Understanding interpopulation variation is important to predicting species' responses to climate change. Recent research has revealed interpopulation variation among several species of Pacific salmonids. Here, we tested for local adaptation and countergradient variation by assessing interpopulation variation among six populations of fall-run Chinook salmon from California, Oregon, and Washington (USA). Juvenile fish were reared at three temperatures and five physiological metrics were measured. Statistical associations between the five physiological traits and 15 environmental predictors supported our hypotheses of local adaptation. Notably, latitude was a poor predictor of population physiology. Instead, our results demonstrate that populations from warmer habitats exhibit higher thermal tolerance (i.e., critical thermal maxima), faster growth when warm-acclimated and greater aerobic capacity at high temperatures. Additionally, populations with longer migrations exhibit higher metabolic capacity. However, overall metabolic capacity declined with warm-acclimation indicating that future climate change may reduce metabolic capacity, negatively affecting long-migrating populations.

This data set contains the growth, critical thermal maxima, metabolic and environmental datasets used in our analysis.  Additionally it contains mass, length and hematocrit values for 300 fish from which we collected tissue samples.

Fish (n = 710, 23.9± 4.25 g) underwent metabolic trials in one of four, 5 L automated swim tunnel respirometers (Loligo, Denmark). The four tunnels were split into two paired systems with two tunnels sharing a single sump and heat pump. Water for each swim tunnel system was pumped (PM700, Danner USA) from the sump into an aerated water bath surrounding each swim tunnel, and then returned to the sump. Sumps were supplied with non-chlorinated fresh water from a designated well and aerated with air stones. The temperature of the sump (and therefore the swim tunnels) was maintained (±0.5°C) by circulating water through a heat pump (model DSHP-7; Aqua Logic Delta Star, USA) using a high-volume water pump (Sweetwater SHE 1.7 Aquatic Ecosystems, USA). In addition, each sump contained a thermostatically controlled titanium heater (TH-800; Finnex, USA). Swim tunnels and associated sump systems were cleaned and sanitized with bleach weekly to reduce potential for bacterial growth.

Dissolved oxygen saturation within the swim tunnels was measured using fibre-optic dipping probes (Loligo OX11250) which continuously recorded data via AutoResp™ software (version 2.3.0). Oxygen probes were calibrated weekly using a two-point, temperature-paired calibration method. Water velocity of the swim tunnels was quantified and calibrated using a flowmeter (Hontzcsh, Germany) and regulated using a variable frequency drive controller (models 4x and 12K; SEW Eurodrive, USA). The velocity (precision <1 cm s^-1) for each tunnel was controlled remotely using the Autoresp™ program and a DAQ-M data acquisition device (Loligo, Denmark). Swim tunnels were surrounded by shade cloth to reduce disturbance of the fish. Fish were remotely and individually monitored using infrared cameras (QSC1352W; Q-see, China) connected to a computer monitor and DVR recorder.

Oxygen consumption rates for both routine and maximum metabolic rates were captured using intermittent respirometry(Brett 1964). Flush pumps (Eheim 1048A, Germany) for each tunnel pumped aerated fresh water through the swim chamber and were automatically controlled via the AutoResp™ software and DAQ-M system. This system would seal the tunnel and enable the measurement of oxygen consumption attributable to the fish. Oxygen saturation levels were not allowed to drop below 80% and restored within three minutes once the flush pump was activated. Oxygen saturation data from AutoResp™ was transformed to oxygen concentration using the following equation:

Where %O²Sat is the oxygen saturation percentage reported from AutoResp™; αO2 is the coefficient temperature-corrected oxygen solubility (mgO₂ L^-1 mmHg^-1); and BP is the barometric pressure (mmHg). Oxygen concentration (milligrams of oxygen per liter) was measured every second and regressed over time, the coefficient of this relationship (milligrams of oxygen per liter per second) was then converted to metabolic rate (milligrams of oxygen per kilogram per minute, Equation 3).

Where R is the calculated coefficient of oxygen over time; V is the volume of the closed respirometer; M is the mass of the fish in kilograms and ’60’ transforms the rate from per second to per minute. An allometric scaling exponent was not incorporated due to similarity in fish sizes and to maximize comparability with metabolic data from the Mokelumne Hatchery (CA) fall-run population (Poletto et al. 2017).

Routine Metabolic Rate

Prior to routine metabolic rate (RMR) trials, fish were fasted to ensure a post-prandial state. Fish reared at 16 or 20°C were fasted for 24 hours, while fish acclimated to 11°C were fasted for 48 hours. Fish were then transferred into a swim tunnel respirometer between 13:00 and 17:00. After a 30-minutes at their acclimation temperature the temperature was adjusted at 2°C h^-1 to the test temperature (8–26°C). Automated intermittent flow respirometry began 30 minutes after the test temperature was achieved and continued overnight. Measurement periods ranged from 900 to 1800 seconds in duration, flush periods were 180–300 seconds. Periods varied in length in response to fish size and test temperature to ensure oxygen saturation was kept high (>80%) during the trial. A small circulation pump (DC30A-1230, Shenzhen Zhongke, China) ensured that water was mixed without disturbing the fish. Fish activity was monitored by overhead infra-red cameras and measurement periods when the fish were active were discarded. RMR was calculated by averaging the three lowest RMR values(Poletto et al. 2017). RMR measurements were concluded by 08:00 ± 40 min.

Maximum Metabolic Rate

A modified critical swimming velocity protocol was used to elicit maximal metabolic rate (MMR)(Poletto et al. 2017). Tunnel speed was increased gradually from 0 to 30 cm s^-1 over an ~2 min period and held there for 20 min. For each subsequent 20-min measurement period, tunnel velocity was increased 10% up to a maximum of 6 cm s^-1 per step. Fish were swum until exhausted and unable to swim. Swimming metabolism was measured by sealing the tunnel for approximately 16 minutes of the 20-minute measurement period. When a fish became impinged upon the back screen (>2/3 of body in contact with screen) the tunnel velocity was stopped for ~1 minute and then gradually returned to the original speed over 2 minutes. A fish was determined to be exhausted if it became impinged twice within the same velocity step. At this point, the tunnel impellor was stopped to allow for recovery. The highest metabolic rate measured over a minimum of 5 minutes during active swimming was taken as the MMR.

Post-experiment, the tunnel was returned to the acclimation temperature and fish were transferred to a recovery tank and monitored. In seeking evidence of metabolic collapse at near-critical temperatures, some metabolic trials were conducted at temperatures exceeding the tolerance of the fish. These mortality events represent potential lethal upper limits for sub-acute thermal persistence (Fig. S1). Data from fish which did not survive the trial or recovery were not used in analysis. After a 24-hour recovery period, fish were euthanized in a buffered solution of MS-222 (0.5g/L). Measurements for mass (g), fork length (cm) and total length (cm) were taken, and Fulton’s condition factor was calculated.

Aerobic scope (AS) was calculated as the difference between a fish’s RMR and MMR. Thermal optimums (TOPT) were defined as the temperature when aerobic scope was maximized, and calculated as the root-value of the derivative of the quadratic function describing the relationship between AS and test temperature. 

Growth Data

Growth measurements were initiated in mid to late spring when all populations would still be rearing prior to outmigration. Growth data were gathered every two weeks by measuring a sample of 30 fish from each treatment (n=~15 per tank, n = 2149 total measurements). Fish were not individually marked and therefore growth rate was calculated across individuals. Fish were arbitrarily netted from their treatment tank and transferred to an aerated five-gallon bucket until measured. Fish were air exposed for ~15–20 seconds to measure mass (± 0.01 grams, Ohaus B3000D) and fork length (± 0.1 cm) and then placed into a second bucket for recovery before returning to their original treatment tank. Fish were netted and measured by the same experimenter across all sampling days.

Condition factor was calculated as Fulton's condition factor (K) using the equation K = 100*Mass/Fork Length³.

Critical Thermal Maxima

Critical Thermal Maximum (CT_Max) values were quantified according to established methods, briefly described below1. We placed six 4L Pyrex beakers in a fiberglass bath tray (1m x 2m x .2m). Beakers were aerated with an air stone to ensure both adequate oxygen saturation and circulation of water within the beaker. The volume of water in each individual beaker (approx. 2.5 L) was calibrated to ensure even heating across all CT_Max beakers (0.33°C/min). Two pumps (PM700, Danner USA) were used to circulate water: one pump recirculated water across three heaters (Process Technology S4229/P11), while the other distributed heated water through the CT_Max bath via a distribution manifold. Experiments began with water temperature set at the fish’s acclimation temperatures (11, 16, or 20°C).

Fish of appropriate size (n = 377, 12.4 ± 0.83 cm) were arbitrarily selected from treatment tanks and transferred to separate tanks for fasting. To ensure fish were in a similar postprandial state, fish reared at 20°C and 16°C were fasted for 24 hours, and 11°C fish were fasted for 48 hours to account for their slower metabolic rate. Once fasted, fish were individually netted and transferred into individual beakers within the CT_Max heat bath. Fish were given 30 minutes to acclimate to their CT_Max beaker after which the CT_Max trial began.

During the CT_Max trial, beaker temperature was taken every 5 minutes using a thermocouple (Omega HH81A). Thermocouple measurements were calibrated to a Fisherbrand® NIST certified mercury thermometer following each trial. Fish were observed continually for signs of distress and loss of equilibrium. The CT_Max trial endpoint was loss of equilibrium, at which point the temperature of the CT_Max beaker was recorded. Fish were then removed and returned to a recovery bath at their acclimation temperature. Fish that did not fully recover within 24-hours were not included in analysis (6% of individuals). After the 24-hr recovery, fish were weighed (wet mass ± 0.01g) and measured (fork length ± 0.1 cm).

Missing values:

Only fish that successfully completed the Critical Thermal Maximum (CTMax) trials are included in this dataset. Fish that did not recover from the trial were excluded from analysis, and therefore this dataset. The CTMax trial is designed to be survived and therefore failure to recover fully is reflective of an abnormality in the fish’s physiology or experimenter error, both of which could bias the ultimate results.

Tissue Samples

Fish (N = ~12) from each treatment group were humanely sacrificed for tissue collection. Additionally, one or more capillary tubes of blood were collected shortly after fish were sacrificed. Tubes were then spun in a centrifuge at ~10,000 RPM for 3 minutes to separate the red blood cells. After centrifugation the hematocrit (% red blood cells) was measured and the plasma was extracted and flash-frozen in liquid nitrogen. 

Missing values:

Fish varied in size so we were unable to get multiple capillary tubes of blood from each fish. Therefore some fish only have a single HCT measure, while others have 3. Other missing values indicate that the data was not recorded. 

1. Becker, C. D. & Genoway, R. G. Evaluation of the critical thermal maximum for determining thermal tolerance of freshwater fish. Environmental Biology of Fishes 4, 245–256 (1979).
2. Beitinger, T. L., Bennett, W. A. & McCauley, R. W. Temperature tolerances of North American freshwater fishes exposed to dynamic changes in temperature. Environmental Biology of Fishes 58, 237–275 (2000).
3. Fangue, N. A., Hofmeister, M. & Schulte, P. M. Intraspecific variation in thermal tolerance and heat shock protein gene expression in common killifish, Fundulus heteroclitus. Journal of Experimental Biology 209, 2859–2872 (2006).

.csv Files can be opened with excel or in R. There are not additional software requirements.