DOI: 10.5061/dryad.m905qfvcg
title: Data from: Investigating the effects of thermal variability and heatwaves on pond zooplankton communities and physiological traits

description: To understand the impacts of climate change, we must understand the
 consequences of multiple and interacting timescales of temperature change.
 While much is known about rising mean temperatures, less is understood
 about the influence of projected thermal variability and extreme events
 like heatwaves on biological communities. This study investigates the
 interaction of short-term (experimental) and long-term (historic) thermal
 variability with heatwaves on zooplankton communities and physiological
 traits. We performed a fully factorial mesocosm experiment with three
 factors: (1) historic thermal variation (four source ponds with similar
 average temperature but different daily thermal ranges including 3.7°C,
 5.9°C, 9.1°C, and 10.7°C); (2) experimental thermal variation (insulated
 and non-insulated tanks); and (3) a 4-day heatwave treatment (+3.5°C)
 halfway through the experiment. We sampled the zooplankton community
 throughout the experiment and assayed the upper thermal limit (CTmax) and
 metabolic rate of Daphnia
 dentifera and Leptodiaptomus
 signicauda immediately before and after the heatwave. Zooplankton
 community composition responded minimally to thermal variability and the
 heatwave. For both species, CTmax response to the heatwave varied by
 experimental thermal variability, increasing in individuals from
 low-variability tanks and decreasing in individuals from high-variability
 tanks. Metabolic rate did not vary significantly by any of the treatments.
 D. dentifera and L. signicauda's upper thermal
 limit seems to be unaffected by their historic thermal history, while
 their CTmax response to a heatwave seems to rely only on their short-term
 thermal variability history. Metabolic rate, on the other hand, is
 unaffected by thermal history or heatwaves of this magnitude. In spite of
 the physiological responses at the individual level, zooplankton community
 structure seems to be buffered and overall unaffected by heatwaves and
 thermal variability at this magnitude. Our experiment provides new insight
 on the effects of thermal variability at both short- and long-term scales
 combined with an acute heatwave to understand the effects of a changing
 climate in a more realistic manner. The data supports that individuals
 from recently thermally stable backgrounds may be better equipped to
 positively respond physiologically to heatwaves and zooplankton community
 structure in this system could be unaffected by warming at this magnitude.
description: <strong>Initial Setup</strong> We
 carried out this outdoor mesocosm experiment at the Sierra Nevada Aquatic
 Research Laboratory near Mammoth Lakes, California from 16 July to 14
 September 2021. The experiment lasted 61 days with sampling performed
 weekly and increased to every 4 days from the beginning of the heatwave to
 2 weeks after the heatwave. We used 208 L cattle tanks with a randomised
 array with the following factors: source site (historic thermal history;
 four ponds), experimental DTR (low and high), and heatwave (heated and
 non-heated). We used a fully factorial design (16 treatments) with 4
 replicates for each treatment for a total of 64 tanks. We covered all
 tanks with 60% shade cloth, filled them with water from nearby Convict
 Creek, and added water weekly to counter evaporation. Stream water was not
 filtered as no zooplankton have been detected in the filtrate of other
 mesocosm experiments at the same site (Symons et al. 2021). To establish
 the four different source site communities, we collected zooplankton from
 four pond sites with a similar average temperature (17°C–19.1°C), but
 varying DTRs (3.7°C, 5.9°C, 9.1°C, and 10.7°C). Pond site temperature data
 was collected over 5 weeks (12 July to 16 August 2020) with temperature
 loggers every 5 min (HOBO pendant, Onset, Massachusetts, USA). Loggers
 were attached to a rock to keep them in the benthic zone and placed within
 1 m of the shoreline. We collected zooplankton from the source sites with
 horizontal tows thrown to the center of the pond from the shoreline with a
 63 μm mesh conical net. The ambient densities of each source site were
 achieved by filtering the total volume of the tanks for each treatment (16
 tanks * 208 L = 3328 L) and distributing zooplankton evenly to the tanks.
 We mixed zooplankton in large containers separated by site and inoculated
 the tanks with equal aliquots, which were achieved by adding the same
 volume of inoculum to each tank. We started by distributing inoculum with
 1 L bottles and then switched to 100 mL bottles as the inoculum volume
 decreased. Each tank received zooplankton from one source site, and all
 tanks were inoculated the same day the zooplankton were collected (16 July
 2021). The source sites, in order of increasing historic thermal
 variability, were: Box Pond, Hidden Pond, PD Pond, and Shell Pond. We
 preserved four replicates of plankton inoculum for each treatment in 70%
 ethanol for later enumeration. We added nutrients on the same day at
 average nutrient levels from the ponds from the previous summer
 (66.9 N μmol/L and 0.51 P μmol/L). We added 42 temperature loggers
 attached to a small piece of PVC pipe at the bottom of the tank to a
 random subset of the tanks to track temperature (HOBO pendant, Onset,
 Massachusetts, USA). <strong>Thermal Variability
 and Heatwave Treatments</strong> We created low-
 and high-thermal variability treatments through insulation. We placed each
 208 L tank inside one 1135 L tank. We filled the outside tanks to a
 consistent level with water to create the insulated, low-thermal
 variability treatment, and left the other 1135 L tanks empty to create the
 non-insulated, high-thermal variability treatment. To
 create the heatwave treatment, we used 300 W aquarium heaters for
 3.5 days. During the heatwave, all heated tanks were set to a consistent
 half insulation level of water in the outer tanks to create the same
 heatwave for both thermal variability treatments. Maintaining variability
 treatments during the heatwave would have caused a more severe heatwave in
 the high-experimental thermal variability tanks (i.e., greater maximum
 temperatures), which would have limited the ability to distinguish the
 effect of insulation (hypothesized to have an acclimation effect) from the
 effect of the higher maximum temperatures during the heatwave. Due to
 electrical constraints at the research site, we separated the heatwave
 treatment into two time points: heatwave A (11–15 August 2021, n = 19) and
 heatwave B (15–19 August 2021, n = 13). Tanks were haphazardly placed into
 the two heatwave blocks. <strong>Water and
 Community Sampling</strong> We sampled the tanks
 10 times total. All tanks were sampled for water chemistry, zooplankton,
 and chlorophyll a at each sampling event. We began sampling 4 days after
 inoculation and then weekly until the beginning of the heatwave
 treatments. The day before the heatwave, we began sampling every 4 days to
 capture the start and end of the heatwave treatment and the subsequent
 community responses. After 2 weeks, we returned to the weekly sampling
 schedule until the end of the experiment. We sampled water chemistry (pH,
 dissolved oxygen [DO], specific conductivity, and total dissolved solids
 [TDS]) with an EXO3 sonde probe (YSI, Yellow Springs, Ohio, USA). We
 sampled chlorophyll-a, a proxy for phytoplankton biomass, by analysing
 tank water in a Trilogy Laboratory Fluorometer with a Chlorophyll In Vivo
 module (TurnerDesigns, San Jose, California, USA). To sample zooplankton,
 we gently agitated the tank water with a plastic pipe and took a 2 L
 sample (1% of tank volume) with a Van Dorn sampler, filtered through 63 μm
 mesh, and preserved with 70% ethanol. For the final sample, we took 3 Van
 Dorn samples for a total of 6 L for each tank. All zooplankton samples
 were counted and identified to the lowest practical taxonomic resolution
 (usually species for crustaceans, and genus for rotifers) using a Leica
 dissecting microscope, identifying all individuals in each sample. We
 sampled nutrients (total nitrogen [TN] and total phosphorus [TP]) by
 filtering 20 mL of water through GF/F filters and analysing the filtrate
 on a Seal Analytical AA3 HR Nutrient Autoanalyser (Norderstedt,
 Germany). <strong>Physiological
 Measurements</strong> We measured CTmax and
 metabolic rate of adult Leptodiaptomus signicauda and Daphnia dentifera,
 which made up 23.2% and 15.1%, respectively, of the zooplankton biomass
 across all sampling times. We were able to get the most data on these
 species because they were visibly conspicuous and highly abundant. Due to
 time constraints, CTmax and metabolic rate were only sampled before and
 after heatwave A, excluding heatwave B from these measurements.
 Additionally, we excluded tanks with the second highest historic thermal
 variability treatment (source site PD, DTR = 9.1°C) for metabolic rate
 measurements. All historic thermal variability treatments were included
 for CTmax. <strong>CTmax</strong>
 We measured CTmax before and after heatwave A to determine how
 CTmax varied with source site (thermal history), between species, and
 before/after heatwave. Pre-heatwave measurements were taken over the
 4 days leading up to the heatwave (7–10 August 2021) and post-heatwave
 measurements were taken over the 3 days after the heatwave (15–17 August
 2021). To collect zooplankton to measure CTmax, we sampled 2 L of water
 from each tank using a Van Dorn water sampler. We gently agitated the tank
 water with a PVC pipe before sample collection. We filtered the sample
 through 63 μm mesh and immediately placed the collected zooplankton into
 filtered Convict Creek water in a 3 L holding tank. We combined samples
 from each replicate to use as a pool for each treatment, then used
 randomly selected zooplankton from these pooled samples to run trials
 before and after the heatwave. All replicates were included pre-heatwave
 (n = 4), as we did not know that we would not be able to heat all the
 tanks at the same time due to electrical limitations. Post-heatwave, only
 tanks that were included in Heatwave A were used for sampling (n = 1–4).
 For D. dentifera, we sampled 1–18 individuals per treatment (mean = 8.25
 individuals), but missed the non-heated, low-experimental variability,
 highest historic thermal variability (shell) treatment. For L. signicauda,
 we sampled 2–30 individuals per treatment (mean = 11 individuals), but
 missed the non-heated, low-experimental variability, second highest
 historic thermal variability (PD) treatment. Treatments were missed when
 species were absent from the subsamples. From each
 pooled sample, we picked out individuals of L. signicauda and D. dentifera
 in equal quantities when possible. These individuals were placed in
 individual 12 mL test tubes. A maximum of 24 test tubes were used at any
 single time point, across two aquaria with an identical set-up (12 tubes
 per aquaria, one zooplankton per tube). We filled each test tube with
 10 mL of filtered stream water from nearby Convict Creek. We placed test
 tubes into an aquaria bath of 7 L of tap water at 20°C and left them for
 5 min to acclimate before trials began. During trials, we increased water
 temperature by ~0.3°C every minute to 30°C, then ~0.1°C every minute at
 temperatures over 30°C using a 300 W heater with a max temperature of 34°C
 and a 50 W heater with a max temperature of 40°C. Both heaters were used
 together to achieve this warming rate, which was within range of other
 experimental warming rates (Geerts, Meester, and Stoks 2015; Kellermann
 and Sgrò 2018; Ribeiro, Camacho, and Navas 2012). We fit each aquarium
 with a water pump to homogenise water temperature. We defined CTmax as the
 temperature at cessation of motor function, following Hutchison's
 dynamic method (Lutterschmidt and Hutchison 1997).
 <strong>Metabolic Rate</strong>
 Using zooplankton samples collected from tanks as described
 above, we placed individual zooplankton from each treatment into 2.5 mL
 glass vials with aerated and filtered (63 μm) water originating from
 nearby Convict Creek. In order to limit feeding and control for food
 digestion costs, zooplankton were held in filtered water for 8 h before
 metabolic rate measurement. We sealed the glass vials with rubber stoppers
 and placed them into the tank from which they originated overnight. We
 used blank vials (filtered creek water only) to control microbial oxygen
 consumption. We measured the oxygen content of the water once immediately
 after incubation in each vial with a FireStingGO2 fibre-optic pocket
 oxygen meter (PyroScience, Aachen, Germany). We calculated oxygen
 consumption as a proxy of metabolism for each zooplankton, using the
 difference in oxygen concentration between vials containing zooplankton
 and vials containing creek water only. The metabolic rate of each
 individual was expressed per microgram mass of O2 and per hour (μg O2
 μg−1 h−1). <em><strong>Data
 Analysis</strong></em>
 <strong>Community Analysis</strong>
 We conducted all analyses in R version 4.2.1 (R Core Team 2022).
 Because we could not strictly use “pre-heatwave” and “post-heatwave” due
 to electrical constraints splitting the heatwave treatment into 2
 timepoints, we created a variable that coded for “not heated” (including
 all samples pre-heatwave and those that remained unheated) or
 “post-heatwave” (including samples only from tanks after they had
 experienced a heatwave). We used this variable as our “Heatwave” variable
 in our analyses. DTR of the source sites (3.7°C, 5.9°C, 9.1°C, and 10.7°C)
 was used as the numeric variable for historic thermal variability for all
 analyses. We assessed shifts in zooplankton community
 composition due to our treatments using permutational multivariate
 analysis of variance (PERMANOVA) based on Bray–Curtis dissimilarities
 using the “vegan” package (Dixon 2003). We used DTR × Experimental thermal
 history × Heatwave × Date as the model for our PERMANOVA analysis. We
 included date in the model to account for time. We used the vegan package
 to visualise compositional differences across treatments and time using
 non-metric multidimensional scaling (NMDS) based on Bray–Curtis
 dissimilarity and total abundances. We used the “lme4”
 package to create linear mixed-effects (LME) models to analyse the
 independent and interactive effects of heatwave, historic thermal
 variability (DTR), and experimental thermal variability, with date and
 mesocosm ID as random variables to account for repeat measures, on each
 response variable (Bates et al. 2015). Our response variables included
 Shannon diversity, total abundance, abundances of each taxonomic group,
 total biomass, and community-weighted mean (CWM) individual length. Total
 biomass and CWM length were calculated using published averages of weights
 and lengths of zooplankton (Dumont, Van de Velde, and Dumont 1975; Jones
 et al. 2020; McCauley et al. 1990). We did not measure individual
 zooplankton lengths or weights in this experiment, other than body lengths
 for metabolic rate calculations. While we acknowledge that body lengths in
 our experiment may have differed from literature values, and that this
 method does not include intraspecific variation in body size,
 interspecific variation in zooplankton body size is usually higher than
 intraspecific variation (Gao et al. 2019).
 <strong>CTmax and Metabolic Rate
 Analysis</strong> For both CTmax and metabolic
 rate analyses, we only used tanks that experienced heatwave A (n = 19) due
 to time constraints. Because of this, we were able to use pre- versus
 post-heatwave for the heatwave variable in our model rather than the
 variable we described for the community composition model. For our LME
 model, the fixed effects included heatwave, DTR, experimental thermal
 history, species, and the two- and three-way interactions among them. We
 used date as a random effect. We did not include the four-way interaction
 between the fixed effects to simplify interpretation.
description: # Investigating the Effects of Thermal Variability and Heatwaves on Pond
 Zooplankton Communities and Physiological Traits" Freshwater Biology.
 ### File: Heatwaves and Thermal Variability Code.R R script using the
 below data files to replicate analysis presented in Bonadonna et al.
 (2024) ### File: "Temp Variability Meso Data.csv" Fields: *
 Tank: factor denoting the unique identifier for experimental mesocosms *
 Date: date of sampling point in format Date-Month-Year * SampleTime:
 factor denoting the sampling time point (T1-T11) * Site: factor denoting
 which pond starting zooplankton community came from * Treatment: factor
 denoting whether tank was in heated (heat) or nonheated (nonheat)
 treatment; and low experimental thermal variability (ins) or high
 experimental thermal variability (nonins) treatment * Heated: factor
 denoting whether tank was in heated (heated) or nonheated (nonheated)
 treatment * Insulated: factor denoting whether tank was in low
 experimental thermal variability (ins) or high experimental thermal
 variability (nonins) treatment * Heatwave: factor denoting if tank was
 included in heatwave A or B, otherwise blank (nonheated) * HeatwaveA:
 factor denoting if tank was included in heatwave A (1) or not (0) *
 HeatwaveB: factor denoting if tank was included in heatwave B (1) or not
 (0) * postheat: factor denoting if sample was from a timepoint before tank
 was heated or never heated (0) or if sample was from a timepoint after
 tank was heated (1) * pH: numeric describing the pH of the tank at that
 sampling point * DO: numeric describing the DO% (dissolved oxygen percent)
 of the tank at that sampling point * sp.cond: numeric describing the
 specific conductivity (μS/cm) of the tank at that sampling point * TDS:
 numeric describing the total dissolved solids (mg/L) of the tank at that
 sampling point * chl.ysi: numeric describing the concentration of
 Chlorophyll-a (μg_L) of the tank at that sampling point, measured using a
 YSI probe * chl.rfu: numeric describing the concentration of Chlorophyll-a
 (raw fluorescence units) of the tank at that sampling point, measured
 using a fluorometer * chl.fluor: numeric describing the concentration of
 Chlorophyll-a (μg_L) of the tank at that sampling point, measured using a
 fluorometer * alo: numeric describing the number of *Alona spp.* per Liter
 * bos: numeric describing the number of *Bosmina spp.* per Liter *
 chironomid: numeric describing the number of chironomids per Liter * clat:
 numeric describing the number of *Ceriodaphnia laticaudata* per Liter *
 csp: numeric describing the number of *Chydorus sphaericus* per Liter *
 dbra: numeric describing the number of *Diaphanosoma brachyurum* per Liter
 * dden: numeric describing the number of *Daphnia dentifera* per Liter *
 eagi: numeric describing the number of *Eucyclops agilis* per Liter * ker:
 numeric describing the number of *Keratella spp.* per Liter * lec: numeric
 describing the number of *Lecane spp.* per Liter * lsign: numeric
 describing the number of *Leptodiaptomus signicauda* per Liter * mosquito:
 numeric describing the number of mosquitos per Liter * nau: numeric
 describing the number of nauplii per Liter * ost: numeric describing the
 number of ostracodas per Liter * plat: numeric describing the number of
 *Platyias spp.* per Liter * pped: numeric describing the number of
 *Polyphemus pediculus* per Liter * smuc: numeric describing the number of
 *Scapholeberis mucronata* per Liter * tri: numeric describing the number
 of *Trichocerca spp.* per Liter * total.norotifers: numeric describing the
 total number of zooplankton per Liter, excluding rotifers * total: numeric
 describing the total number of zooplankton per Liter * species: numeric
 describing the species richness * Cladocera: numeric describing the total
 number of cladocerans per Liter * copepoda: numeric describing the total
 number of copepods per Liter * rotifers: numeric describing the total
 number of rotifers per Liter * (species code).weight: numeric describing
 the estimated total weight (mg) of corresponding group (species code) per
 Liter * totalweight: numeric describing the estimated total weight
 (biomass; mg) of zooplankton per Liter * avgweight: numeric describing the
 estimated community-weighted mean individual weight (mg) of zooplankton
 per Liter * (species code).size: numeric describing the total estimated
 total body length (mm) of corresponding group (species code) * avgsize:
 numeric describing the estimated community-weighted mean individual
 zooplankton body length (mm) * postheatdays: numeric describing the number
 of days before or after the heatwave that the sample was taken *
 postheatdaysavg: numeric describing the number of days before or after the
 heatwave that the sample was taken, where non-heated tanks are averaged
 between the two heatwaves "NA" indicates where we do not have a
 value for a sample, while a "0" indicates that the value for
 that sample is zero. ### File: "ctmax\_all\_dat.csv" Fields: *
 TREAT_CODE: factor denoting if individual is from a tank that experienced
 heatwave A or B * Individual: factor denoting which test tube individual
 was in during CTmax trial * CTmax: numeric describing the temperature (C)
 that the individual became immobilized * TREATMENT: factor denoting the
 full treatment of the individual (source pond, ins/nonins - low/high
 experimental thermal variability, and heated/nonheated) * AQUARIA: factor
 denoting if individual was placed in aquarium 1 or 2 during CTmax trial *
 heatshocked: factor denoting if individual had experienced the heatwave
 (yes or no) * days_after_hw: numeric describing the number of days after
 heatwave that the CTmax trial was run (n/a if before heatwave) * Site:
 factor denoting which pond starting zooplankton community came from *
 Treat: factor denoting whether tank was in low experimental thermal
 variability (ins) or high experimental thermal variability (nonins)
 treatment * Species: factor denoting the species of the individual * Date:
 date of CTmax trial in format Date-Month-Year ### File:
 "metab\_dat" Fields: * Pop: factor denoting which pond starting
 zooplankton community came from * Treat: factor denoting whether tank was
 in low experimental thermal variability (ins) or high experimental thermal
 variability (nonins) treatment * Heated: factor denoting if individual had
 experienced the heatwave (yes or no) * DO_(ug/hr): numeric describing DO
 consumed by individual in μg/hr * DO_(ugO2/hr-1/ug): numeric describing
 mass-corrected DO consumed by individual in μgO2/hr-1/μg * Species: factor
 denoting the species of the individual * Order: factor denoting which
 placement in the metabolism trial array the individual was placed * Date:
 date of metabolism trial in format Date/Month/Year ### File:
 "full\_hobos.csv" Fields: * SampleNumber: numeric describing the
 number of sample taken by each temperature logger * Date_Time: date/time
 of temperature recorded in format Month/Date/Year Hour:Minute * Temp:
 numeric describing the temperature (C) recorded by temperature logger *
 Var: factor denoting whether tank was in low experimental thermal
 variability (ins) or high experimental thermal variability (nonins)
 treatment * Heat: factor denoting whether tank was in heated (heated) or
 nonheated (nonheated) treatment * Pond: factor denoting which pond
 starting zooplankton community in tank came from * Tank: factor denoting
 the unique identifier for experimental mesocosms * Heatwave: factor
 denoting if tank was included in heatwave A or B, otherwise blank (none) *
 Treatment: factor denoting combined treatment factors of "Var"
 and "Heat" * Day: date of sample in simplified format Month Date