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Fine-Scale Ecological and Genetic Population Structure of Two Whitefish (Coregoninae) Species in the Vicinity of Industrial Thermal Emissions


Thermal pollution from industrial processes can have negative impacts on the spawning and development of cold-water fish. Point sources of thermal effluent may need to be managed to avoid affecting discrete populations. Correspondingly, we examined fine-scale ecological and genetic population structure of two whitefish species (Coregonus clupeaformis and Prosopium cylindraceum) on Lake Huron, Canada, in the immediate vicinity of thermal effluent from nuclear power generation. Niche metrics using δ13C and δ15N stable isotopes showed high levels of overlap (48.6 to 94.5%) in resource use by adult fish captured in areas affected by thermal effluent compared to nearby reference locations. Isotopic niche size, a metric of resource use diversity, was 1.3- to 2.8-fold higher than reference values in some thermally affected areas, indicative of fish mixing. Microsatellite analyses of genetic population structure (Fst, STRUCTURE and DAPC) indicated that fish captured at all locations in the vicinity of the power plant were part of a larger population extending beyond the study area. In concert, ecological and genetic markers do not support the presence of an evolutionarily significant unit in the vicinity of the power plant. Thus, future research should focus on the potential impacts of thermal emissions on development and recruitment.


Worldwide a variety of energy generating stations use natural lake or river water as an industrial coolant, which may be released as warmed effluent into the environment. Thermal pollution of this nature can result in localized changes in water temperature ranging from 2 to 15°C above ambient values (e.g., [16]). Freshwater fish species, especially those with narrow temperature tolerances, may be negatively affected by thermal pollution (e.g., [58]). Previous studies have shown that thermal effluents can reduce reproduction and survival [3,7,9], cause changes in species movement and distribution [4,10,11] and alter habitat structure [6]. Individually or collectively, thermal effluent may be associated with local extirpation of sensitive fish species. Ideally, thermal effluent should be managed with population genetic considerations to avoid impacting fish that are distinct populations.

The population structure of fish is often assessed using neutral genetic markers to identify discrete subpopulations that result from reduced gene flow due to a variety of factors, including geographic barriers [1216], human impacts [17,18] and spawning site fidelity [1921]. The polymorphism of microsatellites makes them ideal markers to identify fine-scale population structure within many different species [15,2226]. Genetic data provide excellent insight into long-term aspects of population structure and have been used extensively in fisheries management (e.g., [19,21,27,28]). Important management decisions can be aided using genetic markers; however, many studies often lack ecological data to corroborate genetic findings.

Stable isotopes of carbon and nitrogen are ecological markers that provide a quantitative means of comparing resource use among groups of fish. The range and variance of isotopic values present a two-dimensional metric of niche that incorporates information about carbon source, a proxy for habitat in freshwater, and nitrogen source, indicative of trophic position [2931]. Together these isotopic values describe resource use [3234]. Groups of fish with different isotopic niches are comprised of individuals from different food webs or employing different feeding strategies (e.g., [35]). Thus, stable isotopes may be used to identify fish population structure based on resource use [36]. This metric of structure is shorter-term than genetic markers, reflecting the metabolic turnover time of the tissues analyzed [37]. For spawning aggregations, analysis of isotopic population structure using muscle tissue reveals whether groups used similar or different resources prior to aggregating. Despite the potential advantages of stable isotopes, few fisheries studies have used this approach to assess spatial population structure of individual species (but see [35,36]).

Canada currently has four major nuclear power generating stations on the Laurentian Great Lakes, the largest freshwater system in the world. All three stations operate multiple CANDU reactors and use lake water for once-through cooling processes to cool steam condensers [3842]. The largest power generating station is located on Douglas Point in eastern Lake Huron, where it releases large volumes of warmed water back into the lake. Of concern are potentially negative impacts of thermal emissions on the reproduction and development of members of the Coregoninae subfamily (Salmonidae family), which are fall-spawning species that require a narrow range of cold temperatures for successful embryogenesis [4345]. Specifically, lake whitefish (Coregonus clupeaformis) comprise one of the most important commercial fisheries within the Great Lakes [4649], and round whitefish (Prosopium cylindraceum) may be an important indicator species for environmental monitoring [50]. Recent studies have found that increases in incubation temperature resulted in earlier hatch and decreased survival in both whitefish species [5153]. Early hatch can have potential ecological impacts (e.g. altered predation and food availability), increasing the importance of development temperature beyond morphological effects [5456]. From a conservation and management perspective, it is important to know whether fish spawning in areas receiving thermal emissions are ecologically and genetically distinct from those in reference areas.

Both genetic and ecological population structuring occur among lake whitefish spawning aggregations in Lake Huron on the spatial scale of hundreds of kilometers. Previous studies have identified genetic differentiation among populations in different basins or separated by large geographic distances (e.g., [14,19,5759]). Lake whitefish also vary in diet [60] and habitat use [58] in different areas of the lake, and historically have undergone resource use shifts in association with changes in the environment [6164]. Previous studies of lake whitefish provide excellent evidence of barriers to gene flow and resource use heterogeneity within Lake Huron. However, they were not designed to address questions about fine-scale population structure, such as whether or not fish in the immediate vicinity of point source emissions are distinct from those in nearby reference areas. In addition, very little is known about any aspect of population structure for round whitefish.

In this study we examined fine-scale population structure of spawning lake and round whitefish in the region around thermal emissions from the nuclear power generating station on Douglas Point, Lake Huron. We used niche analysis based on stable isotopes and neutral genetic variation from microsatellites in concert to investigate the ecological and genetic population structure of these fish. Our focus was on fine-scale population structure to address the specific question of whether fish in areas affected by thermal emissions were distinct from adjacent reference areas. For each fish species our specific objectives were to compare the following metrics in areas affected by thermal emissions vs. adjacent reference zones: (1) isotopic niche characteristics; and (2) genetic population structure. The results of this study will inform whitefish management within the study area.

Materials and Methods

Study Area and Species

Our study took place in the vicinity of the Bruce Power site in eastern Lake Huron, Ontario, Canada (Fig 1; 44°19’35.39 N, 81°36’01.22 W). Nuclear power has been produced at this site using CANDU reactor technology since 1968, and the current operation consists of 8 CANDU reactors divided into two generating stations (identified as 1 and 2 in Fig 1). Station 1, also called Bruce A, has an intake and discharge rate of 175,000 L/s, whereas station 2 (Bruce B) has an intake and discharge rate of 193,000 L/s. The maximum permitted difference between discharge and ambient water temperatures for both stations is 11.1°C from April 15 to December 14, and 13.0°C from December 15 to April 14 each year. The extent and movement of the thermal plume resulting from warm water discharge at this site is highly variable. The area potentially affected by both discharges combined is predicted to range from 70 to 3,600 ha in near-shore parts of Lake Huron adjacent to the generating stations [42]. To facilitate monitoring and environmental impact assessment, Bruce Power worked with a consulting company [65] to identify 8 sampling zones for fish in relevant near-shore habitats: 2 reference areas outside of the influence of the thermal plume (R1 and R2 in Fig 1), and 6 areas shown to experience warming from thermal discharge ([65] A1-A6 in Fig 1). These zones were found to have suitable habitat and attracted mature whitefish during spawning [65,66]. Research by Thome et al. [67] has shown that within the potentially affected sites the temperature is highly variable with an average winter temperature of up to 3°C warmer than ambient. We used these areas as the study design for population structure assessment. All 8 areas contain at least some rock-cobble substrate in the 2-8m depth range preferred by spawning whitefish, and adults in spawning condition have been collected throughout the study area. However, the importance of the region for whitefish spawning is currently unclear.

Fig 1. Map of the study area on eastern Lake Huron, Canada (inset) showing the location of two nuclear power generating stations (1 and 2), each operating 4 CANDU reactors.

The locations of outflow channels for thermal effluent are indicated by arrows. Gill netting areas for Lake and Round Whitefish are indicated. A1-A6 are sites potentially affected by warmer temperatures (an average of 3°C [65]), whereas sites R1 and R2 are reference locations outside of the thermal plume. Fish were collected in the falls of 2010 and 2011 at each site.

Both whitefish species we studied are broadcast spawners that cast their eggs over reefs and rock-cobble substrate in shallow (2-8m depth) near-shore areas in the late fall [68]. Lake whitefish spawn from October to mid December and round whitefish spawn during early November to early December [43,44,47,51,69,70]. Whitefish eggs normally incubate over winter, with optimal development temperatures of 0.5°C and 4.5°C for lake and round whitefish, respectively [71]. Laboratory studies that manipulate temperature show that mortality and deformity rates increase significantly when eggs are incubated at warmer temperatures [5153]. Further, within Lake Huron whitefish have faced many recent challenges, including system-level changes with the invasion of dreissenid mussels [6163,72], introduction of non-native predators [47,73] and the degradation of habitat [47].

Sample Collection

All animal research was approved by the University of Regina President's Committee on Animal Care, following the guidelines of the Canadian Council on Animal Care. The approved Animal Use Protocol was AUP 11–13 "Population and Conservation Genetics of Freshwater Fish". The authors did not require a permit to sample fish; the permit was issued to Bruce Power and fish specimens were received after collection

Adult lake and round whitefish were collected as part of Bruce Power’s environmental assessment follow-up program (see [66]) using bottom-set gill nets from the 8 areas described above (2 reference and 6 affected sites), which span approximately 24 km of shoreline (Fig 1). Methods are described in detail elsewhere [66,67]. In brief, nets (457 m length x 1.5m height; 5.7 cm and 11.4 cm mesh size) were set overnight for 19–24 hours on 13 dates in 2010 (Oct 25 –Dec 4) and 15 dates in 2011 (Oct 27 –Dec 13) at 4.5–6 m depths in areas with cobble and boulder substrate. Fish captured in gill nets were examined for morphological measurements and confirmed to be sexually mature. Fish were retained so that we could collect a 5 x 2 x 2 cm piece of dorsal muscle, which was frozen for later DNA extraction and stable isotopes analysis. A total of 336 lake and 319 round whitefish were used for stable isotope analysis, and 208 lake and 327 round whitefish were used for the genetic analysis (Table 1).

Table 1. Lake and round whitefish collected via multi-panel gillnets during 2010 and 2011 spawning seasons at 8 locations in the Douglas Point area of Lake Huron.

Gill net sites were chosen to reflect two reference areas (R1, R2) and 6 potentially thermally affected areas (A1-A6). Muscle tissue was collected for stable isotopes and microsatellite analyses from fish at each site.

Stable Isotopes

Sub-samples of dorsal muscle from individuals from reference and affected sites were rinsed with distilled water, dehydrated in a drying oven at 50°C for 120–168 hours, ground to a fine powder using a dental amalgamator and weighed (0.5–1.0 mg) into tin capsules (Table 1). Stable isotopes values from muscle reflect incorporation for several months [74], which ensured that we compared resource use by fish prior to spawning. Weighed samples were analyzed for carbon and nitrogen stable isotopes using a Thermo Finnigan Delta V isotope ratio mass spectrometer (Institute for Environmental Change and Society, University of Regina). We ran unknowns, laboratory standards of wheat and bovine liver, and replicates of both unknowns and standards in each batch. Isotope values are reported as δ 13CVPDB and δ 15NAIR (delta values) in units of per mil (). Replicates of standards and unknowns generally varied less than 0.2 . We arithmetically lipid-corrected δ 13C with the McConnaughey & McRoy [75] formula when C:N ratios were greater than 3.5.

We created Bayesian standard ellipses using SIBER Metrics to define and compare the isotopic niches for each species at each sample site. Bayesian ellipses encompass 40% of the data, thus this metric enables a robust comparison of niche that is less biased by differences in sample size than traditional metrics [76,77]. The area encompassed by standard ellipses (SEA) is a measure of isotopic niche size (2) and is directly related to resource use diversity [76]. We corrected SEA for small sample size (SEAc; [76]). The SEA of lake and round whitefish at each site was calculated with 10,000 replications, creating a Bayesian SEA (SEAb) to obtain an average SEA with 95% credibility. To compare resource use similarity between fish in the reference and affected sites we quantified isotopic niche overlap by calculating the area shared between standard ellipses of each reference site with each affected site. To compare resource use diversity we calculated the Bayesian probability that SEA of fish in affected sites was larger than fish in reference sites based on SEAb estimations. All niche metrics were calculated with the Stable Isotope Analysis in R (SIAR) package [78,79].

Genetic Analysis

We extracted genomic DNA from 20 mg of dorsal muscle tissue following the manufacturer’s guidelines (Genomic DNA Isolation Kit, Norgen Bioteck Corp., Ontario, Canada), with the exception that we added 28 U of RNase A (Qiagen Inc., Ontario, Canada) and extended proteinase K digestion to 8–12 hours at 56°C. DNA was quantified using a Qubit 2.0 Fluorometer (Life Technologies Inc., Ontario, Canada) prior to diluting to a standard concentration (5 ng/μl) for PCR reactions. Lake whitefish were genotyped at 9, and round whitefish at 6 microsatellite loci previously developed for each species (lake whitefish: [17,80]; round whitefish: [81]). In addition, lake whitefish were genotyped with 11 and round whitefish with 5 additional tetranucleotide microsatellite loci that were developed specifically for this study using the methods described in Lance et al. ([82]; S1 Table).

Microsatellite loci were amplified in multiplexed PCR reactions using 2 sets of primer pairs with the reverse primer of each pair labeled with fluorescent dyes (WellRED D3 and D4 dyes, Integrated DNA Technologies, Ontario, Canada). PCR reactions were performed in a total reaction volume of 25 μL containing 1X PCR Master Mix (Norgen Bioteck Corp., Ontario, Canada), 2 μM forward and reverse primer, and 10 ng of template DNA. Thermocycling conditions for whitefish primers were: 5 min at 95°C, followed by 30 cycles at 95°C for 30 s, 30 s at the locus-specific annealing temperature (see Table 2), 60 s at 72°C and a final extension of 5 min at 72°C. The touchdown conditions started with 5 min denaturation at 95°C, followed by 20 cycles at 95°C for 30 s, 30 s at 65°C (decreasing by 0.5°C per cycle), 30 s at 72°C, and then 20 cycles at 95°C for 30 s, 30 s at 55°C, 30 s at 72°C followed by a final extension for 5 min at 72°C. Negative controls without DNA template were run for all samples.

Table 2. Details of 31 polymorphic microsatellite loci used to genotype lake and round whitefish.

TD refers to a touchdown PCR approach where the annealing temperature ranged from 65°C to 55°C.

PCR products were size fractionated using a Beckman Coulter GenomeLab GeXP Genetic Analysis System with a 400 bp internal size standard (Beckman Coulter, Mississauga, ON). Alleles were scored using GENEMARKER 2.20 software (Softgenetics, State College, PA) under default settings, with the exception of a bin width of 1 nucleotide to reflect the resolution limit of capillary electrophoresis. Automated allele calling was verified manually and confirmed by a second, independent observer. The program MICRO-CHECKER [83] was used to quality check all microsatellite profiles by estimating the potential frequency of null alleles and the observed and expected heterozygosities (HO and HE). Deviations from Hardy-Weinberg Equilibrium (HWE) were examined for each locus using GENEPOP v4.3 [84].

Population structure among spawning groups was assessed using several different approaches. We calculated fixation indices (FST; [85]) in the program GENODIVE [86]. FST values were evaluated by comparing reference and affected regions, individual sampling sites, and sampling years for both lake and round whitefish. Second, we used Bayesian clustering in the program STRUCTURE to identify the number of potential populations in our data sets [87]. The analysis was repeated 10 times for each value of K ranging from 1 to 8 to ensure consistency between runs. We used a burn-in of 100,000 steps and 100,000 MCMC steps. We also calculated the value of ΔK for the data using the methods of Evanno et al. [88]. Only loci that were in HWE were included in FST and Bayesian analyses. Finally, the data were analyzed using Discriminant Analysis of Principle Components (DAPC), a multivariate ordination method in the R package ADEGENET [89]. DAPC does not require the assumption of HWE, so all loci were included in this analysis. We generated ellipses using ADEGENET for each site by using 65 and 46 principal components (one third of the total) for lake and round whitefish, respectively, to avoid over-fitting the discriminant functions.


Stable Isotopes

Mean δ 13C and δ 15N values were similar for fish of each species collected in reference sites to those in affected sites, but varied between species (Table 3). Correspondingly, the isotopic niches based on standard ellipses created using SIBER were largely overlapping within species (Fig 2). Average niche overlap between fish from affected sites and R1 was 82.0% ± 13.7% for lake whitefish and 72.9% ± 14.3% for round whitefish. Similarly, average niche overlap between R2 and affected areas was 77.0% ± 14.1% for lake whitefish and 75.7% ± 11.3% for round whitefish (Table 3). Thus, fish from reference and affected areas were using largely similar resources based on stable isotope values. Niche size (SEAC) was generally similar between reference and affected sites for lake whitefish, with the exception of site A4, which was substantially larger than all other sampling locations with high probability (Table 3 and Fig 3). For round whitefish, sites A4, A5 and A6 had larger SEAC values than both reference sites and the remaining affected sites, also with high probability (Table 3 and Fig 3). Sites with larger niches corresponded with sites that had a smaller niche overlap with reference sites (Table 3).

Fig 2. Bayesian standard ellipses describing isotopic niches of: (a) lake whitefish and (b) round whitefish collected in the fall of 2010 and 2011 from 8 sites in the Douglas Point area of Lake Huron.

Fish were collected from two reference sites (black ellipses) and 6 potentially affected sites (grey ellipses). Isotopic values (δ13C and δ15N) for reference sites (closed symbols) and affected sites (open symbols) are derived from muscle tissue and shown in units of Per Mil (‰). δ13C values are corrected for lipid content.

Fig 3. Density plot of Standard Ellipse Areas (SEA) for: (a) lake whitefish and (b) round whitefish collected from two reference sites (R1, R2) and 6 potentially affected sites (A1-A6) adjacent to Bruce Power on Lake Huron.

SEA is the area (2) encompassed by standard ellipses (SE) and is a measure of isotopic niche size. The larger the SEA the more diverse the resource use is by fish. Boxes represent the 50%, 75% and 95% credible intervals of Bayesian estimates of SEA (10,000 replications), while black dots represent the mode SEA, and asterisks (*) represent SEA corrected for sample size (SEAc).

Table 3. Isotopic niche data based on δ13C and δ15N values derived from adult lake and round whitefish muscle tissue.

Fish were collected from two references sites (R1, R2), and 6 potentially affected sites (A1-A6) in the fall of 2010 and 2011. Standard Ellipse Area corrected for small sample size (SEAC) is a measure of niche size and resource use diversity. The percentage of isotopic niche overlap with reference sites, implying resource use similarity, is calculated for each site based on Bayesian standard ellipse overlap. The percent probability that niche size at each potentially affected site (SEAA) is larger than each reference site (SEAR) is calculated according to 10,000 Bayesian estimations of SEA. δ13C values are corrected for lipid.

Genetic Analysis

We genotyped 208 lake whitefish at 20 microsatellite loci and 327 round whitefish at 11 loci (Tables 2 and S2). For both species quality checks with MICRO-CHECKER did not indicate large allele dropout or scoring errors, although it did reveal that one of the lake whitefish loci (Cocl Lav45-tetra), showed significant null allele frequencies. Also, Cocl Lav1 was monomorphic so both of these loci were excluded from further analyses. None of the loci used to genotype round whitefish showed significant null allele frequencies. Tests using GENEPOP indicated that there were significant deviations from HWE in 7 (BWF2, Cocl Lav6-di, Cocl Lav20, Cocl Lav43, Cocl Lav44, Cocl Lav47 and Cocl Lav68) and 3 (Prwi27, Prwi60 and Prwi56) of the microsatellite loci for lake and round whitefish, respectively, following tests for multiple corrections. Thus after removing loci with significant nulls, monomorphic loci, and loci out of HWE, 11 and 8 loci were retained for lake and round whitefish, respectively.

When comparing the reference versus affected sites with all samples pooled, FST values were small and not significantly different from 0 (lake whitefish FST = 0.001, P = 0.252; round whitefish FST = 0.001, P = 0.070). The outcome was similar when comparing among sampling years (lake whitefish FST = 0.000, P = 0.481; round whitefish FST = 0.001, P = 0.298). Pairwise comparisons among zones also produced very small FST values not different from 0, with an average of -0.0015 for both lake and round whitefish (Tables 4 and 5).

Table 4. Pairwise estimates of FST among lake whitefish sampled from 8 different zones surrounding Bruce Power determined by pooling samples from 2010 and 2011.

The FST value is found below the diagonal with the corresponding P-value above as determined by GENODIVE. These analyses only included 11 loci that were in Hardy-Weinberg equilibrium.

Table 5. Pairwise estimates of FST among round whitefish sampled from 8 different sites surrounding Bruce Power determined by pooling samples from 2010 and 2011.

The FST value is found below the diagonal with the corresponding P-value above as determined by GENODIVE. The analysis only included 8 loci that were in Hardy-Weinberg equilibrium.

Using the program STRUCTURE we evaluated models with the number of genetic clusters ranging from 1–8. The overall posterior probability estimates indicated that K = 1 had the highest probability for both species (Fig 4A and 4B). Further, there were no large peaks present when using the second-order statistics developed by Evanno et al. [88]. As this method is unable to evaluate a model of full panmixia, the lack of peaks implies the presence of one genetic cluster within the data (Fig 4C and 4D).

Fig 4. Probability output for the potential number of clusters (K) ranging from 1–8 with the program STRUCTURE for lake and round whitefish caught in the Douglas Point area.

The procedure described in Pritchard et al. (2000) for: (a) lake whitefish and (b) round whitefish. Second order statistics from Evanno et al. (2005) for: (c) lake whitefish and (d) round whitefish.

The DAPC analysis was run with all loci and contained 83.3% and 86.0% of the variance within the data for lake and round whitefish, respectively. For lake and round whitefish the first two eigenvalues, the horizontal and vertical axes, were large, representing 47.3% and 42.3% of the variation, respectively, indicating that most of the between group variation was captured in the analysis. Overall, the DAPC analysis revealed overlapping, non-differentiated groupings by zone, further supporting the presence of one population for both lake and round whitefish (Fig 5).

Fig 5. Discriminant analysis of principle components of: (a) lake whitefish and (b) round whitefish from 8 zones near Bruce Power on Lake Huron.

Whitefish were collected from reference sites (black ellipses) and potentially affected sites (grey ellipses). Overlapping ellipses indicate no genetic differentiation.


Whitefish of the two species investigated were not ecologically or genetically distinct in areas affected by industrial thermal emissions compared to immediately adjacent reference zones. Thus, fish in both the affected and external reference areas appear to be part of a larger population extending outside of the study area. Our findings suggest that thermal emissions from nuclear power generation are unlikely to be directly affecting a local population of either species that is an evolutionarily significant unit [9095]. However, this finding does not negate the need for management considerations and monitoring in our study area. Elevated temperatures during development reduce survival of embryos and fry [3,7,9,51], potentially reducing the productivity of fish spawning in areas affected by thermal emissions. Previous studies have also found that thermal pollution can change fish behavior [5,6,11,96,97], potentially influencing fish recruitment. Future studies will need to determine how important the spawning habitat is in our study area and estimate how potential thermal effects may affect recruitment.

Based on stable isotopes, the fish captured in affected and reference areas came from similarly diverse food webs. Both lake and round whitefish showed extensive resource use heterogeneity, but mean δ 13C and δ 15N values and niche-overlap analyses indicated that within species they used similar resources across reference and affected zones. Large lakes can have broad geographic and depth-based variation in baseline stable isotopes values (e.g., [63,98100], which provides the opportunity to detect ecological (isotopic) population structure among groups based on location and habitat use. Thus, the adult fish we analyzed from both species likely spent time in a variety of areas in Lake Huron with different isotopic baselines during the summer prior to moving into near-shore areas around Douglas Point in the fall (several months for muscle turnover time; [74,101]). Consequently, spawning fish in our study area are mixed aggregations from several food webs rather than local stocks, a phenomenon also observed in other parts of Lake Huron [58].

Niche size was larger for both whitefish species in the areas expected to be most influenced by thermal emissions. This effect was most pronounced for lake whitefish, which had an SEAC value 1.5- to 2.8-fold higher in Area 4, immediately adjacent to the larger thermal outflow, than any other zone. Similarly, round whitefish SEAC values were 1.3- to 1.5-fold higher in Areas 4 to 6 than in the other areas studied. Comparable differences in SEAc have been documented between aquatic consumers of different feeding guilds [102] and between sympatric fish species [103]. Thus, the differences we observed in SEAc between fish in some affected vs. reference areas are likely biologically relevant differences in resource use diversity. Based on the rationale provided above, levels of fish mixing in the affected areas were higher than in the reference zones. Importantly, this suggests that fish in the most affected areas relied on a more diverse array of diets and habitats, rather than using distinct resources, which has been documented as 0% isotopic niche overlap [104]. In contrast our niche overlap between reference and affected areas ranged from 48.6 to 94.4%. We propose two potential explanations for these findings that are not mutually exclusive: (1) habitat in the thermally affected areas is desirable and attracts more mixing of fish from multiple feeding locations (see [5,105]); or (2) the fish captured in affected zones are not actually spawning there, and our samples contain a more diverse collection of individuals that are simply moving through those areas (whitefish make near shore movements throughout the fall; [58]). Our data do not permit us to distinguish between these explanations, but reinforce the need to understand the importance of our study area for actual spawning activities as identified above.

There was no genetic differentiation between affected and reference zones for either lake or round whitefish, which were both part of single populations across our study area. This finding was not unexpected for lake whitefish, which have significant population structure throughout the Great Lakes system [48,106], and in Lake Huron, but over much larger geographic scales than we studied [14,19,57,59]. In particular, Stott et al. [19] showed no differentiation between fish from Douglas Point and the Fishing Islands more than 70 km to the north. However, in that study no sites were sampled between Douglas Point and the Fishing Islands, and no sampling was conducted to the south. Further, the genotyping only consisted of seven microsatellite loci, which may result in reduced power to detect differentiation between sites [107111]. Interestingly, although there were no distinct genetic clusters present in our DAPC analysis for lake whitefish, comparing the ellipses for the northern most sites, R1, A1 and A2, to the southern reference site, R2, suggests that spawning aggregations farther south are less similar. Additional research will be required to determine the full extent of lake whitefish genetic structuring within Lake Huron with finer resolution to determine how those sampled at Douglas Point fit into the overall structure within the lake.

Round whitefish presented essentially a complete unknown in terms of a priori expectations about population structure. Lake whitefish have been much more intensively studied because of their commercial value (e.g., [48,106,112117]), but interest in genetic studies of round whitefish has only recently emerged (e.g., [81,118]). Round whitefish are ecologically distinct from lake whitefish [44,51,113,119,120] and little is known about their movements or spawning site fidelity. Similar to lake whitefish, round whitefish did not show any genetic population subdivision over our study area. DAPC analyses, our most powerful tool for examining structure, produced ellipses that were completely overlapping and smaller and more focused on the center of the axes than those for lake whitefish. Thus, round whitefish showed essentially no differentiation over the area sampled, which is emphasized by the DAPC analysis where the variance between groups is maximized. Given the limited geographic scope of our study, we can conclude only that there is no genetic distinction between fish captured inside and outside of the thermally affected area. However, round whitefish populations have drastically declined in Lake Huron in recent years and concern for this species is growing [49]. To ensure effective management of this species a large-scale genetic study is required to determine the population structure of round whitefish within their range.

Our study ultimately suggests that concerns over the impacts of thermal effluent should be more focused on potential changes to productivity and recruitment rather than conservation of discrete populations. Both ecological and genetic data indicate that adult fish inside and immediately outside of thermally affected areas are part of larger genetic populations that use similarly diverse resources. Thus, adverse effects of thermal emissions, if any, would be limited to some fraction of a larger genetic and ecological group for both study species. Large-scale commercial harvest of lake whitefish occurs in the Fishing Islands area north of our study location [58]. Our data and those of Stott et al. [19] suggest that fish from Douglas Point are part of a larger population that includes the Fishing Islands. Previous work has shown that the habitat within the vicinity of the power plant attracts ripe and mature whitefish [67], so potential reductions in productivity of spawning fish in the Douglas Point area may be a fisheries management concern if local spawning produces a significant number of recruits for harvest. This information is currently unavailable given limited knowledge of spawning activity in our study area. However, recent in situ work has shown only small changes in temperature with little predicted change to developmental timing of lake whitefish eggs [65]. Thus, thermal impacts on lake whitefish productivity are likely to be minor in comparison to the commercial harvest of over 1 million kilograms within the management unit that includes Douglas Point [56]. In general, the effects of industrial pollution can vary depending on the system, so careful attention to context is required (e.g., [1,3,68,11,51,121123]).

Supporting Information

S1 Table. Details for 16 polymorphic microsatellite loci developed for lake and round whitefish specifically for this study.

The size indicates the range of observed alleles in base pairs and includes the length of the CAG tag; number of individuals genotyped is N; k is number of alleles observed; Ho and He are observed and expected heterozygosity, respectively; PI is the probability of identity for each locus, and TD refers to the touchdown protocol used for PCR (see text).


S2 Table. Summary data for the 31 microsatellite loci used to genotype lake and round whitefish for this study.

The repeat size indicates the length of the repeat within each locus; N is the number of individuals genotyped; k refers to the number of alleles observed; HO and HE are observed and expected heterozygosities, and PIC is the polymorphic information content.



This research was supported by the Natural Sciences and Engineering Research Council of Canada, Bruce Power, the Canada Research Chairs Program, the Canada Foundation for Innovation, McMaster University, the Northern Ontario School of Medicine, and the University of Regina. We are grateful for in-kind support from the University of Regina’s Institute of Environmental Change and Society. We would like to thank J. Thompson, C.L. Fietsch, and M.E. Cybulski for coordinating sample collection. Preparation of this manuscript was partially supported by U.S. Department of Energy under Award Number DE–FC09–07SR22506 to the University of Georgia Research Foundation

Author Contributions

Conceived and designed the experiments: CMS JYW RGM DRB. Performed the experiments: CFG RLE TDM JAM SLL. Analyzed the data: CFG RLE TDM JAM SLL CMS. Contributed reagents/materials/analysis tools: SMR. Wrote the paper: CFG RLE TDM DRB SLL RGM JAM SMR JYW.


  1. 1. Ross MJ, Siniff DB. Temperatures selected in a power plant thermal effluent by adult yellow perch (Perca flavescens) in winter. Canadian Journal of Fisheries and Aquatic Sciences. 1982; 39: 346–349.
  2. 2. Lardicci C, Rossi F, Maltagliati F. Detection of thermal pollution: Variability of benthic communities at two different spatial scales in an area influenced by a costal power station. Marine Pollution Bulletin. 1999; 38: 296–303.
  3. 3. Luksiene D, Sandstrom O, Lounashiemo L, Andersson J. The effects of thermal effluent exposure on the gametogenesis of female fish. Journal of Fish Biology. 2000; 56: 37–50.
  4. 4. Cooke SJ, Schreer J. Environmental monitoring using physiological telemetry- A case study examining common carp responses to thermal pollution in a coal-fired generating station effluent. Water, Air and Soil Pollution. 2003; 142: 113–136.
  5. 5. Encina L, Rodriguez-Ruiz A, Granado-Lorencio C. Distribution of common carp in a Spanish reservoir in relation to thermal loading from a nuclear power plant. Journal of Thermal Biology. 2008; 33: 444–450.
  6. 6. Teixiera TP, Neves LM, Araujo FG. Effects of a nuclear power plant thermal discharge on habitat complexity and fish community structure in Ilha Grande Bay, Brazil. Marine Environmental Research. 2009; 68: 188–195. pmid:19573906
  7. 7. Sandstrom O, Abrahamsson I, Andersson J, Vetemaa M. Temperature effects on spawning and egg development in Eurasian perch. Journal of Fish Biology. 1997; 51: 1015–1024.
  8. 8. Verones F, Hanafiah MM, Pfister S, Huijbregts MAJ, Pelletier GJ, Koehler A. Characterization factors for thermal pollution in freshwater aquatic environments. Environmental Science and Technology. 2010; 44: 9364–9369. pmid:21069953
  9. 9. Casselman JM. Survival and development of lake trout eggs and fry in Eastern Lake Ontario- in situ incubation, Yorkshire Bar, 1989–1993. Journal of Great Lakes Research. 1995; 21: 384–399.
  10. 10. Kelso JRM. Influence of a thermal effluent on movement of brown bullhead (Ictalurus nebulosus) as determined by ultrasonic tracking. Journal of the Fisheries Board of Canada. 1974; 31: 1507–1513.
  11. 11. Teixiera TP, Neves LM, Araujo FG. Thermal impact of a nuclear power plant in a coastal area in Southeastern Brazil: Effects of heating and physical structure on benthic cover and fish communities. Hydrobiologia. 2012; 684: 161–175.
  12. 12. Paetkau D, Calvert W, Stirling I, Strobeck C. Microsatellite analysis of population structure in Canadian polar bears. Molecular Ecology. 1995; 4: 347–354. pmid:7663752
  13. 13. Prugh LR, Ritlands CE, Arthur SM, Krebs CJ. Monitoring coyote population dynamics by genotyping faeces. Molecular Ecology. 2005; 14: 1585–1596. pmid:15813796
  14. 14. Stott W, VanDeHey JA, Sloss BL. Genetic diversity of lake whitefish in lakes Michigan and Huron; sampling standardization and research priorities. Journal of Great Lakes Reseach. 2010; 36: 59–65.
  15. 15. Kanno Y, Vokoun JC, Letcher BH. Fine-scale population strucutre and riverscape genetics of brook trout (Salvelinus fontinalis) distributed continuously along headwater channel networks. Molecular Ecology. 2011: 20; 3711–3729. pmid:21819470
  16. 16. Taylor EB, Gow JL, Witt J, Zemlak R. Connectivity among pygmy whitefish (Prosopium couterii) in northwestern North America inferred from microsatellite DNA analyses. Canadian Journal of Zoology. 2011: 89; 255–266.
  17. 17. Patton JC, Gallaway BJ, Fechhelm RG, Cronin M. Genetic variation of microsatellite and mitrochondrial DNA markers in broad whitefish (Coregonus nasus) in the Colville and Sagavanirktok rivers in northern Alaska. Canadian Journal of Fisheries and Aquatic Sciences. 1997: 54; 1548–1556.
  18. 18. Johnsen A, Brabrand A, Anmarkrud JA, Bjornstad G, Pavels H, Saltveit SJ. Impact of human-induced environmental changes on genetic structure and variability in Atlantic salmon, Salmo salar. Fisheries Management and Ecology. 2014: 21; 32–41.
  19. 19. Stott W, Ebener MP, Mohr L, Schaeffer J, Roseman EF, Harford WJ, et al. Genetic structure of lake whitefish, Coregonus clupeaformis, populations in the northern main basin of Lake Huron. Advanced Limnology. 2008: 63; 241–260.
  20. 20. Moore JS, Bourret V, Dionne M, Bradbury I, O'Reilly P, Kent M, et al. Conservation genomics of anadromous Atlantic salmon across its North American range: outlier loci identify the same patterns of population structure as neutral loci. Molecular Ecology. 2014: 23; 5680–5697. pmid:25327895
  21. 21. Bradbury IR, Hamilton LC, Rafferty S, Meerburg D, Poole R, Dempson JB, et al. Genetic evidence of local exploitation of Atlantic salmon in a coastal subsistence fishery in the Northwest Atlantic. Canadian Journal of Fisheries and Aquatic Sciences. 2015: 72; 83–95.
  22. 22. Newman RA, Squire T. Microsatellite variation and fine-scale population structure in the wood frog (Rana sylvatica). Molecular Ecology. 2001: 10; 1087–1100. pmid:11380868
  23. 23. Spidle AP, Schill WB, Lubinski BA, King TL. Fine-scale population structure in Atlantic salmon from Maine's Penobscot River drainage. Conservation Genetics. 2001: 2; 11–24.
  24. 24. Cabe PR, Page RB, Hanlon Tj, Aldrich ME, Connors L, Marsh DM. Fine-scale population differentiation and gene flow in a terrestrial salamander (Plethodon cinereus) living in continuous habitat. Heredity. 2007: 98; 53–60. pmid:17006531
  25. 25. Eldridge WH, Naish KA. Long-term effects of translocation and release numbers on fine-scale population structure among coho salmon (Oncorhynchus kisutch). Molecular Ecology. 2007: 16; 2407–2421. pmid:17561902
  26. 26. Latch EK, Boarman WI, Walde A, Fleischer RC. Fine-scale analysis reveals cryptic landscape genetic structure in desert tortoises. PLoS one. 2011: 6; e27794. pmid:22132143
  27. 27. Ruzzante DE, Taggart CT, Lang S, Cook D. Mixed-stock analysis of Atlantic cod near the Gulf of St. Lawrence based on microsatellite DNA. Ecological Applications. 2000: 10; 1090–1109.
  28. 28. Beacham TD, Candy JR, McIntosh B, MacConnachie C, Tabatha A, Kaukinen K, et al. Estimation of stock composition and individual identification of sockeye salmon on a Pacific Rim basis using microsatellite and major histocompatibility complex variation. Transactions of the American Fisheries Society. 2005: 134; 1124–1146.
  29. 29. Minagawa M, Wada E. Stepwise enrichment of 15N along food chains: Further evidence and the relation between δ15N and animal age. Geochimica et Cosmochimica Acta. 1984: 48; 1135–1140.
  30. 30. France RL. Carbon-13 enrichment in benthic compared to planktonic algae: Foodweb implications. Marine Ecology Progress Series. 1995: 124; 307–312.
  31. 31. Vander Zanden J, Shuter BJ, Lester N, Rasmussen JB. Patterns of food chain length in lakes: A stable isotope study. The American Naturalist. 1999: 154; 406–416. pmid:10523487
  32. 32. Bearhop S, Adams CE, Waldron S, Fuller RA, Macleod H. Determining trophic niche width: A novel approach using stable isotope analysis. Journal of Animal Ecology. 2004: 73; 1007–1012.
  33. 33. Newsome SD, Martinez de Rio C, Bearhop S, Phillips DL. A niche for isotopic ecology. Frontiers in Ecology and the Environment. 2007: 5; 429–436.
  34. 34. Fink P, Reichwaldt ES, Harrod C, Rossberg AG. Determining trophic niche width: An experimental approach of the stable isotope approach. Okios. 2012: 121; 1985–1994.
  35. 35. Munroe SEM, Heupel MR, Fisk AT, Logan M, Simpfendorfer CA. Regional movement patterns of a small-bodied shark revealed by stable-isotope analysis. Journal of Fish Biology. 2015: 86; 1567–1586. pmid:25846994
  36. 36. Takai N, Sakamoto W. Identification of local populations of Lake Biwa catfish Silurus biwaensis in Japan on the basis of δ13C and δ15N analyses. Canadian Journal of Zoology. 1999: 77; 258–266.
  37. 37. Dalerum F, Angerbjorn A. Resolving temporal variation in vertebrate diets using naturally occurring stable isotopes. Oecologia. 2005: 144; 647–658. pmid:16041545
  38. 38. Hayes, Hebert. Current Status and Prospects for Commercial Nuclear Reactor Systems- The Utility Viewpoint. Planning & Investigations Department States Commission of Victoria. 44th ANZAAS Congress Symposium. 1972.
  39. 39. Clarke. Effects of thermal discharge from the nuclear power industry. Ontario Ministry of Environment. 1973.
  40. 40. Effer Bryce. Thermal discharge studies on the Great Lakes- The Canadian Experience. Proceedings of a Symposium, Oslo, 26–30 August 1974. 1975: 371–388.
  41. 41. Borodczak N. Review and approval of thermal discharges in Ontario. Canadian Water Resources Journal. 1978: 3; 142–150.
  42. 42. Golder & Associates. Bruce A refurbishment for life extension and continued operations project. Environmental Assessment Study Report Volume 1: Main Report. 2005.
  43. 43. Hart JL. The spawning and early life history of whitefish, Coregonus clupeaformis (Mitchill), in the Bay of Quinte, Ontario. Contrib. Can. Biol. Fish. 1931: 6; 165–214.
  44. 44. Bryan JE, Kato DA. Spawning of lake whitefish Coregonus clupeaformis, and Round whitefish Prosopium cylindraceum, in Aishihik Lake and East Aishihik River, Yukon Territory. Journal of the Fisheries Research Board of Canada. 1975: 32; 283–288.
  45. 45. Coutant CC. Compilation of temperature preference data. Journal of the Fisheries Research Board of Canada. 1977: 34; 739–745.
  46. 46. Mohr LC, Ebener MP. Status of lake whitefish (Coregonus clupeaformis) in Lake Huron. Proceedings of a workshop on the dynamics of lake whitefish (Coregonus clupeaformis) and the amphipod Diporeia spp. in the Great Lakes. 2005: 105–126.
  47. 47. Ebener MP, Kinnunen RE, Schneeberger PJ, Mohr LC, Hoyle JA, Peeters P. Management of commercial fisheries for lake whitefish in the Laurentian Great Lakes of North America. International Governance of Fisheries Ecosystems. 2008: 99–143.
  48. 48. VanDeHey JA, Sloss BL, Peeters PJ, Sutton TM. Genetic structure of lake whitefish (Coregonus clupeaformis) in Lake Michigan. Canadian Journal of Fisheries and Aquatic Sciences. 2009: 66; 382–393.
  49. 49. Ebener MP. Status of Whitefish and Ciscoes. The State of Lake Huron in 2010. 2012: 29–42.
  50. 50. Steinhart GB, Mineau M, Kraft CE. Status and recovery of round whitefish (Prosopium cylindraceum) in New York, USA. Final Report to State Wildlife Grant T-3-1, NYSDEC, Bureau of Wildlife, Albany, NY. 2007.
  51. 51. Patrick PH, Chen E, Parks J, Powell J, Poulton JS, Fietsch CL. Effects of fixed and fluctuating temperature on hatch of round and lake whitefish eggs. North American Journal of Fisheries Management. 2013: 33; 1091–1099.
  52. 52. Mueller CA, Eme J, Manzon R, Somers CM, Boreham DR, Wilson JY. Embryonic critical windows: changes in incubation temperature alter survival, hatchling phenotype, and cost of development in lake whitefish (Coregonus clupeaformis). Journal of Comparative Physiology B. 2015: 185;
  53. 53. Eme J, Mueller CA, Manzon R, Somers CM, Boreham DR, Wilson JY. Critical windows in embryonic development: Shifting incubation temperatures alter heart rate and oxygen consumption of lake whitefish (Coregonus clupeaformis) embryos and hatchlings. Comparative Biochemistry and Physiology. 2014: 179; 71–80. pmid:25236178
  54. 54. Hoyle JA, Johannsson OE, Bowen KL. Larval lake whitefish abundance, diet and growth and their zooplankton prey abundance during a period of ecosystem change on the Bay of Quinte, Lake Ontario. Aquatic Ecosystem Health and Management. 2011: 14; 66–74.
  55. 55. Rogers SM, Bernatchez L. The genetic basis of intrinsic and extrinsic post-zygotic reproductive isolation jointly promoting speciation in the lake whitefish species complex (Coregonus clupeaformis). Journal of Evolutionary Biology. 2006: 19; 1979–1994. pmid:17040396
  56. 56. Cushing DH. Plankton production and year class strength in fish populations–an update of the match mismatch hypothesis. Advances in Marine Biology. 1990: 26; 249–293.
  57. 57. Casselman JM, Collins JJ, Crossman EJ, Ihssen PE, Spangler GR. Lake whitefish (Coregonus clupeaformis) stocks of the Ontario waters of Lake Huron. Canadian Journal of Fisheries and Aquatic Sciences. 1981: 38; 1772–1789.
  58. 58. Ebener MP, Brenden TO, Wright GM, Jones ML, Faisal M. Spatial and temporal distributions of lake whitefish spawning stocks in Northern lakes Michigan and Huron 2003–2008. Journal of Great Lakes Research. 2010: 36; 38–51.
  59. 59. Stott W, Ebener MP, Mohr L, Hartman T, Johnson J, Roseman EF. Spatial and temporal genetic diversity of lake whitefish (Coregonus clupeaformis (Mitchill)) from Lake Huron and Lake Erie. Advanced Limnology. 2013: 64; 205–222.
  60. 60. Pothoven SA, Nalepa TF. Feeding ecology of lake whitefish in Lake Huron. Journal of Great Lakes Research. 2006: 32; 489–501.
  61. 61. McNickle GG, Rennie MD, Sprules WG. Changes in benthic invertebrate communities of South Bay, Lake Huron following invasion by zebra mussels (Dreissena polymorpha), and potential effects on lake whitefish (Coregonus clupeaformis) diet and growth. Journal of Great Lakes Research. 2006: 32; 180–193.
  62. 62. Pothoven SA, Madenjian CP. Changes in consumption by alewives and lake whitefish after dreissenid mussel invasions in Lakes Michigan and Huron. North American Journal of Fisheries Management. 2008: 23; 308–320.
  63. 63. Rennie MD, Sprules WG, Johnson TB. Resource switching in fish following a major food web disruption. Oecologia. 2009: 159; 789–802. pmid:19214590
  64. 64. Pothoven SA, Madenjian CP. Increased piscivory by lake whitefish in Lake Huron. North American Journal of Fisheries Management. 2013: 33; 1194–1202.
  65. 65. Bruce Power. Whitefish investigations 2009 summary. B-REP-00531-00035. 2009; Available:
  66. 66. Bruce Power. Whitefish investigations 2010 summary. B-REP-00531-00040. 2010; Available:
  67. 67. Thome C, Mitz C, Somers CM, Manzon RG, Wilson JY, Boreham DR. Incubation of lake whitefish (Coregonus clupeaformis) embryos in cooling water discharge and the impacts of fluctuating thermal regimes on development. Canadian Journal of Fisheries and Aquatic Sciences. In submission.
  68. 68. Roseman EF, Kennedy GW, Boase J, Manny BA, Todd TN, Stott W. Evidence for lake whitefish spawning in the Detroit River: Implications for habitat and population recovery. Journal of Great Lakes Research. 2007: 33; 397–406.
  69. 69. Rawson DS, Studies of the fish of Great Slave Lake. Journal of the Fisheries Research Board in Canada. 1951: 8; 207–240.
  70. 70. Ihssen PE, Evans DO, Christie WJ, Reckahn JA, DesJardine RL. Life history, morphology, and electrophoretic characteristics of five allopatric stocks of lake whitefish (Coregonus clupeaformis) in the Great Lakes region. Canadian Journal of Fisheries and Aquatic Sciences. 1981: 38; 1790–1870.
  71. 71. Wismer DA, Christie AE. Temperature relationships of Great Lakes fishes: A data compilation. Great lakes Fishery Commission Special Publication No. 87–3. 1987.
  72. 72. Nalepa TF, Pothoven SA, Fanslow DL. Recent changes in benthic macroinvertebrate populations in Lake Huron and impact on the diet of lake whitefish (Coregonus clupeaformis). Aquatic Ecosystem Health & Management. 2009: 12; 2–10.
  73. 73. Ebener MP. Recovery of lake whitefish populations in the Great Lakes: A story of successful management and just plain luck. Fisheries Management Success Stories. 1997: 22; 18–20.
  74. 74. Perga ME, Gerdeaux D. Are fish what they eat all year round? Oecologia. 2005: 144; 598–606. pmid:15891838
  75. 75. McConnaughey T, McRoy CP. Food-web structure and the fractionation of Carbon isotope in the Bering Sea. Marine Biology. 1979: 53; 257–262.
  76. 76. Jackson AL, Inger R, Parnell AC, Bearhop S. Comparing isotopic niche widths among and within communities: SIBER-Stable isotope Bayesian ellipses in R. Journal of Animal Ecology. 2011: 80; 595–602. pmid:21401589
  77. 77. Syvaranta J, Lensu A, Marjomaki TJ, Oksanen S, Jones RI. An empirical evaluation of the utility of convex hull and standard ellipse areas for assessing population niche widths from stable isotope data. PLoS One. 2013: 8; e56094. pmid:23405254
  78. 78. Parnell A, Jackson A. SIAR: Stable isotope analysis in R. R package version 4.2. 2013.
  79. 79. R Development Core Team. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. 2014: Available:
  80. 80. Rogers SM, Marchand MH, Bernatchez L. Isolation, characterization and cross-salmonid amplification of 31 microsatellite loci in the lake whitefish (Coregonus clupeaformis, Mitchill). Molecular Ecology Notes. 2004: 4; 89–92.
  81. 81. O'Bryhim J, Somers C, Lance SL, Yau M, Boreham DR, Jones KL, Taylor EB. Development and characterization of twenty-two novel microsatellite markers for the mountain whitefish, Prosopium williamsoni and cross-amplification in the round whitefish, P. cylindraceum, using paired-end Illumina shotgun sequencing. Conservation Genetics Resources. 2013: 5; 89–91.
  82. 82. Lance SL, Love CN, Nunziata SO, O'Bryhim JR, Scott DE, Wesley Flynn RW, Jones KL. 32 species validation of a new Illumina paired-end approach for the development of microsatellites. PLoS One. 2013: 8; e81853. pmid:24312368
  83. 83. Van Oosterhout C, Hutchinson WF, Wills DPM, Shipley P. Micro-Checker: Software for identifying and correcting genotyping errors in microsatellite data. Molecular Ecology Notes. 2004: 4; 535–538.
  84. 84. Rousset F. Genepop'007: A complete reimplementation of the Genepop software for Windows and Linux. Molecular Ecology Resources. 2008: 8; 103–106. pmid:21585727
  85. 85. Weir BS, Cockerham CC. Estimating F-statistics for the analysis of population structure. Evolution. 1984: 38; 1358–1370.
  86. 86. Meirmans PG, Van Tienderen PH. Genotype and Genodive: Two programs for the analysis of genetic diversity of asexual organisms. Molecular Ecology Notes. 2004: 4; 792–794.
  87. 87. Pritchard JK, Stephens M, Donnelly P. Inference of population structure using multilocus genotype data. Genetics. 2000: 155; 945–959. pmid:10835412
  88. 88. Evanno G, Regnaut S, Goudet J. Detecting the number of clusters of individuals using the software Structure: A simulation study. Molecular Ecology. 2005: 14; 2611–2620. pmid:15969739
  89. 89. Jombart T, Devillard S, Balloux F. Discriminant analysis of principal components: A new method for the analysis of genetically structured populations. BMC Genetics. 2010: 11.
  90. 90. Ryder O. Species conservation and systematics: The dilemma of subspecies. Trends in Ecology and Evolution. 1986: 1; 9–10.
  91. 91. Waples RS. Pacific salmon, Oncorhynchus spp., and the definition of "species" under the endangered species act. Marine Fisheries Review. 1991: 53; 11–22.
  92. 92. Vogler AP, Desalle R. Diagnosing units of conservation management. Conservation Biology. 1994: 8; 354–363.
  93. 93. Moritz C. Defining 'evolutionary significant units' for conservation. Trends in Ecology and Evolution. 1994: 9; 373–375. pmid:21236896
  94. 94. Crandall KA, Bininda-Emonds ORP, Mace GM, Wayne RK. Considering evolutionary processes in conservation biology. Trends in Ecology and Evolution. 2000: 15; 290–295. pmid:10856956
  95. 95. Mee JA, Bernatchez L, Reist JD, Rogers SM, Taylor EB. Identifying designatable units of intraspecific conservation prioritization: A hierarchical approach applied to the lake whitefish species complex (Coregonus spp.). Evolutionary Applications. 2015: 8; 423–441. pmid:26029257
  96. 96. Kelso JRM. Influence of a thermal effluent on movement of brown bullhead (Ictalurus nebulosus) as determined by ultrasonic tracking. Journal of the Fisheries Research Board of Canada. 1974: 31; 1507–1513.
  97. 97. Luksiene D, Sandstrom O. Reproductive disturbance in a roach (Rutilus rutilus) population affected by cooling water discharge. Journal of Fish Biology. 1994: 45; 613–625.
  98. 98. Harvey CJ, Kitchell JF. A stable isotope evaluation of the structure and spatial heterogeneity of a Lake Superior food web. Canadian Journal of Fisheries Aquatic Sciences. 2000: 57; 1395–1403.
  99. 99. Sierszen ME, Peterson GS, Scharold JV. Depth-specific patterns in benthic-planktonic food web relationships in Lake Superior. Canadian Journal of Fisheries and Aquatic Sciences. 2006: 63; 1496–1503.
  100. 100. Hobson KA, Ofukany A, Soto DX, Wassenaar LI. An isotopic baseline (δ13C, δ15N) for fishes ok Lake Winnipeg: Implications investigating impacts of eutrophication and invasive species. Journal of Great Lakes Research. 2012: 38; 58–65.
  101. 101. Weidel BC, Carpenter SR, Kitchell JR, Vander Zanden MJ. Rates and components of carbon turnover in fish muscle: Insights from bioenergetics models and a whole-lake 13C addition. Canadian Journal of Fisheries and Aquatic Sciences. 2011: 68; 387–399.
  102. 102. Richoux NB, Ndhlovu RT. Temporal variability in the isotopic niches of rocky shore grazers and suspension-feeders. Marine Ecology. 2014:
  103. 103. Haimdan N, Jackson MC, Britton R. Diet and trophic niche of the endangered fish Garra ghorensis in three Jordanian populations. Ecology of Freshwater Fish. 2015:
  104. 104. Guzzo MM, Blanchfield PJ, Chapelsky AJ. Cott PA. Resource partitioning among top-level piscivores in a sub-Arctic lake during thermal stratification. Journal of Great Lakes Research. 2015: in press.
  105. 105. Sandstrom O, Neuman E, Thoresson G. Effects of temperature on life history variables in perch. Journal of Fish Biology. 1995: 47; 652–670.
  106. 106. Stott W, Todd TN, Kallemeyn L. Genetic variability among lake whitefish from Isle Royale and the Upper Great Lakes. Annual Zoology Fennici. 2004: 41; 51–59.
  107. 107. Rosenberg NA, Lei LM, Ward R, Pritchard JK. Informativeness of genetic markers for inference of ancestry. American Journal of Human Genetics. 2003: 73; 1402–1422. pmid:14631557
  108. 108. Lindholm E, Hodge SE, Greenberg DA. Comparative informativeness for linkage of multiple SNPs and single microsatellites. Human Heredity. 2004: 58; 164–170. pmid:15812173
  109. 109. Liu N, Chen L, Wang S, Oh C, Zhao H. Comparison of single-nucleotide polymorphisms and microsatellites in inference of population structure. BMC Genetics. 2005:
  110. 110. Selkoe KA, Toonen RJ. Microsatellites for ecologists: A practical guide to using and evaluating microsatellite markers. Ecology Letters. 2006: 9; 615–629. pmid:16643306
  111. 111. Beacham TD, McIntosh B, Wallace C. A comparison of stock and individual identification for sockeye salmon (Oncorhynchus nerka) in British Columbia provided by microsatellites and single nucleotide polymorphisms. Canadian Journal of Fisheries and Aquatic Sciences. 2010: 67; 1274–1290.
  112. 112. Pigeon D, Chouinard A, Bernatches L. Multiple modes of speciation involved in the parallel evolution of sympatric morphotypes of lake whitefish (Coregonus clupeaformis, Salmonidae). Evolution. 1997: 51; 196–205.
  113. 113. Carl LM, McGuiness F. Lake whitefish and lake herring population structure and niche in ten south-central Ontario lakes. Environmental Biology of Fishes. 2006: 73; 315–323.
  114. 114. Bernatchez L, Renaut S, Whiteley AR, Derome N, Jeukens J, Landry L, et al. On the origin of species: Insights from the ecological genomics of lake whitefish. Philosophical Transactions of the Royal Society. 2010: 365; 1783–1800.
  115. 115. Renaut S, Nolte AW, Bernatchez L. Mining transcriptome sequences towards identifying adaptive single nucleotide polymorphisms in lake whitefish species pairs (Coregonus spp. Samonidae). Molecular Ecology. 2010: 19; 115–131. pmid:20331775
  116. 116. Renaut S, Nolte AW, Rogers SM, Derome N, Bernatchez L. SNP signatures of selection on standing genetic variation and their association with adaptive phenotypes along gradients of ecological speciation in lake whitefish species pairs (Coregonus spp.). Molecular Ecology. 2011: 20; 545–559. pmid:21143332
  117. 117. Gagnaire PA, Normandeau E, Pavey SA, Bernatchez L. Mapping phenotypic, expression and transmission ratio distortion QTL using RAD markers in the lake whitefish (Coregonus clupeaformis). Molecular Ecology. 2013: 22; 3036–3048. pmid:23181719
  118. 118. McCracken GR, Wilson KL, Brewis HT, McBride MC, Paterson I, Perry R, et al. Development of 26 novel microsatellite markers for the round whitefish (Prosopium cylindraceum) and successful polymorphic cross-specific amplification of seven previously developed salmonid markers. Conservation Genetics Resources. 2014: pmid:25067980
  119. 119. Morin R, Dodson LJ, Power G. Life history variations of anadromous cisco (Coregonus artedii), lake whitefish (C. clupeaformis), and round whitefish (Prosopium cylindraceum) populations of Eastern James-Hudson Bay. Canadian Journal of Fisheries and Aquatic Sciences. 1982: 39; 959–967.
  120. 120. MacPherson A, Holmes JA, Muir AM, Noakes DLG. Assessing feeding competition between lake whitefish Coregonus clupeaformis and round whitefish Prosopium cylindraceum. Current Zoology. 2010: 56; 109–117.
  121. 121. Sylvester JR. Possible effects of thermal effluents on fish: A review. Environmental Pollution. 1972: 3; 205–215.
  122. 122. Reutter JM, Herendorf CE. Thermal discharge from a nuclear power plant: Predicted effects on Lake Erie fish. The Ohio Journal of Science. 1976: 76; 39–45.
  123. 123. Smythe AG, Sawyko PM. Field and laboratory evaluations of the effects of "cold shock" on fish resident in and around a thermal discharge: An overview. Environmental Science & Policy. 2000: 3; S225–S232.