Interpopulation variation in growth, CTMax and metabolism among seasonal phenologies of Chinook Salmon
Zillig, Kenneth; Lusardi, Robert A.; Cocherell, Dennis E.; Fangue, Nann A (2022), Interpopulation variation in growth, CTMax and metabolism among seasonal phenologies of Chinook Salmon, Dryad, Dataset, https://doi.org/10.25338/B8QS66
Conservation of species facing environmental change requires an understanding of interpopulation physiological variation. However, physiological data is often scarce and therefore pooled across populations and species, erasing potentially important variability between populations. Interpopulation variation in thermal physiology has been observed within the Salmonidae family, although it has not been associated with seasonally distinct migratory phenotypes (i.e., seasonal runs). To resolve whether thermal physiology is associated with life-history strategy we acclimated four Sacramento River juvenile Chinook salmon populations (Coleman fall-run, Feather River fall- and spring-run and Sacramento River Winter-run) exhibiting different seasonal migratory phenotypes (fall-, spring- and winter-run), at 11, 16 and 20°C and assessed variation in growth rate, critical thermal maxima and temperature-dependent metabolic traits. We identified population differences in the physiological parameters measured and found compelling evidence that the critically endangered and endemic Sacramento River winter-run Chinook population exhibits thermal physiology associated with its early-migration life-history strategy. Acclimation to warm temperatures limited the growth and metabolic capacity of winter-run Chinook salmon, highlighting the risk of future environmental warming to this endemic population.
Fish 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 was 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 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 = 1528 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 Length^3.
Critical Thermal Maxima
Critical Thermal Maximum (CTMax) 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 CTMax 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 CTMax 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 CTMax heat bath. Fish were given 30 minutes to acclimate to their CTMax beaker after which the CTMax trial began.
During the CTMax 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 CTMax trial endpoint was loss of equilibrium, at which point the temperature of the CTMax beaker was recorded2,3. Fish were then removed and retuned 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).
N ≥ 20 for all treatments (population x. acclimation temperature) except for winter-run fish reared at 16 (n= 17) or 20°C (n=9). Winter-run reared at 20°C were limited due to a mortality event. On October 17th 2018, an outbreak of Columnaris in a single tank of winter-run Chinook salmon rearing at 20°C resulted in the mortality of the remaining tank population (n=7). Necropsy of the salmon indicated empty stomachs. The mortality of this population is hypothesized to be a result of thermal stressed after being reared at 20°C for so long (202 days). CTM data for the 20°C acclimation group was limited to 9 fish tested 41 days prior to the mortality event.
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.
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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).