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Dryad

Multigenerational exposure to increased temperature reduces metabolic rate but increases boldness in Gambusia affinis

Cite this dataset

Moffett, Emma; Fryxell, David; Simon, Kevin (2022). Multigenerational exposure to increased temperature reduces metabolic rate but increases boldness in Gambusia affinis [Dataset]. Dryad. https://doi.org/10.7280/D1MT39

Abstract

Acute exposure to warming temperatures increases minimum energetic requirements in ectotherms. However, over and within multiple generations, increased temperatures may cause plastic and evolved changes that modify the temperature sensitivity of energy demand and alter individual behaviours. Here, we aimed to test whether populations recently exposed to geothermally elevated temperatures express an altered temperature sensitivity of metabolism and behaviour. We expected that long-term exposure to warming would moderate metabolic rate, reducing the temperature sensitivity of metabolism, with concomitant reductions in boldness and activity. We compared the temperature sensitivity of metabolic rate (acclimation at 20 versus 30°C) and allometric slopes of routine, standard, and maximum metabolic rates, in addition to boldness and activity behaviours, across eight recently divergent populations of a widespread fish species (Gambusia affinis). Our data reveal that warm-source populations express a reduced temperature sensitivity of metabolism, with relatively high metabolic rates at cool acclimation temperatures and relatively low metabolic rates at warm acclimation temperatures compared to ambient-source populations. Allometric scaling of metabolism did not differ with thermal history. Across individuals from all populations combined, higher metabolic rates were associated with higher activity rates at 20°C and bolder behaviour at 30°C. However, warm-source populations displayed relatively bolder behaviour at both acclimation temperatures compared to ambient-source populations, despite their relatively low metabolic rates at warm acclimation temperatures. Overall, our data suggest that in response to warming, multigenerational exposure (e.g., plasticity, adaptation) may not result in trait change directed along a simple “pace-of-life syndrome” axis, instead causing relative decreases in metabolism and increases in boldness. Ultimately, our data suggest that multigenerational warming may produce a novel combination of physiological and behavioural traits, with consequences for animal performance in a warming world. 

Methods

Fish acclimation  

Fish from eight populations were acclimated into 16 20L tanks (2 tanks per population) in the laboratory, with each tank containing fish from a single population. We randomly allocated ~12 fish from a population to a tank (n = 198 fish total; details in S1). In each tank, we separated males and females using dividers to minimise sexually antagonistic interactions that can affect survival; however, mosquitofish females store sperm, so most females were pregnant during the time of trait measurements, as they would be in nature. Each population was acclimated to two experimental temperatures (20 ± 0.5 and 30 ± 0.5°C) over four months. Tank temperatures were initially set to the collection temperature for a given population and then adjusted by increasing or decreasing the set temperature of aquarium heaters by a maximum of 1°C every two days until the target temperature was reached. We started with water from the appropriate field site in each aquarium combined with treated tap water to remove chlorine (API Stress Coat) and progressively replaced it with treated water over two weeks. We fed fish twice daily by hand to satiation with freeze-dried Daphnia and Nutrafin MAX small tropical fish micro-granules and maintained a light cycle of 12:12 throughout the experiment. Each aquarium had artificial macrophytes and stones to provide refuge. Water was continuously filtered using sponge air filters, which we cleaned every second day. Fish mortality was low in most populations (see Table S1). We fasted individuals for 24 hours before measuring behavioural and metabolic traits to control for food digestion.

Metabolic Rate

We measured metabolism as maximum metabolic rate (MMR), standard metabolic rate (SMR), and routine metabolic rate (RMR). MMR is the maximum metabolic rate of an individual and sets the upper limit on organismal metabolic performance (Fry, 1971). In contrast, SMR is the minimum metabolic rate, measured after rest, with no digestion cost, on non-stressed fish and sets the lower requirement of an animal to sustain life. RMR was measured under similar conditions as SMR but allowed for some activity and sits between SMR and MMR. As RMR incorporates variation in activity between individuals, it may closely relate to behavioural traits (Mathot & Dingemanse, 2015).

We measured RMR and MMR using static respirometry and SMR using intermittent flow-through respirometry at each fish’s acclimation temperature (Steffensen, 1989; Clark, Sandblom, & Jutfelt, 2013). We used respirometers comprising 40 mL acrylic chambers with magnetic stir bars in the chamber base to ensure water mixing throughout our oxygen measures in all assays. We measured metabolic rate as oxygen consumption (MO2) using a FireSting four-channel oxygen logger with optical oxygen sensors (PyroScience, Germany). Respirometers were placed into 80 L aquaria, filled with treated tap water, fitted with a UV filtration system, an aerator, and a 100W aquarium heater. 

Immediately following behavioural trials (see below), we measured RMR by placing individuals into chambers and measuring oxygen consumption over 15 minutes. Chambers were then connected to a recirculating pump and slowly flushed with oxygenated water for five minutes before beginning SMR measurements. Oxygen consumption measurements for SMR were taken overnight over an approximately 18-hour period. A computer-controlled aquarium pump intermittently flushed chambers for five minutes to ensure a complete turnover of water inside the chambers, then an oxygen measurement period of 15 minutes began after a 30 second wait period. We controlled oxygen flow and data logging through a PC using the software ‘AquaResp’ (Svendsen, 2017). Following SMR measurements, we measured MMR using an exhaustive chase protocol to induce maximum oxygen consumption (Clark et al., 2013; Norin & Clark, 2016). Fish were removed from chambers one by one and placed into a circular tank; in this tank, we used an aquarium net to chase the fish until exhaustion (defined as the lack of ability for burst swimming) (Norin & Clark, 2016). Fish were then immediately placed into a static respirometer, and oxygen consumption was measured for 5 minutes. We chose to measure MMR after SMR measurement to ensure our SMR measurement accuracy as metabolic rates may remain elevated for long periods after exhaustive exercise. We immediately euthanised the fish following the measurement of MMR using clove oil. Fish were then measured for mass, length, sex, and volume, then dried at 60°C for 48 hours and re-weighed for dry mass.

We controlled for microbial oxygen consumption in our metabolism assay water by subtracting the oxygen consumption in blanks (respirometers with water only), which were run before and after every trial. We assumed a linear increase in microbial oxygen consumption between measurements in blanks. 

We calculated each SMR, MMR, and RMR as; 

〖MO〗_2=(V_r-V_f )×〖ΔC〗_wO2/Δt                                                                                                 

Where: MO2 is oxygen consumption rate, Vr is respirometer volume, Vf is fish volume, ΔCwO2 is the change in oxygen concentration, Δt is the change in time.

We calculated SMR using the mean of the lowest 10 % of all measurements, excluding any outliers (± two standard deviations [SD] from the mean), aerobic scope as MMR-SMR, and factorial aerobic scope as MMR/SMR (Clark et al., 2013; Chabot, Steffensen, & Farrell, 2016). 

Behaviour

Immediately before measuring metabolism, we conducted behavioural assays on individuals in a 60 L aquarium with a water depth of 20 cm and temperature set to the acclimation temperature. We fit the aquarium with an air pump and a UV filtration system to maintain high oxygen saturation and control microbial respiration. We measured individual’ boldness’ as latency to exit a refuge and individual ’‘activity' as time spent exploring a novel environment (Cote et al., 2010; Wilson, Godin, & Ward, 2010). For these behavioural measures, we placed individuals into a small enclosed and darkened area (‘refuge,’ 10cm × 30cm) at one end of the 60 L aquarium. The aquarium was covered on all but one side to allow for observation. In the refuge, we provided artificial macrophytes and river stones. Fish were left in the refuge for 10 minutes before a 4 × 4 cm door was opened remotely, allowing fish to exit and explore the remainder of the tank (‘open area’). In the open area, we placed macrophytes opposite the refuge opening as a visual cue for exploration. We measured boldness using a stopwatch as the time it took the fish to leave the refuge. Fish that did not leave were assigned a maximum latency time of 600 seconds and were not measured for activity as forced tests may measure anxiety or fear traits (Brown, Burgess, & Braithwaite, 2007). Once the fish began exploring, we video-recorded their movement and later measured activity as time spent moving (versus remaining stationary) over five minutes following their emergence from the refuge

Usage notes

        • Males have no data in the pregnancy column
  • Individuals that did not leave the refuge were not measured for activity and have no data in the "Time_spent_exploring_s" column
  • NA's in dataset indicate missing data

Column descriptions/  units:

  • Site refers to the location where Gambusia were collected
  • Geothermal refers to the designation of sites as geothermal or ambient, geothermal sites received warm water inputs and ambient sites experience daily and seasonal changes in environmental temperature.
  • Source_Temp refers to the temperature of the site at the time of fish collection in degrees Celcius.
  • Temp_lab refers to the temperature that fish were acclimated in the laboratory in degrees Celcius
  • Run refers to the order in which metabolic rate was measured on fish
  • Fish_ID is a unique identifier for each fish in this study.
  • Sex refers to the sex of the fish measurements were done on (M = male, F = female).
  • Pregnancy describes if the fish was visibly pregnant at the time of metabolic rate measurement, where Y indicates yes or that the fish was pregnant and N indicates no or that the fish was not pregnant.
  • length: fish length (mm)
  • dry_mass_mg: fish dry mass (mg)
  • dry_mass_g: fish dry mass (g)
  • Excretion_rate: Fish excretion rate (ammonium and NOX) measured immediately following RMR (µg N min-1 fish-1)
  • Time_to_leave_s: Time the fish took to leave the refuge, maximum latency was 600 seconds (seconds)
  • Time_spent_exploring_s: Time the fish spent exploring after leaving the refuge (seconds)
  • SMR_rate_fish: standard metabolic rate of each fish (µg min-1 fish-1)
  • RMR_rate_fish: routine metabolic rate of each fish (µg min-1 fish-1)
  • MMR_rate_fish: maximum metabolic rate of each fish (µg min-1 fish-1)

Funding

Royal Society of New Zealand, Award: 16-UOA-23

The Kate Edger Educational Charitable Trust