DOI: 10.5061/dryad.0cfxpnw71
title: Compensatory growth partially mediates the effects of stressors associated with climate change on amphibian physiology

description: Human-induced climate change and urbanization are predicted to
 dramatically impact landscape hydrology, which can have devastating
 impacts on aquatic organisms. For amphibians that rely on aquatic
 environments to breed and develop, it is essential to understand how the
 larval environment impacts development, condition, and performance later
 in life. Two important predicted impacts of climate change and
 urbanization are reduced hydroperiod and increased larval density. Here we
 explored how larval density and hydroperiod affect development,
 morphology, physiology, and immunity at metamorphosis and 35 days post
 metamorphosis in the frog Rana pipiens. We found that high density had a
 large negative impact on development and morphology, which resulted in
 longer larval periods, reduced likelihood of metamorphosis, smaller size
 at metamorphosis, shorter femur-to-body length ratio, and reduced
 microbiome species evenness compared to animals that developed in
 low-density conditions. However, animals from the high-density larval
 conditions experienced compensatory growth post-metamorphosis,
 demonstrating accelerated growth in body size and relative femur length
 compared to animals from the low-density treatments. We also saw an
 increase in relative gut length and relative liver size in animals that
 had developed in the high-density treatment, as well as increased immune
 function, and greater jump distances relative to their leg length across
 different temperatures, which further supports post-metamorphic growth
 compensation following a stressful developmental period. Finally,
 metabolic rate was higher overall but especially at higher temperatures
 for animals that developed under high-density conditions. A higher
 metabolic rate at warmer temperatures might indicate a reduced ability to
 acclimate quickly to increasing environmental temperatures.
description: <em>Mesocosm design</em> The
 experiment took place at the Pymatuning Laboratory of Ecology in
 Linesville, Pennsylvania, United States. Sixteen large cattle tanks (770L,
 Rubbermaid, grey plastic) were cleaned with bleach and allowed to dry for
 24h, then filled to a depth of 41cm (600L) with well water 9 weeks prior
 to the start of the experiment. Lids for the mesocosms were constructed
 using 50% shade cloth and weighted tubing to ensure no insect predators or
 other amphibians could inhabit the mesocosms. Leaf litter was gathered
 from a nearby wooded area and dried, and 250g was added to each mesocosm 6
 weeks prior to the start of the experiment. Pond water (1L per mesocosm)
 with concentrated zooplankton caught with a zooplankton net was added to
 each mesocosm 7 weeks prior to the start of the experiment. Each mesocosm
 was fitted with two temperature loggers (HOBO temperature pendants, Onset
 etc.) set to record the water temperature every 30 minutes, with one 5cm
 above the bottom on the tank, and one 5cm below the water surface of each
 tank. One day before the start of the experiment we added 15g of rabbit
 chow, to provide supplementary food for the animals.
 Five egg masses were laid on June 10, 2017 from commercially
 purchased animals (Connecticut Supply) following hormonal injections of
 leuprolide acetate (Brannelly, Ohmer, & Richards-Zawacki, 2019).
 Eggs were allowed to develop and hatch. On June 15, 2017, day 0 of the
 experiment, tadpoles (stage 25, Gosner, 1960) were evenly sourced from
 these five egg masses and placed inside the mesocosms. Egg masses were
 produced by 12 captive adult <em>R. pipiens</em> housed
 communally for breeding purposes. These 12 adults were swabbed for skin
 microbiome of bacteria and fungi (rinsed with sterile artificial pond
 water, swabbed with a rayon-tipped swab, MS113, Medical and Wire Co.) on
 the first day of hormonal induction and one day after arrival to our
 facility. The swab samples were stored at -20°C until
 processing. The starting density for the high-density
 treatment was 0.12 tadpoles/L, and the starting density of the low-density
 treatment was 0.06 tadpoles/L. The larval developmental portion of the
 experiment ended on day 105. On this day the fast-drying regime was due to
 reach a water depth of 0cm, and the slow-drying treatment reached a depth
 of 17cm (approximately 249L). Before removing water on this final day we
 removed and euthanized (in 0.1% buffered tricaine methanesulfonate,
 MS-222, Sigma Aldrich) the remaining tadpoles (n=32 from the high-density,
 fast-drying treatment at an average tadpole density of 0.18 tadpoles/L and
 n=44 from the high-density slow-drying treatment at an average tadpole
 density of 0.04 tadpoles/L). All tadpoles in the low-density treatments
 metamorphosed and escaped the mesocosm before the end of the experiment
 (low-density fast-drying, day 63 and approximately 249L; low-density
 slow-drying, day 88 and approximately 352L). All animals that
 metamorphosed before the end of the experiment were included in the
 metamorphosis analyses (size at metamorphosis, rate of metamorphosis etc).
 Because the entire experiment ended 105 days after tadpoles entered the
 mesocosms, only animals that metamorphosed by day 70 were included in the
 survival analyses and juvenile condition analyses, so that we could ensure
 that these animals were at least 35 days old at the time of the
 assessments. The densities tested in this study are
 within the range of what *R. pipiens *experiences in the wild. Tadpole
 densities vary dramatically in the wild depending on pond type
 (low-density in permanent or semi-permanent ponds, to extremely
 high-density in drying ephemeral ponds). Of note, we have seen tadpoles at
 extremely high-density (hundreds of tadpoles in small ephemeral forest
 pools (estimated &lt;600 L; pers obs), and this is supported by the
 literature in nearby locations (average density of 0.05 tadpoles/L, with a
 maximum of 0.5 tadpoles/L; Smith et al., 2003). Therefore, the densities
 observed in this study are within the observed range for this species in
 this part of the world, and do not represent extreme densities.
 Additionally, the densities used in this experiment are slightly less
 dense but within the range other experiments that have used in mesocosm
 designes assessing the impacts of rearing density on this species (e.g.,
 low- to high-density of 0.07 - 0.2 tadpoles/L Dare et al., 2006; Distel
 & Boone, 2011). <em>Microbiome
 extraction</em> Skin swabs were extracted using
 the DNeasy 96 blood and tissue extraction (69581, Qiagen) with the
 following modifications during the lysis and incubation steps: 180μL of
 warmed lysozyme lysis buffer (20mg/mL, Lysozyme, 89833, ThermoFisher
 Scientific) was added to the samples and incubated at 37°C for 1hr. Then
 25μL of proteinase K plus 200μL of buffer AL was added and incubated at
 52°C for 30min. then 200μL of 100% ethanol was added, and the rest of the
 kit protocol was followed. We eluted the samples in 100μL of elution
 buffer after a 5 min incubation at room temperature for a final extract
 volume of 100uL. The extracts were frozen and stored until
 sequencing. Samples were PCR processed to amplify the
 v4 region (515f – 806r) of the 16S rRNA gene of bacteria and the ITS-1 and
 ITS-2 region of the fungal ITS gene following the Earth Microbiome
 protocol developed by Caporaso et al. (2012). Individual barcoded primers
 were used for PCR amplification (Parada et al., 2016) and the reaction
 mixture consisted of 11μL of PCR-grade water, 10μL of PCR master mix
 (5PRIME HotMasterMix) 1μL of forward and reverse primers and 2μL of DNA
 sample were added to the 16S PCR reactions. For ITS PCR, 10μL of PCR-grade
 water, 10μL of PCR master mix (5PRIME HotMasterMix), 1μL of forward and
 reverse primers, and 3μL of DNA template were added to each PCR reaction.
 16S thermocycler conditions consisted of 94°C for 3 minutes and then
 35-cycles of 94°C for 45 seconds, 50°C for 60 seconds, and 72°C for 90
 seconds, followed by 72°C for 10 minutes and then a 4°C hold. Fungal ITS
 conditions consisted of 94°C for 3 minutes, and then 35-cycles of 94°C for
 30 seconds, 52°C for 30 seconds, and 68°C for 30 seconds, followed by 68°C
 for 10 minutes and then a 4°C hold. All samples were run in duplicate.
 Duplicate reactions were then pooled and purified using the Thermo
 Scientific GeneJET PCR Purification Kit (K0702, Thomas Scientific).
 Finally, samples were analysed for DNA content using a Nanodrop and
 standardized to 50ng/μL. Sequencing was performed individually for the 16S
 and ITS libraries using a MiSeq Reagent Kit v2 (300-cycle) from
 Illumina. <em>Bacterial killing ability of the
 whole blood</em> The BKA assay was based on Liebl
 and Martin (2009) and modified from the protocol provided at www.ecoimmunology.org, which is funded by NSF-0947177), Savage et al. (2016), and Brannelly et al (2019). The test used 6µL of whole blood from each individual, and we used *Escherichia coli *in the killing assay. We activated one BactiDisk pellet (8739; ATCC®, Manassas, VA, USA) in 10mL phosphate-buffered saline (PBS) at 30˚C for 30 min then diluted the sample to 5 x 104 bacteria per mL and immediately refrigerated it. We vortexed whole blood for 10 sec and added 3µL to 69µL of a solution sterile CO2-independent media (ThermoFisher, Waltham, MA, USA) containing 4mM L-glutamine (ThermoFisher, Waltham, MA, USA) broth. A second tube of blood and CO2-independent media was prepared for each sample as a sample blank. We added 25µL of *E. coli *to each sample, and 25µL of sterile PBS to each sample blank, incubated the samples for 1h at 21˚C, and then added 500µL of sterile tryptic soy broth (TSB; SigmaAldrich, St. Louis, MO, USA) to each sample. We prepared three positive controls and control blanks for each plate, with positive controls containing 500µL of TSB broth, 25µL *E. coli, *and 72µL PBS and blanks containing 500µL of TSB broth and 92µL of sterile PBS. All samples were then vortexed and incubated at 30˚C for 12h (Savage *et al., *2016). We ran each sample, sample blank, control and control blank in triplicate at a 100µL volume and measured absorbance at 405 nm (using an Epoch BioTek plate reader, Winooski, VT, USA) in a 96 well sterile cell culture plate (Costar® Corning Inc., Corning, NY, USA). We adjusted for plate inconstancies (delta=405nm absorbance reading - 560nm absorbance reading) and calculated BKA index (Allen et al., 2009): This index assigns large positive numbers to animals that had high bacterial killing ability (i.e., where many bacteria were killed) and low or negative values when there was little bacterial killing ability within the blood. This index also accounts for bacterial die-off or plate inconsistencies within the assay that is unrelated to the blood’s bactericidal ability (Allen et al., 2009). Individual reaction wells with extreme outliers were removed from the analysis (n=2 reaction wells) if the BKA index value exceeded three standard deviations from the mean. Although two reaction wells were excluded from analyses because they were extreme outliers, all animals (n=137) were included in the analysis. <em>Jumping performance</em> Each animal was tested at all six temperatures over 3–4 days (n=156). We strategically chose five different temperature orders to sequentially test the animals. The temperature orders (in ºC) were A) 20, 15, 10, 30, 25, 5, 20, B) 15, 20, 25, 30, 5, 10, 15 C) 5, 15, 20, 25, 30, 10, 5, D) 10, 15, 20, 5, 25, 30, 10, E) 20, 25, 15, 10, 30, 5, 20. We randomly placed the animals in those these temperature groups, and these temperature orders were included as a covariate in the analysis. Each frog was tested seven times total, where the first temperature was repeated at the end of the temperature regime to ensure animals were not fatigued. This jump trial number (1–7) was included as a covariate in the analysis. Animals were included in the analysis if the mean jump distance was at least 70% of the mean jump distance of the first jump temperature (excluded n=60 animals). For each jumping trial, we removed the animals from the chambers and encouraged them to jump by lightly touching the urostyle up to five times. The first three successful jumps per temperature recorded. Trials in which a frog did not jump successfully at the first or second encouragement were not included in the analysis for that jump temperature, nor were those that successfully jumped only once for that jump temperature (n=96 used in final analysis). Body temperature was recorded using an infrared temperature gun just prior to each jump attempt, and this temperature was used in the analysis. The start and end position of the first jump an animal made from rest was marked and measured to the nearest 1mm. <em>Metabolic rate</em> Prior to the metabolic rate trials we fasted the animals for 5 days before testing. We calculated rate of oxygen consumption using the equation (Vleck, 1987): where VO2=rate of oxygen consumption, and V=Volume of air in the chamber (calculated as V=Vchamber – Vpaper towel – Vanimal). We measured mass of the animal and paper towel subtracted and calculated the volume of each (assuming 0.001 L/g density). Fi is the initial dry O2 fractional reading (i.e., the machine output) and Fe is end dry O2 fractional reading. VH2O is the change in the fractional water vapor concentration and assumed to be equal to 0 because the champer it is constant and saturated (damp paper towel was used as substrate). <em>Microbiome analysis</em> Raw 16S bacterial sequence data were processed through the QIIME2 pipeline version 2018.4 (Bolyen et al., 2018). Sequences were demultiplexed following the DADA2 pipeline within QIIME2, the sequence (McDonald et al., 2012) reads were filtered, processed and assigned to operational taxonomic features (OTFs). Singleton observable taxonomic features were removed, and a phylogenetic tree using FASTTREE (Prince et al., 2010) was built and taxonomy was classified using the q2-feature-classifier (Bokulich et al., 2018) classify-sklearn naïve Bayes taxonomy classifier against Greengenes reference sequences (McDonald et al., 2012), and sequences identified as chloroplasts or mitochondria were removed from downstream analysis. Observable taxonomic features tables were rarefied to 10,000 reads. 71 individual samples were processed and sequenced, and 8 samples were not included after rarefication due to low observable taxonomic features reads; therefore 63 samples were analysed in downstream analyses. A further two metamorph samples were removed due to missing metadata, for a total of 11 adults and 50 metamorph samples. Alpha diversity metrics were used to measure the bacterial community diversity within each rarefied sample. Alpha diversity measures were calculated within QIIME2: the number of observable taxonomic features (qualitative measure of richness), Shannon diversity (quantitative measure of community richness), and Pielou’s evenness (a measure of community evenness). Beta diversity metric outputs from QIIME2 to compare bacterial community composition were weighted UniFrac distances (community structure, which compares samples on the basis of presence, absence and relative abundance of bacterial taxonomic features), and unweighted UniFrac distances (community membership, which compares samples on the basis of presence and absence of bacterial observable taxonomic features). The raw ITS fungal sequence was processed through a similar QIIME2 pipeline, where the taxonomy classifier was built against UNITE reference sequences (Abarenkov et al., 2020). Observable taxonomic features tables were rarefied to 600 reads. Ten samples were not included after rarefication because of low observable taxonomic features reads, and one sample was not included due to missing metadata; therefore, 52 metamorphs and 9 adults were analysed.
description: # Compensatory growth partially mediates the effects of stressors
 associated with climate change on amphibian physiology
 [https://doi.org/10.5061/dryad.0cfxpnw71](https://doi.org/10.5061/dryad.0cfxpnw71) ## Description of the data and file structure #### Survival and larval period of the tadpoles across treatments ***larval period data file:*** the number of days that each animal spent inside each mesocosm, to analyse the length of the larval period and how it is affected by the different density and drying treatments. This dataframe also includes survival within the mesocosms and after they emerged from the mesocosm. And the dataset includes morphological measurements like leg length, femur length, mass and snout to venter length.  This dataframe contains all the metadata for all the individual animals within this study, therefore this represent the metadata included in many of the other dataframes uploaded in this study. Because it includes the morphological data collected throughout the study, this dataframe has been subset and used to assess morphological changes within the frogs overtime after metamorphosis. The whole dataset was used to analyse larval period, as well as proportion emergence from the mesocosms. A subset of the data was used to analyses survival after metamorphosis. Explanation of the data columns: "Larval period" is the number of days before full tail absorbtion. "Days btw" is the number of days between removal from mesocosm and full tail absorption. "Days survived" is the number of days alive after metamorphosis. "Days survived total" is the larval period + days survived. "survival status" is where 0 is the animal remained alive for the duration of the experiment and 1 is the animal died. "Survival subset" is a column used to subset the data for survival analysis if the animal survived 35 days post metamorphosis, where 1 is the animal survived. "Died before emregence" is a 1 when the animal died before it emerged from the mesocosm, and a 0 is it emerged. "Emerged" is where 1 means the animal emerged from the mesocosm and 0 is it did not. SVL and mass was taken at metamorphosis (e.g., Mass at meta), SLV, mass and femur length were taken at week 1 after metamorphosis (e.g. Mass Wk1), and mass, SVL, femur and leg length were taken at test week (e.g., Mass test week). "Femur ratio" is the femur to SVL ratio at the week it was measured (wk 1 or test week). "F LL ratio" is the femur to leg length ratio at test week. "change m 1" is the change in mass between metamorphosis and week 1, "change m 2" is the change in mass between metamorphosis and test week (the same pattern for "change svl 1" and "change svl 2"). "change femur" is the change in femur size from week 1 to test week. "Change in F SVL" is the change in ratio of femur to SVL from week 1 to test week.  We log transformed the measurements (log base 10) (e.g. logmass w1 - to mean log10mass at week 1 after metamorphosis). cells with NA indicate no data, here and throughout the other dataframes. #### Skin microbiome datasets used for analysis after raw data processing using a Qiime2 pipline: ##### 1) comparing the microbiome among the parents and the offspring ***16S alpha diversity adult offspring data file***: used to compare the alpha diversity of 16S sequencing of the bacterial communities on the skin of the adults (parents) and offspring ***16S beta diversity adult offspring data file:*** used to compare the beta diversity of 16S sequencing of the bacterial communities on the skin of the adults (parents) and offspring ***ITS alpha diversity adult offspring data file:*** used to compare the alpha diversity of ITS sequencing of the fungal communities on the skin of the adults (parents) and offspring ***ITS beta diversity adult offspring data file:*** used to compare the beta diversity of ITS sequencing of the fungal communities on the skin of the adults (parents) and offspring ##### 2) comparing the microbiome of the newly metamorphosed animals across the drying and density treatments ***16S alpha diversity data file***: used to compare the alpha diversity of 16S sequencing of the bacterial communities on the skin of the newly metamorphosed animals across drying and density treatments ***16S beta diversity data file:*** used to compare the beta diversity of 16S sequencing of the bacterial communities on the skin of the newly metamorphosed animals across drying and density treatments ***ITS alpha diversity data file:*** used to compare the alpha diversity of ITS sequencing of the fungal communities on the skin of the newly metamorphosed animals across drying and density treatments ***ITS beta diversity data file:*** used to compare the beta diversity of ITS sequencing of the fungal communities on the skin of the newly metamorphosed animals across drying and density treatments Explanation of the data columns: For both 1 and 2 microbiome datasets (the 8 listed above), the metadata for the individuals is from the larval period data frame describe above. "BarcodeSequence" and "LinkerPrimerSequence" collumns were used during sequencing to identify each individual sample. "Well" is the well on the extraction plate. Alpha and beta diveristy measures analysed for these datasets are those listed in the dataframe.  #### Immune function analysis ***BKA data file:*** used to compare the the bacterial killing ability of the whole blood of a subset of animals across drying and density treatments 5-6 weeks post metamorphosis.  Explanation of the data columns: the metadata for the individuals is from the larval period data frame describe above. "Group" indicates which group was being tested during the test week. "Plate" is the plate ID used per group to assess BKA on the spectrophotometer. "BKA index" was calculated via other collumns in the dataframe following the equation listed in the methods section of this manuscript.  #### Morphological data ***liver gut data file:*** the morphological measurements of the liver (g) and the gut (mm) of a subset of animals across drying and density treatments post metamorphosis Explanation of the data columns: the metadata for the individuals is from the larval period data frame describe above. The mass of the liver was measured and listed in "Liver mass", and the length of the gut and hind gut were measured. "Liver per size" is the index of liver mass / frog mass. "Gut by SVL" is the index of gut length / SVL of the frog at test week. "Hindgut by SVL" is the index of hindgut length / SVL of the frog at test week. "Prop hindgut to gut" is the ratio of hindgut to gut length. "logliver" is the log transformed mass (base 10) of the liver mass.  #### Physiological analysis ***Jump data file:*** the length of the first jump of a subset of animals of animals across drying and density treatments post metamorphosis. Jump distances were measures at 7 different temperatures per animal.  Explanation of the data columns: the metadata for the individuals is from the larval period data frame describe above. "Temp group" is the group of animals that were tested together on the same test week. "Temp order" was the order of temperatures predetermined and listed in the methodological section of the manuscript. "Chamber temperature" is the temperature that the chamber was set at for the jump. "Chamber" is A-D to indicate which of the 4 chambers the animals were placed in. "Jump number" was the order of the 7 jumps that each animal was tested. "Temp" was the temperature of the frog at the time of the jump. "Jump distance" was the jump distance for the individual animal.  "n jumps" that the number of jumps that the animal successfully completed for that test. ***Metabolic Rate data file:*** the oxygen consumption data of a subset of animals of animals across drying and density treatments post metamorphosis. The oxygen consumed was measured after 1 hr. Animals were analysed only once, and were assessed across temperatures.  Explanation of the data columns: the metadata for the individuals is from the larval period data frame describe above. "Temp" is the temperature that the animal was measured fot metabolic rate at. "O2.Start" is the O2 reading in the first syringe before the luer locks were closed.  "O2.End" is the O2 reading at then endo of the 1hr trial. "Chamber volume" is the volume of the chamber minuse the volume of the frog and the volume of the paper towel substrate. "VO2" is the volume of oxygen. "VO2.correct" is the VO2 corrected for by the calculated presented in supplemetal methodology. "Vo2.ulO2.g.h" is the metabolic rate as used in the analyses which was calculated by the other collumns using the equation presented within the supplemental methodology.  Missing data: NA