Abstract
The giant kelp Macrocystis pyrifera is a cosmopolitan species of cold-temperate coasts. Its South-American distribution ranges from Peru to Cape Horn and Argentina, encompassing a considerable temperature gradient, from 3 to 20°C. Temperature is known to strongly affect survival, growth and reproduction of many kelp species, and ongoing global warming is already eroding their range distribution. Their response to thermal variability was shown to vary among genetically differentiated regions and populations, suggesting a possible adaptive divergence in thermal tolerance traits. This study aimed at testing the existence of local adaptation in the giant kelp, in regions separated by up to 4000km and strong thermal divergence. Two complementary experiments mimicked reciprocal transplants through a common garden approach, each habitat being represented by a given temperature corresponding to the regional average of the sampled populations. Several proxies of fitness were measured in the haploid stage of the kelp, and sympatric versus allopatric conditions (i.e. individuals at the temperature of their region of origin versus in a different temperature and versus individuals from other regions in that temperature) were compared. Additionally, a heat wave at 24°C was applied to measure the tolerance limits of these gametophytes. A significant interaction between experimental temperature and region of origin revealed that temperature tolerance varied among regions. However, depending on the fitness parameter measured, high latitude populations from the sub-Antarctic region were not always less heat resilient than populations from the warmer region of Peru. Even at 24°C, a temperature that is exceptionally reached in the southernmost part of the kelp’s natural habitat, all the gametophytes survived, although with strong differences in other traits among regions and populations within regions. This large range of temperature tolerance supports the idea of kelp gametophytes being a resistant stage. Finally, local adaptation sensu stricto was not detected. Fertility was more influenced by the geographic origin than by temperature, with possible effects of marginal conditions at the extremes of the distribution range. The latter results also suggest that stochastic dynamics such as genetic drift restricts adaptive processes in some populations of M. pyrifera.
Introduction
Kelp forests are distributed in most cold-temperate coasts. Even though they can be found in inter-tropical regions (e.g. Peru, Brazil, among others), they are restricted to specific areas where temperature do not exceed 22-24°C, such as in deep water (>60m) or upwelling centers. In approximately a third of their worldwide distribution, kelp forests are declining (). Several drivers explain this dynamic of distribution ranges, including overharvesting in some regions but the effect of warming became the major focus of attention, with an increasing number of studies focusing on the low physiological tolerance to temperature increases (; ; ; ; ; , see review by Smale, 2020). Low latitude populations seem particularly affected (Wernberg et al., 2010; ). While most of these studies highlight the sensitivity to heat waves (Smale and Wernberg, 2013; Wernberg, 2021), differences among regions suggest some adaptive divergence in thermal tolerance across the distribution range (; ; ; ). Ecological niche models predict major range shifts towards higher latitudes when including parameters of physiological responses to environmental stressors (; ; ). However, the capacity to evolve adaptations to changing environments is generally not considered (Valladares et al., 2014). Locally adapted populations could theoretically experience fitness reductions in a rapidly changing environment, and could decline as rapidly as maladapted populations (). On the other hand, locally adapted populations could also export favorable alleles to neighboring populations and thus slow down the range shift due to warming (). It has been shown that kelp populations with reduced genetic diversity are less resilient to heat waves and may go extinct (Wernberg et al., 2018), suggesting a lack of genetic variance underlying thermal tolerance traits is actually restricting the evolution of thermal adaptations in these populations.
How thermal adaptations could evolve in kelps? On the one side, the heterogeneity of selective pressures experienced across the distribution range, due for instance to the latitudinal variability in coastal temperatures, is expected to stimulate the evolution of phenotypic traits providing increased fitness in local/regional habitats. The underlying evolutionary process and the resulting pattern correspond to local adaptation (Williams, 1966; see Box 1). Local adaptation emerges if the action of selection is stronger than other evolutionary forces. Notably, local adaptation seems more likely in large populations for which the intensity of drift is weak and does not prevent the action of selection (). On the contrary, by promoting an effective gene flow among populations and habitats, dispersal may limit population divergence and therefore counteract the process of local adaptation (; Slatkin, 1973; ). Migration may also generate maladaptation, because introgression of foreign alleles can be disadvantageous for locally adapted populations (Pujol and Pannell, 2008). The equilibrium between these evolutionary forces and its effect on the process of local adaptation has been widely discussed (e.g. ; ; ; ). For example, when the migration rate is very low, local genetic drift may reduce the additive genetic variance and eventually fix a reduced number of genotypes, therefore hampering local adaptation process. In this context, a moderate migration may speed up the process of adaptive divergence by allowing favorable alleles to be introduced in local populations (). Most kelps have limited dispersal capacities, due to the predominance of spore dispersal, suggesting therefore that population divergence may evolve under an equilibrium between selection and drift. Another layer of complexity corresponds to the heteromorphic haploid-diploid life cycle typical of kelps, which deeply influences population dynamics and evolutionary trajectories (Valero et al., 1992; ; ). The diploid individual, i.e. the sporophyte, is large and constitutes the actual kelp forests. It produces spores after meiosis, which gives rise to a microscopic filamentous haploid stage, the gametophyte. Each sporophyte is able to release tens to hundreds of thousands of spores, which represent a myriad of new genetic combinations on which selection can act in the gametophyte stage. Moreover, because of the absence of dominance effects during the haploid phase, deleterious mutations are expected to be rapidly purged, and selection for beneficial alleles is expected to be more efficient, both mechanisms theoretically favoring the process of local adaptation. However, kelp gametophytes are often depicted as a resistance stage (e.g. ), suggesting they produce an all-purpose phenotype relatively insensitive to environmental variability. The question of selection efficiency in this peculiar haploid and microscopic stage is largely unaddressed in kelps.
Box 1
We aimed to explore this question with the giant kelp Macrocystis pyrifera as a biological model. The giant kelp is the largest brown algae that grows up to 50m long and forms marine forests (Steneck et al., 2002) that host a considerable biodiversity (
Figure 1

Distribution of the sampling locations within the three biogeographic regions. All sites (except LVL* and ALG*) were included in experiment 1. Experiment 2 included all populations indicated on the left of the map. The colored gradation indicates the latitudinal gradient of coastal temperatures. MP, Magellan Province (average temperature of 8°C); CG, Corcovado Gulf (average temperature of 12°C); IR, Intermediate Region (average temperature of 12°C) and PP, Peruvian Province (average temperature of 18°C).
With its wide geographic range and the extent of ecological variability met by its populations, Macrocystis pyrifera appears to be an ideal candidate species to tackle several questions around local adaptation. Does the large and environmentally heterogeneous distribution range promote local adaptation? Are low latitude populations located at the edge of the South American distribution range experiencing maladaptation due to extreme thermal conditions? At what spatial scale do populations diverge in their response to environmental heterogeneity? These questions are relevant to understand how the giant kelp copes with such environmental variability along its wide distribution. In this context, we aimed at examining the regional variance of thermal tolerance of the giant kelp and testing for local adaptation through two experiments. While they differed in their choice of experimental units, both were based on a common-garden approach simulating reciprocal transplantations of individuals among habitats, and were performed under laboratory-controlled conditions. Experiment 1 aimed at maximizing the number of populations sampled per region, following
Material and Methods
Sampling and Isolation of Gametophytes
Twenty-one sampling sites were selected among the three biogeographic provinces of the Chilean coast (Figure 1). For each sampling site, a 200m-transect parallel to the coast (whenever possible) was made. Every 50 meters, one healthy and reproductive blade was collected from two different sporophytes. Such strategy allowed the collection of gametophyte progeny from 10 sporophytes per site. Reproductive blades were washed with fresh water and a 2-4cm2 piece of fertile tissue was placed for 2h in 50mL-tubes filled with sterile seawater for spore release. Tissue was then removed from the tube and spores were allowed to settle on glass slides. The spores developed into the gametophytic phase as they were kept in standardized culture conditions of 12/12 day/night, approximately 10 photons.m-2.s-1. of red light to avoid gamete production. Each gametophyte progeny was stored at 12°C. Individual gametophytes were isolated after their differentiation into males and females and grown individually under vegetative growth conditions (red light) with weekly change of sterile SFC-enriched seawater (
Experimental Designs
The two common garden experiments consisted in submitting gametophytes of different origins to different temperatures (e.g. 8°C, 12°C and 18°C for Magellan Province, MP, Intermediate Region, IR, and Peruvian Province, PP, respectively), each corresponding to the average of each of the 3 sampled regions. In addition, a heat wave was simulated by submitting the gametophytes of Experiment 2 (see below) to 24°C. Such a temperature is largely above the usual coastal temperatures in all the distribution range, but can occasionally be reached in the PP during austral summers. This treatment aimed at evaluating the limit of thermal tolerance of gametophytes. We expected that the northernmost populations would show a better tolerance to this unusually high temperature than populations of IR and MP, which are never exposed to this environmental condition. Before starting the experiments, gametophytes were acclimated at white light for 5 days to activate growth and fertility. Each gametophyte was fragmented in order to obtain hundreds of clones of similar size (Figure 2). These clones were then distributed among the different aliquots, each of which including at least 50 clonal fragments, and cultivated for 14 days at the experimental temperatures. Each of these aliquots were considered as experimental units. The change of temperature from the standard culture condition (i.e. at 12°C) to the experimental temperature was performed smoothly by ramping up or down by 2°C every day until reaching the target experimental temperature (Figure 2). Besides temperature, all treatments were kept at identical culture conditions: light intensity was 25-27 photons. m-2.s-1, a photoperiod of 12:12 h (light:dark), and SFC-enriched sterile seawater.
Figure 2

Upper part: Experimental design for the isolation and manipulation of gametophytes. Initially, spores were collected from sporophylls (i.e. specialized blades located at the base of the sporophyte) and cultivated until male and female could be recognized. Individual gametophytes were then isolated and cultivated separately, and then fragmented into fragments of 5-15 cells. In Experiment 1, pools of clonal fragments from 5 sister females were split in 2 aliquots, one left without males to induce parthenogenesis (P), the other mixed with a pool of 5 males issued from the same parental sporophyte to induce self-fertilization (S). Each of these pools were then split in 3 aliquots, each aliquot being submitted to a different temperature. In Experiment 2, clonal fragments of single females were separated in 4 aliquots, each aliquot then submitted to a different temperature. Lower part: work flow for temperature changes between pre-acclimation conditions to target temperature.
Experiment 1 used 3 to 6 populations per region, and considered the Intermediate Region as 2 different units: the Corcovado Gulf and the open coast (19 populations in total, see Figure 1 for details). These 2 sub-regions experience the same average temperature but the populations of M. pyrifera are strongly differentiated both genetically and phenotypically (
Experiment 2 used up to 8 sporophytes per population (Table S1) and 3 to 5 populations per region (see Figure 1 for further details). This experiment was performed on five sister females per sporophyte. Each of these five female gametophytes were cloned separately to obtain hundreds of fragments (Figure 2), then acclimated under white light and to the temperature of the region of origin. At least 50 clones per female gametophytes were exposed to the different experimental temperatures, i.e. at 8, 12, 18 and 24°C (Figure 2). Growth multiplication factor was estimated using a subsample of 100μL of a homogenized suspension of female’s fragments stained with 50 μL of neutral red solution (concentration of 0.01 g/L). This colorant stains living cells, which can be distinguished from dead cells. Four pictures per sample (in different areas of the well) were taken under microscope at 20x magnification, to obtain an average count at days 2 and 14. A batch-script (Java v 1.8) was run under the software ImageJ (http://imagej.net), to count living and dead cells. Growth multiplication factor (GMF) was estimated as the ratio of living cells at day 14 over day 2. The proxy of physiological vigor was chlorophyll production (following
Data Analysis
Our approach was based on the Sympatric versus Allopatric (SvsA) test recommended by
W ~ TEXP + Region + Population[Region] + (TEXP x Region) + (TEXP x Population[Region])The importance of the random effects of populations was estimated using a likelihood-ratio test. To this aim, a submodel including only fixed effects was designed (W ~ TEXP + Region + (TEXP x Region)). The log-likelihood of each model was estimated, and the significance of the ratio [logL(submodel)]/[logL(full model)] was tested against a χ²-distribution. Tukey’s HSD post hoc tests were then performed, to detail the effect of fixed factors (i.e. region and TEXP). When the interaction (TEXP x Region) was significant, the SvsA comparison, which is embedded in the interaction, was tested in a second phase. Its F-ratio was calculated over the interaction (TEXP x Region), and its significance was assessed against the F-distribution (F, df1 = 1; df2 = df interaction). The obtained p< 0.05 indicates whether or not sympatric region-temperature combinations perform better than allopatric ones (Box 1), which case was considered as evidence of local adaptation sensu stricto (
A second test of local adaptation was performed, according to the definition “Local versus Foreign” (
where and are the mean fitness of respectively local and foreign gametophytes under the considered experimental condition, and α is a corrective term for biases due to sampling size (nL and nF for local and foreign populations or regions respectively). Here, we used α =1 because our interest was in the sign (i.e. negative or positive) of Hedge’s g-values. The pooled standard deviation s* is estimated by:
With sL2 and sF2 the sample variance of fitness for respectively local of foreign groups. This method was detailed in the meta-analysis of
The response of fitness proxies to the simulated heat wave (TEXP = 24°C, experiment 2) was analyzed through an ANOVA performed on the following linear mixed model:
W = Region + Population[Region]
The same likelihood-ratio approach was then used to assess the effect of populations as a random factor nested in regions. These analyses were performed using the functions lm and lmer (package lme4) in R 3.4.4. Survival rates (experiment 1) were previously transformed to sin-1(√x), to fit normality expectations.
Results
Experiment 1
For all fitness proxies surveyed in this experiment (i.e. survival, fertility, fecundity and photosynthetic efficiency), either the effect of the experimental temperature (TEXP) and/or region of origin were strongly significant (p< 0.01; Table 1). Survival rates ranged between 61 and 100% at 8°C and 12°C (Figure 3), but dropped between 6 and 62% at 18°C, indicating a strong negative impact of the northern temperature on survival. Fecundity appeared largely higher at the intermediate temperature (i.e 12°C; fecundity > 20%; Figure 3) than at 8 and 18°C (i.e. between 0 and 11%), except for females from the Magellan Province which maintained a fecundity close to 0. Photosynthetic efficiency varied slightly, and higher values were reached at 8°C (Figure 3). The effect of the region of origin appeared strongly significant for each of the four proxies (p< 0.01; Table 1). This was mainly explained by the gametophytes from Corcovado Gulf, which showed lower survival rates but higher fertility than any other region (Table S4). Fertility of gametophytes from Peruvian Province was close to 0 whatever the experimental temperature, while fecundity was among the highest at 12 and 18°C. Pairwise comparisons among treatments are provided in Table S4 (Tukey’s HSD tests).
Table 1
| Survival | Fertility | Fecundity | Photosynthetic efficiency | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Model | W ~ TEXP + Region + (TEXP x Region) | |||||||||||||||
| L-ratio | 1,783 | p = 0.182 | -1,14E-13 | p = 1 | 0,644 | p = 0.422 | 8,68 | p = 0.003 | ||||||||
| ANOVA on submodel | Df | Sum. Sq | Mean. Sq | F (p-value) | Df | Sum. Sq | Mean. Sq | F (p-value) | Df | Sum. Sq | Mean. Sq | F (p-value) | Df | Sum. Sq | Mean. Sq | F (p-value) |
| TEXP | 2 | 6,411 | 3,205 | 19.333 (<0.001) | 2 | 0,059 | 0,03 | 2.203 (0.11) | 2 | 0,392 | 0,196 | 10.039 (0.001) | 2 | 0,036 | 0,018 | 7.73 (<0.001) |
| Region | 3 | 3,389 | 1.130 | 6.814 (<0.001) | 3 | 0,331 | 0,11 | 8.193 (<0.001) | 3 | 0,213 | 0,071 | 3.648 (0.01) | 3 | 0,043 | 0,014 | 6.109 (<0.001) |
| TEXP x Region | 6 | 0,637 | 0,106 | 0.640 (0.70) | 6 | 0,11 | 0,018 | 1.366 (0.24) | 6 | 0,186 | 0,031 | 1.589 (0.15) | 6 | 0,008 | 0,001 | 0.596 (0.73) |
| Residuals | 100 | 16,58 | 0,166 | 0.000 | 91 | 1,227 | 0,013 | 106 | 2,068 | 0,02 | 108 | 0,254 | 0,002 | |||
Best fit model of the analysis of the variance observed in fitness proxies in the experiment 1, according to the methodology recommended by
Figure 3

Mean fitness of gametophytes from the four regions included in experiment 1, after 14 days under experimental conditions. Related results of ANOVA and Tukey’s HSD tests were consigned in Table 1 and Table S4, respectively. For the definitions of PP, IR, CG and MP, see Figure 1. The survival rate was quantified as the ratio of the number of living gametophytes at the day 14 to the initial number of gametophytes. Fertility was estimated as the ratio of living females bearing reproductive structures at day 6 to the total number of females. Fecundity was defined as the ratio of egg cells successfully fertilized at day 14 to the total number of eggs. Proxies of physiological vigor were estimated through the parameter Fv/Fm at day 14. Note: no interaction TEXP x Region was significant.
The factor “population of origin”, nested within regions, did not significantly contribute to the total variance of the proxies, except for the photosynthetic efficiency – the less variable proxy we used (L-ratio = 8.68, p = 0.003; Table 1, and Table S3 for details about mixed linear models). For the three other proxies, the full models failed to reach convergence (see REML criterion of convergence, Table 1) - likely because of too low sampling size within population relative to the high variance of these proxies in our experimental data. The interaction between experimental temperature and region of origin was significant for none of the four proxies, suggesting no evidence of local adaptation.
The distributions of Hedge’s d at the regional scale did not reveal clear patterns (Figure S1), as the results varied depending on the considered fitness proxy. All g* values for the survival rate and photosynthetic activity of MP versus others regions were positive. Yet, fertility and fecundity responded in the opposite way, i.e. all g*-values were negative. The test performed for the others regions produced both positive and negative g* values, and therefore did not support the hypothesis of local adaptation.
Experiment 2
In this experiment, the number of parental sporophytes per population was sufficient for the likelihood approach to converge, and a significant effect of populations-within-region was detected for growth and fertility, but not for physiological vigor (i.e. chlorophyll production rate; Table 2; Table S5 for details about mixed models). The effects of TEXP and region of origin were significant for some fitness proxies (physiological vigor and fertility respectively; p< 0.01; Table 2) but neither was significant for growth multiplication factor. The highest physiological vigor was reached at TEXP = 18°C, while the highest fertility was observed in gametophytes from the Intermediate Region (Figure 4; Table S6). Interestingly, the Growth multiplication factors were largely homogeneous among treatments, as neither the TEXP, nor the Region and nor their interaction were significant. An uneven distribution of fitness proxies among populations was observed (Figure 4), some of them being substantially “fitter” than others, notably populations FCO and NLH for Intermediate Region and ARV and ANT for Peruvian Province, which outperformed the others at all experimental temperatures. The interaction [TEXP x Region] was significant for the physiological vigor. Yet, neither the SA contrast (F(1; 4) = 0.69; p = 0.45), nor the examination of the Tukey’s test (Table S6) revealed local adaptation sensu stricto. Finally, the distribution of Hedge’s d was in line with the former results (Figure S2), as they were uniformly distributed on both sides of y = 0 (Figure S2).
Table 2
| Growth | Fertility | Physiological Vigor | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Model | W ~ TEXP + Region + (TEXP x Region) | |||||||||||
| L-ratio | 11,79 | p< 0.001 | 7,95E+00 | p = 0.005 | -1,71 | p = 1 | ||||||
| ANOVA on submodel | Df | Sum. Sq | Mean. Sq | F (p-value) | Df | Sum. Sq | Mean. Sq | F (p-value) | Df | Sum. Sq | Mean. Sq | F (p-value) |
| TEXP | 2 | 11,91 | 5,955 | 2.057 (0.131) | 2 | 9,4E-09 | 4,7E-09 | 2.203 (0.113) | 2 | 4,043 | 2,022 | 4.836 (0.009) |
| Region | 2 | 10,07 | 5,037 | 1.740 (0.179) | 2 | 2,0E-08 | 1,0E-08 | 4.760 (0.010) | 2 | 1,44 | 0,72 | 1.723 (0.182) |
| TEXP x Region | 4 | 21,39 | 5,348 | 1.847 (0.122) | 4 | 5,7E-09 | 1,4E-09 | 0.663 (0.618) | 4 | 6,111 | 1,528 | 3.655 (0.006) |
| Residuals | 177 | 512,35 | 2,895 | 179 | 3,8E-07 | 2,1E-09 | 179 | 74,819 | 0,418 | |||
Best fit model of analysis of the variance observed in fitness proxies in the experiment 2, according to the methodology recommended by
Figure 4

Mean fitness of gametophytes included in experiment 2 after 14 days under experimental conditions. Above, the mean fitness was estimated for each region (regional scale, Table 2 and Table S6 for ANOVA and Tukey’s HSD tests). Below, the same experimental outputs were presented at the population-scale. For the definitions of PP, IR, CG and MP, see Figure 1. Populations’ order from left to right on the x-axis corresponds to south-to-north in Figure 1. Growth rate was estimated as the ratio of living cells at day 14 over the day 2. The physiological vigor was estimated as the ratio of chlorophyll a production between day 14 and day 2. Fertility was estimated by counting the number of eggs per living female. The interaction TEXP x Region was only significant for the physiological vigor.
Heat Wave
Regardless of the region of origin, the ability of gametophytes to grow was affected by the experimental temperature of 24°C with GMF generally centered around 1 (Figure 5), indicating that most gametophytes neither grew nor lost biomass due to cell death. This trend was independent of the region of origin (F(2; 60) = 0.73; p = 0.49; Table 3). The factor “population of origin” was not significant (L-ratio = 0, p = 1, Table 3 and Table S7), yet the pool of gametophytes from Antofagasta (ANT) were a noticeable exception, with GMF > 2.5 (Figure 5). The physiological vigor was well explained by the region of origin (F(2; 60) = 11.63; p<0.001; Table 3), with the lowest values observed in the Magellan Province. In fact, gametophytes from this region were the most impacted by the heatwave as they showed the lowest values for the 3 fitness proxies. Contrary to our hypothesis of local adaptation, both physiological vigor and fertility were higher for gametophytes from the Intermediate Region than those from the Peruvian Province, the only region where such high temperature can be reached (Table 3 and Table S8 for Tukey’s tests).
Figure 5

Distribution of fitness of gametophytes facing a simulated heat wave (TEXP = 24°C). This test was performed during experiment 2. Above, the mean fitness was estimated for each region (regional scale, see Table 3 and Table S8 for ANOVA and Tukey’s HSD tests). For the definitions of PP, IR, CG and MP, and locations see Figure 1. Growth rate was estimated as the ratio of living cells at day 14 over the day 2. The physiological vigor, corresponding to the relative chlorophyll a production, was estimated as the ratio between day 14 and day 2. Fertility was estimated by counting the number of eggs per living female.
Table 3
| Growth | Fertility | Physiological Vigor | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Model | W ~ Region | |||||||||||
| L-ratio | 0 | p = 1 | 1,10E-01 | p = 0.73 | 0 | p = 1 | ||||||
| ANOVA on submodel | Df | Sum. Sq | Mean. Sq | F (p-value) | Df | Sum. Sq | Mean. Sq | F (p-value) | Df | Sum. Sq | Mean. Sq | F (p-value) |
| Region | 2 | 8,63 | 4,316 | 0.729 (0.487) | 2 | 1,2E-09 | 5,85E-10 | 1.8882 (0.160) | 2 | 18,821 | 9,411 | 11.625 (<0.001) |
| Residuals | 60 | 355,21 | 5.920 | 60 | 1,9E-08 | 3,10E-10 | 60 | 48,57 | 0.810 | |||
Best fit model of analysis of the variance observed in fitness proxies in the Heat Wave experiment.
Discussion
This study focused on the haploid stage, i.e. the gametophyte, of the giant kelp Macrocystis pyrifera, isolated from different biogeographic regions and covering a large latitudinal range. The physiological state of these gametophytes and the fitness proxies (i.e. growth, survival, fertility and fecundity) varied according to the experimental temperature and the region of origin. This kind of result has been observed in a number of recent studies on kelps thermal tolerance (
The large thermal tolerance of gametophytes represents the first likely explanation, as they were able to survive most experimental treatments, including the heat wave. Surviving gametophytes invested in vegetative growth in both experiments, to the detriment of reproductive functions (notably fertility was reduced at high temperatures, 18°C or above). Such trade-offs among fitness traits (e.g. survival, growth and reproduction) in response to stressful temperature was shown in other kelps (e.g.
Considering the large distribution range, we hypothesize that selection on gametophytes does not promote local adaptation but instead favors all-purpose phenotypes, allowing them to cope with the diverse array of environmental conditions within the range. This would be the case if a stabilizing selection is acting on a large spatial scale (Price et al., 2003). While dispersal through rafting of mature sporophytes is probably too rare to ensure an effective gene flow among populations, it allows the transport of individuals for several hundred (Thiel and Haye, 2006), and up to several thousands of kilometers (
The results of the two experiments also highlighted that low temperature may restrain fertility and fecundity, while survival rate and the physiological state remained globally stable. Therefore, the range of optimal temperature for reproduction in M. pyrifera seems to be restricted to few degrees around 12°C. In fact, regional temperatures tend to be seasonally variable, and may range between 14 and 20°C in the Peruvian Province and between 3 and 10°C in the Magellan Province. In this context, the choice of fixed experimental temperatures at the regional average (8°C for MP and 18°C PP) may have forced the gametophytes to express their plasticity in the form of a resistance state, yet in detriment to the detection of LA (if existing). This is a difficulty inherent to laboratory-controlled experiments, which are oversimplifications of the environmental factors involved, usually disregarding the interaction among them. This being said, several features of the reproductive strategy of M. pyrifera and dispersal capacity of its spores may also prevent the reach of a local adaptive optimum. One of these relates to the likely effect of genetic drift. In their meta-analysis about local adaptations in plants,
Adaptive optima to regional temperatures seem to be hardly reached in M. pyrifera gametophytic populations. We proposed two possible explanations that are non-mutually exclusive. One likely restriction stems from the effect of stochasticity driving the dynamics and evolutionary trajectories of the giant kelp’s populations. In parallel, selection may favor generalist gametophytic phenotypes over specialized ones to local habitat, as a consequence of selection in unpredictable environmental conditions. As the product of meiosis, the gametophyte population holds a large diversity of haploid genotypes expressing different thermal tolerance traits and reproductive strategies on which selection can act. With potentially reduced mutational load and nutrient requirements, and a strong phenotypic plasticity or wide physiological tolerance, this haploid stage is able to transmit most of the standing genetic variance of thermal tolerance traits to the next diploid generation. Therefore, tackling the question of local adaptation requires further experiments on the diploid sporophyte to complete the puzzle of the actual evolutionary trajectory in this heteromorphic haploid-diploid species. So far, we conclude that the large distribution range of this cosmopolitan species is better explained by its capacity to colonize distant and diverse habitats, than by the adaptation to local conditions.
Funding
This study was financed by grants ANID/CONICYT FONDECYT 1160930, FONDECYT 3170597, FB-0001 CeBiB, ANID MIllenium Science Initiative Program NCN2021_033, CNRS International Research Network: Diversity and Biotechnology of Marine Algae, and IDEALG project (France: ANR-10-BTBR-04).
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Statements
Data availability statement
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
Author contributions
RB, SF, and AM planned and designed the experiments. DH, CC, GM performed the experiments and analyzed the data together with RB and SF. All co-authors contributed to the interpretation of the results. SF and MV supervised the project. RB, SF, and MV wrote the manuscript, which was reviewed and approved by all authors. All authors contributed to the article and approved the submitted version.
Acknowledgments
We are grateful to Jessica Beltran for her support in the training and supervision of students DH, CC, and GM during this study.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fmars.2022.802535/full#supplementary-material
Supplementary Table 1Details about sampling effort and the number of parental sporophytes that provided the gametophytes included in our experiments.
Supplementary Table 2Experimental design and structure of our dataset, indicating which are sympatric or allopatric combinations.
Supplementary Table 3Details about the mixed linear models used to analyze data from the experiment 1.
Supplementary Table 4Pairwise comparisons among treatments from the experiment 1 (post hoc Tukey’s HSD tests), performed for significant fixed effects (see ).
Supplementary Table 5Details about the mixed linear models used to analyze data from the experiment 2.
Supplementary Table 6Pairwise comparisons among treatments from the experiment 2 (post hoc Tukey’s HSD test), performed for significant fixed effects (see ).
Supplementary Table 7Details about the mixed linear models used to analyze data from the experiment of Heat Wave.
Supplementary Table 8Pairwise comparisons among treatments from the experiment of Heat Wave (post hoc Tukey’s HSD test), performed for significant fixed effects (see ).
Supplementary Figure 1Hedge’s d distribution for testing the hypothesis of “local is best”, performed with data from Experiment 1 at the regional scale. The null hypothesis (i.e. no local adaptation) cannot be rejected as both negative (maladaptation) and positive (local adaptation) d-values were encountered for each proxy.
Supplementary Figure 2Hedge’s d distribution for testing the hypothesis of “local is best”, performed with data from Experiment 2 at the population scale. The null hypothesis (i.e. no local adaptation) cannot be rejected as both negative (maladaptation) and positive (local adaptation) d-values were encountered for each proxy.
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Summary
Keywords
phenotypic plasticity, latitudinal gradient, common garden experiment, heat tolerance, local adaptation
Citation
Becheler R, Haverbeck D, Clerc C, Montecinos G, Valero M, Mansilla A and Faugeron S (2022) Variation in Thermal Tolerance of the Giant Kelp’s Gametophytes: Suitability of Habitat, Population Quality or Local Adaptation?. Front. Mar. Sci. 9:802535. doi: 10.3389/fmars.2022.802535
Received
26 October 2021
Accepted
09 June 2022
Published
22 July 2022
Volume
9 - 2022
Edited by
Melinda Ann Coleman, New South Wales Department of Primary Industries, Australia
Reviewed by
Georgina Valentine Wood, University of Western Australia, Australia; Nora Diehl, University of Bremen, Germany
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© 2022 Becheler, Haverbeck, Clerc, Montecinos, Valero, Mansilla and Faugeron.
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*Correspondence: Sylvain Faugeron, sfaugeron@bio.puc.cl
This article was submitted to Marine Ecosystem Ecology, a section of the journal Frontiers in Marine Science
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