Statistical Analysis
We first present a descriptive statistical summary of the spawning fish count data for lake whitefish and cisco from 2016 to 2019, and for lake trout from 2016 to 2018, to provide a context for interpreting egg densities and survival rates pre- and post-habitat enhancement. For the habitat data, we calculated the mean proportion of substrate types, mean mid-water column velocity, and mean depth using the data collected in 2016. We compared the habitat characteristics between survey plots with eggs and those without eggs, as well as between survey plots in Reach 1 and the Tailrace Area. To determine distinguishable habitat features for plots with eggs, we conducted Analysis of Variance (ANOVA) and tested for statistical differences between the independent habitat factors and their interaction effect. Prior to the tests, the habitat data were transformed (square root of proportions and logarithm of depths and velocities) to meet the assumption that residuals are normally distributed. Using the egg data collected from 2017 to 2019, we calculated the means and standard errors (SEs) for egg densities per species. We tested the effect of habitat type (Reach 1 Natural, Reach 1 Enhanced, and Tailrace Area), year (2017, 2018, and 2019), and the interaction effect of habitat type and year on egg densities using a two-factor permutational ANOVA (Anderson, 2001). Permutational analysis of variance often provides more power in situations where independence of variance may be an issue and assessing multiple factors (Anderson, 2001). In cases where the interaction term was significant, post hoc tests were conducted for each study year and habitat type, with p-values adjusted using the Holm method to correct for multiple comparisons (Holm, 1979). Chi-squared tests were also performed to analyze the differences in the proportion of live eggs between habitat types and years, with p-values adjusted using the Holm method (Holm, 1979). Statistical significance was determined using an alpha level of 0.05. All statistical summaries and analyses were conducted in R.
RESULTS
During the period of September through October, the mean temperature at Bluefish Lake was 8.6°C, slightly below the long-term average of 8.8°C, which was calculated based on data recorded over a 30-year period from 1991 to 2020. Among the four study years, 2018 had the lowest mean fall temperature, measuring 6.1°C. On the other hand, 2017 had the highest mean fall temperature of 10.4°C. Both 2016 and 2019 had an average fall daily temperature of 9.0°C. The mean daily discharge was recorded as 21.5 m3/s. It is worth noting that these flows were below the long-term average of 30.8 m3/s, which was calculated based on the daily fall flows summarized over a 30-year period from 1991 to 2020. Among the four study years, 2016 had the lowest mean daily discharge, measuring 15.1 m3/s. Subsequently, there was a gradual increase in mean daily discharge, with values of 18.1 m3/s in 2017, 23.4 m3/s in 2018, and 29.2 m3/s in 2019.