MARINE ECOLOGY PROGRESS SERIESMar Ecol Prog Ser

Vol. 495: 263–274, 2014doi: 10.3354/meps10552

Published January 9

INTRODUCTION

As a consequence of climate change, average seasurface temperatures (SSTs) have increased approxi-mately 0.7°C over the past 100 yr, and, according tothe Intergovernmental Panel on Climate Change(IPCC 2007), they are expected to increase another1.5 to 3°C by the end of the 21st century. Obviously,this change will have impacts on marine species.Populations of many species will likely persist under

sub optimal conditions, and to avoid extinction willhave to cope with higher temperatures via plasticand/or evolutionary changes (reviewed by Hoffmann& Sgro 2011). Phenotypic plasticity occurs when thesame genotype produces multiple phenotypes underdifferent environmental conditions (Pigliucci 2005),and the function that describes the variation in thepheno typic response is termed a reaction norm(West-Eberhard 2003). An example is the thermalreaction norms that have likely evolved to maximize

© Inter-Research 2014 · www.int-res.com*Corresponding author: bsantos@mun.ca

Sperm plasticity to seawater temperatures in Atlanticcod Gadus morhua is affected more by population

origin than individual environmental exposure

J. Beirão1,2,*, C. F. Purchase1,2, B. F. Wringe1,2,3, I. A. Fleming1,3

1Fish Evolutionary Ecology Research Group, Memorial University of Newfoundland, St. John’s, Newfoundland and Labrador A1C 5S7, Canada

2Department of Biology, Memorial University of Newfoundland, St. John’s, Newfoundland and Labrador A1B 3X9, Canada3Department of Ocean Sciences, Ocean Sciences Centre, Memorial University of Newfoundland, St. John’s,

Newfoundland and Labrador A1C 5S7, Canada

ABSTRACT: Atlantic cod is a key species of the North Atlantic ecosystem whose distribution willlikely be affected by climate change. Although general temperature effects on reproduction areknown, there is a dearth of information on population and individual level life history and repro-ductive plasticity responses to temperature change. We tested the hypothesis that the sperm ofAtlantic cod of different genetic backgrounds (southern versus more northerly Newfoundland andLabrador) and of different environmental histories (reared in indoor tanks and fed a forage dietversus reared in sea cages and fed pellets) have different average plastic responses to tempera-ture. Male reproductive performance was examined at 4 temperatures by measuring sperm swim-ming characteristics at 10 and 30 s after motility activation. Genetic origin had a larger effect onsperm swimming characteristics than past environmental history. Moreover, groups derived fromthe southern population exhibited a more pronounced positive mean reaction norm than thegroup derived from the Newfoundland and Labrador population. This represents an example ofcogradient variation as genotypes accentuate the thermal phenotypic plasticity. Even thoughthere were differences between the groups in sperm swimming characteristics, this is unlikely sufficient to affect successful reproduction at the temperatures tested unless under sperm compe-tition. Thus, sperm performance should not be a limiting factor for reproduction under predictedincreases in sea surface temperatures.

KEY WORDS: Climate change · Sperm swimming · Seawater temperature · Thermal reactionnorms · Local adaption · Environmental history · Phenotypic plasticity · Cogradient variation

Resale or republication not permitted without written consent of the publisher

Mar Ecol Prog Ser 495: 263–274, 2014

fitness under past climate conditions (Baumann &Conover 2011, Munday et al. 2012).

The extent of the impact of increased SSTs willvary among fish species through several factors,including physiological tolerance or capacity foracclimation and adaptation (Pankhurst & Munday2011). As explained by these same authors, whiletemperature is determinant throughout the life cycleof an individual, it is determinant in the regulation ofthe entire reproductive process, affecting everythingfrom early gametogenesis to larval hatching andjuvenile growth and survival (e.g. Harrald et al.2010, Wang et al. 2010). Thus, to be able to predictthe effects of climate change on fish populations, itis important to examine reproductive performanceunder future temperature scenarios. Nonetheless,these issues are just beginning to be understood (e.g.Donelson et al. 2010, reviewed by Pankhurst & Mun-day 2011). One of the aspects affecting male repro-duction is sperm motility and swimming characteris-tics. Following ejaculation, such characteristics areimportant in determining fertilization success (Cos-son et al. 2008) and are affected by environmentalparameters such as temperature (reviewed by Alavi& Cosson 2005). Usually, an increase in the tempera-ture of the activation solution leads to an increase insperm velocity, which is caused by increased flagel-lar beating and higher ATP consumption that sub -sequently results in a decrease in sperm longevity(Alavi & Cosson 2005, Cosson 2010).

In the present study, we used sperm swimmingcharacteristics to analyze male reproductive plastic-ity in response to expected increases in ocean tem-peratures in different populations of Atlantic codGadus morhua. As suggested by Purchase and col-leagues (Purchase et al. 2010, Purchase & Moreau2012), sperm swimming may be used to examinereproductive thermal plasticity in male fish withexternal fertilization because (1) a single ejaculatecontains billions of cells with similar genetic back-ground that can be divided and exposed to differentconditions, (2) sperm swimming characteristics arecorrelated with fertilization success in several spe-cies (e.g. Atlantic cod; Skjæraasen et al. 2009, Buttset al. 2011) and (3) there are tools available, such ascomputer assisted sperm analysis (CASA) systemsthat allow for the precise measurement of spermswimming characteristics, making detection of plas-ticity possible. Atlantic cod was chosen as our studyspecies for several reasons. First, it is a eurythermalspecies, occupying a wide range of temperaturesfrom −1.5 to 19°C, but this narrows to 1−8°C duringthe spawning season (Righton et al. 2010), making it

a prime candidate to express thermal plasticity. Second, it is a key species of the North Atlantic eco -system, both ecologically and economically (Miesz -kowska et al. 2009), whose distribution is expected tobe affected by increasing SST driven by climatechange (Drinkwater 2005). Third, distinct popula-tions show multi-gene patterns of temperature-related variation indicative of adaptation to localthermal regimes (Bradbury et al. 2010, Behrens et al.2012). Fourth, several studies suggest potential tem-perature effects on cod reproductive performance(Kjesbu et al. 2010, Morgan et al. 2010, Purchase etal. 2010). Fifth, Atlantic cod sperm biology has beenwell researched, providing a good basis by which todesign experiments to test for thermal responses(Trippel & Morgan 1994a, Skjæraasen et al. 2009,Butts et al. 2010, Purchase et al. 2010). Finally, spermperformance plasticity to environmental conditionsmay be highly variable among individual males (Pur-chase & Moreau 2012), including Atlantic cod, asPurchase et al. (2010) found great inter-individualvariability in cod sperm phenotypic plasticity to tem-perature, both in terms of velocity and longevity.However, the fish in their study all originated fromthe same area (Bay of Fundy, New Brunswick,Canada) and, thus, population differences remainunknown.

We focused our attention on 2 evolutionary distinctnorthwest Atlantic cod designatable units (DU) asidentified by the Committee on the Status of Endan-gered Wildlife in Canada (COSEWIC 2010); thesouthern population and the Newfoundland andLabrador population. For these populations, Drink -water (2005) predicted that an increase in SST above3°C would cause the southern cod to decrease or collapse and the Newfoundland and Labrador cod toincrease in abundance. A large thermal gradient ex-ists between these 2 areas (Brander 1994) and Brad-bury et al. (2010) showed that cod from the southernpopulation have mostly ‘warmer’ tempe rature-associated SNPs (single nucleotide polymorphisms),while cod from the Newfoundland and Labrador pop-ulation have mostly ‘cold’ alleles. These polymor-phisms may be partly responsible for the differencesin several phenotypic traits, such as growth (Purchase& Brown 2000, 2001, Salvanes et al. 2004, Harrald etal. 2010), juvenile food conversion efficiency (Pur-chase & Brown 2000), morphology and allometry(Marcil et al. 2006) and metabolic plasticity to tem-perature (Grabowski et al. 2009), among Atlantic codpopulations. Some of these pheno typic changes areconsidered an example of countergradient variation(CnGV), which occurs when genotypes oppose envi-

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ronmental influences, leading to reduced phenotypicvariation along a gradient (as reviewed by Conover etal. 2009). Purchase & Brown (2000), for example,showed that for the same temperature Atlantic codlarvae from a more northerly population had highergrowth rates than those from a more southerly popu-lation. Less common are patterns of cogradient varia-tion (CoGV) that occur when genotype influences ac-centuate environmental plasticity (Conover et al.2009). Using captive wild fish, Harrald et al. (2010)found such a pattern in growth rates of 2 groups ofcod from Scotland. Nonetheless,these studies disregard the pos-sible effect that an individual’senvironmental history can haveon its phenotypic traits, includingthose in volved with reproductiveperformance. Instead, most stud-ies try to control for previous environmental history by eitherusing the F1 generation of cul-tured fish (e.g. Grabowski et al.2009) or allowing individuals toacclimate to a common gardenenvironment (e.g. Harrald et al.2010). In the second case, theremay be lingering effects of dif-ferent environmental historiesprior to introduction to the com-mon garden and the degree towhich this will affect the plasticresponse and hide genotypic dif-ferences is unknown.

To address some of these outstanding uncertainties, wetested the hypothesis thatAtlantic cod of differing genetic

backgrounds (F1 individuals bred from wild fish ofdifferent populations) and of differing environmentalhistories have different average plastic responses totemperature in terms of sperm swimming character-istics. As both factors were expected to have someeffect, we were most interested in resolving their rel-ative importance. Broadly, we were also interested incontributing to knowledge of the effects of increasingocean water temperatures on the reproductive per-formance of high latitude fish and how this may varyamong populations.

MATERIALS AND METHODS

Fish origin and stocking conditions

Three groups of male Atlantic cod differing ineither environmental history (i.e. rearing conditions)or genotype were used in this experiment (Fig. 1).The genetic background of the populations is de -scribed in the COSEWIC report on the Atlantic Cod(COSEWIC 2010). The Newfoundland and Labradorgroup were spawned in 2008 from fish captured inSmith Sound, in Trinity Bay, Newfoundland (Fig. 2)(Northwest Atlantic Fishery Organization [NAFO]division 3L). In 2009, these were placed in sea cages

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Fig. 1. Schematic representation of the Atlantic cod groups’genetic background and environmental history. Below eachgroup name is the number of males that contributed sperm

samples (n)

Fig. 2. Sampling location of the wild parents and grandparents of the culturedAtlantic cod used in the 3 groups. NAFO (Northwest Atlantic Fisheries Organization)divisions and location of the sea cages and the Ocean Science Center (indoor tanks)

Mar Ecol Prog Ser 495: 263–274, 2014

in Fortune Bay, Newfoundland (Fig. 2), and fed commercial feed pellets (hereafter referred to as N-Cage). The second group were southern populationcod, spawned in 2009 from sets of parents and grand-parents captured in the Gulf of Maine (Fig. 2) (NAFOdivisions 4X, 5Ze and 5Y); and in 2010 placed incages directly adjacent to those of the N-Cage fishand fed the same food (hereafter referred to as S-Cage). The third group originated from the samesouthern population broodstock and spawning, butwere raised in indoor aquaculture flow-throughtanks at Memorial University of Newfoundland’sOcean Science Centre (OSC; 47°63’ N, 52° 66’ W) andfed a forage diet (herring Clupea harengus, mackerelScomber scombrus and squid Illex spp.) (hereafterreferred to as S-Tank). For additional information onthe groups see Table 1.

In order to avoid any influence of environmentalconditions during the final stages of gonadal de -velopment, and only test for the separate effects ofpopulation and previous environmental histories, the following conditions were created: 4 mo before thestart of the sperm experiment, the 2 groups raised inoutdoor cages were brought to the OSC and placedtogether with the S-Tank group in a 25.5 m3 roundtank under the same conditions. In total, the tankcontained 171 fish (see Table 1 for the number of fishof each group), in a sex ratio of 1.3:1 (male: female).The fish were fed a forage diet (herring, mackereland squid). The tank was provided with constantaera tion and water exchange of 27% h−1, and thetemperature was maintained at a constant (±SEM)5.3 ± 0.1°C. Rearing and experimentation at the OSCwere conducted in accordance to protocol 12-09-IFapproved by the Memorial University Animal CareCommittee following the regulations of the CanadianCouncil on Animal Care for the treatment and wel-fare of animals.

Semen sampling

Semen samples were collected from each group(n = 18 for N-Cage, n = 9 for S-Cage and n = 18 forS-Tank) during their spawning seasons (S groupsamples were obtained from mid-March to earlyApril and N-Cage group samples from mid-April toearly May 2012). We only collected samples duringthe groups’ peak reproductive period to minimizeeffects related to seasonal variability during thespawning season (see e.g. Butts et al. 2010). When-ever possible, 2 semen samples were collected atleast 1 wk apart for each male to further control for

seasonal variability in sperm quality. The urogenitalpapilla was carefully cleaned and dried and semencollected with the help of a syringe after applyingslight pressure on the abdomen. The first 1 ml ofsemen was discarded to help avoid seawater, urineand feces contamination. Samples were kept in 2 mlsyringes at 3 to 6°C and covered with parafilm untilarrival at the lab (

Beirão et al.: Sperm plasticity to seawater temperatures

tion and immediately covering the slide with a cover-slip. Video was acquired with a Prosilica GE680 mono -chrome camera (Allied Vision Technologies) attachedto an inverted Leica microscope DM IL LED (Leicamicrosystems) using a 20× phase-contrast lens andrecorded from 10 to 31 s after motility activationusing Prostream software (http://prostream. southernvisionsystems.com/) at 100 frames per second (fps).

Videos were analyzed for sperm swimming charac-teristics at 10 and 30 s post-activation with the openCASA software developed by Wilson-Leedy & Inger-mann (2007) and modified by Purchase & Earle(2012). Input parameters (see Table A1 in the Appen-dix) were chosen so that the software could differen-tiate drifting from motile sperm. Because we wereinterested in the temperature effect on overall spermmotility, we were more liberal than some other stud-ies when choosing the parameters by which to con-sider a sperm motile. For example, we used minimumVSL (defined below) of 1 µm s−1 rather than 4 µm s−1

as used by Tuset et al. (2008), although our approachgenerally follows that of Purchase et al. (2010), usingdifferent software. The entire process was repeated3 times for every semen sample at each tempera-ture. Based on their biological meaning and accuracy(Wilson-Leedy & Ingermann 2007), the followingparameters obtained with the CASA plugin werecompared among groups of fish: VCL (curvi linearvelocity, velocity according to the actual path; µms−1), VSL (straight line velocity, velocity according tothe straight path, i.e. displacement; µm s−1), VAP(velocity according to the smoothed path; µm s−1),LIN (linearity; % calculated from VSL/VAP), andWOB (wobble; % calculated from VAP/VCL). Ofnote, high WOB values from this software should beinterpreted as having relatively low side to sidemotion.

Data analysis

All statistical analyses were conducted using R2.15.1 (R De velopment Core Team 2012) and the Rpackage agricolae (de Mendiburu 2012). A total of936 video records were analyzed (45 males × 1−2sperm samples per male × 4 temperatures × 3 repli-cates), giving data on a total of 95584 motile sperma-tozoa. Results of the 3 replicates per semen samplewere averaged and semen samples from the samemale taken on different days were averaged and thisvalue used in the statistical model. Using the individ-ual reaction norms from each fish, we calculated thecoefficient of variation (CV) of the CASA parameters

for the 3 groups. In addition to the parametersobtained with CASA, we also performed a clusteranalysis to group sperm cells across all treatmentsand males with similar swimming features, using theK-means algorithm. We decided to use 4 clustersafter analyzing a plot of within groups sum of squaresby the number of clusters. Of the 4 clusters, the slow-est sperm represent the first cluster, with mean VCLof 67.69 µm s−1 and WOB 37%, and the fastest spermwith ‘straighter’ movement were gathered in thefourth cluster, with a mean VCL of 151.28 µm s−1 andWOB 80% (Table 2). VCL (Skjæraasen et al. 2009)and the percentage of progressive sperm (Rudolfsenet al. 2008), closely related to WOB, are the parame-ters that better correlate with fertilization in Atlanticcod, and thus we focused on this fourth cluster foranalysis of the different treatments (hereafter re -ferred to as the high quality cluster).

We also performed a principal component analysisto help identify patterns of variation using all of theCASA parameters. The principal components werecalculated from the correlation matrix. Based on theexplained variance, we focused on the first 2 compo-nents. The first (PC1) explained 69% of the variationand described the velocity parameters (VAP, VCLand VSL), while PC2 explained 20% of the variationand was related to LIN (see Table A2 in the Appen-dix).

Differences between the groups for the differentvariables were analyzed with a mixed-model nestedANOVA considering the different temperatures asrepeated measures on a given male. Both tempera-ture and group were considered fixed factors, whilemale was considered random and nested withingroup. Except for PC2 at 30 s post-activation, all theother dependent variables had a significant inter -action between group and temperature. Thus, to fur-ther examine this, the ANOVA models were simpli-

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Cluster VCL VAP VSL LIN WOB (µm s−1) (µm s−1) (µm s−1) % %

1 67.69 23.85 21.36 87 372 137.04 89.58 81.45 91 673 111.07 58.15 53.70 92 544 151.28 119.66 112.09 94 80

Table 2. Description of the 4 clusters obtained in this study.Each cluster is described by the mean values for the 5 CASAsoftware parameters used in the analysis: VCL (curvilinearvelocity), VSL (straight line velocity), VAP (velocity ac -cording to the smoothed path), WOB (wobble) and LIN (lin -earity). The 4th cluster (in bold) was considered the high

quality cluster

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fied by creating one for each tested temperature andTukey’s Honestly Significant Difference (HSD) wasapplied for multiple comparisons. Differences wereconsidered significant at p < 0.05. Percentile datawas normalized through arcsine square root transfor-mation. Numeric results are expressed as arithmeticmeans ± standard error of the mean (SEM).

RESULTS

Average phenotypic plasticity of sperm swimmingcharacteristics to the tested temperatures differedamong the 3 groups and among males within thesame group. In general, the N-Cage males had thelowest reaction norms for the tested temperatures for

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Temperature (°C)

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Fig. 3. Individual thermal reaction norms in terms of VAP (velocity according to the smooth path), VCL (curvilinear velocity),VSL (straight line velocity), WOB (wobble) and LIN (linearity) at 10 s after motility activation for the 3 different groups

(S-Tank, S-Cage and N-Cage; see Fig. 1)

Beirão et al.: Sperm plasticity to seawater temperatures

sperm velocities, VAP, VCL and VSL (Fig. 3). Fur-thermore, this group had the highest CV among indi-viduals (except for LIN) (Table 3).

The ANOVA procedure for the high quality clusterdetected a significant interaction between tempera-ture and group at 10 s and 30 s after sperm motilityactivation (Table 4). Thus, the main effects were notinterpreted and separate ANOVAs at each tempera-ture were conducted. At 10 s, significant group ef -fects were detected at each temperature (for 3, 6, 9and 12°C, F2,44 ≥ 8.019, p ≤ 0.001) and the same hap-pened at 30 s (for 3, 6, 9 and 12°C, F2,44 ≥ 7.719, p ≤0.001). At both times, N-Cage males had a lower per-centage of spermatozoa in the high quality cluster

than both S groups, which did not dif-fer (Fig. 4). Pheno typic plasticity inthe percentage of spermatozoa in thehigh quality cluster is also evident aspercentages increase with increasingtemperature for all groups (Fig. 4).Nonetheless, both S groups appearedto show greater plasticity to tempera-ture than the N-Cage males.

For the principal component analy-sis, we also found a significant inter-action between temperature andgroup for both PC1 and PC2 at 10 s,but only for PC1 at 30 s (Table 5). PC1describes sperm velocity and sepa-

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Source Term df Error –—— 10 s —— ——– 30 s —— F p F p

1 Group 2 2 10.770

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rate ANOVAs conducted at each temperatureshowed consistent significant differences in scoresbetween groups at both 10 s (for 3, 6, 9 and 12°C,F2,44 ≥ 7.612, p ≤ 0.001) and 30 s (for 3, 6, 9 and 12°C,F2,44 ≥ 5.125, p ≤ 0.009), with the N-Cage group dif-fering from the 2 S groups, which did not differ fromeach other (Figs. 5 & 6). This indicates that this para-meter was affected by group genotype but not byenvironmental history. On the other hand, for PC2,which mainly describes LIN and accounts for only20% of the variability, the differences occurredbetween the S-Tank group and one or both of theCage groups (F2,44 ≥ 7.417, p ≤ 0.002 for 3, 6, 9 and

12°C; Figs. 5 & 6). The exception was at 10 s and 3°Cwhere there was no significant difference amonggroups (F2,44 = 0.810, p = 0.451). Finally, there wereno overall significant differences between 10 and30 s (p > 0.05, results not shown).

DISCUSSION

Several studies have shown that temperature playsa crucial role in fish reproductive biology (Donelsonet al. 2010, Morgan et al. 2010, Pankhurst & Munday2011), including sperm physiology (reviewed by

Alavi & Cosson 2005). However, the wayin which an individual’s environmentalhistory and genetic background shapethe effect of temperature on reproduc-tive performance has remained unclear.In the present work, our focus on popu-lation-level, in addition to individual-level temperature effects (cf. Pigliucci2005) has shown that phenotypic plas-ticity in sperm swimming characteristicsto different temperatures (i.e. meanthermal reaction norm) was driven moreby genetic background than by environ-mental history. While the mean re actionnorm for the percentage of spermatozoain the high quality cluster was similar forthe groups sharing a common geneticback ground (i.e. southern groups) atboth 10 and 30 s post-activation, it dif-fered for the groups sharing a commonenvironmental history (i.e. the sea-cagegroups) but different genetic back-ground at both times. A similar patternwas observed for PC1, which accountedfor 69% of the data variability. Only forPC2, which accounted for 20% of the

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Source Term df Error —–—————–— 10 s —–————— —————–—— 30 s —–———————–— PC1 —–— ——– PC2 —–— ——– PC1 ——– ——– PC2 ——–

F p F p F p F p

1 Group 2 2 12.070

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variability, were the scores similar between groupssharing a common environmental history and differ-ent for groups of a common genetic background (ex-ception being 10 s at 3°C). Thus, plasticity in spermswimming was more affected by the origin of thesperm donor’s parents — population genetic back-ground — than by their environmental history. Fur-thermore, there was a significant interaction betweengroup and temperature for the proportion of sperma-tozoa in the high quality cluster, meaning that differ-ences between groups were variable according to thetemperature. Even so, groups whose parents origi-nated from historically warmer environments (S-Cage and S-Tank groups) had a higher percentage ofspermatozoa in the high quality cluster than thosefrom historically cooler parental environments (N-Cage). All groups showed a positive mean reactionnorm, though the slopes appeared steeper for the Sgroups than the N-Cage group. In other words, un-equal slopes amplified differences among groupswith increasing temperature. These results are similarto the observations by Harrald et al. (2010) and Pur-chase & Brown (2000) that juvenile growth rates inAtlantic cod populations are higher at 12°C than at 7to 8°C, and to Harrald et al. (2010) where differencesin growth rates are more apparent at higher tempera-tures. Interestingly, the Newfoundland and Labra dor

and southern populations are known toexhibit differences in the frequency oftemperature-associated SNPs (Brad-bury et al. 2010).

Sperm velocity, explained by PC1,appears to be the main source of varia-tion between the different groups in thepresent study. As explained in the intro-duction, an increase in sperm velo citywith temperature was ex pected (seeAlavi & Cosson 2005) and so too shouldan increase in the percentage of sper-matozoa in the high quality cluster beexpected. All groups exhibited positivemean thermal reaction norms, averageplastic responses, with a higher per-centage of spermatozoa in the highquality cluster at 12°C than at 3°C.Nonetheless, this variation with tem-perature was more evident in the south-ern groups. The positive plastic re-sponse to increasing water temperaturecould be attributed to both a decreasein water viscosity and an increase insperm metabolism. Seawater viscositydecreases with in creasing temperature

such that for the same amount of effort the spermcells displace farther (Larsen & Riisgard 2009). More-over, higher temperatures also cause increased meta-bolic rates that are expected to affect flagellarbeating and consequently the swimming velocity(e.g. Mansour et al. 2002). While a decrease ofmotility duration at higher temperatures caused by ahigher rate of ATP con sumption (Alavi & Cosson2005) might also be expected, we did not measurethis. However, there was no decrease in speed be-tween 10 and 30 s after motility activation in any ofthe groups, which could be because Atlantic codsperm can remain motile for more than 1 h (Trippel &Morgan 1994a). Nonetheless, Purchase et al. (2010),also working with Atlantic cod sperm, measuredsperm swimming for 180 s at 3, 6, 11 and 21°C, andfound a decrease in sperm velocity (VCL) for all tem-peratures between all time intervals starting at 30 to60 s. This decrease in VCL observed by Purchase etal. (2010) was higher at 11 than at 6°C and higher at21 than at 11°C, supporting the hypothesis of a de-crease in motility duration at higher temperatures.

In contrast to the southern groups, the mean spermswimming phenotype of the N-Cage group showedlittle thermal plasticity, perhaps related with thelarge variation in reaction norms among males for theCASA parameters. The N-Cage group showed

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Fig. 6. Mean PC1 and PC2 values for the 3 groups at the different tempera-tures 30 s after motility activation. Value in parentheses on the y-axis is thepercentage of variance explained by each component. Each box representsthe 50% quartile and the dark line the median, the whiskers represent 1.5times the inner quartile range. Different letters represent significant differ-ences be tween the groups for the same temperature. Significant differences

detected with Tukey’s HSD test (p < 0.05).

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greater inter-individual variation than both southerngroups. Nonetheless, while some N-Cage males hadpositive thermal plastic responses, most of themshowed flat (canalized) reaction norms. If the averagereaction norms are representative of what happens inthe wild, according to Valen’s (1965) ‘niche variationhypothesis’, the Newfoundland and Labra dor popu-lation has a wider reproductive niche than that of thesouthern population. In species such as cod that re-produce under sperm competition, sperm swimmingvelocities should always be high, and plasticity to de-creasing temperatures would be maladaptive. In ad-dition, the present results are an example of uncom-mon CoGV as colder water and northern genotypesproduce slower sperm. Most studies reporting gradi-ent variation in Atlantic cod populations have foundCnGV (Purchase & Brown 2000, Salvanes et al. 2004,Marcil et al. 2006), which is biologically more in tui -tive since it counteracts the phenotypic plasticityalong an environmental gra dient, and is usually con-sidered to be adaptive (Conover et al. 2009). None -theless, the observation made by Harrald et al. (2010)of 2 northeast Atlantic cod populations showing thatthe one from the warmer environment has higher ju-venile growth rates no matter the test temperature isindicative of CoGV, a pattern similar to ours. Thecause of the CoGV with temperature in our studyand that of Harrald et al. (2010) remains unclear.Nonetheless, unless these 2 populations come in con-tact in the future, and there is sperm competition be-tween males of the 2 populations, the magnitude ofsperm swimming variation is not enough to jeo -pardize fertilization.

Variation in reaction norm slopes among individuals(I) is referred to as an individual-by-environment in-teraction (I × E; Pigliucci 2005, Nussey et al. 2007, Pur-chase & Moreau 2012). In the present study, we testedthe hypothesis that both genotype and the environ-mental history would affect individual re action norms.The groups with the same environmental history butdifferent genotypic background, N-Cage and S-Cage, presented much more significant differencesthan the groups with the same genotypic backgroundbut different environmental history (S-Cage, S-Tank).However, both factors were shown to affect pheno-types, and for this reason, when averaging individualreaction norms, it is im portant to understand theorigin of variation before making conclusions. None -theless, any extrapolation of these results to wild pop-ulations should be done cautiously. The present studycompared F1 indivi duals reared in a single commonenvironment (sea cages) that allowed us to control environmental history; however, patterns could be

different in a different common environment. More-over, the N-Cage group was one year older than the Sgroups, and while some studies in Atlantic cod haveindicated that sperm quality is not affected by the individual’s age (Trippel & Morgan 1994b, Rakitin etal. 1999), there is the possibility of some influence. Inaddition, southern groups had a higher condition fac-tor than the N-Cage group, a pattern that is similar tothat found by Purchase & Brown (2001) where fishfrom the Grand Banks (corresponding to our New-foundland and Labrador population) always devel-oped a lower condition factor, no matter the tem -perature, than individuals from the Gulf of Maine(corresponding to our southern population). In cod,condition factor seems to influence sperm quality, butpatterns are inconsistent. Tuset et al. (2008) founda negative correlation between condition factor andsperm swimming straightness while Rakitin et al.(1999) found a positive relation between conditionfactor and male fertilization success. Also, there mayhave been other non-genetic parental effects that wedid not control. Finally, climate change is expected tooccur over several generations, yet we know littleabout the evolutionary potential of these populationsto respond to such change.

Our different population responses to temperatureshow that adaptations in traits related to reproduc-tion that are likely to mediate responses to climatechange can be driven by males, as was also demon-strated by Donelson et al. (2010) in a tropical reeffish. Under the predicted increase in sea surface temperatures, our results indicate that the ability ofthe sperm to achieve fertilization should not be a limiting factor in reproductive performance, evenwhen considering individual variation in responses.Nevertheless, our data show that when in spermcompetition, a male’s genotype and environmentalhistory will affect fertilization success and, ulti-mately, selection. Thermal plasticity in gonadal mat-uration, embryo development and viability, larvalsurvival and mismatch between spawn timing andfood availability will also affect Atlantic cod re -silience to climate change. As an example, Purchase& Brown (2000) detected a greater positive plasticityto temperature in terms of growth, for a northernpopulation of cod from the western Atlantic com-pared to a more southerly population. Moreover,sperm thermal reaction norms should increase withtemperature up to a critical temperature at whichpoint sperm swimming characteristics are likely todecrease, resulting in a dome shape as observed byPurchase et al. (2010). It is expected that we wouldhave observed this effect if we had tested higher

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temperatures. For example, in the case of the reeffish Acanthochromis polyacanthus an increase ofonly 3°C in the water temperature caused a reduc-tion in the proportion of the spermatozoa in the testis(Donelson et al. 2010). In this context, although notreflected in our study, extreme temperatures, such as12°C or higher, will most likely have a negative effecton Atlantic cod gametogenesis. Indeed, to counteracteffects of higher temperatures, southern Atlantic codpopulations migrate to areas with a maximum watertemperature of 8°C during the spawning season(Righton et al. 2010). Thus, rather than remain intheir current locations, cod populations will likelymove northward to new areas looking for their pre-ferred temperature range.

Acknowledgements. The authors thank the staff of JBARBfor their assistance in maintaining the cod stocks and to thepeople who helped with sample analyses: M. Bachan, J.Lewis and M. McGrath. We are grateful to Dr. E. Trippel forresearch advice and to D. Mercer for the map in Fig. 2. Wealso appreciate the comments from the anonymous review-ers. Funding was provided by the Natural Sciences andEngineering Research Council of Canada by way of aStrategic Project grant to I.A.F. and C.F.P., and the spermanalysis equipment was acquired by grants to C.F.P. fromthe Canada Foundation for Innovation and the Research andDevelopment Corporation of Newfoundland and Labrador.

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Plugin parameter Value used

Minimum sperm size (pixels) 3.0Maximum sperm size (pixels) 12.0Minimum track length (frames) 50.0Maximum sperm velocity between frames (pixels) 10.0Minimum VSL for motile (µm s−1) 1.0Minimum VAP for motile (µm s−1) 2.0Minimum VCL for motile (µm s−1) 4.0Low VAP speed (µm s−1) 2.0Maximum percentage of path with zero VAP 1.0Maximum percentage of path with low VAP 25.0Low VAP speed 2 (µm s−1) 10.0Low VCL speed (µm s−1) 15.0High WOB (percent VAP/VCL) 80.0High LIN (percent VSL/VAP) 80.0High WOB 2 (percent VAP/VCL) 50.0High LIN 2 (percent VSL/VAP) 60.0Frame Rate (frames per second) 100.0Microns per 1000 pixels 956.0

Table A1. Parameters used to set the ImageJ CASA plugin

Parameter PC 1 PC 2

VCL 0.420 −0.335VAP 0.532 −0.140VSL 0.535 0.024LIN 0.172 0.927WOB 0.473 0.089Proportion of variance 0.687 0.197Cumulative proportion 0.687 0.884

Table A2. Summary results of the 2 principal compo-nents (PC) analyses. PC1 and PC2 are the first 2 PCAextracted from the analysis. The table shows, for eachPC, the comparison of factor loadings for each startingvariable, the variance explained by the PC and its

cumulative proportion

Editorial responsibility: Stylianos Somarakis, Heraklion, Greece

Submitted: May 17, 2013; Accepted: September 3, 2013Proofs received from author(s): December 15, 2013

Appendix

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