Canadian Journal of Fisheries and Aquatic Sciences
Effects of natal water concentration and temperature on the behaviour of up-river migrating sockeye salmon
Journal: Canadian Journal of Fisheries and Aquatic Sciences
Manuscript ID cjfas-2017-0490.R1
Manuscript Type: Article
Date Submitted by the Author: 22-Feb-2018
Complete List of Authors: Middleton, Collin; University of British Columbia, Department of Forest and Conservation Sciences Hinch, Scott; University of British Columbia, Department of Forest and ConservationDraft Sciences Martins, Eduardo; University of Northern British Columbia, Ecosystem Science and Management Program Braun, Douglas; Department of Fisheries and Oceans Patterson, David; Department of Fisheries and Oceans Burnett, Nicholas; University of British Columbia, Department of Forest and Conservation Sciences; Instream Fisheries Research Minke-Martin, Vanessa; University of British Columbia, Department of Forest and Conservation Sciences Casselman, Matthew; BC Hydro Burnaby Office
Is the invited manuscript for consideration in a Special Oceans Tracking Network Issue? :
Homing, Behaviour, Migration Delay, TELEMETRY < General, OLFACTION < Keyword: General
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1 Effects of natal water concentration and temperature on the behaviour of up-river
2 migrating sockeye salmon
3 Collin T Middelton1*, Scott G Hinch1, Eduardo G Martins2, Douglas C Braun3, David A
4 Patterson3, Nicholas J Burnett4, Vanessa Minke Martin1, Matthew T Casselman5
5 1Department of Forest and Conservation Sciences, University of British Columbia, 2424 Main
6 Mall, Vancouver, BC, Canada. [email protected] & [email protected]
7 2Ecosystem Science and Management Program, University of Northern British Columbia, 3333
8 University Way, Prince George, BC, V2N 4Z9, Canada. [email protected]
9 3Fisheries and Oceans Canada and School of Resource and Environmental Management, Simon
10 Fraser University, 643 A Science Road,Draft Burnaby, British Columbia, V5A 1S6, Canada.
11 david.patterson@dfo mpo.gc.ca & douglas.braun@dfo mpo.gc.ca
12 4InStream Fisheries Research Inc., 215 – 2323 Boundary Road, Vancouver, British Columbia,
13 V5M 4V8, Canada. [email protected]
14 5BC Hydro, 6911 Southpoint Drive, 11th Floor, Burnaby, British Columbia, V3N 4X8, Canada.
16 *correspondence author: Collin Middleton, 2424 Main Mall, Vancouver, BC, V6T 1Z4, 778
17 928 7094, [email protected]
18
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19 Abstract 20 Impoundments and diversions in freshwater corridors can alter the availability and
21 concentration of natal water cues that migratory salmon rely on to guide homing during
22 spawning migrations, although this has rarely been examined. By combining radio telemetry and
23 non invasive biopsy, we provide the first detailed account of the effects of varying natal water
24 concentrations, temperature, and individual physiology on the homing behaviour of wild adult
25 Pacific salmon migrating through a regulated river. Most (89%) of the 346 sockeye salmon from
26 the two distinct populations tracked in this study in southwestern British Columbia (Canada)
27 delayed their migration in the outlet of a powerhouse that discharges strong concentrations of
28 natal lake water, and subsequently wandered in the Fraser River before continuing upstream into 29 the Seton River, where natal water cuesDraft can also vary. There were few associations between 30 metabolic stress indices and reproductive hormone levels with this behaviour in either
31 population, however, higher temperatures and elevated natal water concentrations in the Seton
32 River were associated with shorter powerhouse delays and less wandering in late run migrants.
33
34 Keywords:
35 Olfaction; homing; migration delay; behaviour; Oncorhynchus nerka; telemetry 36
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37 Introduction 38 Anadromous fishes exhibit some of the most complex behaviours of any group of
39 organisms (Dingle and Drake 2007), in large part because of the variable abiotic conditions
40 encountered throughout their migrations and the inherent physiological changes associated with
41 reproductive development (Alerstam et al. 2003; Donaldson et al. 2011). In the case of Pacific
42 salmon (Oncorhynchus spp.), up river migrating adults use olfactory cues to locate natal areas
43 (Keefer and Caudill 2014) and do so while maturing and coping with environmental factors (e.g.
44 high discharge and/or high temperature) that can lead to physiological stress, increased energy
45 use (reviewed in Hinch et al. 2006), and slowed or delayed migration (e.g. Bugert et al. 1997;
46 Keefer et al. 2008a). Because adults cease feeding prior to entering freshwater, individuals must 47 complete migration, gonad development,Draft and spawn using finite energy reserves (Brett 1971). 48 Thus, any environmental factors that may delay migrations could influence migration or
49 spawning success (Burnett et al. 2016).
50 Many freshwater corridors used by migratory salmon have been altered by
51 impoundments or diversions (see reviews in Waples et al. 2008; Thorstad et al. 2008). While
52 numerous studies have examined how changes in the amount of flow can affect migratory
53 salmon (e.g. Quinn et al. 1997; Keefer et al. 2004b; Murchie et al. 2008), there have been few
54 direct investigations of how changes in the specific natal water composition of flows affect
55 migrations. For example, multiple impoundments of the Columbia River, U.S.A. have increased
56 river channel cross sections and led to substantial odour diffusion from natal tributaries (Quinn
57 2005; Keefer and Caudill 2014). Many adult salmon now exhibit wandering behaviour in this
58 system which could be reflective of orientation challenges and active searching for natal water
59 cues, though this is largely speculation (Keefer et al. 2008a). Adult salmon are known to be
60 attracted to and delay their migrations in power station outlets which discharge natal water along
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61 migration routes (Andrew and Geen 1958; Thorstad et al. 2003b, 2008). Numerous forays in and
62 out of these facilities into mainstem flows can result in substantial migration delays or failure to
63 continue migrations upstream to pass dams (Fretwell 1989; Thorstad et al. 2003b). Adult
64 Atlantic salmon (Salmo salar) have also been documented making 'yo yo' movements or
65 wandering back and forth between power station outlets and dam tailraces, ultimately causing
66 migration delays and reduced dam passage success (Lundqvist et al. 2008). Many lab based
67 experiments have revealed that migration responses in adult salmonids can be triggered by even
68 slight changes in natal water concentrations (reviewed in Bett and Hinch 2015), yet there has
69 been comparatively little research examining how such changes to natal water along migration
70 routes can influence the migration behaviour of free swimming wild salmon.
71 In recent years, freshwater migrationDraft corridors have been warming (e.g. Patterson et al.
72 2007; Isaak et al. 2012) and many Pacific salmon now often encounter temperatures that can
73 exceed population specific thermal limits (Eliason et al. 2011). For adult sockeye salmon (O.
74 nerka), exposure to high temperatures accelerates maturation (Hinch et al. 2006), depletes energy
75 reserves (Hinch and Rand 1998; Burnett et al. 2014), increases physiological stress and disease
76 development (Crossin et al. 2008; Bradford et al. 2010), and reduces aerobic scope (Eliason and
77 Farrell 2015) – any or all of which can lead to en route mortality (e.g. Keefer et al. 2009; Hinch
78 et al. 2012). Pacific salmon will seek cool water refuges (e.g. hypolimnion of lakes, tributary
79 outlets; Newell and Quinn 2005; Goniea et al. 2011) to reduce exposure to high temperatures and
80 increase chances of migration survival (Mathes et al. 2010). However, the use of thermal refugia
81 could also limit exposure to natal water cues if refuge is taken in non natal tributaries or areas of
82 substantial homestream odour diffusion, which could in turn lead to missed migration cues in the
83 mainstem migration corridor, and potentially increase migration delays. Prolonged delay in
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84 thermal refuges has also been shown to reduce the probability of surviving to natal sites by
85 migrating adult salmon (e.g. Columbia River steelhead O. mykiss; Keefer et al. 2009).
86 The physiological state of salmon can have strong effects on migration behaviours (Hinch
87 et al. 2006). For instance, elevated levels of acute metabolic stress and energy expenditure (as
88 reflected by increased plasma glucose and lactate levels; Milligan 1996; Farrell et al. 2000) in
89 ocean migrating adult Fraser River sockeye salmon are associated with delayed river entry and
90 slowed migration rates (Cooke et al. 2006; Crossin et al. 2007). Whereas in contrast, advanced
91 maturation (as reflected by high levels of plasma testosterone; Truscott et al. 1986; Leonard et al.
92 2002) is correlated with earlier river entry and fast migration rates (Sato et al. 1997; Crossin et
93 al. 2009). The important role of physiology is further emphasized in how sexes can differ in
94 migration behaviours. Females devote moreDraft energy to gonad development (Crossin et al. 2008)
95 and typically have higher levels of reproductive hormones than males throughout freshwater
96 migrations (Truscott et al. 1986). In the Fraser River, female sockeye salmon are energetically
97 more efficient swimmers (Hinch and Rand 2000), but are often less successful at passing
98 hydraulically challenging areas (Hinch and Bratty 2000; Burnett et al. 2013) compared to males.
99 How an individual’s physiological condition or sex affects migration behaviour in regulated
100 systems where natal water concentrations and flow composition can change during migration has
101 not yet been examined.
102 In this study, we used radio telemetry to track wild adult sockeye salmon from two
103 populations as they migrated during the summer and fall from a large mainstem system (Fraser
104 River) into a small, regulated, natal tributary (Seton River). Immediately prior to entering the
105 Seton River, migrants must pass by a powerhouse tailrace, which is likely attractive because it
106 discharges pure natal lake (Seton Lake) water directly into the migration route and is sometimes
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107 cooler than the Fraser River, offering a potential thermal refuge. Natal water cues in the Seton
108 River can vary daily because of inputs from a non natal tributary (Cayoosh Creek), which in turn
109 affects the availability and strength of natal Seton River water entering the Fraser River just
110 upstream of (and passing by) the powerhouse. This locale provides an ideal system in which to
111 examine the relative roles that flow composition (e.g. natal water cues), water temperature, and
112 thermal refugia can have on individual adult salmon behaviour as they migrate towards spawning
113 grounds.
114 We predicted that, if variation in natal water concentration does indeed affect migration
115 behaviour, adult sockeye salmon would spend more time in the powerhouse tailrace when natal
116 water concentration in the Seton River, entering the Fraser River just upstream, was low (see Fig.
117 1). We also predicted that if higher concentrationsDraft of natal water in the Seton River are expected
118 to encourage upstream migration, fish would display signs of ‘migratory confusion’, such as
119 enhanced wandering, when natal water concentration in the Seton River was reduced. Whereas,
120 we predicted that migrants would make more direct migrations towards the Seton River when its
121 natal water concentration was higher. We further hypothesized that if mainstem Fraser River
122 temperatures were approaching physiologically critical levels, fish would spend more time
123 delaying in the powerhouse tailrace, potentially using this area as a thermal refuge. Lastly, given
124 the physiological condition and sex of migrants are known to differentially affect behaviour, we
125 predicted that individuals that were more mature at tagging would migrate faster and more
126 directly towards the Seton River, whereas those that showed signs of stress would delay their
127 migration, likely in the powerhouse tailrace. We also expected that females would exhibit less
128 wandering and less delay at the powerhouse given their more limited energy budget.
129 Methods 130 Study system
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131 The Bridge Seton hydrosystem is a complex network of reservoirs, inter basin diversions,
132 and power generating stations operated by BC Hydro near Lillooet, British Columbia, Canada
133 (Fig. 1). Adult sockeye salmon first encounter the Seton Powerhouse (powerhouse) ~ 340 km
134 from the Pacific Ocean on the western bank of the Fraser River near the confluence of the Seton
135 River and Fraser River (Fig. 1). At the powerhouse, natal Seton Lake water diverted by the Seton
136 Dam is discharged from an underwater outlet into a 5 meter deep tailrace directly adjacent to the
137 Fraser River (Fig. 1). Notably, there is no fish passage facility at the powerhouse and migrants
138 are prevented from entering the underwater outlet by steel grates. During adult sockeye salmon
139 migrations, mean discharge from the powerhouse is ~ 84.5 m3s 1, or ~ 5% of the mean 1492.5
140 m3s 1 of the adjacent Fraser River. Discharge from the powerhouse creates a plume of natal Seton
141 Lake water that visibly extends ~ 800 mDraft downstream into the Fraser River (Fig. 1). The Seton
142 River flows into the Fraser River 1.5 km upstream of the powerhouse (Fig. 1). The 5 km long
143 Seton River (22.7 m3s 1mean annual discharge) is regulated by the Seton Dam, which is made
144 passable to migratory fish by a 107 m long, 32 pool vertical slot fishway. Cayoosh Creek (13.9
145 m3s 1 mean annual discharge) is the only tributary of the Seton River; it drains a separate, non
146 natal watershed (Fig. 1). During times of increased discharge from Cayoosh Creek, which occurs
147 due to operational changes at the Seton Dam or at Walden North (a small non BC Hydro
148 diversion dam on Cayoosh Creek), or during large precipitation events, flows from this tributary
149 can ‘dilute the olfactory signature’ of the Seton River (Fretwell 1989) by reducing the
150 concentration of natal water cues in the Seton River and its plume. It is the combination of pure
151 natal Seton Lake water discharged at the powerhouse and reduction in natal water concentration
152 in the Seton River that creates the variable olfactory conditions of interest in this study (Fig. 1).
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153 Gates Creek (hereafter, GC) and Portage Creek (hereafter, PC) sockeye salmon are the
154 two populations of Fraser River sockeye salmon that spawn and rear in this system, representing
155 distinct ‘early summer’ and ‘late run’ populations, respectively. The GC population typically
156 begins migrating into the hydrosystem in late July, travelling ~ 55 km past the Seton Dam
157 through Seton and Anderson Lakes to reach terminal spawning grounds at Gates Creek. PC
158 sockeye salmon begin migrating into the hydrosystem at the end of September, travelling ~ 20
159 km past the Seton Dam through Seton Lake to reach spawning grounds in Portage Creek.
160 Studies conducted throughout the 1970’s by the International Pacific Salmon Fisheries
161 Commission indicated that the upstream migration of both populations could be delayed at the
162 powerhouse, and that migrants often had difficulty navigating beyond this point (Fretwell 1989).
163 Results of behavioural choice (Y maze)Draft experiments and limited radio telemetry studies
164 suggested that minimizing delay and encouraging upstream migration past the powerhouse was
165 dependent on maintaining natal water levels in the Seton River and its plume at or above 80%
166 and 90% during the GC and PC migrations, respectively (Fretwell 1989). BC Hydro currently
167 operates the hydrosystem with measures in place to maintain these natal water dilution targets,
168 though large fluctuations still occur. Migration delays at the powerhouse followed by wandering
169 in the Fraser River are still observed in both populations (Casselman et al. 2015).
170 Fish capture and tagging
171 It was not possible to capture target or control populations of sockeye salmon in the
172 Fraser River for this study; therefore, all fish were captured using a full spanning fence and trap
173 at a site 200 m downstream from the Seton Dam in the Seton River (Fig. 1). In total, we radio
174 tagged and monitored the movements of 517 sockeye salmon through the summer and fall of
175 2013 and 2014. Specifically, 138 GC sockeye salmon were tagged between 5 August and 2
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176 September 2013, and 166 were tagged between 5 August and 7 September 2014. In 2013, PC
177 sockeye salmon co migrated with ~ 0.8 million pink salmon (O. gorbuscha) returning to the
178 Seton River, making capture of PC sockeye salmon extremely difficult – only 24 individuals
179 were tagged from 3 – 9 October 2013. However, pink salmon were not present in 2014 (pinks
180 only return during odd years in the Seton River), enabling 189 PC sockeye to be captured and
181 tagged from 27 September to 9 October.
182 Radio transmitters [(43 mm length × 16 mm diameter; 15.2 g in air); Sigma Eight,
183 Newmarket, Ontario, Canada] were gastrically inserted into individual fish. Tags had a burst rate
184 of 3 s and a unique digital identification code. Individually labeled spaghetti tags (Floy
185 Manufacturing, Seattle, WA, U.S.A.) were attached externally through the dorsum of each fish,
186 with a tissue sample from the adipose finDraft and a 1.5 mL blood sample from the caudal vasculature
187 taken for population identification and physiological assays. Average time to tag and biopsy
188 sample each fish was < 4 minutes. Fish were not anesthetized to minimize handling and related
189 stress (Cooke et al. 2005). All handling and intra gastric tagging methods followed procedures
190 used in many adult salmon tracking studies and are known not to affect behaviour or survival
191 (e.g. Ramstad and Woody 2003; Cooke et al. 2005). All procedures followed the methods
192 described in greater detail in (Roscoe et al. 2010b; Burnett et al. 2013, 2014), and were
193 conducted in accordance with the guidelines of the Canadian Council of Animal Care
194 administered by the University of British Columbia (A11 0125).
195 We selected fish for tagging based on visual inspection of injury, external pathogens and
196 somatic lipid content (measured by a hand held microwave energy meter – Fatmeter model 692;
197 Distell Inc., West Lothian, Scotland, UK; see Crossin and Hinch 2005). Severely injured fish
198 (e.g. lacerations exposing the coelomic cavity or skeletal system) or those with extensive fungus
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199 cover on body or gills were not tagged, nor were those with high somatic lipid concentrations.
200 An earlier study which compared DNA population identification to Fatmeter output from fish
201 captured at the fish fence revealed that these high energy fish were strays which had entered the
202 Seton River but whose spawning grounds were several 100 km’s further upstream in tributaries
203 of the Fraser River (Casselman et al. 2015). Sex was assigned by analysis of 17 β estradiol and
204 testosterone concentrations in blood plasma. Plasma concentrations of glucose and lactate were
205 used as indices of metabolic stress (Cooke et al. 2008), and testosterone concentrations were
206 used to infer maturity level (Crossin et al. 2007). All blood plasma analyses followed the
207 methods described in (Roscoe et al. 2010b).
208 To examine how migrants behaved when they first encountered the powerhouse outflows
209 and Seton River plume, tagged fish wereDraft transported by truck downstream of the powerhouse for
210 release into the Fraser River. Groups of up to twelve individuals (approximate 50:50 sex ratio)
211 were moved via a 1000 L insulated and oxygenated transport tank and released within 30 min (±
212 10 min) of tagging, 1.5 km downstream from the powerhouse on the western bank of the Fraser
213 River (Fig. 1). We highlight that the use of passive capture methods followed by downstream
214 transport have been used in other studies with little effect on behaviour or survival (Keefer et al.
215 2004a, 2009; Hubert et al. 2012). Moreover, methods of upstream capture and downstream
216 release are common in studies of salmon migrating through regulated rivers (Thorstad et al.
217 2003b; Naughton et al. 2005; Caudill et al. 2007), and there is little evidence suggesting adult
218 salmon have the ability to learn migration routes or consequently behave differently from non
219 study fish (Hansen and Jonsson 1994; Thorstad et al. 2003b).
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220 Radio-telemetry monitoring of migration behaviour
221 We used a combination of fixed SRX (Lotek Wireless, Inc., Newmarket, Ontario,
222 Canada) and Orion (Sigma Eight, Inc., Newmarket, Ontario, Canada) radio receivers fitted with
223 aerial Yagi antennas at different locations in the hydrosystem to monitor fish movement (Fig. 1).
224 The powerhouse receiver was configured to detect tags only in the tailrace and not in the
225 adjacent Fraser River. The receiver at the Seton Fraser confluence was configured to only detect
226 tags within a ~ 100 m radius of the Seton River mouth. A receiver at the Fraser River release site
227 served as a ‘gate’ for detecting individuals exhibiting fallback in the Fraser River, whereas
228 receivers upstream in the Seton River confirmed Seton River entry or arrival at the Seton Dam
229 (Fig. 1). All receivers operated > 85% of the study duration, providing sufficient ability to
230 monitor fish movements (e.g. Release Site:Draft 92.4%; Seton Powerhouse: 98.3%; Lower Seton
231 River: 94.8%; Seton Fraser confluence: 91.2%; Seton Cayoosh confluence: 91.2%; Seton Dam:
232 95.7%)
233 Raw telemetry data were filtered to remove false detections (e.g. likely false detections of
234 study tag ID’s, non study tag ID’s, detections recorded before release (Beeman & Perry 2012)
235 and generate migration histories. Migration behaviour was quantified by (1) counting the number
236 of entries individuals made into the powerhouse tailrace (hereafter ‘forays’) as a measure of
237 attraction to the outflows at this facility; (2) determining the number of inter receiver movements
238 (hereafter ‘wandering’) in the Fraser River between radio receivers at the powerhouse and the
239 Seton Fraser confluence as an index of migration confusion; and (3) summing the duration of
240 each foray into the powerhouse tailrace as an estimate of the total amount of migration delay
241 incurred by individuals at this facility (hereafter ‘delay’). To ensure that the number of forays
242 and thus delay at the powerhouse were representative of true migration behaviour, we calculated
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243 each metric based on detections that were part of ‘residence events’. Residence events for a
244 given fish were defined as a series of consecutive detections at an individual receiver separated
245 by no more than 30 minutes. The duration of a residence event continued indefinitely until being
246 terminated when either (1) the time elapsed between any two consecutive detections was > 30
247 minutes, or when (2) a detection was recorded on another receiver.
248 Individual migration histories were visually examined to count the number of wandering
249 events in the Fraser River. We classified every change in direction prior to final assignment of
250 fate as a single wandering event. Fish with wandering values of zero exhibited directed
251 movements in the Fraser River, while fish with increasing wandering values exhibited the same
252 corresponding number of changes in direction prior to final assignment of fate. Fate was
253 assigned to individuals as having (1) successfullyDraft entered the Seton River if their last known
254 detection occurred at any receiver upstream of the Seton Fraser confluence or into the Seton
255 Anderson watershed, (2) passed the Seton River and migrated further upstream in the Fraser
256 River if their last detection occurred at the Seton Fraser confluence, (3) exhibited fallback
257 downstream in the mainstem Fraser River if their last detection occurred at the release site
258 receiver, or (4) be of unclassified fate if detections did not conform any of the aforementioned
259 patterns. Of the 304 GC sockeye salmon originally released for this study, 90% (274 of 304)
260 successfully entered the Seton River, 4% (12 of 304) migrated upstream of the Seton Fraser
261 confluence, 3% (9 of 304) fell back downstream in the Fraser River, and 3% (9 of 304) had
262 unclassified fates. Of the 213 PC fish released, 80% (170 of 213) successfully entered the Seton
263 River, 6% (13 of 213) migrated upstream of the Seton Fraser confluence, 13% (28 of 213)
264 returned downstream, and 1% (2 of 213) had unclassified fates. Fish that fell back downstream
265 after release and did not re ascend may have suffered from some form of experimenter induced
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266 stress. However, given that this occurred in a relatively small component of released fish, and
267 93% and 86% of GC and PC fish, respectively, reached the Seton River, we suspect our handling
268 and transport approaches probably had minimal effects on fish behaviour and short term
269 survival.
270 Environmental conditions
271 We used hourly measurements from the Water Survey of Canada
272 (www.wateroffice.ec.gc.ca) to monitor discharge in Cayoosh Creek (Station No. 08ME002) and
273 the Seton River below the Seton Dam (Station No. 08ME003). Hourly discharge data from the
274 powerhouse were provided by BC Hydro. We calculated hourly lower Seton River discharge by 275 summing (1) the upper Seton River discharge,Draft (2) Cayoosh Creek discharge, and (3) a constant 276 2.1 m3s 1 of Seton Lake water diverted to an artificial spawning channel that is returned into the
277 lower Seton River before the Seton Fraser confluence. We then calculated the concentration of
278 natal water in the lower Seton River and its plume using discharges in the following equation:
ℎ % = 100− 100 × + ℎ + ℎ 279 We confirmed differences in the water chemistry between natal Seton River and non natal
280 Cayoosh Creek water – which reflects differences in olfactory cues – by collecting daily
281 conductivity measurements from Cayoosh Creek, the upper and lower Seton River, and the
282 powerhouse using a hand held YSI Pro30 conductivity meter (YSI Inc., Yellow Springs, OH,
283 USA). Conductivity has previously been used to distinguish between water sources used by other
284 anadromous fishes that use olfaction to guide homing (e.g. Leduc et al. 2010; Vrieze et al. 2011).
285 Hourly water temperatures were measured and collected using TidbiT v2 data loggers (Onset
286 HOBO data loggers, Bourne, MA) at locations in the Fraser River, the powerhouse, and the
287 lower Seton River (Fig. 1).
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288 Data analysis
289 Statistical models
290 We used both generalized linear (GLM) and linear models (LM) to relate migration
291 behaviour to characteristics of individual migrants and the environmental conditions they
292 encountered. Our analyses included three specific models to examine: (1) the number of forays
293 made into the powerhouse tailrace (Poisson or negative binomial GLM), (2) the number of
294 wandering events between the powerhouse tailrace and Seton Fraser confluence (Poisson or
295 negative binomial GLM), and (3) the total amount of migration delay incurred at the powerhouse
296 tailrace (LM). All analyses were conducted on the GC and PC populations independently given 297 the different run timing and environmentalDraft conditions experienced by the two populations. 298 Model construction
299 All global models included explanatory variables to account for effects of sex,
300 physiological state (plasma glucose and lactate levels), and the maturity level (plasma
301 testosterone level) of individuals at the time of tagging. Preliminary analyses included
302 interactions between sex and testosterone to test for the differences in reproductive actions this
303 hormone can have between males and females (Truscott et al. 1986; Ueda 2011). However, no
304 significant effects were observed, so this interaction was removed from the models reported on
305 below. Additionally, each model included variables to account for the effects of environmental
306 conditions on different migrant behaviours, including: temperatures encountered in the Fraser
307 River and in the powerhouse tailrace, the temperature differential between these two locations as
308 a measure of thermal refuge potential, and the natal water concentration of the Seton River
309 plume. Neither Fraser River nor Seton River discharge were included in any of the models
310 because GC and PC sockeye migrate up river when flows are lowest in the migration season and
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311 at levels unlikely to affect behaviour (Rand et al. 2006; Macdonald et al. 2007). Moreover, water
312 temperature and discharge were highly correlated (r = 0.89). Powerhouse discharge was also not
313 included in any analyses because all fish included in the models experienced consistent discharge
314 of ~ 87.3 m3s 1 in the tailrace.
315 Calculations of environmental variables were based on residence events and dependent
316 on each model response. Variables were calculated as means to ensure the best representation of
317 the overall conditions experienced by tagged individuals, and weighted means to emphasize the
318 effect of conditions experienced over longer periods of time. For Model 1, measurements were
319 used from the time of an individual’s the first detection of every foray into the powerhouse to
320 represent what conditions were like at the moment of movement into the tailrace. In Model 2,
321 means of conditions were weighted basedDraft on the duration of residence events that occurred at the
322 moment individuals changed migration direction between the powerhouse tailrace and the Seton
323 Fraser confluence. In Model 3, environmental variables were calculated as an overall average of
324 means were weighted by the duration of each foray into the powerhouse. Because each of the
325 models included explanatory variables that were measured on different scales (e.g. °C, %), and to
326 facilitate comparisons of the relative effect size of each, all the data for these variables were
327 standardized by centering (subtracting the mean) and dividing by two standard deviations
328 (Gelman 2008; Schielzeth 2010).
329 Prior to analysis, the data exploration protocols described in Zuur et al. (2010) were
330 applied to each model separately. Examinations of Cleveland dotplots were used to identify
331 outliers and variables with inordinate values to the majority of observations were removed (1 – 4
332 observations per model). Pearson correlation coefficients > 0.7 and variance inflation factors
333 (VIF) > 3 were used as thresholds to identify collinear variables (Zuur et al. 2010). In Models 1
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334 and 3 for PC sockeye salmon, the Fraser River temperature variable was highly collinear with the
335 natal water concentration variable. To account for this, we substituted tagging date for Fraser
336 River temperature because the two were related (r = 0.68), but not to the extent that tagging date
337 was collinear with the natal water concentration variable (VIF < 3). All models were constructed
338 based on a sample size of at least ten observations per explanatory variable.
339 Models 1 and 2 were initially fit with a Poisson GLM and assessed for over dispersion by
340 summing the square of the Pearson residuals and dividing by the degrees of freedom (McCullagh
341 and Nelder 1989). These models were deemed over dispersed (dispersion parameter > 1) and
342 subsequently re fit with a negative binomial GLM (O'Hara and Kotze 2010). All final GLMs fit
343 the data adequately as assessed by a Chi square test (P > 0.05; Smyth 2003). In Model 3, the
344 response variables were log transformedDraft to satisfy assumptions of linearity and homogeneity of
345 residual variance (both assessed visually); linear model fits were evaluated using adjusted R2.
346 Model selection and multimodel averaging
347 In each analysis, models with all possible subsets of explanatory variables were fit to the
348 data. Models were then ranked using the bias corrected Akaike Information Criterion (AICC) and
349 compared using AICC weights (wi), which describes the probability of a model in a candidate set
350 being the most parsimonious, given the data (Burnham and Anderson 2003). Uncertainty in
351 model selection was accounted for by calculating model averaged estimates of the coefficients
352 using the ‘zero’ method (Grueber et al. 2011), where variables not included in the models were
353 assigned coefficient values of 0 to indicate no effect. Only models included in the 95%
354 confidence set were used for model averaging (Burnham and Anderson 2003), and only
355 explanatory variables with 95% confidence intervals that did not include zero were considered to
356 have an important effect on the response. Model selection statistics for all models with AIC
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357 values < 2 are presented in Table 2. All statistical analyses were conducted in R using the
358 MuMIn package (R Development Core Team, 2008; version 3.1.2). All summary variables are
359 presented as means ±SD.
360 Results 361 Environmental conditions 362 The mean Fraser River temperature experienced by GC sockeye salmon in this study was
363 18.3°C (±1.3°C), although temperatures varied considerably over the entire 2013 and 2014
364 migrations, with some periods reaching near record summer highs (~ 22°C; Fig. 2a). On average,
365 GC fish encountered temperatures in the powerhouse tailrace of 17.9°C (±1.1°C); there were
366 opportunities for migrants to seek thermal refuge in this area as temperatures were between 0.5 –
367 4.0°C cooler than the adjacent Fraser RiverDraft for 42% of the GC migration; although temperatures
368 in this area could also be warmer than the Fraser River as well (Fig. 2a). For more than 83% of
369 both study years, natal water concentration in the Seton River plume remained above the
370 recommended 80% target for the GC population (Fig. 2b), with tagged fish on average
371 experiencing concentrations of 90.3% (±4.6%) natal water.
372 PC sockeye salmon are a late run population that migrates during the fall months, thus
373 they encountered Fraser River temperatures that were substantially cooler than during the GC
374 migration (Fig. 2a). For example, PC fish tracked in this study experienced mean Fraser River
375 temperatures of 11.8°C (±0.7°C) with no need for thermal refuge in the Powerhouse tailrace as
376 the average temperature in this area of 14.6°C (±0.5°C) was consistently warmer than the
377 adjacent Fraser River (Fig. 2a). Natal water concentration in the Seton River plume remained
378 above the 90% target for the PC population for over 87% of both 2013 and 2014 migrations,
379 while the mean concentration experienced by PC fish in this study was 91.4% (±1.2%) (Fig. 2b).
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380 Physiological state and reproductive hormone levels 381 We compared mean levels of plasma glucose, lactate, and testosterone between sexes,
382 populations, and years. There were no differences between years within each of the parameters
383 measured for each population (Table 1). Glucose levels were very similar among males and
384 females, both within and between the populations (Table 1). However, lactate was ~1.4 times
385 higher in females compared to males in each population, and ~1.3 times higher among all GC
386 fish relative to PC fish (Table 1). Testosterone was considerably higher in females compared to
387 males for both populations (5.6 times higher in GC population; 4.9 times higher in PC
388 population), and PC sockeye salmon had 2.2 times higher levels of this hormone than GC
389 sockeye salmon (Table 1).
390 Powerhouse attraction and forays Draft 391 Of all the tagged GC and PC sockeye salmon released into the Fraser River, 87% (265 of
392 304) and 91% (193 of 213), from each population respectively, made at least one foray into the
393 powerhouse. However, we only included fish in models predicting forays that had complete
394 physiological profiles (255 GC and 90 PC sockeye salmon) (fates are given by sex and
395 population in Supplementary Table 1). Fifty six percent (142 of 255) of these GC fish made only
396 one foray into the powerhouse, while the remainder made up to 8 forays (Fig. 3a). In contrast,
397 43% of the modeled PC fish (39 of 90) made only one foray into the powerhouse, while the
398 remainder made up to 17, with one PC female making 24 forays (Fig. 3b). On average, modeled
399 PC sockeye salmon (3.6 forays ± 4.0) made nearly twice as many forays into the powerhouse as
400 GC fish overall (1.9 forays ± 1.4) (Fig. 3 a & b).
401 AIC model selection results indicated a large amount of uncertainty in foray models for
402 GC fish, whereas there was less uncertainty in models for PC fish (Table 2; Supplementary Table
403 2). Nevertheless, there are trends among explanatory variables that are consistent between
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404 populations. Sex was absent from the majority of models in the 95% confidence set for both
405 populations because males and females made a similar number of forays (Table 2; Fig. 3 a & b).
406 Model averaged estimates for the effect of blood glucose on forays in both populations were
407 negative and ~ 2 times larger than those of lactate, suggesting individuals with elevated levels of
408 glucose may have made fewer forays into the powerhouse (Fig. 3 c & d). Testosterone effects
409 were positive for both populations, implying that increasingly mature fish may have made more
410 forays into this facility (Fig. 3 c & d). Blood glucose and testosterone, however, did not appear to
411 influence forays in either population, as the 95% confidence intervals (hereafter ‘CIs’) included
412 zero (Fig. 3 c & d).
413 Natal water concentration and powerhouse temperature had the largest effects on forays
414 among PC fish and were included in theDraft majority of models from the 95% confidence set (Table
415 2). Estimates for these effects were negative and had CIs that did not include zero, indicating that
416 PC fish that encountered higher natal water concentrations or elevated powerhouse temperatures
417 made fewer forays into this facility (Fig. 3d). Foray behaviour among GC sockeye salmon was
418 largely unaffected by natal water concentration or powerhouse temperatures, as these effects
419 were absent from most of the models in the 95% confidence set (Table 2; Fig.3c). We found little
420 indication that foray behaviour in fish from either population was affected by the temperature
421 differential between the powerhouse tailrace and Fraser River (Fig. 3 c & d).
422 Wandering 423 Models predicting wandering behaviour included 235 GC and 78 PC sockeye salmon
424 with complete physiology and maturity profiles (fates are given by sex and population in
425 Supplementary Table 1). Eighty three percent (195 of 235) and 73% (57 of 78) of GC and PC
426 sockeye salmon, respectively, migrated upstream in the Fraser River without exhibiting any
427 inter receiver movements (Fig. 4 a & b). Males and females within each population displayed
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428 similar amounts of wandering (Fig. 4 a & b), although there was more variability in this
429 behaviour among PC fish. Twenty seven percent of PC migrants wandered from 1 and 5 times,
430 while 17% of the GC migrants wandered from 1 to 4 times (Fig. 4 a & b).
431 There was a fair amount of uncertainty in the model selection results from models
432 predicting wandering (Table 2; Supplementary Table 2). Lactate was included in the majority of
433 the models from the 95% confidence set for both populations and had a negative effect that was
434 more than twice that of glucose, suggesting that wandering may have been reduced in fish with
435 higher levels of this stress metabolite (Table 2; Fig. 4 c & d). In each case, the CIs for these
436 effect estimates of lactate narrowly included zero (Fig. 4 c & d).
437 Fraser River temperature had little effect on wandering among GC fish but was included
438 in the majority of the models in the 95%Draft confidence set for the PC population, suggesting this
439 behaviour may have been reduced in PC fish that encountered cooler Fraser River temperatures
440 (Table 2; Fig. 4 c & d). Temperatures in the powerhouse tailrace had similar size but opposite
441 effects on the two stocks, implying that warmer temperatures at this facility may have been
442 associated with increased wandering among GC sockeye salmon and less among PC sockeye
443 salmon (Fig. 4 c & d). We did not find evidence that the temperature differential between the
444 powerhouse tailrace and the Fraser River influenced wandering in either population (Table 2;
445 Fig. 4 c & d).
446 Natal water was included in the majority of the models from the 95% confidence set for
447 PC fish (Table 2) and had the largest effect of all predictors on wandering within this population
448 (Fig. 4d). Wandering was reduced among PC sockeye salmon that encountered higher
449 concentrations of natal water in the Seton River plume, while wandering among GC fish was
450 largely unaffected by changes in natal water (Fig. 4c).
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451 Powerhouse delay 452 Models predicting the total amount of migration delay incurred by individuals in the
453 powerhouse tailrace included 256 GC and 90 PC sockeye salmon with complete physiology and
454 maturity profiles (fates are given by sex and population in Supplementary Table 1). We found no
455 effect of sex on powerhouse delay in models for either population (Table 2; Fig. 5 b & c). Mean
456 delay times of GC females (5.3 hours ± 6.4) were only slightly higher than GC males (3.4 hours
457 ± 3.9), and only slightly lower among PC females (19.5 hours ± 18.5) compared to PC males
458 (23.4 hours ± 27.1). Overall, PC sockeye salmon (21.1 hours ± 22.3) delayed ~ 5 times longer
459 than GC fish (4.5 hours ± 5.6) (Fig. 5a).
460 Glucose was included in the majority of models from the 95% confidence set and had the 461 largest effect on delay among GC sockeyeDraft salmon (9 times greater than that of lactate), 462 indicating that GC fish with elevated levels of this stress metabolite incurred less delay in the
463 powerhouse tailrace (Table 2; Fig. 5b). Neither glucose nor lactate had any effect on delay
464 among PC fish, and there was little support for testosterone effects on delay in either population
465 (Table 2; Fig. 5 b & c).
466 Natal water concentration was included in the majority of models from the 95%
467 confidence set for the PC population, with the largest relative effect size of all predictors (Table
468 2; Fig. 5c). Delay at the powerhouse decreased when PC fish encountered increasing
469 concentrations of natal water emanating from the Seton River plume. Effects of temperatures in
470 the powerhouse tailrace itself were also well supported in models for the PC population, with a
471 strong negative effect indicating that PC fish delayed less during periods of elevated
472 temperatures at this facility (Table 2; Fig. 5c). Despite a similar trend among GC fish, CIs for the
473 effect of powerhouse tailrace temperature included zero (Fig. 5b). Finally, there was no
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474 indication that the temperature differential between the powerhouse tailrace and the Fraser River
475 affected delay in either population (Fig. 5 b & c).
476 Discussion 477 We monitored the behaviour of two populations of Fraser River sockeye salmon in
478 relation to metabolic stress, river temperature, and varying natal water concentration during
479 migration past a powerhouse outlet and passage into their natal tributary, the Seton River.
480 Contrary to our expectations, metabolic stress indices in fish from both populations had little
481 influence on behaviour in this short section of the migration corridor. Fraser River temperature
482 was also unrelated to behaviour in both populations, and there was little evidence that the ‘early
483 summer’ GC population utilized the powerhouse tailrace as an area of thermal refuge. However, 484 encounters with higher concentrations ofDraft natal water led individuals from the ‘late run’ PC 485 population to make more direct migrations into the Seton River, in contrast to the GC population
486 who’s behaviour was unaffected by changes in natal water concentration.
487 All radio tagged sockeye salmon in this study entered the powerhouse tailrace as they
488 migrated up the Fraser River enroute to the Seton River, spending varying amounts of time in
489 this area before resuming their migration. Adult Atlantic salmon migrating up rivers in Norway
490 and Sweden are known to be attracted to turbine outlets and can make several movements in and
491 out of these tailrace areas (Thorstad et al. 2003a; Lundqvist et al. 2008). In these studies, tailrace
492 discharges were usually far greater than bypass flows, and thus hypothesized to be the primary
493 cause of tailrace attraction. However, in our study, discharge from the powerhouse was only ~
494 5% of Fraser River discharge, suggesting that initial attraction to the powerhouse occurs either
495 because of the strong olfactory cues coming directly from the natal Seton Lake water discharged
496 at the powerhouse, and/or because the powerhouse provides some degree of thermal refuge
497 during periods of the GC migration.
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498 One of the most striking findings in this study were the population specific differences in
499 how migrants behaviourally responded to the environmental factors encountered in this short
500 segment of their shared migration corridor. On average, PC sockeye salmon spent 4 to 5 times
501 longer than GC sockeye in the powerhouse tailrace (mean ~ 25 hours vs. 5 hours, respectively).
502 Late run populations of Fraser River sockeye salmon (e.g. PC fish) are known to migrate slower
503 up the Fraser River than summer run populations (e.g. GC fish; English et al. 2005). Unlike
504 summer runs, late run fish usually mill in natal lakes prior to entering spawning grounds (Hinch
505 et al. 2012), so this extended delay in the powerhouse tailrace was not unexpected considering
506 that PC fish are only ~ 8 km from their natal lake. Consistent with our hypothesis, we found that
507 changes in the concentration of natal water had a strong effect on migration behaviour, but only
508 for the PC population. Specifically, lowerDraft natal water concentrations emanating from the Seton
509 River into the Fraser River were associated with more forays into the powerhouse tailrace, more
510 overall time in the tailrace, and more wandering in the Fraser River. It thus appeared that PC
511 migrants became confused when natal water concentrations were reduced and migrated less
512 directly along their correct migration path. Given the narrower natal water concentration range
513 experienced by PC migrants during the study (~ 85 – 94% natal water) compared to that of GC
514 migrants (~ 60 – 95% natal water), it is possible that PC migrants could be more sensitive to
515 subtle changes in olfactory cues. PC fish were likely more mature than GC fish (based on higher
516 testosterone concentrations and proximity to natal spawning sites) at the time of tagging, and
517 thus may exhibit a degree of heightened olfactory sensitivity with increased maturity, similar to
518 that observed in common carp (Cyprinus carpio) in the Mississippi River, U.S.A (Irvine and
519 Sorensen 1993). If such a relationship does indeed exist, this may explain why PC fish could be
520 more sensitive to even slight changes in natal homestream water concentration at this stage in
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521 their migration. In addition, the densities of co migrating conspecifics from other populations of
522 Fraser River sockeye salmon are much higher during the GC migration than during the PC
523 migration (English et al. 2005). Thus, the additional directional cues that adult salmon rely on for
524 navigation (e.g. conspecific pheromones; Groot et al. 1986; Bett and Hinch 2015) may be less
525 present during the PC migration and lead to more ‘confusion’ and delay within this later run
526 population.
527 High migration temperatures are stressful for up river migrating adult salmon and
528 individuals will alter their migration times to avoid peak temperatures (e.g. Columbia River
529 sockeye & steelhead; Quinn and Adams 1996; Robards and Quinn 2011), and seek cool water
530 refugia in tributaries and lakes when possible (e.g. Columbia and Fraser River sockeye &
531 Chinook; Hodgson and Quinn 2002; GonieaDraft et al. 2011). However, the Fraser River provides
532 very few areas of thermal refuge during summer migration periods (Donaldson et al. 2009), so
533 we had hypothesized that the powerhouse tailrace could serve as a thermal refuge for migrants if
534 mainstem temperatures were high. Indeed, many GC fish experienced Fraser River temperatures
535 that were well above the population optimum (~ 17°C; Lee et al. 2003) and near their known
536 thermal limit (~ 21°C; Eliason et al. 2011), where aerobic scope collapses and fish must rely on
537 anaerobic metabolism risking acidosis and cardiorespiratory failure (Farrell et al. 2008).
538 However, we found no evidence for GC fish that the number of forays into or delay in the
539 powerhouse tailrace increased when tailrace water was cooler or when the temperature
540 differential between the tailrace and the Fraser River was large. In fact, there were many periods
541 in which tailrace temperatures were very similar to, or even greater than Fraser River
542 temperatures, thus limiting opportunities for the powerhouse tailrace to act as a thermal refuge.
543 Contrary to our hypothesis, GC fish spent relatively little time in the powerhouse tailrace, and
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544 instead migrated quickly into the Seton River. It is worth noting, however, that the hypolimnion
545 of Seton Lake is only ~ 6 km from the powerhouse tailrace; GC sockeye are known to occupy
546 this cool lake water while en route to spawning grounds (Roscoe et al. 2010a) perhaps in part
547 explaining the limited delays in the powerhouse tailrace and relatively fast passage through the
548 lower hydrosystem. During the migration of PC fish, there was likely no need for individuals to
549 seek thermal refuge in the powerhouse tailrace as the Fraser River was always 2 – 3°C cooler.
550 Yet, temperature still appeared to play a role in behaviour in that warmer tailrace temperatures
551 were associated with shorter delays and less forays into the tailrace of this facility. Caudill et al.
552 (2013) found that adult Snake River Chinook salmon and steelhead would avoid high
553 temperatures in fishways and remain in cooler dam tailraces. In a similar manner, PC fish may
554 choose to avoid the powerhouse tailraceDraft and spend more time in the cooler Fraser River where
555 temperatures are closer to optimum for late run sockeye at this time of year (Lee et al. 2003;
556 Farrell et al. 2008; Eliason et al. 2011). High concentrations of natal Seton River water entering
557 the Fraser River were associated with less delay and fewer forays into the tailrace, but the
558 interactive roles of olfaction and thermal biology in altering behaviour of migrating PC fish
559 could not be examined in these models because temperature and natal water variables were
560 highly collinear.
561 We had anticipated that initial physiological state would play a role in population specific
562 behaviours by predicting that sockeye salmon which were initially more mature would migrate
563 more directly toward their natal tributary, while those with high levels of stress metabolites
564 would delay their migration, likely in the powerhouse tailrace where they might be able to
565 recover from stressful conditions away from the mainstem Fraser River. However, we found
566 little evidence that the physiological state of individuals within a population influenced
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567 behaviour. The only exception was GC fish, which spent less time delaying in the powerhouse
568 tailrace when their plasma glucose concentrations were relatively high. Elevated glucose can be
569 indicative of recovery from swimming fatigue and excessive handling or confinement (Nielsen et
570 al. 1994; Farrell et al. 1998; Kubokawa et al. 1999). It is possible that GC fish were experiencing
571 some modest physiological stress from migrating ~ 340 km up river during peak summer
572 temperatures. Plasma glucose levels at time of capture were well above baseline, although
573 similar to levels found previously in GC fish captured at this locale (Roscoe et al. 2010b), but not
574 as high as those recorded for summer run sockeye salmon captured in the lower Fraser River
575 (Donaldson et al 2010). Because we found there was only limited opportunity for thermal refuge
576 in the powerhouse tailrace during the GC migration, exhausted or physiologically compromised
577 individuals may have chosen to avoid thisDraft unfavorable area and move more quickly to the Seton
578 River where flows and temperatures were lower and more conducive to physiological recovery.
579 Indeed, it has been shown that sockeye salmon in the Columbia River migrate more rapidly
580 toward natal tributaries as mainstem temperature increases (Naughton et al. 2005; Keefer et al.
581 2008b).
582 We had hypothesized that given their more limited energy budgets for swimming activity
583 females would exhibit less wandering and less delay at the powerhouse compared to males.
584 Testosterone levels were substantially higher among females from both populations, which is
585 typical of sockeye salmon throughout their freshwater migration (Truscott et al. 1986; Crossin et
586 al. 2007; Donaldson et al. 2010). Testosterone also increases steadily in both sexes with
587 decreasing distance to natal sites as oocytes and testes prepare for final maturation (Truscott et
588 al. 1986; Hinch et al. 2006), perhaps explaining why PC fish had nearly twice as high plasma
589 testosterone as GC fish given the much shorter distance remaining to PC spawning grounds.
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590 However, despite their higher testosterone level, females from both populations did not behave
591 differently than males. We highlight that this was unexpected given that recent findings from
592 physiological telemetry have found that females swim with more anaerobic effort (more burst
593 swimming) when passing through the Seton Dam tailrace and through the adjoining fishway
594 compared to males (Burnett et al. 2014). Female sockeye often suffer higher levels of mortality
595 than males towards the end of freshwater migrations (Hodgson and Quinn 2002; Keefer et al.
596 2004a, Donaldson et al. 2010; Martins et al. 2012), in part due to exhaustion of energy reserves
597 or cardiorespiratory collapse since they have a smaller ventricular mass (Sandblom et al. 2009).
598 Perhaps we did not observe behavioural differences between sexes because our short study reach
599 did not offer significant enough energetic challenges or obstacles (e.g. high discharge,
600 temperatures frequently above optimal) Draftnecessitating females to either attempt to conserve
601 energy by slowing or delaying migration, or, require a high degree of burst swimming.
602 Management implications
603 Although it is widely recognized that migrating adult salmon rely on the detection of
604 natal water cues to successfully navigate toward natal spawning sites (reviewed in Bett and
605 Hinch 2015), it is often overlooked how river regulation for hydropower production can affect
606 flow composition and natal water concentration in migration corridors. Indeed, adult salmon
607 have been documented exhibiting signs of migration confusion in rivers where natal water cues
608 have become diffuse or re directed through regulation (e.g. Columbia River Chinook salmon,
609 Keefer et al. 2008; Atlantic salmon, Lundqvist et al. 2008). However, until now, there has been
610 little research examining the relative effect of this factor on the behaviour of adult salmon
611 migrating through regulated river corridors. In the current study, we present some of the first
612 detailed analyses of how varying concentrations of natal water cues, in combination with
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613 dynamic river temperatures, and the physiological condition of migrants can affect behaviour in
614 wild adult salmon. We highlight the importance of accounting for dynamic natal water
615 conditions in future studies aimed at improving adult salmon passage through regulated
616 migration corridors.
617 In the Seton hydrosystem, it has long been recognized that the environmental conditions
618 created by the Seton powerhouse and fluctuating natal water concentrations in the Seton River
619 could cause significant delays for up river migrating sockeye salmon (Fretwell 1989). Water
620 preference experiments (‘Y maze’ behaviour studies) conducted in the late 1970s and early
621 1980s demonstrated that adult sockeye salmon were capable of discriminating between Seton
622 River and Cayoosh Creek water, and that olfaction was the primary sensory mechanism used by
623 fish to select different water sources forDraft homing through the hydrosystem (Fretwell 1989). These
624 studies provided in-situ experimental evidence that suggested migration delay in the powerhouse
625 tailrace could be mitigated by controlling Seton River discharge to maintain natal Seton River
626 water concentrations equal to or greater than the threshold of sensitivity exhibited by the two
627 populations (80% GC and 90% PC; Fretwell 1989). Based on these results, BC Hydro built a
628 diversion dam on Cayoosh Creek in an attempt to maintain the Cayoosh Creek component of the
629 Seton River discharge to 20% and 10% during the upstream migration period for GC and PC
630 sockeye runs, respectively. Recent Y maze experiments with both populations have re confirmed
631 these olfactory sensitivity thresholds (Casselman et al. 2015). In the present study, natal water
632 concentrations generally exceeded threshold targets except for a one week period during the
633 2013 GC migration (Fig. 2b). Despite a large range of natal water concentrations experienced by
634 GC sockeye, we could not find any effects of this factor on delay or other behaviours, and these
635 fish seemed to have little difficulty rapidly homing into the Seton River. On the other hand, even
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636 though threshold natal water concentrations were exceeded for PC migrants, lower natal water
637 concentration relative to the 90% threshold for this population increased tailrace delay and
638 slowed migration into the Seton River. Given that tailrace temperature also affected delay at the
639 powerhouse and the apparent olfactory sensitivity displayed by PC fish, the 10% Cayoosh Creek
640 water threshold may need to be re evaluated. Because of the difficulties associated with
641 capturing control fish from non natal populations of co migrating sockeye salmon in the
642 mainstem Fraser River, future experimental manipulation of natal water concentration in the
643 Seton River and its plume should be explored to isolate the effect of the natal water factor from
644 temperature and more thoroughly understand its effect on the migration behaviour of the PC
645 population.
646 Fraser River water temperaturesDraft have a significant effect on sockeye salmon migration
647 and spawning success and affect the condition of individuals upon arrival in the Seton Anderson
648 watershed. Peak summer water temperatures in the Fraser River have increased > 2°C in the past
649 60 years, with recent years exhibiting record high levels and climate models predicting even
650 warmer peak temperatures in future years (Patterson et al. 2007; Ferrari et al. 2007). GC fish
651 now typically encounter Fraser River temperatures exceeding 18 – 19 °C, with prolonged
652 exposure to such stressful temperatures causing migration mortality (Eliason et al. 2011). Even
653 though GC fish did not delay for long periods in the powerhouse tailrace enroute to the Seton
654 River, the fact that fish are increasingly encountering thermally stressful migrations prior to
655 reaching the Seton hydrosystem means that any small delay caused by the powerhouse or by
656 varying olfactory cues from the Seton River could be devastating if delays expose fish to
657 additional thermal stress. Thus, managers should continue to strive to achieve the natal water
658 targets established for this population.
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659 Acknowledgments 660 We thank W. Payne, R. Ledoux, J. Hopkins, A. Adolph, and C.F. White for their
661 assistance in the field. We acknowledge D. McCubbing (InStream Fisheries Research), Lance
662 and Leo O’Donaghey and C. Fletcher (N’Quatqua First Nation) for their support with the fish
663 fence. C. Storey, T. Nettles, and J. Hills (Fisheries and Oceans Canada) provided logistical
664 support and ran all physiological assays. Project funding was provided by B.C. Hydro, St’át’imc
665 Eco Resources, National Science and Engineering Research Council of Canada (NSERC)
666 Discovery, Strategic and Network (Canada’s Ocean Tracking Network) grants to S.G.H. Some
667 infrastructure was also supported by the Canada Foundation for Innovation. C.T.M. was
668 supported by an NSERC CGS M scholarship and a MITACS Accelerate internship.
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43 https://mc06.manuscriptcentral.com/cjfas-pubs Page 44 of 57 ) for female (♀) and and (♀) for female ) 1 2014 2014 5.0 ± 0.8 ± 0.8 5.0 3.8 ± 1.5 ± 1.5 3.8 4.6 ± 1.0 ± 1.0 4.6 2.8 ± 1.1 ± 1.1 2.8 61.6 ± 2.9 ± 2.9 61.6 58.3 ± 2.3 ± 2.3 58.3 (1.5 – 8.5) 8.5) – (1.5 (1.1 – 4.7) 4.7) – (1.1 (3.7 – 8.0) – (3.7 (2.6 – 7.5) – (2.6 = 41 (♀) 41 = n (♂) 30 = n (51.5 – 67) – (51.5 (5.7 – 42.9) – (5.7 138.4 ± 73.3 ± 73.3 138.4 16.57 ± 10.0 ± 10.0 16.57 (49.5 – 62.5) – (49.5 (13.3 – 306.8) – (13.3 Portage Creek Portage 2013 2013 3.7 ± 1.0 ± 1.0 3.7 4.7 ± 2.1 ± 2.1 4.7 4.1 ± 1.1 ± 1.1 4.1 2.6 ± 1.5 ± 1.5 2.6 (55 – 61) – (55 (54 – 60) – (54 = 6 (♂) 6 = n 57.8 ± 1.9 ± 1.9 57.8 56.3 ± 1.9 ± 1.9 56.3 (2.2 – 5.3) – (2.2 (2.2 – 8.4) – (2.2 (2.5 – 7.0) – (2.5 (0.9 – 4.7) – (0.9 = 13 (♀) 13 = n 88.3 ± 66.7 ± 66.7 88.3 ), and testosterone (ng ml (ng testosterone and ), 148.8 ± 108.9 ± 108.9 148.8 (18.3 – 365.2) – (18.3 (33.5 – 216.2) – (33.5 1 2014 2014 5.4 ± 1.4 ± 1.4 5.4 4.5 ± 0.8 ± 0.8 4.5 ± 2.5 5.0 3.7 ± 1.9 ± 1.9 3.7 (53 – 69) 69) – (53 (51 – 63) – (51 61.9 ± 4.0 ± 4.0 61.9 8.0 ± 6.63 ± 6.63 8.0 57.4 ± 4.0 ± 4.0 57.4 = 83 (♀) 83 = n (♂) 62 = n (3.0 – 9.3) – (3.0 (1.2 – 31.1) – (1.2 (1.4 – 11.0) – (1.4 (0.7 – 10.0) – (0.7 (2.5 – 10.1) – (2.5 53.32 ± 56.5 ± 56.5 53.32 ), lactate), (mmol L (2.1 – 385.6) – (2.1 1
Gates Creek Creek Gates Draft 2013 2013 5.6 ± 1.5 ± 1.5 5.6 5.5 ± 1.3 ± 1.3 5.5 ± 3.7 5.5 3.6 ± 2.3 ± 2.3 3.6 60.0 ± 3.1 ± 3.1 60.0 56.6 ± 3.0 ± 3.0 56.6 = 63 (♀) 63 = n (♂) 48 = n (52 – 67.5) 67.5) – (52 (49 – 65.5) 65.5) – (49 16.7 ± 17.7 ± 17.7 16.7 82.0 ± 97.4 ± 97.4 82.0 (0.9 – 83.6) – (0.9 (2.9 – 10.2) – (2.9 16.1) – (0.9 (0.8 – 10.2) – (0.8 (4.2 – 13.7) – (4.2 (1.1 – 398.1) – (1.1 https://mc06.manuscriptcentral.com/cjfas-pubs Canadian Journal of Fisheries and Aquatic Sciences ♂ ♂ ♂ ♂ ♂ ♂ ♀ ♀ ♀ ♀ ♀ ♂ ♂ ♀ ♀
) ) 1 1 ) 1 Lactate Lactate (mmol L Glucose Glucose (mmol L length Fork (cm) Testosterone Testosterone ml (ng male (♂) Gates Creek and Portage Creek sockeye salmon. *Note, preliminary analyses of physiological variables from the three three the from physiological variables of analyses preliminary *Note, sockeye salmon. Creek and Creek Portage Gates (♂) male example. an as 3 used in Model data the reports this table values; similar 3 and 2, 1, Models yielded behavioural in used datasets Table 1. Mean ± SD (range) of fork length (cm), glucose (mmol (mmol L glucose (cm), fork length of (range) ± SD Mean 1. Table
2
adj R i
w
c
AIC c
log Lik log AIC 420.30 420.30 850.85 1.91 0.01 420.87 420.87 849.91 0.97 0.02 419.84 419.84 849.91 0.97 0.02 420.35 420.35 850.94 420.35 1.99 850.94 1.99 0.01 0.01 420.22 420.22 850.68 1.73 0.01 420.35 420.35 850.94 1.99 0.01 204.36 204.36 421.73 0.00 0.06 420.35 420.35 850.94 1.99 0.01
421.42 421.42 848.94 420.67 0.00 849.50 420.68 0.56 849.52 422.82 0.03 0.57 849.69 421.80 0.02 0.74 849.70 420.84 0.02 0.75 849.84 421.90 0.02 0.89 849.90 0.02 0.96 0.02 420.89 0.02 849.94 422.12 1.00 850.33 421.18 1.39 850.52 0.02 1.57 0.01 0.01
Draft https://mc06.manuscriptcentral.com/cjfas-pubs Canadian Journal of Fisheries and Aquatic Sciences
Glucose + FRT + Tdiff + + FRT Glucose Tdiff + + FRT Glucose PHT + + FRT Glucose + PHT Tdiff + Glucose Glucose + PHT + Glucose +Tdiff Glucose Intercept Tdiff PHT + Testosterone Testosterone testosterone + Glucose + PHT testosterone + Glucose NW + Glucose PHT Tdiff + Testosterone Tdiff +NW + Glucose Tdiff Testosterone + + Glucose Glucose Glucose
the powerhouse, (2) the amount of wandering in the Fraser River between the release site and the Seton Fraser River confluence, and and River confluence, Seton Fraser the and site release the Riverbetween in theFraser the amount wandering (2) of powerhouse, the Creek Portage (GC) and Creek for Gates tailrace powerhouse in the individuals by delay incurred migration of amount total the (3) salmon. sockeye (PC) Table 2. AICc model selection statistics for generalized linear models and linear models predicting (1) the number of into forays number made the (1) predicting models and linear models generalized linear for statistics selection model AICc 2. Table
=255) N model and variable Response
GC ( forays Powerhouse (1) PC NW Tdiff + + PHT + TD Page 45 of 57 Page 46 of 57
73.94 73.94 161.07 1.00 0.02 141.95 141.95 296.27 1.83 0.02 142.01 142.01 296.40 142.01 1.95 296.40 1.95 0.02 0.02 142.01 142.01 296.40 1.95 0.02 73.44 73.44 160.07 0.00 0.03 142.01 142.01 296.40 1.95 0.02 204.99 204.99 422.99 1.26 0.03 203.78 203.78 422.93 1.20 0.04 205.27 205.27 423.55 1.82 0.03 205.65 205.65 422.02 0.29 0.06 204.08 204.08 423.52 1.79 0.03 205.14 205.14 423.29 1.56 0.03 204.17 204.17 423.70 1.97 0.02 205.20 205.20 423.40 1.67 0.03 206.02 206.02 422.75 1.02 0.04
206.68 206.68 421.84 205.56 0.11 421.84 0.11 206.00 0.06 422.72 0.06 0.99 0.04 142.09 142.09 294.44 0.00 144.06 296.29 0.05 1.84 0.02 74.72 74.72 75.96 160.28 0.21 160.47 0.40 0.03 0.03
Draft https://mc06.manuscriptcentral.com/cjfas-pubs Canadian Journal of Fisheries and Aquatic Sciences PHT + Tdiff + NW + Tdiff + PHT PHT NW + + Testosterone NW + Sex PHT + + PHT NW + Glucose Testosterone + PHT + Tdiff + NW PHT Tdiff + + + Testosterone +NW + PHT Tdiff + Glucose NW + Tdiff + Sex PHT + NW + + PHT TD Tdiff + + Glucose NW + PHT Testosterone + + Glucose NW Tdiff + + PHT + Sex TD + Testosterone + TD + PHT + Tdiff + + NW PHT TD Tdiff + + + Testosterone
Sex + Lactate + Testosterone + PHT + Testosterone + Sex + Lactate PHT+ Lactate PHT + + FRT Sex + Lactate Sex + Lactate + PHT + Sex + Lactate Sex + Lactate + FRT + NW + + FRT Sex + Lactate + NW FRT + Lactate NW + FRT NW + + FRT Testosterone + Lactate Sex + Lactate + PHT + Tdiff + PHT + Sex + Lactate Tdiff + + FRT Sex + Lactate Tdiff + + FRT Sex + Lactate
=235) =235) =90) =90) NW + PHT =78) N N N
GC ( ( Wandering (2) PC (
72.91 72.91 161.42 1.35 0.02 72.91 72.91 161.42 1.35 0.02 74.31 74.31 74.31 161.81 1.74 161.81 1.74 0.01 0.01 72.91 72.91 161.42 1.35 0.02 74.31 74.31 161.81 1.74 0.01 480.02 480.02 972.38 0.03 0.03 0.06 72.91 72.91 161.42 1.35 0.02 74.32 74.32 161.83 1.77 0.01 74.31 74.31 161.81 1.74 0.01 481.06 481.06 972.35 0.00 0.03 0.05 481.68 481.68 973.60 1.24 0.02 0.04
76.34 76.34 77.52 161.22 1.15 161.36 1.29 0.02 0.02 76.65 75.52 161.85 1.78 75.59 161.86 1.80 75.59 162.02 0.01 1.95 75.59 162.02 0.01 1.95 75.59 162.02 0.01 1.95 76.75 162.02 0.01 1.95 162.04 0.01 1.98 0.01 0.01 482.40 482.40 972.97 482.49 0.61 973.13 482.49 0.78 973.14 0.02 0.79 0.02 0.04 0.02 0.04 0.04
Draft https://mc06.manuscriptcentral.com/cjfas-pubs Canadian Journal of Fisheries and Aquatic Sciences
Lactate Lactate NW Tdiff + + + FRT Sex + Lactate NW Tdiff + + + FRT Sex + Lactate NW + PHT + + FRT Sex + Lactate NW Tdiff + + PHT + Sex + Lactate + NW + Tdiff FRT + Lactate + NW + Tdiff FRT + Lactate PHT + + NW FRT + Lactate Tdiff + NW + PHT + Lactate + PHT NW + Sex + Lactate Sex + Lactate NW + Sex FRT + NW Tdiff + + FRT NW Tdiff + + FRT NW + PHT + FRT NW + Tdiff + PHT PHT+ Lactate Lactate FRT + Lactate Glucose + Testosterone + Tdiff + + NW Tdiff Testosterone + + Glucose Tdiff + Glucose NW + Glucose PHT + Glucose + PHT NW + Glucose Glucose + Tdiff + NW Tdiff + + Glucose =256) =256) N
GC GC ( delay Powerhouse (3) Page 47 of 57 Page 48 of 57
is an is an 2
480.87 480.87 974.07 1.72 0.01 0.05 482.02 482.02 974.28 1.92 0.01 0.04 161.87 161.87 336.75 1.98 0.03 0.25 481.69 481.69 973.62 1.27 0.02 0.04 481.77 481.77 973.79 1.44 0.02 0.04 161.83 161.83 336.67 1.90 0.03 0.25 481.79 481.79 973.82 1.46 481.79 0.02 973.82 0.04 1.46 0.02 0.04 480.86 480.86 974.05 1.70 480.86 0.01 974.05 0.05 1.70 0.01 0.05 480.95 480.95 974.24 1.88 0.01 0.05 160.46 160.46 336.29 1.53 0.03 0.27 481.79 481.79 973.82 1.46 0.02 0.04 480.86 480.86 974.05 1.70 0.01 0.05 161.20 161.20 335.41 0.65 0.05 0.26 161.53 161.53 336.07 1.30 0.04 0.25 481.79 481.79 973.82 1.46 0.02 0.04 480.86 480.86 974.05 1.70 0.01 0.05 162.08 162.08 334.88 0.12 0.06 0.24
484.01 484.01 974.12 1.77 0.01 0.03 163.15 163.15 334.76 0.00 162.56 0.07 335.83 0.23 1.07 0.04 0.24
Draft and the top model in the candidate set. Models are ranked ranked from set. are Models candidate in the top model the and i https://mc06.manuscriptcentral.com/cjfas-pubs Canadian Journal of Fisheries and Aquatic Sciences – the probability that a given model is the best in the 95% confidence set. adj R set. confidence 95% the in best is the model a that given probability the – i values between model between model values c , and by , w by and c
Glucose + Testosterone NW Testosterone + + Glucose Tdiff + + FRT Glucose PHT + + FRT Glucose + PHT Tdiff + Glucose Tdiff + + FRT Glucose Tdiff + NW + + FRT Glucose + PHT NW + + FRT Glucose +NW + PHT Tdiff + Glucose Tdiff + NW + + FRT Glucose NW Tdiff + + + Lactate Glucose Glucose + Testosterone Tdiff Testosterone + + Glucose Glucose Glucose NW Tdiff + + Glucose NW + + Lactate Glucose PHT + NW + PHT Glucose NW + + PHT Tdiff + TD NW + + PHT TDNW + + PHT + TD Glucose NW + + PHT Tdiff + + TD Glucose NW + + PHT + Testosterone Glucose NW + + PHT + Lactate Glucose NW + + PHT is the difference in AIC difference is the c =90) =90) N estimate of the proportion of variance explained by each model, adjusted by the number of explanatory variables; this is only variables; explanatory of number the by model, each adjusted by explained variance proportion of the of estimate Abbreviations Methods). (see tests Chi square by evaluated model were fits linear models generalized as linear for shown lowest to highest AIC to highest lowest
Portage Portage ( AIC
Draft https://mc06.manuscriptcentral.com/cjfas-pubs Canadian Journal of Fisheries and Aquatic Sciences used for model variables include: Fraser River temperature (FRT), powerhouse temperature (PHT), temperature differential differential temperature (PHT), temperature powerhouse (FRT), temperature River Fraser variables include: model for used temperature. River Fraser for substituted date was tagging that to indicate parentheses in FRT with is PC, shown the TD between the Fraser River and powerhouse (Tdiff), natal water concentration (NW), and tagging date (TD). In Model 3 for Model for 3 In date (TD). tagging and (NW), concentration water (Tdiff), natal powerhouse River and the Fraser between Page 49 of 57 Page 50 of 57 d ) sockeye salmon a ) and Portage – Model-averaged panel a ), and natal water Panels c & d c ) and Portage Creek (
Draft ) in 2013 (grey) and 2014 (black). Shaded grey boxes represent the periods in panel b ) in 2013 (grey) and 2014 (black). Shaded grey boxes represent https://mc06.manuscriptcentral.com/cjfas-pubs Canadian Journal of Fisheries and Aquatic Sciences b , 1 female that made 24 forays was removed from the histogram for clarity. – Histograms of the number of forays female (grey bars) and male (black Gates Creek ( Panels a & b – Histograms of the number Fig. 1. Study area in the Seton-Anderson watershed in southwestern British Columbia, Canada (inset). Capture, release and fixed Canada (inset). Capture, Fig. 1. Study area in the Seton-Anderson watershed southwestern British Columbia, The location of the legend and map. Seton monitoring locations, are indicated by the radio-telemetry stations, along with temperature water given relative flow Fraser River, as is the extent of Seton River plume that fluctuates in its concentration natal of Cayoosh Creek. contributions ( Fig. 2. Mean daily Fraser River (solid lines) and powerhouse tailrace (dashed temperatures which fish from each population were tagged. Dashed red lines represent the current natal water concentration targets for Gates Creek the current natal water which fish from each population were tagged. Dashed red lines represent population proportional(80%) and Portage Creek (90%) sockeye salmon, are approximately to the migration timing of each through the hydrosystem. Fig. 3. concentration of the Seton River and its plume ( ) sockeye salmon made into the powerhouse as a proportion of all the individuals included in models predicting this Creek ( b ) sockeye salmon made into the powerhouse as a proportion of all individuals included in models made into the Seton powerhouse. Coefficient estimates with 95% confidence intervals that do not cross zero are highlighted by solid made into the Seton powerhouse. Coefficient estimates with 95% confidence intervals that do not cross standardized coefficient estimates for models predicting the number of forays Gates Creek ( powerhouse tailrace and the visible extent of the powerhouse discharge plume of natal Seton Lake water is shown extending into the extent of the powerhouse discharge plume natal Seton Lake powerhouse tailrace and the visible behaviour. In panel black circles. Vertical dashed line indicates the coefficient value of zero. Abbreviations for predictor variables include: Fraser River for predictor variables black circles. Vertical dashed line indicates the coefficient value of zero. Abbreviations c ) b ) b ) and Portage Creek ( a ) and Portage Creek ( – Model-averaged standardized d ) sockeye salmon. Coefficient – Model-averaged standardized Panel b & c Panels c & d c ) and Portage Creek (
Draft d only). Note the difference in x-axis scales between panels. https://mc06.manuscriptcentral.com/cjfas-pubs Canadian Journal of Fisheries and Aquatic Sciences – Beanplots of total migration delay in the powerhouse tailrace for female (black beans) and male (grey beans) Gates Panel a – Beanplots of total migration delay in the powerhouse tailrace for female (black beans) – Histograms of wandering (the number of back-and-forth movements) in the Fraser River between the release of back-and-forth movements) in the Fraser River between release Panels a & b – Histograms of wandering (the number coefficient estimates from models predicting the total amount of migration delay incurred by Gates Creek ( coefficient estimates from models predicting the total amount of migration delay incurred by Gates Creek and Portage Creek sockeye salmon used in models predicting this behaviour. Shaded polygons represent the distribution of the distribution Creek and Portage sockeye salmon used in models predicting this behaviour. Shaded polygons represent means. individual delay times (small horizontal lines) and bold lines represent estimates with 95% confidence intervals that do not include zero are highlighted by solid black circles. Vertical dashed line indicates estimates with 95% confidence intervals that do not include zero are highlighted by solid black circles. (FRT), powerhouse temperature the coefficient value of zero. Abbreviations for predictor include: Fraser River temperature variables concentration (NW). Note the differential between the Fraser River and powerhouse (Tdiff), natal water (PHT), temperature difference in x-axis scales between panels. Fig. 5. coefficient estimates for models predicting wandering Gates Creek ( temperature (FRT), powerhouse temperature (PHT), temperature differential between the Fraser River and powerhouse (Tdiff), differential between the (PHT), temperature (FRT), powerhouse temperature temperature date was substituted for Fraser River natal water concentration (NW). FRT is shown with TD in parentheses to indicate that tagging in the Portage Creek foray model (panel temperature Fig. 4. Creek ( site and the Seton-Fraser River confluence for female (grey bars) male (black Gates sockeye salmon shown as a proportion of all individuals included in the models predicting this behaviour for each population. In panel sockeye salmon shown as a proportion of all individuals included in the models predicting this behaviour a , 1 female that wandered 9 times was removed from the histogram for clarity. Page 51 of 57 Page 52 of 57 c only). Note the difference in x-axis scales between
Draft https://mc06.manuscriptcentral.com/cjfas-pubs Canadian Journal of Fisheries and Aquatic Sciences ! ! sockeye salmon in the powerhouse tailrace. Coefficient estimates with 95% confidence intervals that do not include zero are sockeye salmon in the powerhouse tailrace. Coefficient estimates with 95% confidence intervals of zero. Abbreviations for model variables highlighted by solid black circles. Vertical dashed line indicates the coefficient value between the Fraser River and differential (PHT), temperature (FRT), powerhouse temperature include: Fraser River temperature in the Portage Creek delay model (panel substituted for Fraser River Temperature panels. powerhouse (Tdiff), and natal water concentration (NW). FRT is shown with TD in parentheses to indicate that tagging date was powerhouse (Tdiff), and natal water concentration (NW). FRT is shown with TD in parentheses to indicate ! ":+;/:!&3@/:! ! !!!!!!!!!!!!!!!!!!!!! xxxxxxxxx xxxxxxxxx xxxxxxxxx xxxxxxxxx xxxxxxxxx xxxxxxxxx xxxxxxxxx xxxxxxxxx xxxxxxxxx xxxxxxxxx xxxxxxxxx xxxxxxxxx xxxxxxxxx xxxxxxxxx xxxxxxxxx xxxxxxxxx xxxxxxxxx xxxxxxxxx xxxxxxxxx xxxxxxxxx xxxxxxxxx !!!!!!!!!!!!!!!!!!!!! !
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Draft https://mc06.manuscriptcentral.com/cjfas-pubs Canadian Journal of Fisheries and Aquatic Sciences (d) (b) ! ! ! ! ! ! 0.3 0.1 ! ! 0.7 ! ! ! 1.1 1 3 5 7 9 11 13 15 17 (c) (a) Powerhouse forays Powerhouse ! ! Draft coefficients Standardized ! ! ! ! https://mc06.manuscriptcentral.com/cjfas-pubs ! Canadian Journal of Fisheries and Aquatic Sciences ! ! 0.16 0.04 0.19 1 3 5 7 9 11 13 15 17
0.6 0.5 0.4 0.3 0.2 0.1 0.0 NW Sex Proportion Tdiff PHT Lactate Glucose FRT (TD) FRT Testosterone Figure 3 Page 55 of 57 Page 56 of 57
(b) (d)
! ! !
! ! ! ! 1.0 0.2 ! ! ! 2.2 0 1 2 3 4 5 (c) (a) Draft Wandering events Wandering ! Standardized coefficients Standardized ! https://mc06.manuscriptcentral.com/cjfas-pubs ! Canadian Journal of Fisheries and Aquatic Sciences ! ! ! 0.2 0.4 1.0 ! ! ! ! 0.8 0 1 2 3 4 5
0.8 0.6 0.4 0.2 0.0 NW Sex Proportion FRT Tdiff PHT Lactate Glucose
Testosterone Wandering
Figure 4
(a) (c) ! ! ! ! ! ! ! 1.0 0.0 1.0 ! ! 2.0 ! Portage Creek Portage ! 3.0 (b) ! Draft ! ! Standardized coefficients Standardized ! ! ! https://mc06.manuscriptcentral.com/cjfas-pubs Canadian Journal of Fisheries and Aquatic Sciences Gates Creek ! ! ! 0.6 0.0 0.3 0.6 5 85 75 65 55 45 35 25 15
NW Sex Tdiff Powerhouse delay (hrs) delay Powerhouse PHT Lactate Glucose FRT (TD) FRT Testosterone Figure 5 Page 57 of