Post-Habitat Enhancement Construction Monitoring (2017-2019)
Following the enhancement of riverbed substrate in Reach 1, we conducted surveys covering a total of 226 survey plots. These plots were distributed among three areas: Reach 1 Enhanced (n = 97), Reach 1 Natural (n = 52), and known spawning locations in the Tailrace Area (n = 77). In Reach 1 Enhanced, the substrate cover in the habitat enhancement area consisted of 69% gravel, 24% cobble, and 7% boulder (Figure 2B). In comparison, Reach 1 Natural had a higher proportion of cobble (41%), boulder (31%), and bedrock (12%) cover (Figure 3). When comparing Reach 1 Natural to the Tailrace Area, the substrate cover in Reach 1 Natural showed similar levels of cobble and boulder cover, but slightly more gravel and no fines. In the Tailrace Area’s known spawning locations, the sampled area was primarily composed of gravel (61%) and cobble (24%), with smaller amounts of boulder (7%) and fines (6%) (Figure 3).
The maximum number of adult lake trout observed during a complete survey of Reach 1 and the Tailrace Area showed a steady increase over the years. In 2016, the maximum count was 42 fish, which rose to 54 fish in 2017 and further increased to 60 fish in 2018. In contrast to lake trout, the numbers of lake whitefish and cisco generally declined over time. The highest count of lake whitefish was observed in 2016, with a maximum of approximately 1,343 fish, slightly surpassing the maximum count of 1,000 fish recorded in 2017. In 2018, the maximum count of lake whitefish decreased to 411 fish, and in 2019 it further reduced to 683 fish. As for cisco, they were most abundant in 2017, with a maximum count of approximately 5,200 fish during one survey, slightly higher than the maximum count of 4,420 cisco recorded in 2016. However, the maximum count of cisco declined in the subsequent years. In 2018, the maximum count was 670 cisco, and in 2019 it dropped to 93 cisco during one survey. Overall, the snorkel surveys provided valuable data on the abundance of spawning schools of lake trout, lake whitefish, and cisco, showing different patterns of change over the years.
Overall lake trout egg densities were, on average, 50.9 eggs per m2 ± 11.9 SE. Across study years, mean egg densities for Lake trout ranged from a high of 56.5 eggs per m2in 2018 to a low of 42.8 eggs per m2 in 2019. When pooling the data across three study years, the mean density of lake trout eggs was highest in Reach 1 Enhanced (68.5 eggs per m2 ± 10.2 SE), followed by non-modified areas of Reach 1 (51.6 eggs per m2 ± 11.9 SE) and the Tailrace Area (28.1 eggs per m2 ± 6.2 SE) (Figure 3). Habitat type and year were not statistically significant for lake trout egg densities for the permutational ANOVA; however, the interaction of habitat type and year was statistically significant (Table II, Figure 3). Post hoc test of mean lake trout egg densities in Reach 1 Enhanced identified statistically significant differences between years, including higher densities in 2018 versus 2017, and in 2019 versus 2017. Lake trout egg densities in Reach 1 Enhanced were similar between 2019 and 2018. Densities in Reach 1 Natural and Tailrace Area were also similar between years. Post hoc tests of mean lake trout egg densities identified significant effects of habitat type during each study year (Table II). Lake trout egg density in Reach 1 Enhanced was statistically lower than the density in Reach 1 Natural during 2017, but higher than the density in the Tailrace Area during 2018 and 2019 (Figure 3). Pooling 2018 and 2019 data combined (n = 180 plots), mean egg density for lake trout was 2.4-times higher in Reach 1 Enhanced versus Reach 1 Natural, and 3.0-times higher in Reach 1 Enhanced versus Tailrace Area.
Overall, coregonid egg densities were, on average, 413.6 eggs per m2 ± 38.9 SE. Across study years, mean egg density for coregonids was more variable than that recorded for lake trout with a high of 613.8 eggs per m2 in 2018, 3.4-times greater than densities in 2017, and 3.5-times greater than densities in 2019. Similar to lake trout, the mean density of coregonid eggs was highest in Reach 1 Enhanced across habitat types when pooling data collected across study years (n = 226 plots): Reach 1 Enhanced = 725.7 eggs per m2 (± 71.7 SE), Reach 1 Natural = 288.1 eggs per m2 (± 57.5 SE), and Tailrace Area = 105.3 eggs per m2 (± 21.2 SE). Overall mean egg density was 2.5-times greater in Reach 1 Enhanced versus Reach 1 Natural, and 7.0-times greater in Reach 1 Enhanced versus Tailrace Area. Habitat type and year were statistically significant for coregonid egg densities for the permutational ANOVA and the interaction of habitat type and year was also statistically significant (Table II, Figure 4). Post hoc tests of mean coregonid egg densities identified significantly higher densities in 2018, versus 2017 and 2019 for both the Tailrace Area and Reach 1 Enhanced (Figure 4). Mean coregonid egg densities in Reach 1 Natural were similar between study years. Post hoc tests of mean coregonid egg densities identified statistically significant effects of habitat type during 2018 and 2019, with non-significant effects in 2017 (Table II). In 2018, densities were significantly higher in Reach 1 Enhanced versus Reach 1 Natural and Tailrace Area, and were similar between Reach 1 Natural and Tailrace Area. In 2019, densities were significantly higher in Reach 1 Enhanced and Reach 1 Natural, versus the Tailrace Area, and were similar between Reach 1 Enhanced and Reach 1 Natural.
Total lake trout egg count across all plots was 191 eggs in 2017, 620 eggs in 2018, and 273 eggs in 2019. The annual range of the survival rate metric was 0.424 to 0.542, with the highest survival rate metric in 2019 (0.542 ± 0.03 SE), followed by 2017 (0.515 ± 0.02 SE), and 2018 (0.424 ± 0.03 SE). Annual trends for Lake Trout within a specific habitat type included a higher egg survival metric in Reach 1 Enhanced in 2019 versus 2018 (Chi-squared = 34.5, p < 0.001) (Figure 5). The egg survival metric for Reach 1 Natural was also statistically higher in 2018 versus 2017 (Chi-squared = 8.17, p = 0.012). Of note, relatively few lake trout eggs were recorded in Reach 1 Enhanced during 2017 (n = 8 eggs) and in Reach 1 Natural during 2019 (n = 4 eggs) to provide a reliable comparison with other years and habitat types. The egg survival metric for the Tailrace Area was statistically similar (p > 0.05) for comparisons of 2017 versus 2018, and 2017 versus 2019; however, the metric was statistically higher in 2018 versus 2019 in the Tailrace Area (Chi-squared = 6.91, p = 0.026) (Figure 5).
For the period from 2017 to 2019, egg count for lake trout was 626 eggs in Reach 1 Enhanced, followed by 242 eggs in non-modified Reach 1, and 216 eggs in Tailrace Area. When pooling the data across three study years, the proportion of surviving eggs within a plot as a metric for egg survival for lake trout was highest in Reach 1 Enhanced (0.558 ± 0.02 SE), followed by non-modified Reach 1 Natural (0.545 ± 0.03 SE), and Tailrace Area (0.31 ± 003 SE). Within years, the egg survival metric for lake trout was statistically similar between Reach 1 Natural and Tailrace Area during 2017 (p > 0.05). During 2018, the egg survival metric was higher in Reach 1 Natural versus Reach 1 Enhanced (Chi-squared = 7.96, p = 0.014), and higher in Reach 1 Natural versus Tailrace Area (Chi-squared = 8.07, p = 0.014), but was statistically similar between Reach 1 Enhanced and Tailrace Area (p > 0.05). In 2019, the egg survival metric was higher in Reach 1 Enhanced versus Tailrace Area (Chi-squared = 74.86, p < 0.001).
Total egg count for coregonids across all plots was 756 eggs in 2017, 6740 eggs in 2018, and 1121 eggs in 2019. The annual range of survival rate metric was 0.558 to 0.707, with the highest survival rate metric in 2019 (0.707 ± 0.01 SE), followed by 2017 (0.577 ± 0.02 SE), and 2018 (0.558 ± 0.01 SE). Annual trends for coregonids within a habitat type included year-over-year increases in the egg survival metric for Reach 1 Enhanced in 2018 versus 2017 (Chi-squared = 128.25, p < 0.001), and in 2019 versus 2018 (Chi-squared = 218.33, p < 0.001) (Figure 5). The egg survival metric was similar across years for Reach 1 Natural (p > 0.05). For the Tailrace Area, the egg survival metric was similar between 2017 and 2019 (p > 0.05) but was statistically higher in 2018 versus 2017 (Chi-squared = 32.99, p < 0.001) and in 2018 versus 2019 (Chi-squared = 145.42, p < 0.001).
For the period from 2017 to 2019, egg count for coregonids was 6478 eggs in Reach 1 Enhanced, followed by 1377 eggs in non-modified Reach 1, and 762 eggs in Tailrace Area. Based on all data collected across the three study years, the overall egg survival rate metric for coregonids was highest in the Tailrace Area (0.719 ± 0.02 SE), followed by Reach 1 Enhanced (0.611 ± 0.01 SE) and non-modified Reach 1 Natural (0.351 ± 0.01 SE). For 2017, the egg survival metric for coregonids was statistically similar between Reach 1 Natural and Tailrace Area (p > 0.05) and was higher in Reach 1 Enhanced versus Reach 1 Natural (Chi-squared = 211.28, p < 0.001), and Tailrace Area (Chi-squared = 42.36, p < 0.001). As observed in 2017, the egg survival metric was higher in Reach 1 Enhanced versus Reach 1 Natural during 2018 (Chi-squared = 142.66, p < 0.001) and 2019 (Chi-squared = 122.30, p < 0.001). The egg survival metric for coregonids in the Tailrace Area peaked in 2018, statistically higher than Reach 1 Enhanced (Chi-squared = 167.72, p < 0.001) and Reach 1 Natural (Chi-squared = 142.66, p < 0.001) for that study year. In 2019, the egg survival metric for the Tailrace Area was lower than Reach 1 Enhanced (Chi-squared = 169.95, p < 0.001), and statistically similar with that observed in Reach 1 Natural (p > 0.05).
DISCUSSION
The upper Yellowknife River in Northern Canada is a unique location for the application of a habitat enhancement project as it supports spawning adfluvial populations of lake trout, lake whitefish, and cisco. This study focused on the reach below the Bluefish facility, which provides suitable spawning substrates and regulated flows to sustain populations of lake trout and coregonids. The area is part of the Great Slave Lake ecosystem and has a history of unregulated harvests that lasted for several decades through the mid 20th century (Evans et al., 2002; Golder, 2019; Stewart, 1997). The opportunity to monitor and research the spawning behavior and habitat requirements of adfluvial lake trout and coregonids in this study area was made possible by the long-term resilience of fish populations and the presence of important spawning areas near an active hydroelectric facility. The regulatory requirement to study fisheries in proximity to the facility and offset any adverse impacts also contributed to the research efforts. The field sampling conducted for this study, as well as the installation of artificially constructed spawning habitat, were carried out to comply with federal and territorial environmental legislation. The accessibility of the study site, in comparison to other remote locations in Northern Canada where adfluvial lake trout and coregonids may be found, facilitated the research and monitoring activities.
A robust dataset on egg incubation densities and survival were provided by the 226 egg survey plots that were sampled within the gravel augmented Reach 1 Enhanced area, Reach 1 Natural, and known spawning locations for the Tailrace Area. Key findings were observations of overall higher densities of coregonid eggs (> 2x) on the installed spawning habitat in the Reach 1 in comparison to other naturally occurring spawning habitats below the facility, with statistically significant effects in 2018. Lake Trout egg density was trending higher in the installed habitat in comparison to other naturally occurring spawning habitats below the facility in 2018 and 2019, with annual year over year increases in mean egg densities.
Although the methods and scope of this study did not look to evaluate the specific mechanisms that resulted in the increase in egg density, only to document and analyze densities of eggs and survivability across different natural and enhanced habitats, we can make some conjecture based on our data and previous studies. Lake trout, lake whitefish and cisco are lithophilic broadcast spawners, as they do not create a nest but deposit fertilized eggs over suitable substrates which drift and settle into the interstitial spaces within those substrates (Bégout Anras, Cooley, Bodaly, Anras, & Fudge, 1999; Evans et al., 2002; Richardson et al., 2001; Roberge et al., 2002). Prior to the installation of the artificially enhanced habitat, existing conditions in Reach 1 were largely dominated by boulder and bedrock, where there was no anchorage and a lack of suitable interstitial spaces for egg development (Golder, 2019). Two potential mechanisms that likely interacted to result in the increase in egg densities are habitat selection and the suitability of the installed substrate to hold eggs. An increase in egg density due to habitat selection would occur through the fish actively seeking out the best spawning habitats and substrates, which based on the egg density results, is the installed habitat, and spawning directly in or above these locations. An increase in egg density due to the suitability of the installed substrate to hold eggs would occur when the fish continue to spawn where they have always historically spawned but the newly installed substrates, of gravel and cobble, have more interstitial spaces and are better at holding eggs in place therefor increasing egg densities. Given the broadcast spawning nature of these three species and the associated variability further study would be required to define precisely which mechanism was the driving force behind the increase in egg density. Further study into the mechanisms behind the increases in egg density would contribute to the body of knowledge for spawning site selection for these species for which there are still many unknowns (Bégout Anras et al., 1999; Evans et al., 2002; Sawatzky et al., 2007; Stewart, 1997).
The two potential mechanisms may also explain why the response to the installed habitat for egg densities for both lake trout and coregonids was delayed, specifically why the 2017 results showed no obvious increase in density on the installed habitat. The first year post-installation in 2017 included a relatively small area of only 9 m2, and that area increased to 40 m2the following year. As such, the smaller area of installed habitat in 2017 in comparison to 2018 and 2019 may have had an impact on the delayed response in egg densities for both lake trout and coregonids. Possible explanations include that the small area was inefficient at capturing and holder drifting eggs from nearby spawning fish or failed to elicit a habitat selection response by spawning fish. Related to the latter mechanism, the new rock installed within the study reach in 2017 may have altered environmental and olfactory cues for spawning, deterring fish that arrived later that fall to spawn. Environmental and olfactory cues can be important factors in the choice of spawning location (Bett & Hinch, 2016; Keefer & Caudill, 2014), and such cues were potentially adequate or better during 2018 and 2019, particularly for Lake Trout. The potential preference for the artificially enhanced spawning habitat, and use of augmented substrates for egg incubation in the Reach 1 Enhanced steadily increased year over year while the preference for the natural spawning habitat, and use of natural substrates for egg incubation in Reach 1 Natural, decreased over time. Although the mean egg density statistic for coregonids was variable across years, coregonids may have spawned in higher numbers over the enhanced spawning habitat, compared to surrounding natural substrate during the second and potentially third year of post-installation monitoring, suggesting that spawning cues were also adequate for spawning fish.
The installed habitat had mixed results on the survival rate of developing embryos, with no obvious benefit for lake trout. However, lake trout egg survival rates in R1 Enhanced did trend higher over time. Furthermore, overall numbers of lake trout eggs were lower than coregonid eggs with an average egg plot density of 51/m2 for lake trout eggs and 414/m2for coregonids across all egg survey plots, and as such, the lower amount of eggs for lake trout may have precluded a fulsome study of survivability of eggs. Importantly, the survival rate metic of coregonid eggs was statistically higher on the installed habitat each year of post-installation monitoring in comparison to the natural substrates in Reach 1 Natural. Overall, the proportion of live coregonid eggs was 1.7-times higher on enhanced substrate versus natural substrate in Reach 1. The consistent results across year and overall magnitude of effects suggests that the artificially installed substrates were effective at providing better interstitial spaces and protection for the eggs to survive than that of the naturally occurring substrates in the Reach 1 area. Of note, the proportion of live coregonids eggs on the installed habitat dipped during 2018 when coregonid egg densities were highest. Therefore, it is possible that the benefits of the augmented spawning substrate in mitigating the effects of overcrowding on survival were reduced when densities of eggs were highest. It is also possible that the cooler water temperatures in 2018 may have also limited the spread of the water mould such that the benefit of the augment substrate for improving survival was limited under cooler temperatures.
The results of this study suggest that the enhanced habitat installed in the Reach 1 area of the Yellowknife River employed successful design principles and that the installation methods have the potential to increase recruitment and ultimately benefit the overall population abundance for adfluvial coregonids, and possible lake trout). The results of our study are also generally consistent with other studies on lacustrine lake trout and whitefish and anadromous salmonines spawning habitat where gravel and cobble substrates are more productive for egg incubation than fine substrates as the gravel and cobble provide sufficient interstitial spaces for egg survival (Barlaup et al., 2008; Bégout Anras et al., 1999; Evans et al., 2002; Pedersen et al., 2009). Given the previous characterizations for the importance of interstitial spaces for lacustrine fish eggs for protection from predation, water flow, currents and wave action (Gatch et al., 2020; Marsden et al., 2016; Marsden, Casselman, et al., 1995; Sly, 1988), the egg density results from 2016 and the mass mortality of deposits of eggs in clumps on the unsuitable bedrock and boulder substrates throughout Reach 1 before the habitat installation (Golder, 2019) a key factor in the design was ensuring a proper substrate composition of the installed habitat and integration of pre-installation data on substrate in 2016.
Indeed, the substrate composition for the installed habitat was very close to the design parameters (i.e., 70% gravel, 25% cobble, and 5% boulder), with the mean substrate composition recorded through egg survey plots in the Reach 1 Enhanced area being 69% gravel, 24% cobble and 7% boulder (Figure 3). The substrate composition for the installed habitat was also very similar to the substrate composition for egg plots at known spawning locations in the Tailrace Area where the mean substrate was 62% gravel, 24% cobble, 6% fines and 7% boulder. This design may have been critical in providing suitable interstitial spaces for egg development to avoid the effects of overcrowding and transmission of pathogenic water moulds (e.g., Saprolegnia spp.) (Brown & Bruno, 2002). The results and findings of this study works towards filling the gap in published data for spawning behavior and habitat characteristics for adfluvial lake trout, lake whitefish and cisco populations and can be used by fisheries managers to identify spawning habitat locations in other river systems across the northern portion of the ranges for these three species where adfluvial life history types are more common (Evans et al., 2002).
ACKNOWLEDGEMENTS
The support from the Northwest Territories Power Corporation environment and operations staff and the Golder Associates project team throughout the duration of the study, specifically during the field sampling events, is gratefully acknowledged. Key field staff on the Golder Associates project team included Paul Vescei, Francois Larouche, Monica Redmond, Damian Panayi, Edward Hunt, and Dylan Cooke. The collaboration with Fisheries and Ocean Canada (DFO) file managers throughout the duration of the study is also greatly appreciated. This work was conducted as part of requests from DFO related to Fisheries Act Authorization No. 09-HCAA-CA-00079.
Table I. Analysis of variance (ANOVA) results for mean differences in habitat variables between Reach 1 and Tailrace Area and for sampling locations with eggs versus without eggs (lake trout and coregonid species) in the Yellowknife River, fall 2016.