS; Innovasea Ltd., Bedford, NS, Canada) was deployed before the spawning season of 2021 to observe the spawning behaviour of any returning tagged fish. Using a VPS, which allows the fine-scale tracking of acoustically-tagged fish (Binder et al., 2018; Dahl and Patterson, 2020; Orrell and Hussey, 2022; Lennox et al., 2023), we compared the dates of arrival and departure from the study area, spatial use of the spawning shoal and surrounding area, and sex-specific movement metrics throughout both the day and night over the duration of the spawning period.

We took inspiration from the Two-Eyed Seeing approach, where Indigenous ecological knowledge and western science were both used to guide our research (Reid et al., 2021; Almack et al., 2023). Two-Eyed Seeing is a framework conceptualized by Mi’kmaq Elder Dr. Albert Marshall, that uses the strengths of multiple knowledge systems (here, Indigenous ecological knowledge and western science), to work toward a common goal (Reid et al., 2021). Our study was part of two broader Two-Eyed Seeing research studies named Together with Giigoonyag and Bima’azh, both of which were co-designed with SON to address their specific priorities about lake whitefish. SON members identified that using a Two-Eyed Seeing approach, where both western science and SON’s ecological knowledge were included, was needed to gain a broader understanding of the reproductive behaviour and spawning habitat of lake whitefish (Gobin et al., 2023). The ultimate goal is that this broader understanding will help inform stewardship actions aimed at addressing declining lake whitefish. SON’s ecological knowledge (herein SON-EK) is the local Indigenous knowledge of SON that has been passed down over generations of living and relying on the land and water for survival. SON have been harvesting fishes in Lake Huron, including lake whitefish, for thousands of years and have intimate knowledge about changes in the lake. SON-EK was a part of our study in both direct and indirect ways, including in generating study questions and objectives, determining the best locations to place receivers on the shoal, locating and capturing fish on the spawning shoal to be tagged, and interpreting results.

2 Methods

2.1 Saugeen Ojibway Nation-Ecological Knowledge guidance, participation, and inclusion

Our research study of lake whitefish spawning behaviour was guided by SON-EK from the earliest stages of the project’s inception through to the interpretation and sharing of results. Many SON members contributed to the project, including to the identification of research questions and study objectives, study design, field work, and results interpretation. Research questions and project objectives were identified at community meetings (e.g., see summary by Gobin et al., 2023). Through informal meetings, SON fish harvesters used their intimate knowledge of the site to provide feedback and insight on the VPS array design. In the field, SON fish harvesters improved our receiver deployments (i.e., from reading the waters, to ensuring our receivers wouldn’t be swept away, to setting nets for successful tagging). SON harvesters also identified the locations to capture spawning fish and they conducted the netting to capture the fish that were tagged. Formal meetings with SON fish harvesters provided opportunities to discuss results and to learn from these knowledge holders about dikameg behaviour. Results were also shared and discussed with SON members at various events including PowWow’s (i.e. a celebratory, cultural gathering of members of the First Nation), feasts, conferences, project meetings and through documentaries made with SON ( and Community members received various forms of compensation for their involvement in the research (e.g., including through providing meals at community events or through providing funds for conducting field work).

2.2 Study area and bathymetry mapping

The study area is a partly sheltered bay, known as Port Elgin Bay, on the eastern side of Neyaashiinigmiing in Georgian Bay (Ontario, Canada), home of the Chippewas of Nawash Unceded First Nation (Nawash) (Fig. 1). Port Elgin Bay includes a spawning shoal (the Little Port Elgin or LPE shoal) that is actively fished by SON harvesters. The LPE shoal consists of a main spawning shoal (main LPE shoal) with a 2–5 m depth, as well as other locations within the study area, such as an adjacent “finger” to the main shoal (near Stn 8) in slightly deeper waters (5–10 m), where spawning is also thought to occur by SON harvesters (Fig. 2). SON has described parts of the LPE shoal as being ‘honeycomb rock’, a flat rocky substrate with small circular holes that give the lakebed a dimpled texture. Other substrate types are also present in the study area, for example, sandy flats are at the southern edge of our study site beyond the main shoal (Fig. 2). Fine-scale bathymetric mapping was completed in the study area by the Ontario Ministry of Natural Resources and Forestry (MNRF) in the summer of 2020 to inform the VPS design (Fig. 2). The surveyed area was roughly 2.1 km × 2.9 km at the widest points, with recorded depths ranging from 2 to 77 m.

thumbnail Fig. 1

Map of the study area (WGS84 projection), Port Elgin Bay (red shading), located in Georgian Bay, Lake Huron. Port Elgin Bay is offshore of Neyaashiinigmiing, home of the Chippewas of Nawash Unceded First Nation (Nawash). The study area is part of the larger Saugeen Ojibway Nation Traditional Territory (light green shading), that is occupied by both the Chippewas of Saugeen First Nation and Nawash (collectively know as the Saugeen Ojibway Nation).

thumbnail Fig. 2

Map of the VEMCO Positioning System (VPS) study area in Port Elgin Bay showing VPS receivers, lake whitefish capture locations, surgery site, and sentinel receivers. Sandy substrate (green) and the main spawning shoal (black) within Port Elgin Bay are shown as polygons. The sandy substrate and main shoal polygons were informed by Saugeen Ojibway Nation-Ecological Knowledge (SON-EK).

2.3 Fish sampling and tagging

All sampling and fish handling procedures were approved by the MNRF’s Animal Care Committee (Project #166) and SON’s Joint Council and Joint Fisheries Committee. Adult lake whitefish were captured at night by SON harvesters on the main LPE shoal between 21 and 28 November 2020 using gill nets (36 mm mesh size; mean set time ± SD was 3.69 ± 3.77 h) set from a “punt” commercial fishing vessel (i.e., a flat-bottomed vessel with square bow). Immediately upon retrieval from the net, fish were placed in a holding tank on the vessel to transport to the surgery location onshore, ∼800 m north on the Nawash government dock (Fig. 2). Before surgeries, fish were transferred to a large holding tank (∼34 ft3) onshore (∼1 m from the lake) for observation. The holding tank was continuously fed with freshwater from the lake. Individuals deemed healthy (e.g., swimming upright, no signs of injury) were removed from the holding tank for each surgery. Surgeries occurred in a mobile tagging station set up in a trailer on the dock, where a semi-controlled environment provided optimal handling and surgical conditions. Individuals were anaesthetized in a buffered 120 ppm solution of tricaine methanesulfonate (MS-222) until loss of body and fin mobility and reduced gill movement occurred. Fish were measured before surgery for fork length (mm), total length (mm), and round weight (g; five fish were not measured for weight). Only fish greater than 1300 g underwent surgery to ensure an adequate tag-to-fish weight ratio (mean ± SD tag-to-fish weight ratio was 0.76 ± 0.16 % for V16-4x-69 kHz transmitters and 0.78 ± 0.16 % for V16P-4x-69 kHz transmitters), which is typically no more than 2% of a fish’s body weight (Winter, 1983).

Following measurements, fish were placed into a cradle for immobilization and freshwater was irrigated slowly over the gills. Fish were implanted with V16 transmitters (herein tags) from Innovasea Ltd. (Bedford, NS, Canada), including 40 V16-4x-69 kHz (16 × 68 mm, 24 g in air) and 10 pressure V16P-4x-69 kHz (16 × 71 mm, 26 g in air, 68 m max depth, ± 3.4 m accuracy at room temperature) tags set to a nominal delay of 120 seconds. Tags were surgically inserted through a ∼50 mm ventral incision slightly off mid-line, anterior of the pelvic fins and closed using 2–3 box sutures depending on the incision size. Fish were sexed visually, either prior to surgery (if a fish was expelling eggs or milt) or following incision (visual inspection of gonads). Surgical equipment was sterilized using Ovadine® and rinsed with deionized water after each surgery. Floy cinch tags were inserted (∼2 cm anterior of the adipose fin) as a visual marker in case of later capture by harvesters. Following surgery (mean surgery time ± SD was 3.8 ± 0.77 min), fish were placed back into the holding tank for post-surgery monitoring, assessed for condition, then released off the side of the dock. The mean fork length and round weight of tagged fish was 609.60 mm (± 37.29 mm SD) and 3300 g (± 694 g SD), respectively (Supplementary Material S1). In total, 50 lake whitefish were tagged and successfully released, including 22 females and 28 males (Supplementary Material S1).

2.4 VPS design

In a VPS, receivers need to be placed at a distance from one another that allows for at least three receivers to detect the ping emitted by a tag, allowing for the position of the fish to be triangulated and tracked over time (Smith, 2013). Tag positions are calculated from raw detections using hyperbolic positioning algorithms which are based on the time-distance-of arrival of transmissions among receivers at fixed locations with synchronized clocks (Smith, 2013; Meckley et al., 2014; Roy et al., 2014).

For our study, the VPS was designed using a Two-Eyed Seeing approach where both local Indigenous knowledge and western science were used to determine receiver placement. The spatial extent of the main spawning shoal and study area were determined using the bathymetric map and SON-EK of spawning habitat and spawning locations. Before receiver deployment, range tests were completed to assess detection range within the study area and to help inform appropriate receiver spacing (see Supplementary Material S2 for details). Consultation with experts working with the Great Lakes Acoustic Telemetry Observation System (GLATOS) noted that we likely had a >1 km detection range in the study area (T. Binder, C. Vandergoot, and C. Holbrook, personal communication). From this information, we created multiple potential designs for the VPS and brought these to SON harvesters for input. SON harvesters noted two concerns: first, the receivers were too close, which might interfere with fishing activity on the shoal, and second, receivers would be difficult to see, resulting in the potential for entanglement with fishing gear. To accommodate these concerns, receivers were placed further apart and we added a visual flag above the water surface by attaching a small 10-lb mushroom anchor to the main anchor with rope. Overall, the receivers were placed between 500 m (addressing harvester concerns of fishing interference) and 750 m (ensuring triangulation of detections) apart.

We used VR2AR-69 kHz receivers manufactured by Innovasea Ltd. (Bedford, NS, Canada). Two receivers (“sentinel” receivers) were placed in the study site during tagging in 2020 and were left out until they were retrieved and incorporated into the VPS in mid-October 2021 (Fig. 2). One sentinel receiver was placed near the netting locations (Receiver ID: 549910) and the other was placed just off the dock where the fish were released (Receiver ID: 549915). These sentinel receivers were meant to provide information on the fate of tagged fish (for example, to determine if a fish immediately died following the surgery and if fish returned to Port Elgin Bay over time) and were part of a broader acoustic telemetry array deployed in Lake Huron as part of the Together with Giigoonyag project ( Once the final array design was agreed upon with SON and project team members, eleven receivers (designated as stations, ‘Stn’ 1-11) were deployed on 15 October 2021 at the study site as part of a VPS and removed on 18 January 2022, for a total of 96 days in the water (Fig. 2). The receivers were placed in depths ranging from ∼5 m (Stn 2) to ∼36 m (Stn 3). Receivers collected hourly information, including noise (dB), temperature (°C), the number of detections, and the number of pings received. Internal transmitters (‘synctags’) were enabled and programmed to ping at a rate of 540–660 s (nominal 600 s) for the purpose of clock synchronization (Smith, 2013).

2.5 Data filtering

All analyses were conducted in R 3.6.4 (R Development Core Team, 2022) and QGIS 3.20.1 (QGIS Development Team, 2023). Basemaps were from Esri using the QuickMapServices plugin in QGIS 3.20.1 (Copyright © Esri. All rights reserved). Initial pre-processing of fish position data was completed by Innovasea Ltd. From the 50 fish tagged in 2020, we analyzed the movement patterns of 26 individuals (nmales= 15, nfemales = 11) that returned to the LPE spawning shoal and had positions calculated for them on the VPS in 2021 (npositions = 143,318). Two fish were captured (and removed) by harvesters in December 2020 and 2021 (Fish IDs: 64602, 64592, respectively) and one fish was not detected at all post-release (Fish ID: 64588). Fish ID 64592 was used in our analyses because we had over 2800 positions before the fish was harvested. One fish (Fish ID: 4282) with a depth tag was assumed dead, or had the tag expelled, in mid-January 2021 because it was detected on a single sentinel receiver for an extended period and its depth remained unchanged; that fish was removed from the dataset post-HPE filtering.

Horizontal positioning error (HPE), calculated during pre-processing from the algorithms used to calculate fish positions, was provided for sync and animal positions as a relative, unitless estimate of error sensitivity (Smith, 2013). An actual measured error estimate (HPEm) was provided for synctag positions only, which produces a horizontal distance (m). Typically, a significant relationship between HPE and HPEm for synctags indicates that fish positions can be filtered by a specific HPE value that is set based on project goals (Coates et al., 2013; Meckley et al., 2014). Based on discussions between SON and the research team we decided that an HPEm value of 10 m would provide a suitable resolution for studying lake whitefish behaviour. To facilitate the filtering process, we followed Coates et al. (2013) to then bin HPE values (bin width = 1) and calculate the corresponding 90th percentile of HPEm (see Supplementary Material S3 for details). For synctag positions, a 90th percentile of HPEm at 10 m corresponded to HPE 14, which resulted in 79.4% of fish positions being retained in our dataset for further analyses (n = 113,861). Overall, post-filtering, our synctag positions had a mean ± SE HPEm of 3.29 m ± 0.01 m. However, this filtering resulted in a loss of three females in the dataset, leaving a total of 23 fish in our analyses, including 3 with depth tags.

2.6 Data visualization and heatmapping

An abacus plot was created to visualize the positions of individual males and females over the study period and we also plotted the number of unique individuals detected per day. Heatmaps depicting the percentage and the number of individual males and females detected during the day and night were created using the position_heat_map() function in the glatos package (Holbrook et al., 2021). Mirroring the position error, the study area for the heatmaps was divided into 10 m × 10 m grid cells. Day and night designations for each position were calculated by the sunriset() function in the maptools package, where day is sunrise to sunset and night is sunset to sunrise (Bivand and Lewin-Koh, 2022).

2.7 Lake depth and vertical movement analysis

To quantify the extent to which males and females differed in their depth associations during the spawning season, the movement patterns of fish relative to the depth of the lake were examined. For the depth analyses, we estimated depth of the lake at each unique fish position by interpolating the contour lines of the bathymetry map in QGIS. The TIN interpolation and PCRaster tools were used to interpolate depth between contour lines at 1 × 1 pixel resolution and convert the resulting raster to a scalar PC Raster map. Positions were then overlaid onto the raster map and the Sample raster values tool was used to obtain the lake depth at each unique fish position.

Mean daily lake depth was calculated per individual and averaged per sex and diel period to characterize changes over the study period. We also calculated the average lake depth displacement per hour (m h−1) per individual, representing the average hourly change in vertical lake depth for each individual fish (herein ‘vertical movement’). These data were calculated by taking the mean lake depth per hour and then subtracting the mean lake depth from the next consecutive hour for each individual. If there was greater than a one-hour gap between the consecutive hours, these data were omitted from the dataset as we wanted to calculate only consecutive hourly displacement values within individuals. Positive mean vertical movement values indicated that, on average, tagged fish were moving into shallower depths, while negative vertical movement values indicated that, on average, fish were moving into deeper depths. We then plotted the mean hourly vertical movement by day of the year (DOY), hour, and sex. We examined lake depth at each position rather than depth of the fish within the water column (i.e., swimming depth) for our vertical movement analyses as only three depth-tagged fish remained in the dataset after HPE filtering. For the three fish with depth tags, we plotted the mean daily swimming depth per day, along with the raw swimming depth per day separated by diel period, and examined the relationship between swimming depth (response variable) and lake depth (explanatory variable) for each individual fish using linear regression.

2.8 Horizontal movement

To quantify the horizontal rate of movement (m s−1; herein ‘horizontal movement’), we followed procedures by Dahl and Patterson (2020) where we calculated the Euclidean distance between consecutive VPS positions and divided them by the time between each consecutive position for each individual fish. These data were further filtered to remove consecutive timesteps that were greater than one hour. Filtering by time in this way mitigates potential overestimation of distances and horizontal movement measurements that may occur when an individual leaves and then re-enters the array (Dean et al., 2014). We then plotted the mean horizontal movement by sex and diel period for each DOY.

2.9 Statistical analyses of movement variables

Statistical analyses were based on data collected between 15 October and 22 December 2021 as males were no longer in the study area after 22 December. Full linear mixed models were developed with the lmerTest package (Kuznetsova et al., 2022) to examine the extent to which variation in key movement variables (vertical and horizontal movement; i.e., the dependent variables) were explained by sex and diel period (i.e. the independent variables; Tab. 1). For vertical movement, hour of the day was added as a random effect to account for hourly variation and to aid with non-independence among observations. In the horizontal movement model, raw values of horizontal movement were averaged per hour for each individual and used as the input to the model to reduce autocorrelation. Additionally, individual fish and hour nested within DOY were added as random effects to account for repeated sampling among individuals and aid with non-independence among observations and the number of raw movement values used to calculate each averaged value was added as a covariate. Alternative (sub) models that included all possible combinations of explanatory variables were compared using their Akaike Information Criteria (AIC) values to choose the model of best fit (Supplementary Material S4). A p-value of ≤0.05 was used to assess significance. Assumptions of normality and homogenous residuals were evaluated for each model by plotting model residuals using quantile-quantile plots and histogram plots with supplementary Levene’s tests (car package; Fox and Weisberg, 2019). We assessed independence of residuals using autocorrelation function plots.

Table 1

Final models to assess the relationships between independent (sex; diel period; number of raw values) and dependent (vertical movement in m h−1, n = 12,688; and horizontal movement in m s−1; n = 13,106) variables. Hour (hour of the day), Day (each day of the study period), and Individual fish (unique IDs of the fish) were included, but varied, as random variables between the models. Bolded p-values indicate a significant result (p < 0.05).

3 Results

3.1 Annual patterns of fish detected on a sentinel receiver

We noted several patterns in tagged fish detected on the sentinel receiver placed near the gill netting location (Receiver ID: 549910) during tagging in November 2020 and left in the water year-round. First, 46.0% of fish (nmales= 13, nfemales = 10) were detected in the area for 1–3 months after tagging in 2020 before leaving; of those fish, 5 males and 1 female returned and were detected on the VPS in 2021 (Supplementary Material S5). Second, 20.0% (nmales = 4, nfemales = 6 females) of individuals were more resident in nature, either having relatively higher detections compared to other fish and/or were detected most months from tagging onwards; of those, 3 males and 6 females were detected on the VPS in 2021. The remaining 32.0% of tagged fish (nmales = 11, nfemales = 5) were detected in the area at various times throughout 2021 with no apparent patterns; of those fish, 7 males and 5 females returned and were detected on the VPS in 2021.

3.2 Environmental conditions and VPS positions summary

During the VPS deployment (i.e., the entire time during which the VPS was in the water), temperature (°C) consistently declined over time (Supplementary Material S6). There were two noticeable drops in temperature in late October and mid-November of 2021, which appeared to correspond to precipitation events (rain, ice showers) and declines in air temperature that were recorded 1–2 days prior on a nearby weather buoy (Wiarton, Ontario; 44° 44’ 39” N, 81° 06’ 31” W; operated by Environment and Climate Change Canada).

In total, 256,752 positions were calculated on the VPS, of which 61.6% were fish positions (158,138) and 38.4% were synctag positions (98,614). The remaining results herein only include HPE-filtered data. Two female fish (Fish ID: 64605, Fish ID: 64601) accounted for nearly 75.4% of the total female positions (23,802 and 19,647, respectively). Additionally, despite having twice the number of males than females, total positions for each sex were near equal (female positions = 57,619; male positions = 56,242).

3.3 Spatial patterns of occupancy

Fish occupancy on our VPS resembled a bell-shaped curve, where there was an increase up to a peak and subsequent decrease in the number of individuals detected (Fig. 3, Tab. 2). To aid in the description of the results, we divided the curve into five stages (pre-activity; escalation; peak activity; de-escalation; post-activity). Before November 2, there were few individuals present and the slope of the relationship between the number of individuals and date was flat, indicating little change in number of fish arriving in the study area (‘pre-activity’). In general, the pre-activity stage included fish that were detected in the study area for a few days, hours, or once, and then left (Supplementary Material S7). During the pre-activity stage, individuals of both sexes appeared for short periods of time and then left, except for two females (Fish ID: 64601 and 64605), which were present for almost the entire VPS deployment period. Following the pre-activity stage, there was a steady positive increase in the number of individuals over time (‘escalation’), and these fish were detected in the area for more extended periods of time than during the pre-activity stage (Fig. 3a, Supplementary Material S7). Except for the two females consistently positioned during the study and another female (Fish ID: 64621), males arrived, and generally became established in the study area earlier than females during the escalation stage (Supplementary Material S7). The height of activity (‘peak activity’) lasted for approximately one week (25 November − 1 December), where as many as 22 fish were present per day and the number of individuals remained steady over time (Fig. 3a). Following peak activity, there was a decline in the number of individuals (‘de-escalation’), which ended when the number of individuals detected per day flattened and remained relatively constant (‘post-activity’). The slope of the relationship between number of individuals and date appeared steeper during the de-escalation stage than during the escalation stage, indicating that fish left the area quicker than they arrived, which was especially true for males (Fig. 3b). In the post-activity stage, no males were detected after December 22, whereas three females were still detected until retrieval of the VPS on 18 January 2022.

During the pre-activity stage, males and females were never observed on the main shoal. During the day, both sexes occupied deeper waters to the east and shallower waters to the south, with females tending to be more dispersed (Supplementary Material S8, Fig. S7). At night during pre-activity, both sexes were more concentrated with females moving up the slope into a narrow band of shallower water (∼15 m) to the northeast of the shoal and males occupying a band to the southeast (∼25 to 30 m).

There were then three distinct areas used during the escalation stage (Fig. 4). First, males and females during the day were concentrated along the same narrow band to the northeast that females used during pre-activity at night, although a slightly wider depth range was used (10–25 m). At night, females shifted into shallower depths ranging from 5 to 20 m. Second, during both day and night, fish were concentrated to the south in a gradually sloped and sandy region (Fig. 2). Third, at night, males alone used the main LPE shoal, where up to 53% of males (n = 15) were present in some grid cells (Fig. 4). This use of the main LPE shoal for males began on 5–11 November, three weeks prior to peak activity (Supplementary Material S9, Fig. S12) when water temperatures were consistently 10 °C or less (Supplementary Material S6). Aggregations of males (>2 individuals per grid cell) on the shoal began appearing on 12–18 November, two weeks prior to peak activity (Supplementary Material S9, Fig. S13).

During peak activity (25 November − 1 December), there were clear differences between sexes in their spatial positions. During the day, males very clearly occupied the shallower sandy substrate whereas at night males used the main LPE shoal (Fig. 4). Females occupied the sandy area to the south and narrow band to the northeast during both the day and night, but rarely used the LPE shoal.

During the de-escalation stage, the sandy areas to the south were heavily utilized by both sexes during the day (Fig. 4). At night, males then also concentrated on the LPE shoal while females were observed there too although to a lesser extent than males. At night females also occupied the sandy area to the south like males, as well as the narrow band extending from the north down to the “finger” just south of the shoal and near Stn 8 (Fig. 2). Males were also found in this “finger” at night, most notably in the second week of the de-escalation stage (Supplementary Material S9, Fig. S17). During the post-activity stage, males were present only for the first two days (Supplementary Material S8, Fig. S8), while females were no longer present in either the sandy or LPE shoal area and they had returned to the sloped areas north and adjacent to the LPE shoal and shoreline.

thumbnail Fig. 3

The number of individuals detected per day during the VEMCO Positioning System deployment overall (a) and by sex (b). Five stages of activity are depicted based on patterns of occupancy.

Table 2

Description of stages of occupancy in Port Elgin Bay between 15 October 2021 and 18 January 2022. Includes dates (total number of days), stage characteristics, cumulative number of individuals, ratio of males to females, and ratio of number of telemetry positions between males and females.

thumbnail Fig. 4

Heatmap displaying the percentage of male and female lake whitefish during the day and night present in each grid cell (10 m × 10 m) in the study area during the escalation (15 males, 7 females; 2–24 November 2021), peak activity (15 males, 7 females; 25 November–1 December 2021), and de-escalation (15 males, 5 females; 2–19 December 2021) stages. The number of positions for each sex for the day and night were 10,003 and 19,032 for males and 6191 and 11,796 for females for the escalation stage, 2978 and 3064 for males and 1763 and 2705 for females for the peak activity stage, and 7225 and 9863 for males and 2265 and 4989 for females for the de-escalation stage, respectively.

3.4 Depth occupancy

Both sexes generally used shallower lake depths at night than during the day across the entire study period (Fig. 5). During the night, there was an obvious decrease in mean depths occupied (i.e., depths were getting shallower) up until peak activity, after which time the depths occupied became deeper again. During the day, a similar pattern was observed except for a few days which were more variable. During pre-activity, males used deeper habitats at night than females. Midway through the escalation stage (10–11 November) and onwards, the mean depth of males at night became shallower than females (by ∼3 m). There were no differences in mean depths occupied between the sexes during the day.

For the three fish implanted with depth tags, the male (Fish ID 4287) had a mean ± SD swimming depth of 7.17 ± 1.99 m during peak activity, with the two females (Fish ID’s 4283 and 4286) having mean swimming depths of 7.97 ± 2.27 m (Supplementary Material S10). Neither female was positioned at depths less than 5 m until the last day of the escalation stage (24 November; Fish ID 4286) and at the middle of the peak activity stage (30 November, Fish ID 4283). However, the male swam at depths less than 5 m several times throughout the escalation and peak activity stages. Lake depth usage patterns largely mirrored swimming depth patterns for the three depth tagged fish (Supplementary Material S10). There was a statistically significant and positive relationship between swimming depth and lake depth for the three fish with depth tags (p < 0.0001; R2 ranging from 0.72 to 0.88; Supplementary Material S10, Fig. S25). For some positions from Fish ID’s 4283 and 4287, swimming depths were deeper than lake depths, potentially due to depth tag accuracy or lake depth inconsistencies. For all positions where swimming depths were shallower than lake depths, swimming depths were on average 2.88 m shallower than lake depths, although this was highly variable (SD ± 2.22 m).

thumbnail Fig. 5

Lake depths occupied by lake whitefish during the VPS deployment. Means and standard deviations are shown for males (N = 15; blue) and females (N = 8; orange) between 15 October 2021 and 18 January 2022 for the 5 stages of occupancy.

3.5 Movements during the spawning period

Lake whitefish moved into shallower waters at night and deeper waters during the day during the VPS study period (Fig. 6). Vertical movements were less extreme about a week leading up to, during, and about a week after peak activity, which was particularly evident between ∼07h00–08h00 local time (Fig. 6). Typically, movements into deeper waters occurred around dawn (∼07h00–08h00) and into shallower waters during dusk (∼17h00–18h00). Generally, both sexes exhibited larger vertical movements during the day than the night, however, the largest amplitudes of movement occurred around dawn and dusk. Overall, diel period had a significant effect on vertical movement (df = 7695, p = 0.004; Tab. 1). Specifically, our model predicted that night had a positive effect on vertical movement, indicating movement into shallower lake depths at a mean rate of 0.184 m h−1. In contrast, day had a negative effect on vertical movement, indicating fish were moving into deeper lake depths during the day at a mean rate of 0.130 m h−1 (Tab. 1).

Between 15 October and 22 December, the mean horizontal movement rate for all individuals was 0.158 (± 0.127) m s−1. Horizontal movement rates for both sexes decreased gradually until a week after peak activity (Fig. 7). During the day, mean horizontal movement rates were 18.0% higher for females than males (0.245 ± 0.133 m s−1 and 0.201 ± 0.122 m s−1, respectively). The opposite was observed at night when the mean horizontal movement rate was 39.5% higher for males than for females (0.157 ± 0.130 m s−1 and 0.095 ± 0.08 m s−1, respectively). There was a significant interaction between sex and diel period on mean rate of movement (df = 12,260, p < 0.0001; Tab. 1), where the model predicted females were moving horizontally on average 0.057 m s−1 slower than males at night and 0.006 m s−1 faster than males during the day. For the pre-activity, escalation, de-escalation, and post-activity stages, mean horizontal movement rates were lower at night than during the day for both sexes (Supplementary Material S11). Conversely, during peak activity, male horizontal movement rates during the night were faster than during the day. Specifically, during peak activity, mean horizontal rate of movement during the day and night was 0.203 (± 0.11) and 0.139 (± 0.11) m s−1, respectively, for females and 0.184 (± 0.11) and 0.221 (± 0.18) m s−1, respectively, for males (Supplementary Material S11).

thumbnail Fig. 6

Mean vertical movement (m h−1) over the study period (15 October 2021–18 January 2022) based on 15 males and 8 females. Positive values (yellow hues) indicates fish were moving into shallower lake depths and negative values (purple hues) indicates fish were moving into deeper lake depths.

thumbnail Fig. 7

Mean horizontal movement rate (m s−1) per sex and diel period over each day of the study period (15 October 2021–18 January 2022) based on 15 males and 8 females. Error bars represent the standard deviation.

4 Discussion

At an active spawning shoal in Georgian Bay (Lake Huron), lake whitefish demonstrated obvious patterns of sex-specific behaviour and diel movements during the 2021 spawning season. Lake whitefish displayed a distinct pattern of occupancy, reaching a maximum of 22 individuals per day detected on the VPS. Both sexes moved into and occupied shallower waters at night and deeper waters during the day, with the peak of these movements occurring at dawn and dusk. Horizontal movement depended on whether the fish was male or female and whether it was day or night, with males moving faster at night and females moving faster during the day. We also found that lake whitefish used other areas in addition to the main spawning shoal, including the southern portion of Port Elgin Bay that is characterized by a sandy bottom and narrow bands of depth to the east of the main shoal that run parallel to the shoreline. Information gathered by our study, including habitat usage, arrival times on the shoal, and how the sexes differ in their movement could be helpful for future efforts in understanding factors contributing to variation in reproductive output, larval production, habitat use, and recruitment.

There was a distinct increase, peak, and subsequent decrease in the number of lake whitefish detected on our VPS (Fig. 3). The escalation through de-escalation stages had a duration of about 48 days (2 November − 19 December), generally indicative of the duration of the spawning season of lake whitefish in our study. The peak of activity lasted for about a week, although we don’t know exactly when fish were spawning. Our graph (Fig. 3) quantifying the arrival and departure of lake whitefish to a known spawning shoal, is among the first direct measurements of the timing and duration of the spawning season for lake whitefish that we are aware of. In Lac la Ronge (Saskatchewan, Canada), lake whitefish underwent spawning migrations into shallower waters and river mouths between the 3rd and 4th week of October, with the spawning season described as lasting into the middle of November (Qadri 1968). These accounts in Lac la Ronge are based on netting and sampling of lake whitefish during the fall, but no data or results were provided showing arrival timing on specific shoals (Qadri 1968). Goodyear et al. (1982) generally described the spawning period for lake whitefish in the Great Lakes to occur between October-December based mostly on catches in commercial fishing nets. Bégout Anras et al. (1999) tracked lake whitefish in a small lake using acoustic telemetry and found a similar result to ours where peak spawning activity in the nearshore, as indicated by the higher frequency of tag detections, lasted for about 5 or 6 days. The duration and timing of the spawning period can be influenced by climate, population demographics, and fishing pressure, causing contractions or protractions (Rogers and Dougherty, 2019; Starzynski and Lauer, 2014). Defining the timing window during which fish are present in and around the shoal and surrounding habitats for spawning, as well as how this timing varies with environmental conditions and population size would be valuable for designing stewardship strategies aimed at protecting spawning fish and critical spawning habitat.

We found evidence of lake whitefish staging behaviours in this study. Except for the two female fish that accounted for most of the female positions, males arrived first in the study area during the escalation stage, and except for another female (Fish ID: 62621), became relatively resident to the study area about one week before other females arrived (Supplementary Material S7). Additionally, a shift in habitat usage occurred at night on 10–11 November (mid-escalation stage) when males began to occupy shallower depths than females (Fig. 5). This change in occupancy was closely related to when more than one male was detected per grid cell on the main LPE shoal (the week of 12–18 November), perhaps indicating a start to spawning (Supplementary Material S9, Fig. S13). Male lake whitefish have been previously described as generally undergoing spawning migrations or arriving on spawning shoals prior to females (Qadri, 1968; Hart, 1930), although little direct quantitative evidence for this was provided in these historical accounts as most information was from anecdotal reports from harvesters or from broad netting surveys. Studies of other Coregonus spp. in European lakes have observed males arriving on spawning shoals prior to females (Dabrowski, 1981; Luczynski, 1986). Staging has been used in other studies to officially demarcate the beginning of the spawning for behavioural analyses and thus can be useful to identify. For example, in Binder et al.’s (2016) study of lake trout (Salvelinus namaycush Walbaum 1792), the spawning period was defined by males moving from deep offshore water into shallower nearshore water, as males generally arrived earlier and in higher densities on spawning shoals than females. A more equal sex ratio among tagged fish and a higher number of implanted depth tags would allow for a better understanding of lake whitefish staging behaviour.

Both sexes of lake whitefish moved into shallow waters during the night and deeper waters during the day. This pattern is consistent with spawning occurring at night, mostly on the main spawning shoal, as reported by SON knowledge holders. Both sexes exhibited larger amplitudes of vertical movement during the day, perhaps because they were utilizing more variable habitat while in areas beyond the main shoal. At night, fish tended to move onto the shoal (thus moving shallower), potentially to find receptive partners and initiate spawning. This was especially true for males during the peak activity stage and for both sexes during the de-escalation stage. Once on the shoal, vertical movement was more limited. In a previous telemetry study of lake whitefish in a small lake (253 ha), males and females also exhibited strong diel vertical migrations during the spawning season, where tagged fish had higher vertical velocities during the day than at night (Gorsky et al., 2012). Thus, there appears to be some consistency in the diurnal patterns of the spawning season for lake whitefish across different systems.

Male and female lake whitefish differed in the rate at which they moved during the day versus the night (Fig. 7). Overall, the decrease in the horizontal rate of movement during the day leading up to peak activity was similar to findings by Bégout Anras et al. (1999) in their study of movement and habitat use of lake whitefish in an Ontario boreal lake, where swimming speed decreased leading up to peak spawn, although sex and diel comparisons were not made. Interestingly, we found that the horizontal movement rates of both sexes increased at night leading up to peak activity, contrasting Bégout Anras et al. (1999). This difference indicates the importance of diel period when conducting movement analyses on fish. Females in our study exhibited faster horizontal movement rates during the day, while males had faster horizontal movement rates at night. These differences could arise, for example, if males were searching more actively for females on the shoal at night which has been observed in brook trout (Salvelinus fontinalis Mitchill 1814) in Scott Lake, Ontario, where males were highly mobile and revisited spawning sites in search of mating opportunities (Blanchfield and Ridgway, 2023). The overlapping space use observed for males coupled with a higher occupancy of the main shoal than females in our study may indicate there is endurance rivalry in males (the ability to stay reproductively active throughout the spawning season), which has been documented in other salmonids, like arctic charr (Salvelinus alpinus Linnaeus 1758) (Johnson, 1980; Esteve, 2005). Differences in the rates of movement between the sexes also has implications for bioenergetics, for example, in understanding how the reproductive costs of spawning vary between males and females (Koch and Wieser, 1983). Lake whitefish bioenergetic models (e.g., Rudstam et al., 1994; Madenjian et al., 2006, Madenjian et al., 2013), which rely on laboratory-derived parameters or make assumptions based on estimates collected for other species, would benefit from having field-based sex-specific rates of movement measured during the spawning period, such as those provided by our study.

Evidence of spawning site fidelity was observed among our tagged male and female lake whitefish. More than half of the fish tagged during the spawning season at our study site in 2020 were detected in the study area during the spawning season in 2021, including both males and females. Interestingly, 20% of tagged lake whitefish were detected in the study area almost year-round. In contrast, other lake whitefish left for an extended period or for repeated, shorter durations before returning for the 2021 spawning season. This indicates that lake whitefish not only show spawning site fidelity but that some individuals in this population show residency at this site year-round. A quantitative analysis of spawning site fidelity at this location based on telemetry would require additional years of data and ideally knowledge of the fate of fish that didn’t return (Binder et al., 2016; Hayden et al., 2018). Genetic studies have revealed that stock structure indeed exists for lake whitefish within the Great Lakes, which would require some level of spawning site fidelity to maintain, however, the spatial scale of the structure varies for different stocks and locations (VanDeHey et al., 2009; Stott et al., 2012; Stott et al., 2013). Spawning site fidelity has been shown to varying degrees in previous tagging studies of lake whitefish in the Great Lakes including Lake Huron (Ebener and Copes, 1985; Walker et al., 1993; Ebener et al., 2010; Ebener et al., 2021). For example, a mark-recapture study of lake whitefish in Grand Traverse Bay, Lake Michigan found that all tag returns during the November spawning season were from the original tagging sites, indicating that each of three spawning stocks examined showed spawning site fidelity (Walker et al., 1993). Conversely, another mark-recapture study in Saginaw Bay, Lake Huron found little evidence of spawning site fidelity as most tag returns during subsequent spawning seasons occurred outside of where November tagging had occurred (Walker, 1992). Ebener et al. (2021) synthesized mark recapture recoveries across Lakes Superior, Huron, and Michigan for 1975–2008 and found that 68% of tag recoveries were made in the management unit of tagging. However, the ability of these prior tagging studies to estimate spawning site fidelity is relatively limited because they were relying on the capture and reporting of fish caught in nets (which can be few in number) and recoveries were generally assigned to larger areas (e.g., 10-min statistical grid) that might include several spawning shoals. Also, fish were not necessarily targeted on specific spawning shoals during actual spawning as was the case with our study. Acoustic telemetry has the added advantage of tracking the movements of tagged fish in a more specific and direct way. A lake-wide acoustic telemetry array recently implemented in Lake Huron will hopefully be able to provide further insights into spawning site fidelity of lake whitefish.

Lake whitefish used various locations other than the main spawning shoal within Port Elgin Bay during the spawning season. At various times throughout the study, both sexes used sloped areas to the north and east. Females especially also heavily utilized multiple narrow bands of depth contours (∼5–30 m) running parallel to shore and connecting the north to southern region of the study area. Males concentrated on the main LPE shoal at night from two weeks before pre-activity (Supplementary Material S9, Fig. S13) until two weeks after peak activity (Supplementary Material S9, Fig. S17). Females, on the other hand, were positioned on the shoal to a much lesser extent and only during peak activity and the subsequent week where there was minimal spatial overlap among individuals. These results concur with lake trout mating strategies observed in the Great Lakes, where males tend to be captured more significantly and congregate more on spawning sites than females (Muir et al., 2012). Male congregations are consistent with a bet-hedging strategy where males maximize their encounters with females by remaining at a high-quality spawning site while awaiting the arrival of females (Leggett, 1977; Krebs and Davies, 1993). During the day, males and females in our study tended to favour areas that SON membership identified as being sandy substrate, particularly over the escalation to de-escalation stages (Fig. 4). According to SON-EK, lake whitefish use these sandy areas, known for being productive and having lots of prey, for feeding. As spawning approaches, females rub their bellies on the sandy substrate in these areas to loosen up their eggs. The use by lake whitefish of this broader range of locations and habitats indicates their reproductive habitat is more complex than just the spawning shoal. This knowledge is valuable for management because it could help support efforts towards habitat restoration or protection during the spawning season.

There were limitations in our study that are important to acknowledge. First, we provided results from only one spawning season at one spawning location with a relatively small and male-dominant sample size. Multiple years of observations from more than one spawning site would be needed to corroborate the behaviours we observed and to build a more broadly applicable conceptual model of the spawning behaviour of lake whitefish, like what was done for lake trout (Binder et al., 2021; Marsden et al., 2021). Second, we do not know precisely where and when lake whitefish spawned their gametes, including whether they spawned at all or where embryos might have settled. Our heatmaps give us an idea of where potential spawning hotspots were; however, there was roughly 10 m of error surrounding our positions owing to the criteria for HPE filtering and based on the size we set for our grid cells. Future studies should consider using divers (Binder et al., 2018), egg mats (Marsden et al., 2001), or remotely operated vehicles (Pacunski et al., 2008), to not only confirm spawning, but to characterize the functional spawning habitat of lake whitefish. Fortunately, we had SON-EK to help interpret the spatial patterns we observed and to identify the location of the main spawning shoal in our study. Ebener et al. (2021) recommended that an important step in understanding lake whitefish recruitment would be understanding the productive capacity, quantity, and distribution of lake whitefish spawning habitat in the Laurentian Great Lakes. Coupling a VPS study like ours with detailed substrate mapping and sampling of early life stages (e.g., eggs, larvae) would provide a way of quantifying the productive capacity of a spawning shoal as a function of key variables such as how much spawning habitat is available.

Applying a Two-Eyed Seeing approach substantially enhanced our study of the spawning behaviour of lake whitefish. In a Two-Eyed Seeing approach, Indigenous ecological knowledge (in this case, SON-EK) and western science are bridged in an effort to gain a deeper understanding of the natural world (Muir et al., 2023; Reid et al., 2021). Through our approach, the independence and strength of each knowledge system was recognized and valued (Reid et al., 2021; Almack et al., 2023). SON membership directed the study objectives and research questions and SON-EK provided guidance on where to catch spawning fish for tagging and on where to place receivers. Additionally, SON-EK gave context and explanations as to why lake whitefish were using areas beyond the spawning shoal. Through the other eye of knowledge, western science contributed to the technological aspects of the study including calculating detection range to inform receiver spacing and in the statistical analysis of data. Furthermore, through ceremony and community events that were part of the Two-Eyed Seeing process, project team members were able to feel a deeper appreciation for the importance of building reciprocal and ethical relationships with each other and with the lake and fish and gained a deeper awareness of the importance of dikameg to SON. We hope that our study provides a valuable example of putting Two-Eyed Seeing into practice and how it has potential for supporting the building of relationships between Indigenous and non-Indigenous Peoples. Readers should seek out future publications arising from our Two-Eyed Seeing research that includes further elements of SON-EK, including the results of interviews with knowledge holders about declines of dikameg and ecosystem changes in Lake Huron.

Fine-scale acoustic telemetry and local Indigenous ecological knowledge allowed us to quantify the movement and space use of male and female lake whitefish during the spawning season. As Brenden et al. (2010) recommended, by taking a fine-scale look at spawning locations, researchers can tease out factors affecting lake whitefish recruitment. Our detailed examination of sex-specific movements during the spawning season will hopefully lead to future work aimed at understanding linkages between spawning behaviour, environmental conditions, habitat quality, and recruitment. Future work, for example, could characterize substrate, habitat quality in the face of invasive and nuisance species like dreissenid mussels and filamentous algae, and the presence of egg predators such as round gobies, all of which could influence embryo survival and recruitment (Ebener et al., 2021). The declines of lake whitefish in many regions of the Laurentian Great Lakes threaten the ecosystem services that these fish provide. Understanding the causes of lake whitefish declines and identifying potential stewardship opportunities are priorities for natural resource management agencies and First Nations (Ebener et al., 2021; Almack et al., 2023). As shown for many aquatic species (Dean et al., 2014; Binder et al., 2018; Dahl and Patterson, 2020; Withers et al., 2021), fine-scale acoustic telemetry offers promise for filling knowledge gaps on the spawning behaviour and habitat use of fish as they face stressors like invasive species, climate change, and overexploitation.

Supplementary material

Appendix S1. Lake whitefish tagging and total positions summary.

Appendix S2. Range testing.

Appendix S3. HPE filtering.

Appendix S4. Full and alternative model tables.

Appendix S5. Yearly detections and patterns on a sentinel receiver.

Appendix S6. Mean daily temperature over time.

Appendix S7. Abacus plot of individual fish positions over time.

Appendix S8. Pre-activity and post-activity heatmaps.

Appendix S9. Weekly heatmaps.

Appendix S10. Swimming depth and lake depth plots.

Appendix S11. Mean horizontal rate of movement in each activity stage.

Access here


This research would not have been possible without the input by Saugeen Ojibway Nation members, including harvesters, councillors, youth, and elders. We thank N. Saunders, C. Akiwenzie, J. Ritchie, A. Duncan, P. Thiede, J. Chegahno, and J. Jones in particular for their assistance with the project and for sharing their knowledge. We gratefully acknowledge the contributions from staff of the Upper Great Lakes Management Unit of the MNRF (including C. Davis, J. Ritchie, B. Perry, S. Talbot and W. Zeinstra), from the Aquatic Research Section of the MNRF (including J. Trumpickas, D. Lipskie, C. Taylor, and M. Pinder), and from Fathom Five National Marine Park (including C. Harpur, G. Ceaser and Z. Melnick). We thank T. Binder, C. Vandergoot, C. Holbrook, N. Nate, G. Raby, R. Marotte, and K. Dahl for aid in project design and analysis. We also wish to acknowledge the Great Lakes Acoustic Telemetry Observation System (GLATOS) for assistance with this project.


This research was funded by the Great Lakes Observation System (Smart Great Lakes Program) and the Government of Canada’s Nature Legacy for Canada Initiative for the project Together with Giigoonyag.

Data availability statement

Data generated or analyzed during this study are available from the corresponding author upon reasonable request. All SON-EK shared in this study is subject to the principles of OCAP® (ownership, control, access, and possession) (First Nations Information Governance Centre, n.d.).


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Cite this article as: Ryther CM, Lauzon R, Buell M-C, Duncan R, Redford B, Dunlop ES. 2024. Spawning behaviour of lake whitefish in Lake Huron revealed by fine-scale acoustic telemetry and Indigenous ecological knowledge. Int. J. Lim. 60: 8:

All Tables

Table 1

Final models to assess the relationships between independent (sex; diel period; number of raw values) and dependent (vertical movement in m h−1, n = 12,688; and horizontal movement in m s−1; n = 13,106) variables. Hour (hour of the day), Day (each day of the study period), and Individual fish (unique IDs of the fish) were included, but varied, as random variables between the models. Bolded p-values indicate a significant result (p < 0.05).

Table 2

Description of stages of occupancy in Port Elgin Bay between 15 October 2021 and 18 January 2022. Includes dates (total number of days), stage characteristics, cumulative number of individuals, ratio of males to females, and ratio of number of telemetry positions between males and females.

All Figures

thumbnail Fig. 1

Map of the study area (WGS84 projection), Port Elgin Bay (red shading), located in Georgian Bay, Lake Huron. Port Elgin Bay is offshore of Neyaashiinigmiing, home of the Chippewas of Nawash Unceded First Nation (Nawash). The study area is part of the larger Saugeen Ojibway Nation Traditional Territory (light green shading), that is occupied by both the Chippewas of Saugeen First Nation and Nawash (collectively know as the Saugeen Ojibway Nation).

In the text
thumbnail Fig. 2

Map of the VEMCO Positioning System (VPS) study area in Port Elgin Bay showing VPS receivers, lake whitefish capture locations, surgery site, and sentinel receivers. Sandy substrate (green) and the main spawning shoal (black) within Port Elgin Bay are shown as polygons. The sandy substrate and main shoal polygons were informed by Saugeen Ojibway Nation-Ecological Knowledge (SON-EK).

In the text
thumbnail Fig. 3

The number of individuals detected per day during the VEMCO Positioning System deployment overall (a) and by sex (b). Five stages of activity are depicted based on patterns of occupancy.

In the text
thumbnail Fig. 4

Heatmap displaying the percentage of male and female lake whitefish during the day and night present in each grid cell (10 m × 10 m) in the study area during the escalation (15 males, 7 females; 2–24 November 2021), peak activity (15 males, 7 females; 25 November–1 December 2021), and de-escalation (15 males, 5 females; 2–19 December 2021) stages. The number of positions for each sex for the day and night were 10,003 and 19,032 for males and 6191 and 11,796 for females for the escalation stage, 2978 and 3064 for males and 1763 and 2705 for females for the peak activity stage, and 7225 and 9863 for males and 2265 and 4989 for females for the de-escalation stage, respectively.

In the text
thumbnail Fig. 5

Lake depths occupied by lake whitefish during the VPS deployment. Means and standard deviations are shown for males (N = 15; blue) and females (N = 8; orange) between 15 October 2021 and 18 January 2022 for the 5 stages of occupancy.

In the text
thumbnail Fig. 6

Mean vertical movement (m h−1) over the study period (15 October 2021–18 January 2022) based on 15 males and 8 females. Positive values (yellow hues) indicates fish were moving into shallower lake depths and negative values (purple hues) indicates fish were moving into deeper lake depths.

In the text
thumbnail Fig. 7

Mean horizontal movement rate (m s−1) per sex and diel period over each day of the study period (15 October 2021–18 January 2022) based on 15 males and 8 females. Error bars represent the standard deviation.

In the text

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