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.