Daniel Liesner1, Louise Fouqueau2, Myriam Valero2, Michael Y Roleda3,4, Gareth A Pearson5, Kai Bischof6, Klaus Valentin1, Inka Bartsch1. 1. Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research Bremerhaven Germany. 2. UMI EBEA 3614, Evolutionary Biology and Ecology of Algae, CNRS Sorbonne Université, UC, UACH, Station Biologique de Roscoff Roscoff Cedex France. 3. Norwegian Institute of Bioeconomy Research Bodø Norway. 4. The Marine Science Institute, College of Science University of the Philippines, Diliman Quezon City Philippines. 5. Centre for Marine Sciences (CCMAR) University of Algarve Faro Portugal. 6. Marine Botany University of Bremen Bremen Germany.
Abstract
To understand the thermal plasticity of a coastal foundation species across its latitudinal distribution, we assess physiological responses to high temperature stress in the kelp Laminaria digitata in combination with population genetic characteristics and relate heat resilience to genetic features and phylogeography. We hypothesize that populations from Arctic and cold-temperate locations are less heat resilient than populations from warm distributional edges. Using meristems of natural L. digitata populations from six locations ranging between Kongsfjorden, Spitsbergen (79°N), and Quiberon, France (47°N), we performed a common-garden heat stress experiment applying 15°C to 23°C over eight days. We assessed growth, photosynthetic quantum yield, carbon and nitrogen storage, and xanthophyll pigment contents as response traits. Population connectivity and genetic diversity were analyzed with microsatellite markers. Results from the heat stress experiment suggest that the upper temperature limit of L. digitata is nearly identical across its distribution range, but subtle differences in growth and stress responses were revealed for three populations from the species' ecological range margins. Two populations at the species' warm distribution limit showed higher temperature tolerance compared to other populations in growth at 19°C and recovery from 21°C (Quiberon, France), and photosynthetic quantum yield and xanthophyll pigment responses at 23°C (Helgoland, Germany). In L. digitata from the northernmost population (Spitsbergen, Norway), quantum yield indicated the highest heat sensitivity. Microsatellite genotyping revealed all sampled populations to be genetically distinct, with a strong hierarchical structure between southern and northern clades. Genetic diversity was lowest in the isolated population of the North Sea island of Helgoland and highest in Roscoff in the English Channel. All together, these results support the hypothesis of moderate local differentiation across L. digitata's European distribution, whereas effects are likely too weak to ameliorate the species' capacity to withstand ocean warming and marine heatwaves at the southern range edge.
To understand the thermal plasticity of a coastal foundation species acpaclass="Chemical">n class="Chemical">rosn>s its latitudinal distribution, we assess physiological responses to high temperature stress in the kelp pan class="Species">Laminaria digitata in combination with population genetic characteristics and relate heat resilience to genetic features and phylogeography. We hypothesize that populations from Arctic and copan class="Species">ld-temperate locations are less heat resilient than populations from warm distributional edges. Using meristems of natural L. digitata populations from six locations ranging between Kongsfjorden, Spitsbergen (79°N), and Quiberon, France (47°N), we performed a common-garden heat stress experiment applying 15°C to 23°C over eight days. We assessed growth, photosynthetic quantum yield, carbon and nitrogen storage, and xanthophyll pigment contents as response traits. Population connectivity and genetic diversity were analyzed with microsatellite markers. Results from the heat stress experiment suggest that the upper temperature limit of L. digitata is nearly identical across its distribution range, but subtle differences in growth and stress responses were revealed for three populations from the species' ecological range margins. Two populations at the species' warm distribution limit showed higher temperature tolerance compared to other populations in growth at 19°C and recovery from 21°C (Quiberon, France), and photosynthetic quantum yield and xanthophyll pigment responses at 23°C (Helgoland, Germany). In L. digitata from the northernmost population (Spitsbergen, Norway), quantum yield indicated the highest heat sensitivity. Microsatellite genotyping revealed all sampled populations to be genetically distinct, with a strong hierarchical structure between southern and northern clades. Genetic diversity was lowest in the isolated population of the North Sea island of Helgoland and highest in Roscoff in the English Channel. All together, these results support the hypothesis of moderate local differentiation across L. digitata's European distribution, whereas effects are likely too weak to ameliorate the species' capacity to withstand ocean warming and marine heatwaves at the southern range edge.
Temperature is one of the main drivers determining latitudinal species distributions on the global scale (Jeffree & Jeffree, 1994; Lüning, 1990; Stuclass="Chemical">art‐Smith, Edgn class="Chemical">ar, & Bates, 2017). For sedentary organisms, the thermal limits of the realized niche are broadly described by mean summer and winter isotherms (van den Hoek, 1982; Jeffree & Jeffree, 1994; Stuart‐Smith et al., 2017), between which a species can complete its life cycle, while single extreme temperature events can further alter local species abundances especially at the range edges (Ruthrof et al., 2018; Smale, Wernberg, & Vanderklift, 2017; Straub et al., 2019). As a result of climate change, isotherms in the northern hemisphere have been shifting predominantly poleward since 1960 (Burrows et al., 2011), with consequent phenological and distributional changes in many taxa (Chen, Hill, Ohlemüller, Roy, & Thomas, 2011; Poloczanska et al., 2013).
Predictions of species distributions during climate change class="Chemical">are often based on class="Chemical">niche models, which assume that all individuals within a species respond uniformly (King, McKeown, Smale, & Moore, 2018; Müller, Laepple, Bn class="Chemical">artsch, & Wiencke, 2009; Reed, Schindler, & Waples, 2011). Consequently, trait variability needs to be integrated into estimates of future range shifts (Bennett, Duarte, Marbà, & Wernberg, 2019; Cacciapaglia & pan class="Disease">van Woesik, 2018; Chardon, Pironon, Peterson, & Doak, 2020), especially as recent evidence suggests a central role of plasticity and local adaptation in species’ responses to climate change (Atkins & Travis, 2010; Liesner, Shama, Diehl, Valentin, & Bartsch, 2020; Valladares et al., 2014).
Along copaclass="Chemical">n class="Species">ldn>‐temperate to polar rocky shores, kelps (large pan class="Species">brown algae in the order pan class="Species">Laminariales) provide important ecosystem services as foundation species of marine forests (Steneck et al., 2002; Teagle, Hawkins, Moore, & Smale, 2017; Wernberg & Filbee‐Dexter, 2019). Their coastal habitats are highly affected not only by gradual global warming, but also further by the accompanying changing onset of the warm season (Lima & Wethey, 2012) as well as the frequency and magnitude of extreme temperature events such as marine heatwaves (MHW; Hobday et al., 2016; Oliver et al., 2018). Poleward range shifts have already been documented for various kelp and fucoid seaweeds, which were attributed to global warming (Lima, Ribeiro, Queiroz, Hawkins, & Santos, 2007; Nicastro et al., 2013; Smale, Wernberg, Yunnie, & Vance, 2015).
Further range shifts class="Chemical">are predicted for many species, including the North Atlantic kelp n class="Chemical">pan class="Species">Laminaria digitata (Hudson) J.V. Lamouroux (Assis, Araújo, & Serrão, 2018; Raybaud et al., 2013). At high latitudes, L. digitata occurs on Spitsbergen and Greenland, while its southern distribution limit along the European coastline is in Brittany, France (Lüning, 1990). It thereby occurs between the 0°C winter and 18°C summer sea‐surface isotherm (Müller et al., 2009) indicating its wide temperature performance range as an Arctic to cold‐temperate species (sensu Lüning, 1990). Comparative laboratory studies described an upper survival temperature of western and eastern Atlantic juvenile L. digitata sporophytes of 23°C over seven days (Bolton & Lüning, 1982) and of 21°C over 14 days (tom Dieck, 1992), indicating high stability of thermal characteristics across regions. However, these investigations only compared single unialgal strains, which may not represent the entire species. Investigations on wildL. digitata sporophytes from Nova Scotia show mortality within one week at 21°C and tissue damage at 18°C (Simonson, Scheibling, & Metaxas, 2015). In South West England L. digitata, stress signals and reduced growth were evident after 16 days at 18°C (Hargrave, Foggo, Pessarrodona, & Smale, 2017).
class="Chemical">n class="Species">L. digitatan> is a relatively young species, which probably originated from a Pacific ancestor cclass="Chemical">rossing the Arctic toward the Atlantic ca. 5.3 million years ago (Lüning & tom Dieck, 1990; Rothman, Mattio, Anderson, & Bolton, 2017; Starko et al., 2019). Therefore, L. digitata was likely present in the Atlantic over multiple glacial cycles during the Quaternary (Assis et al., 2018), including the most recent Last Glacial Maximum 20,000 years ago (LGM; Clark et al., 2009). Recently, it has been proposed that L. digitata persisted during the LGM in only two disjoint refugia in the Northeast Atlantic, one located in the Armorican/Celtic Sea and one further north in the region of Ireland and Scotland (Neiva et al., 2020). Such a northern refugium for L. digitata was also suggested by King et al. (2020). Therefore, not only might the current climate since the LGM have affected thermal plasticity of L. digitata populations, but also the repeated retreat into glacial refugia and subsequent recolonization of the Northern Atlantic might have modulated genetic diversity and structure over several glacial cycles (Hewitt, 2004; Maggs et al., 2008). This possibly facilitated phenotypic divergence along what is presently a widespread latitudinal distribution gradient.
Local adaptation can occur along environmental gradients or in populations under unique selection pressures and affects response traits to increase the class="Chemical">paclass="Chemical">n class="Disease">fitnessn> of individuals in their specific environment (Kawecki & Ebert, 2004). For populations at their ecological range margins (i.e., marginal populations sensu Soulé, 1973), the unfavorable local environment can result in smaller population size and low genetic diversity (Eckert, Samis, & Lougheed, 2008; Hampe & Petit, 2005; Kawecki, 2000). Therefore, genetic drift may impair natural selection leading to maladaptation in marginal populations (Eckert et al., 2008; Pearson, Lago‐Leston, & Mota, 2009). Conversely, a highly selective environment at a species’ range margin might eventually facilitate local adaptation in these unique populations (reviewed by Hardie & Hutchings, 2010) and even increase their performance following climate change (Halbritter, Billeter, Edwards, & Alexander, 2015).
Meanwhile, there is much evidence for intraspecific vclass="Chemical">ariation among populations of seaweeds and seagrass (reviewed by King, McKeown, et al., 2018). Local adaptation might be common in kelps and seaweed populations generally, due to their low dispersal can class="Chemical">pacity and strong spatial structuring (King, McKeown, et al., 2018; Miller et al., 2019). Studies on local adaptation in n class="Species">L. digitata suggest that differentiation between populations could have occurred due to their geographic position (range central and marginal as well as southern and northern). King et al. (2019) investigated the expression of genes coding for heat shock proteins (HSP) in response to an hour‐long heat shock in L. digitata from Scotland (range center) and Southern England (trailing edge). Maximum HSP response was present at 4–8°C higher temperatures in the southern populations in this short‐term study, despite comparably low genetic diversity (King et al., 2020). The reduced genetic diversity and altered reproductive strategy in a southern marginal population in Brittany, France, also suggests that local differentiation has taken place (Oppliger et al., 2014; Valero et al., 2011). Overall, research on integrative responses such as growth is lacking when assessing the intraspecific thermal variation of L. digitata. Additionally, few studies on thermal responses of kelps incorporate physiology and population genetics over large geographic scales, although they may help to better predict climate change effects (Nepper‐Davidsen, Andersen, & Pedersen, 2019).
The main objective of this study was thus to assess differentiation in heat stress responses among populations of class="Chemical">paclass="Chemical">n class="Species">Laminn class="Chemical">aria digitata present along the entire Northeast Atlantic distribution zone through a mechanistic, common‐garden experiment. We hypothesized that an increasing thermal selection pressure toward the southern distribution limit increased heat resilience of sporophytes from southern class="Chemical">n>n class="Species">L. digitata populations. Because of high similarities of thermal characteristics across regions reported in previous comparative studies (Bolton & Lüning, 1982; tom Dieck, 1992), we expected local differentiation in response to heat to be of small extent and to occur mainly toward the upper temperature limit (see also King et al., 2019). We further expected phenotypic differentiation to occur more prominently in populations experiencing low amounts of gene flow, while we expected low genetic diversity to be associated with reduced heat resilience as a result of genetic drift and possible maladaptation, which we investigated by the use of neutral microsatellite markers.
MATERIAL AND METHODS
Sample collection and preparation
We collected 30–35 fertile paclass="Chemical">n class="Species">L. digitatan> sporophytes (Figure 1a) from the low intertidal zone, ensuring a distance of >1 m between samples (for the samples collected by diving in Spitsbergen, this was not guaranteed), in each of the following locations during summer (Figure 1b): Stuphallet, Kongsfjorden, Spitsbergen, Norway (SPT; 78.975 N, 11.633 E; 16 July 2019; approximate SST at time of sampling: 6.5°C); north of Tromsø, Norway (TRO; 69.790 N, 19.054 E; 14 August 2018; 8.5°C); Bodø, Norway (BOD; 67.284 N, 14.383 E; 12 June 2018; 9°C); pan class="Chemical">Helgoland, Germany (HLG; 54.178 N, 7.893 E; 13 August 2018; 18°C); pan class="Chemical">Roscoff, France (ROS; 48.727 N, 4.005 W; 11 September 2018; 16.5°C); and Quiberon, France (QUI; 47.470 N, 3.091 W; 10 September 2018; 16°C). Sampling in Norway and France and handling of data was conducted in accordance with the French legislation on the Access to Genetic Resources and Benefit‐Sharing. Maps (Figure 1b) were generated using a European Environment Agency coastline shapefile (European Environment Agency, 2019) and QGIS 3.8.2‐Zanzibar software (QGIS Development Team, 2019). To represent the current temperature ranges experienced by the sampled sporophytes, satellite‐obtained daily mean sea‐surface temperature data (Figure 1c) with a resolution of 0.05° × 0.05° were generated representatively for 2018 using E.U. Copernicus Marine Service Information (E.U. Copernicus Marine Service, 2019).
Figure 1
(a) Seven‐year‐old Laminaria digitata sporophyte from Spitsbergen, July 2019. The black reference square measures 5 × 5 cm. (b) Sampling locations of the L. digitata populations used in this study and (c) temperature amplitudes in 2018 marking minimum, mean, and maximum temperatures based on satellite‐obtained mean daily sea‐surface temperature datasets (E.U. Copernicus Marine Service, 2019). Abbreviations: BOD, Bodø; HLG, Helgoland; QUI, Quiberon; ROS, Roscoff; SPT, Spitsbergen; TRO, Tromsø
(a) Seven‐yeclass="Chemical">ar‐on class="Chemical">pan class="Species">ld class="Chemical">n>n class="Species">Laminaria digitata sporophyte from Spitsbergen, July 2019. The black reference square measures 5 × 5 cm. (b) Sampling locations of the L. digitata populations used in this study and (c) temperature amplitudes in 2018 marking minimum, mean, and maximum temperatures based on satellite‐obtained mean daily sea‐surface temperature datasets (E.U. Copernicus Marine Service, 2019). Abbreviations: BOD, Bodø; HLG, Helgoland; QUI, Quiberon; ROS, Roscoff; SPT, Spitsbergen; TRO, Tromsø
Entire sporophytes were stored in ambient seapaclass="Chemical">n class="Chemical">watern> for up to two days before processing. At the sampling locations, clean material from the meristematic region was preserved in pan class="Chemical">silica gel for micpan class="Chemical">rosatellite genotyping. For the heat stress experiment, six disks (Ø 20 mm) were cut from the meristematic region of each sporophyte (i.e., 180 disks per population) in a distance of 5–10 cm from the stipe‐blade transition zone. Disks were stored moist in cool boxes (<15°C) and transported to the laboratory within 30 hr. All experiments were performed at the Alfred Wegener Institute in Bremerhaven, Germany.
Heat stress experiment
Experimental design
We designed the experiment (Figure 2) as a mechanistic short‐term exposure to heat stress class="Chemical">around the upper survival temperature of n class="Chemical">pan class="Species">L. digitata sporophytes (21°C for a two week exposure; tom Dieck, 1992). A temperature of 19°C was considered to be a sublethal treatment for all populations, 21°C a threshoclass="Chemical">n>n class="Species">ld treatment (lethal over a longer exposure time; tom Dieck, 1992; Wilson, Kay, Schmidt, & Lotze, 2015), and 23°C a critical stress treatment (Bolton & Lüning, 1982), which also surpassed mean daily maximum temperatures of all sampled populations in 2018 (Figure 1c). We exposed all samples to the same temperatures, irrespective of the ecological significance for local populations, to investigate the thermal plasticity and potential of L. digitata across its entire distribution range. The heat stress experiment was conducted in independent runs in common‐garden conditions with material from Spitsbergen, Tromsø, Helgoland, Roscoff, and Quiberon. Due to logistic constraints, Bodø had to be excluded, and Spitsbergen material was only tested for growth and fluorescence characteristics and not for biochemistry and pigments.
Figure 2
Timeline of the heat stress experiment of Laminaria digitata. Dotted lines separate experimental phases of acclimation at 15°C (days −5–0), heat treatment (days 0–8), and recovery at 15°C (days 8–15). Growth and Fv/Fm were measured on days −5, 0, 3, 6, 8, and 15. On days 0 and 8, rapid light curves were performed and samples were frozen for biochemical and pigment analyses
Timeline of the heat stress experiment of class="Chemical">paclass="Chemical">n class="Species">Laminn class="Chemical">aria digitata. Dotted lines sepan>rate experimental phases of acclimation at 15°C (days −5–0), heat treatment (days 0–8), and recovery at 15°C (days 8–15). Growth and Fv/Fm were measured on days −5, 0, 3, 6, 8, and 15. On days 0 and 8, rapid light curves were performed and samples were frozen for biochemical and pigment analyses
For each population, five replicate pools each contained all meristem disks of six distinct sporophytes to prevent pseudoreplication. Meristem disks were transferred into sterile 5 L glass bottles filled with modified half‐strength paclass="Chemical">n class="Chemical">Provasolin>‐enriched natural seapan class="Chemical">water (PES; pan class="Chemical">Provasoli, 1968; modifications: HEPES buffer instead of TRIS, double concentration of Na2glycerophosphate; iodine enrichment following Tatewaki, 1966), which was exchanged every 3–4 days. Irradiance ranged between 30 and 35 µmol photons m−2 s−1 at the bottom of the beakers in a 16:8‐hr light:dark (L:D) cycle (ProfiLux 3 with LED Mitras daylight 150, GHL Advanced Technology, Kaiserslautern, Germany). Beakers were aerated gently to ensure motion of disks and even light and nutrient availability.
To allow recovery from sampling stress, disks were cultivated at 10°C for two (Tromsø) or nine days (Spitsbergen due to logistic issues), or at 15°C for four (paclass="Chemical">n class="Chemical">Rosn>coff, pan class="Chemical">Quiberon) or three days (pan class="Chemical">Helgoland) before the acclimation phase of the experiment. From each replicate pool, eight disks were then randomly assigned to one replicate 2 L glass beaker in each of the four temperature treatment groups (15, 19, 21, 23°C, n = 5). Six disks per replicate were marked by punching a small hole on the outer rim with a Pasteur pipette to be frozen for biochemical and pigment analysis during the experiment. The two unmarked disks were used for growth and fluorometric measurements over the course of the experiment.
At the beginning of the experiment, disks were acclimated at 15°C for five days to obtain a similclass="Chemical">ar metabolic state (day −5 to day 0; Figure 2). Although the class="Chemical">northern populations Spitsbergen and Tromsø do class="Chemical">not usually experience temperatures this high (Figure 1c), 15°C is a temperature within the growth optimum of n class="Chemical">pan class="Species">L. digitata (Bolton & Lüning, 1982; tom Dieck, 1992), which is considered to be stable (Wiencke, Bartsch, Bischoff, Peters, & Breeman, 1994), even for the Spitsbergen population (Franke, 2019). Starting the heat stress treatment on day 0, temperature was increased by increments of 2°C day−1 until the desired temperature was reached. The maximum temperature 23°C was applied for five days, while 21°C and 19°C were applied for six and seven days, respectively, according to the acclimation scheme (Figure 2). On day 8, temperature was set to 15°C for all treatment groups to initiate a recovery period of seven days. Measurements took place at the beginning of the experiment (day −5; Figure 2), the beginning of the heat treatment (day 0), before applying the maximum temperature 23°C (day 3), in the middle of the heat treatment (day 6), at the end of the heat treatment (day 8), and after the recovery period (day 15).
Relative growth rates
Two disks per replicate were repeatedly measured for growth over the course of the experiment (n = 5). Disks were class="Chemical">paclass="Chemical">n class="Disease">blotted dryn> and weighed for growth analyses. Relative growth rates (RGR) were calculated as
where x
1 = weight (g) at time 1, x
2 = weight at time 2, t
1 = time 1 in days, and t
2 = time 2 in days.
PAM Fluorometry
Fluorescence class="Chemical">parameters were assessed to estimate photoacclimation reactions in response to temperature (Davison, Greene, & Podolak, 1991; Machalek, Davison, & Falkowski, 1996) and were all conducted using a n class="Chemical">pan class="Chemical">PAM‐2100 class="Chemical">n>n class="Chemical">chlorophyll fluorometer (Walz, Effeltrich, Germany). Maximum quantum yield of photosystem II (Fv/Fm) was repeatedly measured in two disks per replicate over the course of the experiment following 5 min dark acclimation (n = 5). Before and after the heat treatment (day 0 and day 8), rapid light curves (RLC) were conducted after Fv/Fm measurements on one disk (n = 3). RLC irradiance steps ranged from 0 to 511 µmol photons m−2 s−1. Based on the photon flux density (PFD) and the effective quantum yield, relative electron transport rates (rETR) in photosystem II were calculated following Hanelt (2018) as
rETR was plotted against PFD, and the resulting curves were fitted following the modeclass="Chemical">paclass="Chemical">n class="Species">l on>f Jassby and Platt (1976) to calculate the maximum relative electron transport rate rETRmax, the saturation irradiance Ik, and the photosynthetic efficiency α of each curve.
Nonphotochemical quenching was calculated following Serôdio and Lavaud (2011) aswhere F = maximum fluorescence of a dclass="Chemical">ark‐adapted sample, and F′ = maximum fluorescence of a light‐adapted sample.
NPQ versus irradiance curves were fitted following the modeclass="Chemical">paclass="Chemical">n class="Species">l on>f Serôdio and Lavaud (2011) to calculate maximum nonphotochemical quenching NPQmax, the saturation irradiance E50, and the sigmoidicity coefficient n.
Biochemistry
Biochemical and pigment analyses were conducted with material from Tromsø, paclass="Chemical">n class="Chemical">Helgolandn>, pan class="Chemical">Roscoff, and pan class="Chemical">Quiberon. We assessed the early photosynthetic product mannitol, which is accumulated during summer (Schiener, Black, Stanley, & Green, 2015), and elemental carbon and nitrogen to estimate carbon assimilation and nutrient storage in response to temperature. In wild sporophytes, assimilated mannitol is metabolized into the long‐term storage polysaccharide laminarin and translocated into the distal thallus (Gómez & Huovinen, 2012; Yamaguchi, Ikawa, & Nisizawa, 1966). As the meristematic region only contains minimal amounts of laminarin in wild sporophytes (Black, 1954), and as maximum laminarin contents occur with a seasonal delay of 1–2 months in late autumn (Haug & Jensen, 1954; Schiener et al., 2015), we did not assess laminarin storage in our short‐term experiment on isolated meristematic disks.
Before the stclass="Chemical">art and at the end of the heat treatment (day 0 and day 8), three disks per replicate beaker (class="Chemical">n = 5) were frozen in lin class="Chemical">pan class="Chemical">quid class="Chemical">n>n class="Chemical">nitrogen for biochemical and pigment analysis and stored at −80°C. For mannitol, carbon, and nitrogen analyses, samples were lyophilized and ground to a fine powder. For the analysis of carbon and nitrogen contents, 2–3 mg ground tissue per sample was packed into tin cartridges, compressed, and combusted at 1,000°C in an elemental analyzer (EURO EA, HEKAtech GmbH) with acetanilide as standard. Mannitol was extracted in 70% ethanol from three technical replicates of each experimental sample (Karsten, Thomas, Weykam, Daniel, & Kirst, 1991). Analysis was performed in an HPLC Agilent Technologies system (1200 Series) with an Aminex Fast Carbohydrate Analysis Column HPAP (100 × 7.8 mm, 9 µm, Bio‐Rad, Munich, Germany) protected by a guard cartridge (Phenomenex, Carbo‐Pb‐2 + 4 × 3.00 mm I.D., Aschaffenburg, Germany).
Pigments
We assessed class="Chemical">n class="Chemical">chlorophyll an>nd class="Chemical">xanthophyll pigments in response to heat stress as a further indicator of photoprotection (Bischof & Rautenberger, 2012; Uhrmacher, Hanelt, & Nultsch, 1995). Pigment samples were lyophilized separately from biochemical samples (n = 5). They were ground under dim light conditions, weighed to 50–80 mg, and extracted in 90% aqueous acetone in darkness for 24 hr at 7°C. HPLC analysis followed the protocol and equipment described by Scheschonk et al. (2019), using a LaChromElite system (L‐2200 autosampler with Cooling Unit; DAD detector L‐2450; VWR‐Hitachi International) with a Spherisorb ODS‐2 column (25 cm × 4.6 mm, 5 µm particle size, Waters, Milford, USA) protected by a guard cartridge (LiChrospher 100‐RP‐18; Merck). The elution gradient was applied according to Wright et al. (1991). We used standards of chlorophyll a and c, fucoxanthin, β‐carotene, violaxanthin, antheraxanthin, and zeaxanthin (DHI lab products, Hørsholm, Denmark). To assess parameters of photoprotection as a stress response, we calculated the mass ratio of xanthophyll pigmentsviolaxanthin (V), antheraxanthin (A), and zeaxanthin (Z) per chlorophyll a (Chl a) following Bollen, Pilditch, Battershill, and Bischof (2016) as.
and de‐epoxidation ratio of class="Chemical">paclass="Chemical">n class="Chemical">xanthophylln> cycle pigments following Colombo‐Pallotta, García‐Mendoza, and Ladah (2006) as.
Statistical analyses of physiological parameters
As we measured two disks per replicate, we calculated growth rates and Fv/Fm from mean values per replicate. One disk was removed from the Spitsbergen 23°C treatment due to bleaching during the heating ramp. Despite identification efforts in the fiepaclass="Chemical">n class="Species">ldn>, almost none of the micpan class="Chemical">rosatellite markers amplified in two samples from Spitsbergen (see also 2.3.2). This led to the assumption that the two samples were of Hedophyllum nigripes (J. Agardh) Starko, S.C.Lindstrom & Martone, which is morphologically very similar to pan class="Species">L. digitata (Dankworth, Heinrich, Fredriksen, & Bartsch, 2020; Longtin & Saunders, 2015). One replicate pool probably containing meristem disks from both species was therefore removed from the experiment. Due to the mannitol extraction performed in triplicates, means of the three subsamples of each mannitol replicate were analyzed. In carbon and nitrogen analyses, four data points were deleted due to a measuring error on day 0. In the xanthophyll pool and de‐epoxidation analyses, one outlier was deleted due to implausibly high zeaxanthin contents about four times higher than the next highest value.
All analyses of the heat stress experiment were performed in the R statistical environment version 3.6.0 (R Core Team, 2019). We fitted generalized least squclass="Chemical">ares models for all n class="Chemical">parameters and tested for significance using analyses of variance (ANOVA). All models were fitted using the “gls” function from the R package “nlme” (Pinheiro, Bates, DebRoy, & Sarkar, 2019) with weights arguments to counteract heterogeneity of variance of normalized model residuals (Zuur, Ieno, Walker, Saveliev, & Smith, 2009). Normalized model residuals were assessed with Shapiro–Wilk normality tests and Levene's tests for homogeneity of variance. For repeated measures analyses of variance (RM ANOVA) of growth rates and Fv/Fm, temperature, population, and time were modeled as interactive fixed effects and a compound symmetry correlation structure was incorporated using a time covariate and replicate as grouping factor (Pekár & Brabec, 2016; Zuur et al., 2009). Analyses of variance were then performed on the models with the “anova” function to assess the effects of the fixed effects temperature, population and exposure time, and their interactions. For all biochemical, pigment, and fluorometric analyses, initial contents at day 0 were incorporated in the models as covariates to account for baseline differences, and temperature and population were modeled as fixed effects. Analyses of variance were performed to assess the effects of the initial value covariate and the fixed effects temperature and population, and their interaction. Pairwise comparisons were performed using the R package “emmeans” (Lenth, 2019) and using the “Satterthwaite” mode for calculation of degrees of freedom and Tukey adjustment of p‐values for multiple comparisons between independent groups. For pairwise comparisons in the repeated measures analyses (growth and Fv/Fm), the “df.error” mode for calculation of degrees of freedom was applied. Because of the repeated measures design and because the “df.error” mode overestimates the degrees of freedom (Lenth, 2019), p‐values were adjusted by means of the conservative Bonferroni correction for multiple testing to reduce the probability of type I errors. Correlation analyses (Kendall's rank correlation) were conducted between all parameters measured after the heat treatment (relative growth rates calculated between day 0 and day 8) using the “cor.test” function from the default R package “stats” (R Core Team, 2019).
Microsatellite genotyping
DNA extraction
DNA was extracted from 8–12 mg of dried tissue using the NucleoSpin 96 Plant II kit (Macherey‐Nagel GmbH & Co. KG) following the manufacturer's instructions. The lysis, micclass="Chemical">paclass="Chemical">n class="Chemical">rosn>atellite amplification and scoring was performed for 12 polymorphic loci following Robuchon, Le Gall, Mauger, and Valero (2014). Multiplex PCRs were modified using 5X GoTaq Flexi colorless reaction buffer (Promega Corp., Madison, USA) instead of 1X and performed using a T100™ Thermal Cycler (Bio‐Rad Laboratories Inc.).
Microsatellite amplification, scoring, and correction
Among the mclass="Chemical">arkers used, six were previously developed for n class="Chemical">pan class="Species">Laminaria digitata (Ld148, Ld158, Ld167, Ld371, Ld531, and Ld704; Billot et al., 1998) and six for Laminaria ochroleuca (Lo4‐24, Lo454‐17, Lo454‐23, Lo454‐24, Lo454‐27, and Lo454‐28; Coelho, Serrão, & Alberto, 2014). Alleles were sized using the SM594 size standard (Mauger, Couceiro, & Valero, 2012) and scored manually using GeneMapper 4.0 (Applied Biosystems). Individuals, for which more than one locus did not amplify, were removed from the dataset. Amplification was faulty for the population of Helgoland sampled in 2018, which could be linked to poor preservation or insufficient dehydration. Therefore, the dataset of the same population sampled at the same site in 2016 was used in the genetic analysis instead. In total, 190 individuals were initially genotyped for twelve microsatellite markers and 179 were retained.
Genetic diversity
Prior to genetic analysis, the presence of null alleles was tested using the ENA method in FreeNa (Chapuis & Estoup, 2007). Single and multilocus estimates of genetic diversity were calculated for each population as the mean number of alleles per locus (Na), unbiased expected heterozygosity (He, sensu Nei, 1978), observed heterozygosity (Ho), and number of private alleles (class="Chemical">Pa) using GenAlEx 6.5 (Peakall & Smouse, 2006). In addition, allelic richness (n class="Chemical">AR) was computed using FSTAT 2.9.3 (Goudet, 2001) for each locus using the rarefaction method. Linkage disepan class="Chemical">quilibrium between pairs of loci and single estimates of deviation from random mating (FIS) was calculated according to Weir and Cockerham (1984), and statistical significance was computed using FSTAT based on 7920 permutations for linkage disepan class="Chemical">quilibrium and 104 for FIS. To test the null hypothesis that populations did not differ in genetic diversity, a one‐way ANOVA was performed for AR, Pa, and He in R (R Core Team, 2019). Pairwise differences between means were tested by Fisher Individual Tests for Differences of Means (Minitab® Statistical Software, version 19.2). The homoscedasticity of the dataset and the normality of residuals was visually checked prior to the analyses.
Population structure
Population structure was investigated first by the analysis of the class="Chemical">pairwise estimates of FST (Weir & Cockerham, 1984), and their significance were computed using FSTAT (Goudet, 2001). Second, a Bayesian clustering method as implemented in Structure 2.3.4 (Pritchn class="Chemical">ard, Stephens, & Donnelly, 2000) was used to determine the existence of differentiated genetic groups within n class="Species">L. digitata populations categorizing them into K subpopulations. A range of clusters (K) from one to six was tested with 100 iterations, a burn‐in period of 100,000, and a Markov chain Monte Carlo of 500,000 (Gilbert et al., 2012). The most likely value of K was determined using Evanno ΔK (Evanno, Regnaut, & Goudet, 2005) obtained using Structure Harvester (Earl & vonHoldt, 2012). Replicates of Structure runs were combined using CLUMPP software (Jakobsson & Rosenberg, 2007). Bar plots were created with Distruct (Rosenberg, 2004).
RESULTS
The significant main effects of independent factors class="Chemical">are only reported in the absence of significant interactive effects. Therefore, in the presence of significant interactive effects, the simultaneous effects of two or more independent vn class="Chemical">ariables on a given dependent variable are given more emphasis than significant main effects.
Growth
The significant population × temperature × time interaction for relative growth rates (Figure 3; Table 1) indicates that growth in the temperature treatments differed significantly between populations over exposure time. However, there were differences in general growth activity between populations already during acclimation at 15°C (Figure 3a), which persisted during the heat and recovery phases (Figure 3b,c), indicating a different physiological status among populations. This is represented by the significant main effect of population on growth rates (Figure 3; Table 1). Mean growth over all temperatures and time points was significantly lower in material from the northern populations Spitsbergen and Tromsø (by 34%–70%) than in material from the southern populations paclass="Chemical">n class="Chemical">Helgolandn>, pan class="Chemical">Roscoff, and pan class="Chemical">Quiberon ((ROS = QUI) > HLG > SPT > TRO, Bonferroni‐corrected pairwise comparisons, p < .001).
Figure 3
Relative growth rates of Laminaria digitata disks over the experimental phases of (a) acclimation at 15°C, (b) heat treatment, and (c) recovery at 15°C. Mean values ± SD (n = 5, for Spitsbergen n = 4). Lowercase letters indicate significant differences between all mean population responses over time (Bonferroni tests, p < .05). Dashed lines indicate significant differences between temperature treatments within populations (Bonferroni tests, p < .05). Arrows indicate significant differences between temperature treatments over time (Bonferroni tests, p < .05). Significance levels are given in the text
Table 1
Results of generalized least squares models to examine variability of relative growth rates (RGR) and maximum quantum yield (Fv/Fm) of Laminaria digitata disks in the heat stress experiment
Parameter
numDF
denDF
RGR
Fv/Fm
F‐value
p‐value
F‐value
p‐value
Population
4
228
283.25
<.0001
36.77
<.0001
Temperature
3
228
60.38
<.0001
29.06
<.0001
Time
2
228
54.56
<.0001
104.37
<.0001
Population × temperature
12
228
12.13
<.0001
5.56
<.0001
Population × time
8
228
7.70
<.0001
8.09
<.0001
Temperature × time
6
228
31.83
<.0001
32.91
<.0001
Population × temperature × time
24
228
3.20
<.0001
5.58
<.0001
Fresh weight relative growth rates and maximum quantum yield Fv/Fm over acclimation, heat treatment, and recovery periods were tested against interactive effects of population, heat stress temperature treatment, and time. Tested values are means of 2 per replicate (n = 5, n = 4 for Spitsbergen). numDF, numerator degrees of freedom; denDF, denominator degrees of freedom. Statistically significant values are indicated in bold text.
Relative growth rates of class="Chemical">paclass="Chemical">n class="Species">Laminn class="Chemical">aria digitata disks over the experimental phases of (a) acclimation at 15°C, (b) heat treatment, and (c) recovery at 15°C. Mean values ± SD (n = 5, for Spitsbergen n = 4). Lowercase letters indicate significant differences between all mean population responses over time (Bonferroni tests, p < .05). Dashed lines indicate significant differences between temperature treatments within populations (Bonferroni tests, p < .05). Arrows indicate significant differences between temperature treatments over time (Bonferroni tests, p < .05). Significance levels are given in the text
Results of generalized least squclass="Chemical">ares models to examine vn class="Chemical">ariability of relative growth rates (RGR) and maximum quantum yiepan class="Species">ld (Fv/Fm) of pan class="Species">Laminaria digitata disks in the heat stress experiment
Fresh weight relative growth rates and maximum quantum yiepaclass="Chemical">n class="Species">ldn> Fv/Fm over acclimation, heat treatment, and recovery periods were tested against interactive effects of population, heat stress temperature treatment, and time. Tested values are means of 2 per replicate (n = 5, n = 4 for Spitsbergen). numDF, numerator degrees of freedom; denDF, denominator degrees of freedom. Statistically significant values are indicated in bopan class="Species">ld text.
During the heat stress treatment (Figure 3b), interactive effects of temperatures and populations became evident. While temperature effect sizes were small in the northern populations, possibly because of the generally low growth activity, growth rates of paclass="Chemical">n class="Chemical">Helgolandn>, pan class="Chemical">Roscoff, and Quiberon material at 21°C and 23°C were 50%–60% lower than at 15°C. In both Helgoland and Roscoff samples, 19°C–23°C significantly reduced growth compared to the 15°C control (Bonferroni test, p < .01), whereas samples from Quiberon grew significantly slower only at 21°C and 23°C compared to 15°C (Bonferroni tests, p < .001). Quiberon was the only population where growth did not decrease significantly at 19°C neither over time nor compared to the 15°C control.
Over the recovery period at 15°C (Figure 3c), specimens from all populations showed significantly decreased growth after exposure to 23°C comclass="Chemical">pared to lower temperature treatments (Bonferroni tests, p < .05). Spitsbergen and Tromsø essentially ceased growth (RGR < 0.001 and 0.002 g g−1 day−1, respectively), while n class="Chemical">pan class="Chemical">Helgoland, class="Chemical">n>n class="Chemical">Roscoff, and Quiberon maintained slow growth (0.006, 0.004, and 0.01 g g−1 day−1, respectively). However, during recovery after exposure to 23°C, there were no significant differences between growth rates of the different populations (Bonferroni tests, p > .05). Quiberon material recovered best, in that there were no significant differences between the 15 and 21°C treatments while disks in these treatments simultaneously grew significantly faster than those from the former 23°C treatment (Bonferroni tests, p < .01).
In the more detailed time course of growth rates (Figure A1), it became evident that all populations showed a trend of recovery from 21°C as growth rates increased between day 8 and day 15 (Figure A1), which was significant only for paclass="Chemical">n class="Chemical">Quin>beron (RM ANOVA; Table A1; Bonferroni test, p < .001) and Spitsbergen (RM ANOVA; Table A1; Bonferroni test, p < .01). Additionally, only pan class="Chemical">Helgoland and pan class="Chemical">Quiberon material slightly, but not significantly, recovered growth rates from the 23°C treatment (RM ANOVAs; Table A1; Bonferroni tests, p > .05). At the end of the experiment, one Spitsbergen disk had bleached in the 23°C treatment, while all other disks survived.
Figure A1
Relative growth rates (RGR) of Laminaria digitata disks from (a) Spitsbergen, (b) Tromsø, (c) Helgoland, (d) Roscoff, and (e) Quiberon over the heat stress experiment. Points represent growth rates between subsequent measuring days. Mean values ± SD (n = 5, for Spitsbergen n = 4). Points at day 0 represent growth over acclimation at 15°C, the end of the heat treatment at day 8 is marked with a vertical dotted line, and zero growth is marked with a horizontal dotted line. For statistical analysis, see Table A1.
Table A1
Results of generalized least squares models to examine variability of growth rates and maximum quantum yield of Laminaria digitata disks in the detailed time course of the heat stress experiment (Figures A1, A2)
Population
Parameter
RGR
Fv/Fm
numDF
denDF
F‐value
p‐value
numDF
denDF
F‐value
p‐value
Spitsbergen
Temperature
3
60
17.43
<.0001
3
72
46.35
<.0001
Time
4
60
72.81
<.0001
5
72
9.31
<.0001
Temperature × time
12
60
5.24
<.0001
15
72
14.78
<.0001
Tromsø
Temperature
3
80
87.90
<.0001
3
96
8.87
<.0001
Time
4
80
778517.93
<.0001
5
96
45.61
<.0001
Temperature × time
12
80
29.20
<.0001
15
96
7.02
<.0001
Helgoland
Temperature
3
80
159.35
<.0001
3
96
209.26
<.0001
Time
4
80
23.36
<.0001
5
96
9198.09
<.0001
Temperature × time
12
80
27.92
<.0001
15
96
7.47
<.0001
Roscoff
Temperature
3
80
168.27
<.0001
3
96
15.32
<.0001
Time
4
80
22.71
<.0001
5
96
71.51
<.0001
Temperature × time
12
80
14.12
<.0001
15
96
12.45
<.0001
Quiberon
Temperature
3
80
271.81
<.0001
3
96
14.08
<.0001
Time
4
80
813970892.83
<.0001
5
96
67.21
<.0001
Temperature × time
12
80
75.62
<.0001
15
96
4.34
<.0001
Fresh weight relative growth rates and maximum quantum yield Fv/Fm over all time points (T‐5 (only Fv/Fm), T0, T3, T6, T8, T15) were tested against interactive effects of heat treatment and time for each population separately. Generalized least squares models were performed as described in the methods section, but without the fixed effect for population. Tested values are means of 2 per replicate (n = 5, n = 4 for Spitsbergen). numDF, numerator degrees of freedom; denDF, denominator degrees of freedom. Statistically significant values are indicated in bold text.
Table A5
Frequency of null alleles per marker and per population of Laminaria digitata obtained using FREENA software
Ld148
Ld158
Ld167
Ld371
Ld531
Ld704
Lo454‐23
Lo454‐24
Lo454‐17
Lo454‐27
Lo454‐28
Lo4‐24
Spitsbergen
0.00001
0.29297
0.07023
0.17081
0.12798
0.00001
0
0.07593
0.001
0.00001
0
0.00836
Tromsø
0
0.001
0
0.23131
0.00001
0
0.02599
0
0.00004
0.10953
0.00006
0.00001
Bodø
0.11562
0.00001
0.00001
0.13494
0.00001
0
0.20983
0.11409
0.00006
0.00001
0.00006
0.00001
Helgoland
0.00012
0
0
0
0.12754
0.01587
0.09471
0.00007
0.001
0.001
0.00007
0.001
Roscoff
0.01255
0.17234
0.04511
0.01372
0.01204
0.02449
0.01144
0.072
0
0.001
0.03801
0.11747
Quiberon
0.00002
0.13067
0
0.00001
0.00001
0.06379
0.00001
0.01969
0.01643
0.001
0.00001
0.13145
Significant values (>0.05) are highlighted in bold text.
Photoacclimative responses
Maximum quantum yieclass="Chemical">paclass="Chemical">n class="Species">ldn> of photosystem II (Fv/Fm) in the temperature treatments differed between populations over time, which is represented by the significant population × temperature × time interaction (Figure 4, Table 1). After acclimation, all samples showed no signs of stress with Fv/Fm ranging between 0.7 and 0.8 (Figure 4a).
Figure 4
Maximum quantum yield (Fv/Fm) of Laminaria digitata disks after the experimental phases of (a) acclimation at 15°C, (b) heat treatment, and (c) recovery at 15°C. Mean values ± SD (n = 5, for Spitsbergen n = 4). Lowercase letters indicate significant differences between all mean population responses over time (Bonferroni tests, p < .05). Dashed lines indicate significant differences between temperature treatments within populations (Bonferroni tests, p < .05). Arrows indicate significant differences between temperature treatments over time (Bonferroni tests, p < .05). Significance levels are given in the text
Maximum quantum yiepaclass="Chemical">n class="Species">ldn> (Fv/Fm) of pan class="Species">Laminaria digitata disks after the experimental phases of (a) acclimation at 15°C, (b) heat treatment, and (c) recovery at 15°C. Mean values ± SD (n = 5, for Spitsbergen n = 4). Lowercase letters indicate significant differences between all mean population responses over time (Bonferroni tests, p < .05). Dashed lines indicate significant differences between temperature treatments within populations (Bonferroni tests, p < .05). Arrows indicate significant differences between temperature treatments over time (Bonferroni tests, p < .05). Significance levels are given in the text
At the end of the heat treatment (Figure 4b), temperature effects on quantum yiepaclass="Chemical">n class="Species">ldn> contrasted between the two populations of Spitsbergen and pan class="Chemical">Helgoland. Spitsbergen material was most susceptible to the heat treatments: At 21°C and 23°C, quantum yiepan class="Species">ld was significantly lower (by 12% and 25%, respectively) than at 15°C and 19°C (Bonferroni tests, p < .001). Tromsø, Roscoff, and Quiberon samples responded with a significant decrease in quantum yield by 11%–13% only at 23°C (Bonferroni tests, p < .05). In contrast, Helgoland samples were most stress resistant and showed a general stability of quantum yield in all conditions over time. Only at 23°C, at the end of the heat treatment, there was a slight decrease in quantum yield (significantly different only to the 19°C treatment; Bonferroni test, p < .001), but Fv/Fm was still significantly higher (9%–28%) than in all other populations at 23°C (Bonferroni tests, p < .01).
At higher temporal resolution (Figure A2), a general difference between southern and northern populations became more pronounced. While the significant decrease in quantum yiepaclass="Chemical">n class="Species">ldn> at 23°C took place between day 6 and day 8 for pan class="Chemical">Helgoland, pan class="Chemical">Roscoff, and Quiberon (RM ANOVA; Table A1; Bonferroni tests, p < .05), this decrease already started between day 3 and 6 in Spitsbergen and Tromsø material (Bonferroni tests, p < .001). Only specimens from Spitsbergen, as the most susceptible population, significantly decreased quantum yield also at 21°C, between day 6 and day 8 (Bonferroni test, p < .01).
Figure A2
Maximum quantum yield (Fv/Fm) of Laminaria digitata disks from (a) Spitsbergen, (b) Tromsø, (c) Helgoland, (d) Roscoff, and (e) Quiberon over the heat stress experiment. Mean values ± SD (n = 5, for Spitsbergen n = 4). End of the acclimation at 15°C and end of the heat treatment are marked with dotted lines. For statistical analysis, see Table A1.
The stronger heat susceptibility of Spitsbergen material became evident also following the recovery period (Figure 4c). While alclass="Chemical">paclass="Chemical">n class="Species">l on>ther populations recovered from 23°C, in that there were no significant differences to the 15°C control, Spitsbergen only recovered successfully from 21°C (Bonferroni tests, p > .05). However, Fv/Fm did not recover in Spitsbergen material following the 23°C treatment (compared to 15–19°C; Bonferroni tests, p < .01), indicating chronic photoinhibition and likely damage to photosystem II.
Contrclass="Chemical">ary to quantum yien class="Chemical">pan class="Species">ld, the photoacclimation pan>rameters obtained from rapid light curves at the end of the heat treatment, maximum relative electron transport rate rETRmax (Figure A3a), saturation irradiance Ik (Figure A3b), and photosynthetic efficiency α (Figure A3c) did not show significant effects or interactions of temperature and population (Table A2). In contrast, nonphotochemical quenching (NPQ) class="Chemical">parameters showed no significant interaction effects, but significant effects of population on maximum nonphotochemical quenching NPQmax and saturation irradiance E50, and of temperature on the sigmoidicity coefficient n (Figure A4; Table A3). Mean NPQmax (Figure A4a) was 47%–56% lower in Helgoland material than in Tromsø, class="Chemical">Roscoff, and Quiberon over all temperatures ((QUI = ROS =TRO = SPT) > (SPT = HLG); Tukey tests, p < .05), indicating intrinsically low nonphotochemical quenching in the Helgoland population. Mean E50 (Figure A4b) of Spitsbergen material was significantly lower than in Tromsø, Helgoland, and Quiberon by 29%–38% over all temperatures ((QUI = ROS =HLG = TRO) > (ROS = SPT); Tukey tests, p < .05), indicating an onset of NPQ already at low irradiances for Spitsbergen. The significant effect of temperature on n (Figure A4c) was visible as a mean downward trend of n by 29% between 15 and 23°C over all populations ((15°C = 19°C) > (19°C = 21°C) > (21°C = 23°C); Tukey tests, p < .001), indicating a greater response of NPQ under lower irradiances at high temperatures.
Figure A3
Photoacclimation parameters of Laminaria digitata disks obtained via rapid light curves after acclimation at 15°C (day 0, empty circles) and after the heat treatment (day 8, colored points). (a) Maximum relative electron transport rate rETRmax (relative unit), (b) saturation irradiance Ik (µmol photons m−2 s−1), (c) photosynthetic efficiency α (rETR/µmol photons m−2 s−1). Mean values ± SD (n = 3, for Spitsbergen n = 2). Analyses of variance returned no significant differences between populations (indicated by lowercase letters) and temperatures (Table A2).
Table A2
Results of generalized least squares models to examine variability of photoacclimation parameters of Laminaria digitata disks obtained via rapid light curves in the heat stress experiment (Figure A3)
Parameter
numDF
denDF
rETRmax
Ik
α
F‐value
p‐value
F‐value
p‐value
F‐value
p‐value
Initial values
1
35
0.49
.4877
0.03
.8571
0.54
.4665
Population
4
35
2.32
.0760
2.25
.0831
0.39
.8149
Temperature
3
35
2.87
.0503
0.59
.6284
1.83
.1601
Population × temperature
12
35
1.59
.1413
1.38
.2197
1.04
.4390
Maximum relative electron transport rate rETRmax, saturation irradiance Ik, and photosynthetic efficiency α were tested against initial values as covariate and interactive effects of population and heat stress temperature treatment. n = 3, n = 2 for Spitsbergen. numDF, numerator degrees of freedom; denDF, denominator degrees of freedom. Statistically significant values are indicated in bold text.
Figure A4
Nonphotochemical quenching parameters of Laminaria digitata disks obtained via rapid light curves after acclimation at 15°C (day 0, empty circles) and after the heat treatment (day 8, colored points). (a) Maximum nonphotochemical quenching NPQmax (relative unit), (b) saturation irradiance E50 (µmol photons m−2 s−1), (c) sigmoidicity coefficient n (unitless). Mean values ± SD (n = 3, for Spitsbergen n = 2). Significant differences between mean population responses are indicated by lowercase letters (Table A3; Tukey tests, p < .05).
Table A3
Results of generalized least squares models to examine variability of nonphotochemical quenching parameters of Laminaria digitata disks obtained via rapid light curves in the heat stress experiment (Figure A4)
Parameter
numDF
denDF
NPQmax
E50
n
F‐value
p‐value
F‐value
p‐value
F‐value
p‐value
Initial values
1
35
78.00
<.0001
8.60
.0059
0.47
.4980
Population
4
35
20.73
<.0001
4.73
.0037
2.07
.1063
Temperature
3
35
1.68
.1883
2.14
.1132
11.43
<.0001
Population × temperature
12
35
1.86
.0761
1.17
.3397
0.91
.5448
Maximum nonphotochemical quenching NPQmax, saturation irradiance E50, and sigmoidicity coefficient n were tested against initial values as covariate and interactive effects of population and heat stress temperature treatment. n = 3, n = 2 for Spitsbergen. numDF, numerator degrees of freedom; denDF, denominator degrees of freedom. Statistically significant values are indicated in bold text.
Tissue class="Chemical">n class="Chemical">manclass="Chemical">nitoln> and class="Chemical">carbon contents were not significantly affected by interactive effects of population and temperature (Figure 5; Table 2), indicating that all populations responded uniformly to the temperature treatments in carbon storage. The significant effect of population on mannitol contents (Table 2) was due to the lowest contents in Roscoff and 80% higher contents in Tromsø material (TRO > (HLG = QUI) > ROS; Tukey tests, p < .05). The significant effect of temperature on mannitol (Table 2) shows that 21°C and 23°C induced significantly higher mannitol contents compared to the 15°C and 19°C treatments over all populations ((23°C = 21°C) > (19°C = 15°C); Tukey tests, p < .05). Carbon contents were not affected by temperature, but differed significantly only between populations (Figure 5b; Table 2). As with mannitol, Tromsø material maintained a higher carbon content, in that the means were significantly (7%–9%) higher in Tromsø and Helgoland material than in Roscoff and Quiberon material ((TRO = HLG) > (ROS = QUI); Tukey tests, p < .001).
Figure 5
Biochemical characteristics of Laminaria digitata disks after acclimation at 15°C (day 0, empty circles) and after the heat treatment (day 8, colored points). (a) Mannitol contents, (b) carbon contents, (c) nitrogen contents, (d) molar C:N ratio. Mean values ± SD (n = 5, n = 4 for Quiberon in carbon, nitrogen, and C:N ratio), except for (a) means of mean values due to extraction in triplicates. Significant differences between mean population responses are indicated by lowercase letters (Tukey tests, p < .05). Significant differences between temperature treatments within populations are indicated by dashed lines (Tukey tests, p < .05). Significance levels are given in the text
Table 2
Results of generalized least squares models to examine variability of biochemical characteristics of Laminaria digitata disks in the heat stress experiment
Parameter
numDF
denDF
Mannitol
Carbon
Nitrogen
C:N ratio
F‐value
p‐value
F‐value
p‐value
F‐value
p‐value
F‐value
p‐value
Initial values
1
63 (59)
96.04
<.0001
65.82
<.0001
49.08
<.0001
8.56
.0049
Population
3
63 (59)
19.54
<.0001
42.76
<.0001
17.48
<.0001
2.93
.0410
Temperature
3
63 (59)
9.67
<.0001
2.46
.0718
7.78
.0002
8.63
.0001
Population × temperature
9
63 (59)
0.92
.5133
1.90
.0688
6.18
<.0001
4.82
.0001
Molar mannitol content, carbon content, nitrogen content, and C:N ratio were tested against initial values as covariate and interactive effects of population and heat stress temperature treatment. n = 5, n = 4 for Quiberon in carbon, nitrogen, and C:N ratio. numDF, numerator degrees of freedom; denDF, denominator degrees of freedom. denDF = 59 for carbon, nitrogen, and C:N ratio. Statistically significant values are indicated in bold text.
Biochemical chclass="Chemical">aracteristics of n class="Chemical">pan class="Species">Laminaria digitata disks after acclimation at 15°C (day 0, empty circles) and after the heat treatment (day 8, colored points). (a) Mannitol contents, (b) carbon contents, (c) nitrogen contents, (d) molar C:N ratio. Mean values ± SD (n = 5, n = 4 for Quiberon in carbon, nitrogen, and C:N ratio), except for (a) means of mean values due to extraction in triplicates. Significant differences between mean population responses are indicated by lowercase letters (Tukey tests, p < .05). Significant differences between temperature treatments within populations are indicated by dashed lines (Tukey tests, p < .05). Significance levels are given in the text
Results of generalized least squclass="Chemical">ares models to examine vn class="Chemical">ariability of biochemical characteristics of pan class="Species">Laminaria digitata disks in the heat stress experiment
Molclass="Chemical">arn class="Chemical">pan class="Chemical">mannitol content, class="Chemical">n>n class="Chemical">carbon content, nitrogen content, and C:N ratio were tested against initial values as covariate and interactive effects of population and heat stress temperature treatment. n = 5, n = 4 for Quiberon in carbon, nitrogen, and C:N ratio. numDF, numerator degrees of freedom; denDF, denominator degrees of freedom. denDF = 59 for carbon, nitrogen, and C:N ratio. Statistically significant values are indicated in bold text.
class="Chemical">n class="Chemical">Nitrogenn> contents were significantly affected by interactive effects of population and temperature (Figure 5c; Table 2). Only class="Chemical">Roscoff and Quiberon samples showed a significant decrease in nitrogen contents at high temperatures (at 23°C for Roscoff, Tukey tests, p < .05; at 21°C and 23°C for Quiberon, Tukey tests, p < .001). Compared to the 15°C control, 23°C led to a reduction in nitrogen content by 20% in Roscoff and 15% in Quiberon samples. In a pattern reverse to that of nitrogen, molar C:N ratios were significantly affected by interactive effects of population and temperature (Figure 5d; Table 2). C:N ratios in the 21°C and 23°C treatments were therefore significantly higher than in the 15°C control for Roscoff and Quiberon samples (Tukey tests, p < .05).
The model covclass="Chemical">ariate for initial values had a significant effect on all biochemical n class="Chemical">parameters taken at the end of the experiment (Table 2), in which higher initial values were correlated with higher values at the end of the heat treatment. Significant negative correlations of growth rates with n class="Chemical">mannitol (Kendall's tau = −0.5570; p < .0001; Table A4), carbon (Kendall's tau = −0.4218; p < .0001), and nitrogen contents (Kendall's tau = −0.2547, p = .0011) indicated growth at the expense of storage.
Table A4
Correlation coefficients (Kendall’s rank correlation tau) and p‐values in parentheses between relative growth rates (RGR), maximum quantum yield (Fv/Fm), biochemical, and pigment characteristics of Laminaria digitata during / after the heat treatment.
Fv/Fm
Mannitol
Carbon
Nitrogen
C:N ratio
Chl a
VAZ : Chl a
De‐epox.
RGR
0.1176 (0.0903)
−0.5570 (<0.0001)
−0.4218 (<0.0001)
−0.2547 (0.0011)
0.0337 (0.6668)
0.2013 (0.0082)
−0.2911 (0.0001)
−0.1269 (0.0979)
Fv/Fm
−0.1117 (0.1436)
0.0943 (0.2293)
0.3068 (<0.0001)
−0.3125 (<0.0001)
−0.1148 (0.1325)
−0.2828 (0.0002)
−0.3954 (<0.0001)
Mannitol
0.3691 (<0.0001)
0.1895 (0.0154)
0.0288 (0.7131)
−0.1785 (0.0191)
0.2444 (0.0014)
0.1035 (0.1769)
Carbon
0.3053 (<0.0001)
0.0758 (0.3327)
−0.0912 (0.2436)
0.1186 (0.1323)
−0.1964 (0.0127)
Nitrogen
−0.6189 (<0.0001)
−0.1418 (0.0700)
−0.0494 (0.5309)
−0.2317 (0.0033)
C : N ratio
0.0779 (0.3194)
0.1928 (0.0144)
0.1993 (0.0114)
Chl a
−0.3431 (<0.0001)
−0.0841 (0.2729)
VAZ : Chl a
0.3372 (<.0001)
n = 80, except n = 96 for the correlation of RGR and Fv/Fm due to the inclusion of Spitsbergen material. Outliers (see Section 2.2.6) were not included in the analysis and further reduced n in the following comparisons: n = 76 for comparisons involving data from C:N analysis; n = 79 for comparisons involving xanthophyll pigment data; n = 75 for comparisons involving both. Statistically significant values are indicated in bold text.
class="Chemical">n class="Chemical">Chlorophyll an> content was not significantly affected by interactive effects of population and temperature, but differed significantly between populations (Figure 6a; Table 3). Mean class="Chemical">chlorophyll a contents were significantly (24%–36%) lower in Tromsø samples than in Roscoff and Quiberon material ((QUI = ROS = HLG) > (HLG = TRO); Tukey tests, p < .05), while chlorophyll a content in Helgoland material did not differ significantly from the other populations.
Figure 6
Pigment characteristics of Laminaria digitata disks after acclimation (day 0, empty circles) and after the heat treatment (day 8, colored points). (a) Chlorophyll a contents, (b) mass ratio of xanthophyll pigments per Chlorophyll a (VAZ : Chl a ratio), (c) de‐epoxidation ratio of xanthophyll pigments. Mean values ± SD (n = 5, n = 4 for Tromsø 23°C in VAZ : Chl a ratio and de‐epoxidation ratio). Significant differences between mean population responses are indicated by lowercase letters (Tukey tests, p < .05). Significant differences between temperature treatments within populations are indicated by dashed lines (Tukey tests, p < .05). Significance levels are given in the text
Table 3
Results of generalized least squares models to examine variability of pigment characteristics of Laminaria digitata disks in the heat stress experiment
Parameter
numDF
denDF
Chl a
VAZ : Chl a ratio
De‐epoxidation ratio
F‐value
p‐value
F‐value
p‐value
F‐value
p‐value
Initial values
1
63 (62)
1.22
.2731
22.95
<.0001
95.39
<.0001
Population
3
63 (62)
9.08
<.0001
3.53
.0198
22.96
<.0001
Temperature
3
63 (62)
0.53
.6653
51.39
<.0001
42.51
<.0001
Population × temperature
9
63 (62)
1.30
.2534
2.25
.0298
6.96
<.0001
Chlorophyll a content, xanthophyll pigment (VAZ) : Chl a ratio, and de‐epoxidation ratio were tested against initial values as covariate and interactive effects of population and heat stress temperature treatment. n = 5, n = 4 for Tromsø 23°C in VAZ : Chl a ratio and de‐epoxidation ratio. numDF, numerator degrees of freedom; denDF, denominator degrees of freedom. denDF = 62 for VAZ : Chl a ratio and de‐epoxidation ratio. Statistically significant values are indicated in bold text.
Pigment chclass="Chemical">aracteristics of n class="Chemical">pan class="Species">Laminaria digitata disks after acclimation (day 0, empty circles) and after the heat treatment (day 8, colored points). (a) Chlorophyll a contents, (b) mass ratio of xanthophyll pigments per Chlorophyll a (VAZ : Chl a ratio), (c) de‐epoxidation ratio of xanthophyll pigments. Mean values ± SD (n = 5, n = 4 for Tromsø 23°C in VAZ : Chl a ratio and de‐epoxidation ratio). Significant differences between mean population responses are indicated by lowercase letters (Tukey tests, p < .05). Significant differences between temperature treatments within populations are indicated by dashed lines (Tukey tests, p < .05). Significance levels are given in the text
Results of generalized least squclass="Chemical">ares models to examine vn class="Chemical">ariability of pigment characteristics of pan class="Species">Laminaria digitata disks in the heat stress experiment
class="Chemical">n class="Chemical">Chlorophyll an> content, class="Chemical">xanthophyll pigment (VAZ) : Chl a ratio, and de‐epoxidation ratio were tested against initial values as covariate and interactive effects of population and heat stress temperature treatment. n = 5, n = 4 for Tromsø 23°C in VAZ : Chl a ratio and de‐epoxidation ratio. numDF, numerator degrees of freedom; denDF, denominator degrees of freedom. denDF = 62 for VAZ : Chl a ratio and de‐epoxidation ratio. Statistically significant values are indicated in bold text.
The mass ratio of paclass="Chemical">n class="Chemical">xanthophyll pigmentsn> per pan class="Chemical">chlorophyll a (pan class="Chemical">VAZ : Chl a ratio) was affected significantly by initial values, and interactive effects of population and temperature (Figure 6b; Table 3). Temperature had a significant, overall increasing effect on VAZ : Chl a ratios (23°C > 21°C > (19°C = 15°C), Tukey tests, p < .05), indicating accumulation of xanthophyll pigments as a photoprotective stress response toward temperature. Tromsø material significantly increased VAZ : Chl a ratios in the 21°C and 23°C treatments compared to the 15°C control (Tukey tests, p < .05) by 20% and 34%, respectively. A significant increase in VAZ : Chl a ratios became evident in the 23°C treatment compared to all other temperatures within the Roscoff (Tukey tests, p < .05) and Quiberon (Tukey tests, p < .01) populations. Compared to the 15°C control, 23°C led to an increase in VAZ : Chl a by more than 50% for both populations from Brittany, thereby presenting the strongest response in xanthophyll accumulation. In contrast, no significant differences between temperature treatments arose within the Helgoland population, further demonstrating a lack of heat stress response.
De‐epoxidation ratios of paclass="Chemical">n class="Chemical">xanthophylln> cycle pigments were affected significantly by initial values, and interactive effects of population and temperature (Figure 6c, Table 3). The significant differences between populations in mean de‐epoxidation ratios over all temperatures (Table 3) show that de‐epoxidation ratios were significantly lower in pan class="Chemical">Helgoland samples than in alpan class="Species">l other populations ((QUI = ROS = TRO) > HLG; Tukey tests, p < .01). This result supports low values for nonphotochemical quenching in Helgoland material (NPQmax; Figure A4a). Overall, higher temperatures significantly increased de‐epoxidation ratios (23°C > (21°C = 19°C) > (19°C = 15°C), Tukey tests, p < .05). The highest temperature of 23°C led to a mean increase in the de‐epoxidation ratio by a factor of 2 in Tromsø, a factor of 3 in Helgoland, a factor of 6 in Roscoff, and a factor of 4.5 in Quiberon material compared to the respective 15°C controls. However, the only significant within‐population temperature response to 23°C emerged in the Quiberon samples (Tukey tests, p < .05), showing the most pronounced heat response in the southernmost population.
class="Chemical">n class="Chemical">Chlorophyll an> content was positively correlated with growth (Kendall's tau = 0.2013; p = .0082; Table A4), while growth rates and class="Chemical">VAZ : Chl a ratios were strongly negatively correlated (Kendall's tau = −0.2911; p = .0001), indicating negative effects of the heat treatments and resulting stress responses on growth. Fv/Fm after the heat treatment was strongly negatively correlated with VAZ : Chl a ratios (Kendalls tau = −0.2828; p = .0002) and to de‐epoxidation ratios (Kendall's tau = −0.3954; p < .0001), supporting the interpretation of xanthophyll‐derived parameters as photoprotective stress proxies. Additionally, de‐epoxidation ratios positively correlated with maximum nonphotochemical quenching NPQmax (Kendall's tau = 0.2155, p = .0328), further emphasizing the relation of xanthophyll pigments and photoprotection.
Population genetics
Microsatellite amplification
Null alleles were present in every population for at least two mclass="Chemical">arkers (Table A5). However, differences between FST values in the n class="Chemical">pairwise comparison were never greater than 10–3 (data not shown). Therefore, we concluded that the frequency of null alleles was negligible and our dataset was analyzed without taking into account correction for null alleles. No significant linkage disen class="Chemical">quilibrium was observed in any of the populations (Table A6). We thus considered all of the markers as independent. The number of alleles per locus ranged from 2 to 22 (Lo454‐27 and Ld371, respectively).
Table A6
p‐values for linkage disequilibrium based on 7,920 permutations using FSTAT for each pair of markers and for each tested population of Laminaria digitata.
Spitsbergen
Tromsø
Bodø
Helgoland
Roscoff
Quiberon
All
Ld148 × Ld158
0.0601
NA
0.03169
0.72551
0.86768
0.24407
0.12702
Ld148 × Ld167
0.48548
0.22184
0.42841
0.39836
0.85303
0.08611
0.23763
Ld148 × Ld371
0.86351
0.67891
0.67071
0.97235
1.000
0.58561
0.95379
Ld148 × Ld531
0.25341
0.92727
0.03485
0.53889
0.86793
0.64343
0.53876
Ld148 × Ld704
0.63838
0.74798
0.42247
0.73977
0.99242
0.95783
0.99255
Ld148 × Lo454‐23
0.57816
0.22096
0.30152
0.04836
0.46035
0.68763
0.15758
Ld148 × Lo454‐24
0.64104
0.73687
0.28207
0.23068
0.92172
0.19432
0.56023
Ld148 × Lo454‐17
NA
0.71098
0.11995
NA
0.67348
0.49886
0.61439
Ld148 × Lo454‐27
0.89369
0.69785
0.36667
NA
NA
NA
0.63232
Ld148 × Lo454‐28
0.22159
0.43359
1.000
1.000
0.68952
0.50316
0.50682
Ld148 × Lo4‐24
0.03573
0.42323
0.42854
NA
0.54268
0.6423
0.32374
Ld158 × Ld167
0.86679
NA
0.76705
0.02525
0.64356
0.12525
0.29356
Ld158 × Ld371
0.15985
NA
0.69912
0.80833
0.52942
0.08106
0.25694
Ld158 × Ld531
0.00328
NA
0.18043
0.14495
0.9149
0.80038
0.05467
Ld158 × Ld704
0.4952
NA
0.42841
0.32866
0.43321
0.54899
0.45783
Ld158 × Lo454‐23
0.02033
NA
0.65568
0.28081
0.50934
0.01995
0.01667
Ld158 × Lo454‐24
0.87917
NA
0.64545
1.000
0.59116
0.01414
0.43258
Ld158 × Lo454‐17
NA
NA
0.06465
NA
0.22841
0.0178
0.00051
Ld158 × Lo454‐27
0.19419
NA
0.71275
NA
NA
NA
0.22614
Ld158 × Lo454‐28
0.19078
NA
1.000
0.20543
0.63182
0.65328
0.3702
Ld158 × Lo4‐24
0.70341
NA
0.87551
NA
0.67866
0.20783
0.62247
Ld167 × Ld371
0.36174
0.00025
1.000
0.34293
1.000
0.3322
0.00455
Ld167 × Ld531
0.05758
0.56717
0.55909
0.04444
0.40821
0.97942
0.13775
Ld167 × Ld704
0.83005
0.60568
0.95101
0.2303
0.99886
0.00379
0.80126
Ld167 × Lo454‐23
0.18662
0.69457
0.38965
0.05707
0.13788
0.26174
0.05972
Ld167 × Lo454‐24
0.30391
0.91503
0.85732
1.000
0.71831
0.03157
0.51402
Ld167 × Lo454‐17
NA
0.69116
0.33434
NA
0.79356
0.16944
0.3524
Ld167 × Lo454‐27
0.92083
0.32462
0.25682
NA
NA
NA
0.58106
Ld167 × Lo454‐28
0.34066
1.000
0.35177
0.49015
0.36124
0.86629
0.43093
Ld167 × Lo4‐24
0.47664
0.32159
0.68194
NA
0.85593
0.09508
0.4077
Ld371 × Ld531
0.76705
0.26389
0.40669
0.72311
0.58157
0.36275
0.47146
Ld371 × Ld704
0.84331
0.36035
0.50631
0.46111
0.11136
0.25328
0.27121
Ld371 × Lo454‐23
0.89356
0.8221
0.68662
0.1923
1.000
0.95732
0.84381
Ld371 × Lo454‐24
0.83624
0.32134
0.31301
0.40543
0.94672
0.04836
0.29495
Ld371 × Lo454‐17
NA
0.31957
0.77841
NA
0.84066
0.1779
0.3404
Ld371 × Lo454‐27
0.35467
0.23144
0.92778
NA
NA
NA
0.45985
Ld371 × Lo454‐28
0.4375
0.57008
0.60114
1.000
0.89609
0.0928
0.37576
Ld371 × Lo4‐24
0.42058
0.2971
0.53636
NA
0.775
0.1327
0.22071
Ld531 × Ld704
0.81288
0.81149
0.12412
0.38674
0.15543
0.61932
0.36818
Ld531 × Lo454‐23
0.07538
0.13788
0.54545
0.84091
0.11351
0.06641
0.03737
Ld531 × Lo454‐24
0.19268
0.92639
0.82361
1,000
0.59975
0.55025
0.81225
Ld531 × Lo454‐17
NA
0.84457
0.15303
NA
0.97071
0.49293
0.71755
Ld531 × Lo454‐27
0.47929
0.31073
0.73043
NA
NA
NA
0.31742
Ld531 × Lo454‐28
0.34861
1.000
1.000
1.000
0.30404
0.90366
0.75455
Ld531 × Lo4‐24
0.52273
0.57109
0.19495
NA
0.12828
0.91831
0.5899
Ld704 × Lo454‐23
0.50972
0.00947
0.53687
0.19646
0.44167
0.7471
0.13674
Ld704 × Lo454‐24
0.4298
0.14419
0.69066
1.000
0.72083
0.80783
0.59609
Ld704 × Lo454‐17
NA
0.68649
0.74924
NA
1.000
0.67487
0.92891
Ld704 × Lo454‐27
0.11439
0.72702
0.63068
NA
NA
NA
0.41111
Ld704 × Lo454‐28
0.24886
1.000
0.52702
1,000
0.44937
0.15909
0.32626
Ld704 × Lo4‐24
0.70265
0.45909
0.84861
NA
1.000
0.67361
0.88182
Lo454‐23 × Lo454‐24
0.92702
0.65505
0.90543
0.65492
0.51919
0.31389
0.86705
Lo454‐23 × Lo454‐17
NA
0.4721
0.34811
NA
0.83005
0.6101
0.70707
Lo454‐23 × Lo454‐27
0.47083
0.65593
0.36629
NA
NA
NA
0.54091
Lo454‐23 × Lo454‐28
0.69482
0.72866
0.34167
0.06098
0.74419
0.9197
0.76465
Lo454‐23 × Lo4‐24
0.35202
0.8721
0.85316
NA
0.55833
0.36427
0.81338
Lo454‐24 × Lo454‐17
NA
0.21427
1.000
NA
0.96174
0.09684
0.32399
Lo454‐24 × Lo454‐27
0.23636
0.75164
1.000
NA
NA
NA
0.82412
Lo454‐24 × Lo454‐28
1,000
1,000
0.21465
1.000
0.89381
0.88232
0.96944
Lo454‐24 × Lo4‐24
0.11982
0.37437
0.07917
NA
0.40707
0.09482
0.02134
Lo454‐17 × Lo454‐27
NA
0.72412
1.000
NA
NA
NA
0.77513
Lo454‐17 × Lo454‐28
NA
1.000
1.000
NA
0.23914
0.63902
0.61717
Lo454‐17 × Lo4‐24
NA
0.6721
1.000
NA
0.1197
0.00745
0.05101
Lo454‐27 × Lo454‐28
0.02109
0.06742
1.000
NA
NA
NA
0.00303
Lo454‐27 × Lo4‐24
0.86869
0.84432
1.000
NA
NA
NA
0.98295
Lo454‐28 × Lo4‐24
0.51023
1.000
0.50189
NA
1.000
0.41717
0.70063
Microsatellite loci published for Laminaria digitata (Ld; Billot et al., 1998) and Laminaria ochroleuca (Lo; Coelho et al., 2014). The p‐value after multiple testing correction for 5% nominal level is 0.000126. No linkage disequilibrium is significant in the dataset.
Values of genetic diversity averaged over the 12 loci class="Chemical">are provided in Table 4 for each population (for details of genetic diversity estimates locus by locus see Table A7). Most quantities vn class="Chemical">aried by a factor of 1.5 among populations; the lowest genetic diversity was always observed in n class="Chemical">Helgoland and the highest in Roscoff. Variation was the highest for the mean number of private alleles (Pa) which ranged from 0.083 to 0.583. The differences between populations were not significant when each parameter was tested independently (one‐way ANOVA, data not shown). However, a Fisher test of pairwise differences between means revealed that AR and Pa were significantly lower in Helgoland compared to Roscoff (data not shown). In addition, three of the twelve loci were monomorphic in Helgoland, compared to the other populations, in which a maximum of one monomorphic locus was observed (Table A7).
Table 4
Genetic characteristics of the Laminaria digitata populations used in the heat stress experiment
Population
Year
n
Na
AR
Pa
He
Ho
FIS
Spitsbergen
2019
26
3.667 ± 0.620
3.494 ± 0.427
0.250 ± 0.131
0.436 ± 0.069
0.362 ± 0.058
0.127 ± 0.054
Tromsø
2018
30
3.583 ± 0.596
3.447 ± 0.422
0.250 ± 0.131
0.363 ± 0.074
0.350 ± 0.073
0.051 ± 0.055
Bodø
2018
32
4.833 ± 1.065
4.464 ± 0.699
0.500 ± 0.195
0.444 ± 0.088
0.376 ± 0.077
0.117 ± 0.033 *
Helgoland
2016
35
2.833 ± 0.638
2.594 ± 0.422
0.083 ± 0.083
0.306 ± 0.076
0.296 ± 0.078
0.039 ± 0.032
Roscoff
2018
28
5.167 ± 1.120
4.875 ± 0.786
0.583 ± 0.229
0.480 ± 0.082
0.429 ± 0.083
0.171 ± 0.044 *
Quiberon
2018
28
4.583 ± 0.773
4.186 ± 0.511
0.333 ± 0.142
0.432 ± 0.061
0.408 ± 0.067
0.106 ± 0.035
Year: year of the samples used for genetic analysis (except for Helgoland, the genotyped individuals are the same than those analyzed for the heat stress experiment); n, number of individuals for which at least 11 markers amplified; Na, mean number of observed alleles; AR, allelic richness standardized for equal sample size (21 individuals); Pa, mean number of private alleles per locus; He, expected heterozygosity; Ho, observed heterozygosity; FIS, fixation index (inbreeding coefficient) of individuals with respect to local subpopulation. All parameters are expressed as means over all markers ± standard error. *, significant departure from random mating after correction for multiple testing (p < .0069, FSTAT).
Table A7
Estimates of genetic diversity and deviation from random mating for each locus and each population of Laminaria digitata tested in this study.
Population
Locus
n
Na
AR
Pa
He
Ho
FIS
Spitsbergen
Ld148
26
3
2.808
0
0.212
0.231
−0.110
Ld158
25
4
4
1
0.709
0.200
0.712
Ld167
26
5
4.802
1
0.714
0.615
0.121
Ld371
26
9
8.355
0
0.796
0.500
0.360
Ld531
26
3
2.966
1
0.520
0.308
0.396
Ld704
21
2
2
0
0.136
0.143
−0.077
Lo454‐23
26
5
4.61
0
0.531
0.615
−0.182
Lo454‐24
26
5
4.581
0
0.281
0.231
0.164
Lo454‐17
26
1
1
0
0.000
0.000
#NV
Lo454‐27
26
2
2
0
0.510
0.538
−0.077
Lo454‐28
26
3
2.808
0
0.446
0.500
−0.144
Lo4‐24
26
2
2
0
0.483
0.462
0.025
Tromsø
Ld148
30
3
3
0
0.603
0.800
−0.350
Ld158
30
1
1
0
0.000
0.000
#NV
Ld167
30
4
3.883
1
0.274
0.300
−0.113
Ld371
30
9
8.456
1
0.793
0.367
0.530
Ld531
30
3
2.89
0
0.159
0.167
−0.068
Ld704
30
4
3.89
0
0.393
0.467
−0.209
Lo454‐23
30
5
4.614
0
0.667
0.600
0.086
Lo454‐24
30
4
3.976
0
0.444
0.500
−0.146
Lo454‐17
30
2
2
0
0.398
0.400
−0.023
Lo454‐27
30
2
1.976
0
0.097
0.033
0.649
Lo454‐28
30
2
1.7
1
0.033
0.033
−0.017
Lo4‐24
30
4
3.975
0
0.569
0.533
0.047
Bodø
Ld148
32
4
3.963
1
0.634
0.438
0.299
Ld158
32
3
2.882
0
0.203
0.188
0.061
Ld167
31
8
7.664
2
0.839
0.839
−0.016
Ld371
31
15
12.946
1
0.871
0.613
0.285
Ld531
32
3
2.874
0
0.177
0.156
0.101
Ld704
32
5
4.884
1
0.684
0.688
−0.021
Lo454‐23
32
6
5.538
0
0.635
0.313
0.500
Lo454‐24
32
5
4.542
1
0.590
0.438
0.246
Lo454‐17
32
2
1.656
0
0.031
0.031
−0.016
Lo454‐27
32
2
1.999
0
0.173
0.188
−0.103
Lo454‐28
32
2
1.656
0
0.031
0.031
−0.016
Lo4‐24
32
3
2.963
0
0.549
0.594
−0.098
Helgoland
Ld148
34
2
2
0
0.504
0.500
−0.008
Ld158
35
3
2.6
1
0.520
0.600
−0.169
Ld167
35
4
3.687
0
0.512
0.600
−0.189
Ld371
35
9
7.861
0
0.618
0.657
−0.078
Ld531
35
4
3.937
0
0.493
0.314
0.353
Ld704
35
2
2
0
0.487
0.457
0.048
Lo454‐23
35
3
2.843
0
0.535
0.371
0.295
Lo454‐24
35
2
1.6
0
0.029
0.029
−0.014
Lo454‐17
35
1
1
0
0.000
0.000
#NV
Lo454‐27
35
1
1
0
0.000
0.000
#NV
Lo454‐28
35
2
1.6
0
0.029
0.029
−0.014
Lo4‐24
35
1
1
0
0.000
0.000
#NV
Roscoff
Ld148
28
7
6.678
2
0.782
0.750
0.023
Ld158
28
4
3.749
1
0.477
0.250
0.466
Ld167
28
7
6.718
2
0.727
0.643
0.100
Ld371
28
15
14.025
0
0.906
0.893
−0.003
Ld531
28
4
3.997
0
0.658
0.571
0.115
Ld704
28
4
3.691
0
0.475
0.429
0.081
Lo454‐23
28
9
8.211
1
0.779
0.714
0.067
Lo454‐24
28
4
3.737
1
0.410
0.286
0.290
Lo454‐17
28
2
2
0
0.299
0.357
−0.217
Lo454‐27
28
1
1
0
0.000
0.000
#NV
Lo454‐28
28
2
2
0
0.249
0.214
0.125
Lo4‐24
28
3
2.691
0
0.105
0.036
0.652
Quiberon
Ld148
28
6
5.497
0
0.664
0.643
0.014
Ld158
28
3
2.941
0
0.257
0.143
0.434
Ld167
28
5
4.441
0
0.318
0.321
−0.031
Ld371
28
11
9.927
1
0.836
0.786
0.043
Ld531
28
4
3.737
0
0.497
0.500
−0.023
Ld704
28
3
2.75
0
0.408
0.321
0.199
Lo454‐23
28
7
6.191
1
0.519
0.536
−0.050
Lo454‐24
28
6
5
1
0.344
0.321
0.047
Lo454‐17
28
4
3.999
1
0.603
0.607
−0.025
Lo454‐27
28
1
1
0
0.000
0.000
#NV
Lo454‐28
28
2
2
0
0.503
0.536
−0.084
Lo4‐24
28
3
2.75
0
0.328
0.179
0.446
Locus, microsatellite loci published for Laminaria digitata (Ld; Billot et al., 1998) and Laminaria ochroleuca (L
o; Coelho et al., 2014); n, number of individuals for which the marker amplified; Na, number of observed alleles; AR, allelic richness standardized for equal sample size (21 individuals); Pa, number of private alleles per locus; He, expected heterozygosity; Ho, observed heterozygosity; FIS, fixation index (inbreeding coefficient) of individuals with respect to local subpopulation; #NV, no calculation of FIS in monomorphic loci. Note that in Helgoland, Roscoff and Quiberon, the locus Lo454‐27 is fixed while it is polymorphic for Spitsbergen, Tromsø and Bodø. This explains why this locus was not included in the study of Robuchon et al. (2014).
Genetic chclass="Chemical">aracteristics of the n class="Chemical">pan class="Species">Laminaria digitata populations used in the heat stress experiment
Yeclass="Chemical">ar: yen class="Chemical">ar of the samples used for genetic analysis (except for pan class="Chemical">Helgoland, the genotyped individuals are the same than those analyzed for the heat stress experiment); n, number of individuals for which at least 11 markers amplified; Na, mean number of observed alleles; AR, allelic richness standardized for equal sample size (21 individuals); Pa, mean number of private alleles per locus; He, expected heterozygosity; Ho, observed heterozygosity; FIS, fixation index (inbreeding coefficient) of individuals with respect to local subpopulation. All parameters are expressed as means over all markers ± standard error. *, significant depan>rture from random mating after correction for multiple testing (p < .0069, FSTAT).
Genetic structure
Genetic differentiation was significant for each class="Chemical">pairwise population comn class="Chemical">parison (p = .003 for all pairs; FSTAT) with an average FST value of 0.3795 (Table A8), while the strongest differentiation occurred between n class="Chemical">Helgoland and Tromsø and the weakest between Helgoland and Roscoff. Structure analyses results show that the optimal number of genetic clusters was K = 2 according to the method of Evanno et al. (2005) (Figure A5). We detected a clear hierarchical distinction in genetic structure between two groups (Figure 7a) of northern populations (Spitsbergen, Tromsø, Bodø) and southern populations (Helgoland, Roscoff, Quiberon). A subsequent analysis run separately for northern and southern populations revealed distinct structuring between the three populations present in each subset (Figure 7b,c; K = 3). While gene flow between populations is generally very weak, the relatively highest connectivity occurred between the adjacent Roscoff and Quiberon populations. Additionally, a difference between northern and southern populations is visible at Lo454‐27 (Table A7), where one allele is fixed for all southern populations.
Table A8
Fixation index (FST) for each pair of the Laminaria digitata populations tested in this study
Tromsø
Bodø
Helgoland
Roscoff
Quiberon
Spitsbergen
0.422
0.344
0.468
0.338
0.444
Tromsø
0.293
0.582
0.466
0.520
Bodø
0.442
0.319
0.385
Helgoland
0.156
0.352
Roscoff
0.162
All p‐values obtained with 300 permutations using FSTAT were 0.003 and therefore significant (the p‐value corrected for multiple testing is .003).
Figure A5
ΔK (Evanno et al., 2005) plotted against K, associated with K = 2 to K = 5 obtained with Structure Harvester during the analysis of genetic structure of Laminaria digitata populations
Figure 7
Structure bar plot of Laminaria digitata populations along the entire distribution range. (a) First hierarchical level of structure obtained for K = 2 genetic clusters. (b) Second hierarchical level of structure for northern populations and (c) second hierarchical level of structure for southern populations of L. digitata obtained for K = 3 genetic clusters. Individuals (vertical bars) were assigned probabilities of belonging to clusters (colors) based on differences in genetic variance
Structure bclass="Chemical">ar plot of n class="Chemical">pan class="Species">Laminaria digitata populations along the entire distribution range. (a) First hierarchical level of structure obtained for K = 2 genetic clusters. (b) Second hierarchical level of structure for northern populations and (c) second hierarchical level of structure for southern populations of L. digitata obtained for K = 3 genetic clusters. Individuals (vertical bars) were assigned probabilities of belonging to clusters (colors) based on differences in genetic variance
Reproductive system
class="Chemical">n class="Species">L. digitatan> from Tromsø and class="Chemical">Helgoland did not show any significant departure from random mating (FIS). We identified FIS > 0.1 for Spitsbergen, Bodø, Roscoff, and Quiberon, (Table 4 for multilocus estimates of FIS; Table A7 for single locus estimates of FIS). However, when p‐values were corrected for multiple testing (p < .0069, FSTAT), heterozygote deficiency was significant only for Bodø and Roscoff.
DISCUSSION
We identified a uniform growth limit acpaclass="Chemical">n class="Chemical">rosn>s European pan class="Species">Laminaria digitata populations following a short‐term application of 23°C, which conforms with previous studies (Bolton & Lüning, 1982; tom Dieck, 1992). Despite this, we observed slight deviations in magnitude and onset of stress responses among pan class="Species">L. digitata populations at the cold and warm range margins. Arctic Spitsbergen material presented the strongest heat stress reaction. On the other hand, the two populations naturally experiencing summer temperatures near their upper long‐term survival limit, Helgoland and Quiberon, showed moderate advantages in stress responses and growth during the heat treatments. We therefore provide further evidence for the existence of thermal ecotypes of L. digitata (King et al., 2019) across the species’ entire Northeast Atlantic distribution. The strong genetic structuring of L. digitata within northern and southern clades might have facilitated phenotypic divergence, while neutral genetic diversity was not connected to clear patterns of genetic drift or maladaptation along L. digitata's latitudinal distribution.
Similarities in growth and biochemical responses along the latitudinal gradient
Growth responses among our tested populations suggest that the upper temperature tolerance limit of paclass="Chemical">n class="Species">Laminn class="Chemical">aria digitata is uniform along its European latitudinal distribution. Growth is an integrative pan>rameter of all metabolic processes and can thus be interpreted as a proxy for organismal stress response. We observed that growth almost completely ceased in the 23°C treatment for all populations (Figure 3), while all populations showed signs of recovery from 21°C when transferred to 15°C (Figure A1). The populations of Tromsø and Spitzbergen showed significantly lower overall growth rates than the southern populations. The lower growth rates of the Arctic populations might be related to prevailing local environmental conditions during sampling (e.g., long day lengths, copan class="Species">ld temperature) which may influence growth rates and circannual rhythmicity in kelps (Olispan class="Chemical">chläger & Wiencke, 2013; Schaffelke & Lüning, 1994). Still, results of our study using meristematic disks of wild adult L. digitata material support previous studies using laboratory‐cultivated whole juvenile L. digitata sporophytes, which also showed uniform upper temperature limits on both sides of the Atlantic and Spitsbergen (Bolton & Lüning, 1982; Franke, 2019; tom Dieck, 1992).
The definition of thermal limits acpaclass="Chemical">n class="Chemical">rosn>s populations strongly depends on the experimental design (e.g., cultivation conditions and sample age, among other independent variables) and on the response variables measured. Previous studies using photosynthesis (pan class="Chemical">Helgoland: Lüning, 1984) and tissue damage (pan class="Disease">Nova Scotia: Simonson et al., 2015) as proxies defined the upper thermal tolerance of wildL. digitata sporophytes at 18°C to 20°C in experiments that lasted one week. Higher temperatures of 21°C (Simonson et al., 2015) and 23°C (Lüning, 1984) were lethal. However, common‐garden experiments demonstrated the capacity for cultivated and wild juvenile L. digitata sporophytes from these locations to survive temperatures >20°C for at least one week using growth and occurrence of tissue bleaching as proxies (Helgoland and Nova Scotia: Bolton & Lüning, 1982; tom Dieck, 1992; Nova Scotia: Wilson et al., 2015). Physiological responses may also differ depending on the treatment duration. Whereas maximum quantum yield (Fv/Fm) of Southern English L. digitata decreased over a period of 16 days at 18°C (Hargrave et al., 2017), Fv/Fm was stable at 19°C over a shorter period of seven days in our experiment. Still, the reduced growth at 18°C in Hargrave et al. (2017) matches the decrease in growth at 19°C in our study. Thus, uniformity or differences in thermal limits among populations can only be reliably assessed under common‐garden conditions, for example, as performed here.
In addition to the strong similclass="Chemical">arities in the upper thermal limits of growth in our study, n class="Chemical">pan class="Chemical">carbon contents (Figure 5b) and chlorophyll a contents (Figure 6a) did not differ between temperature treatments at all. In contrast, the overall trend of increasing mannitol contents at high temperatures (Figure 5a) has been described for Saccharina latissima (Davison & Davison, 1987) and might be linked to the seasonal increase in kelp mannitol storage in summer during the period of slow growth (Haug & Jensen, 1954; Schiener et al., 2015), which, in wild sporophytes, is followed by a peak of the long‐term storage compound laminarin in autumn (Haug & Jensen, 1954; Schiener et al., 2015).
The consistent responses of growth and biochemical contents acpaclass="Chemical">n class="Chemical">rosn>s populations reported here indicate a strong acclimation potentiapan class="Species">l of pan class="Species">L. digitata's metabolism to high temperature. Acclimation to wide temperature ranges would reduce selective pressure of temperature in the wild and might explain the small magnitude of local differentiation observed in this study.
Differences in growth and photosynthetic parameters among marginal populations
Despite the stability of the upper thermal growth limit, we observed subtle physiological differences in the common‐gclass="Chemical">arden heat stress experiment, mainly in the mn class="Chemical">arginal populations of Spitsbergen, n class="Chemical">Helgoland, and Quiberon. Maximum quantum yield of photosystem II was most sensitive to thermal stress at 21°C and 23°C in Spitsbergen material (Figure 4; Figure A2). This is concordant with the subarctic to Arctic regional climate and provides first evidence for a loss of function in a leading‐edge L. digitata population, but whether this represents an adaptive trait is yet unknown. Generally, very few cold‐temperate algae occurring in the Arctic show true adaptations to the Arctic climate compared to their Atlantic populations (Bischoff & Wiencke, 1993; Wiencke et al., 1994), possibly because the Arctic did not provide a sufficiently stable environment for adaptive evolutionary processes to occur (Wiencke et al., 1994).
At the southern range edge, a slight advantage of paclass="Chemical">n class="Chemical">Quin>beron material to grow at elevated temperatures became evident in the growth response at 19°C during the heat treatment, and in the full recovery from the 21°C treatment (Figure 3; Figure A1). In contrast, photoacclimative responses suggest that the marginal population on the island of pan class="Chemical">Helgoland was most resistant to heat stress. Photosystem II of pan class="Chemical">Helgoland material was minimally impaired by 23°C (Figure 4). Additionally, reactions of xanthophyll pigments (Figure 6b,c) were significantly weaker in Helgoland material than other populations. Increased xanthophyll contents may indicate a photoprotective acclimation reaction (Latowski, Kuczyńska, & Strzałka, 2011; Pfündel & Bilger, 1994; Uhrmacher et al., 1995), while the de‐epoxididation ratio of xanthophyll cycle pigments represents the current capacity to quench excessive energy from the photosystem (Pfündel & Bilger, 1994). Helgoland material did not show a significant increase in xanthophyll pigments and presented significantly lower de‐epoxidation ratios and therefore lower nonphotochemical quenching (NPQmax, Figure A4) than all other populations. Therefore, the two populations growing in the warmest of the tested locations, which may experience >4 week long periods of mean in situ temperatures of 18°C to 19°C in summer (Helgoland: Bartsch, Vogt, Pehlke, & Hanelt, 2013; Wiltshire et al., 2008; Quiberon: Oppliger et al., 2014; Valero, unpubl.), showed slight physiological advantages to short‐term heat exposure in growth and stress responses.
The southernmost populations of paclass="Chemical">n class="Chemical">Quin>beron and pan class="Chemical">Roscoff were curiously the only populations with significantly reduced tissue pan class="Chemical">nitrogen contents in the heat treatments (Figure 5c). A variety of factors including temperature affects nutrient uptake and consequently tissue nitrogen contents, which could be species‐specific (Roleda & Hurd, 2019). Therefore, published studies on the impacts of heat stress on nitrogen uptake and storage in kelps differ in their reports of decreased (Gerard, 1997), unaffected (Nepper‐Davidsen et al., 2019), or increased nitrogen contents (Wilson et al., 2015). Whether the underlying cause of reduced nitrogen during heat in our study is adaptive, maladaptive, or neutral toward heat resilience in the southern populations remains unclear until further investigation.
Population genetics in relation to physiological thermal responses
Population genetics suggest that the slight phenotypic divergence of paclass="Chemical">n class="Species">L. digitatan> might have been facilitated through phylogeographic separation into two clades and low genetic connectivity between populations. The hierarchical division into a northern and a southern clade in the Northeast Atlantic (Figure 7a) is likely due to postglacial recolonization by two distinct genetic groups located in refugia proposed for the Armorican/Celtic Sea (Brittany and South West UK) and a potential northern refugium at the west coast of Ireland and/or Scotland (Neiva et al., 2020; see also King et al., 2020). Currently, the highest genetic diversity (He ≥ 0.6) published for L. digitata populations was observed in Scotland (King et al., 2019, 2020), Northwest Ireland (Neiva et al., 2020), and Northeast Ireland (Brennan et al., 2014), which all exceeded the genetic diversity of the populations investigated in this study. Due to a lack of data, it remains unclear whether a potential glacial refugium of class="Species">L. digitata also corresponds to the well‐described Southwest Ireland refugium proposed for many marine species (Kettle, Morales‐Muñiz, pan class="Chemical">Roselló‐Izquierdo, Heinrich, & Vøllestad, 2011; Provan & Bennett, 2008).
Populations at the “leading edge” (high latitude) class="Chemical">are said to be associated with low genetic diversity due to recolonization processes following the Last Glacial Maximum (Hampe & Petit, 2005; for mn class="Chemical">arine seaweeds of the North Atlantic see Assis, Serrão, Claro, Perrin, & Pearson, 2014; Neiva et al., 2016; Provan & Maggs, 2012). Therefore, effects of genetic drift (e.g., depleted genetic diversity, increased inbreeding) may be expected to reduce physiological function in these populations. Here, genetic diversity characteristics of n class="Species">L. digitata at its northern range limit (i.e., Spitsbergen) were not significantly lower compared to the other populations in this study and were similar to other Northern Norwegian populations (Neiva et al., 2020). A similar pattern was observed for another Arctic to cold‐temperate kelp species, Saccharina latissima (Guzinski, Mauger, Cock, & Valero, 2016). Therefore, rather than effects of genetic drift, a lack of selection pressure in the Arctic might have led to a potential reduction of heat tolerance at the northern distribution limit (i.e., relaxed selection; Lahti et al., 2009; Zhen & Ungerer, 2008).
Probably due to the continuous rocky substrata along the Brittany coast, connectivity may be maintained between paclass="Chemical">n class="Chemical">Quin>beron and neighboring populations, which may explain a certain levepan class="Species">l of gene flow between Roscoff and Quiberon via stepping stone habitats (Figure 7c). Low gene flow can reduce inbreeding depression and associated deleterious effects and may facilitate local adaptation at this southern range edge (Fitzpatrick & Reid, 2019; Sanford & Kelly, 2011). Genetic diversity characteristics for Brittany L. digitata populations in this study comply with previous reports (Oppliger et al., 2014; Robuchon et al., 2014). Compared to Roscoff, genetic diversity of L. digitata from the island of Helgoland was significantly lower. The population's reduced genetic diversity can be partly explained by genetic isolation due to habitat discontinuity as Helgoland is a rocky substrate surrounded by continuous sandy seafloor (Reichert, Buchholz, & Giménez, 2008). This may rather suggest maladaptation due to less effective selection (such as in Fucus serratus; Pearson et al., 2009). However, samples from Helgoland presented the weakest heat stress response in this study. Therefore, we can hypothesize either that historically greater diversity/connectivity was reduced via isolation and drift after resilience to local conditions was established, or that strong selective forces toward the upper thermal limit of L. digitata have counterbalanced the effect of genetic drift.
Significant declass="Chemical">partures from random mating were only observed for the populations of Bodø and n class="Chemical">pan class="Chemical">Roscoff (FIS; Table 4) and match the magnitude of recent descriptions for class="Chemical">n>n class="Species">L. digitata populations (King et al., 2020; Neiva et al., 2020). The higher FIS values in Roscoff L. digitata in our study compared to the nearby population of Santec (Robuchon et al., 2014) might be explained by the distance of >1 km between sites, which may already cause substantial variation in FIS (Billot, Engel, Rousvoal, Kloareg, & Valero, 2003). In contrast, the higher FIS values of Quiberon L. digitata in our study compared to Oppliger et al. (2014) who sampled at the same location (Pointe de Conguel North) may be an artifact of differing microsatellite markers or might indicate a change in the reproductive system over time (Oppliger et al., 2014; Valero et al., 2011). In all cases, in the absence of data on reproductive ecology, the underlying causes remain speculative.
Outlook
The mechanistic temperature treatments applied in this study do not represent realistic temperature scenclass="Chemical">arios for all tested populations, especially class="Chemical">not for the class="Chemical">northern clade. However, during our sampling period in August 2018, acute heat spikes surn class="Chemical">passed 20°C on twelve days on n class="Chemical">Helgoland, and on nine days in Quiberon in the shallow sublittoral (in situ data; Bartsch, unpubl.; Valero, unpubl.). Also in South England, L. digitata already encounters marine heatwaves reaching 20°C (Burdett, Wright, & Smale, 2019; Joint & Smale, 2017). According to predictions of ocean warming (Müller et al., 2009) and marine heatwaves (Oliver et al., 2018), L. digitata will possibly encounter prolonged summer periods of 21°C–23°C at its warm distribution limit until the end of the century.
As a low intertidal to shallow sublittoral species, paclass="Chemical">n class="Species">L. digitatan> is not only threatened by increasing summer SST and marine heatwaves (Bartsch et al., 2013; Hargrave et al., 2017), but also by other stressors during emersion such as desiccation and warm air temperature (Hereward, King, & Smale, 2020; King, Wilcockson, et al., 2018), high irradiance, and UV radiation (Gruber, Roleda, Bartsch, Hanelt, & Wiencke, 2011; Roleda, Hanelt, & Wiencke, 2006). These multiple stressors are most likely responsible for the die‐off event of pan class="Chemical">Helgoland pan class="Species">L. digitata sporophytes after exposure to SST > 19°C over a prolonged period of 11 days (Bartsch et al., 2013). Additionally, rising temperatures may negatively affect sporophyte and gametophyte reproduction (sporogenesis: Bartsch et al., 2013; gametogenesis: Lüning, 1980; Martins, Tanttu, Pearson, Serrão, & Bartsch, 2017) which might contribute to range contractions of L. digitata. Therefore, despite the slight physiological advantages we identified in the southern populations, L. digitata is threatened by a substantial loss of genetic diversity at its current southern distribution limit (King et al., 2020; Neiva et al., 2020; Oppliger et al., 2014; Robuchon et al., 2014).
Models have predicted a northwclass="Chemical">ard shift of the entire distribution range of n class="Chemical">pan class="Species">L. digitata until 2100 in the RCP 8.5 emission scenario, implying possible extinction of southern populations, including class="Chemical">n>n class="Chemical">Roscoff and Quiberon (Assis et al., 2018; Raybaud et al., 2013). A potential loss of more heat‐tolerant populations at the trailing edge and a simultaneous expansion of northern, slightly less heat‐tolerant L. digitata phenotypes implies that global warming might drive a decrease in the overall adaptive capacity to warming in the kelp Laminaria digitata. Neutral genetic diversity was recently described as an indicator for heat resilience of kelp populations by indicating physiological versatility among individuals (Wernberg et al., 2018). Conversely, marine heatwaves can deplete the genetic diversity of kelp populations in strong selective bottleneck events (Gurgel, Camacho, Minne, Wernberg, & Coleman, 2020). Therefore, response variability among individuals shapes the adaptive capacity of populations to withstand bottleneck events and to allow directional selection (Chevin, Lande, & Mace, 2010; Kelly, 2019; King, McKeown, et al., 2018). This implies that genetically depleted populations (e.g., marginal populations) are at even higher risk of extinction. A recent study showed high phenotypic variation among five genotypes of HelgolandL. digitata (Liesner et al., 2020), but studies correlating inter‐individual response variation to genetic diversity across populations are necessary to investigate the implications of genetic diversity for population resilience during climate change.
CONFLICT OF INTEREST
All authors declclass="Chemical">are that they n class="Chemical">are free of competing interests.
Authors: Samuel Starko; Marybel Soto Gomez; Hayley Darby; Kyle W Demes; Hiroshi Kawai; Norishige Yotsukura; Sandra C Lindstrom; Patrick J Keeling; Sean W Graham; Patrick T Martone Journal: Mol Phylogenet Evol Date: 2019-04-10 Impact factor: 4.286
Authors: Katy R Nicastro; Gerardo I Zardi; Sara Teixeira; João Neiva; Ester A Serrão; Gareth A Pearson Journal: BMC Biol Date: 2013-01-23 Impact factor: 7.431
Authors: Luz Valeria Oppliger; Peter von Dassow; Sarah Bouchemousse; Marine Robuchon; Myriam Valero; Juan A Correa; Stéphane Mauger; Christophe Destombe Journal: PLoS One Date: 2014-07-14 Impact factor: 3.240
Figure 1
Figure 2
Figure 3
Figure A1
Figure 4
Figure A2
Figure A3
Figure A4
Figure 5
Figure 6
Figure A5
Figure 7