Herbivorous zooplankton channel the energy from microalgal primary producers to primary carnivores and play many roles in the oceanic carbon cycle (Hobson et al., 2002; Wassmann et al., 2006; Darnis and Fortier, 2012). In Arctic seas, copepods dominate the zooplankton with the primarily herbivorous genus Calanus accounting for up to 80% of mesozooplankton biomass (Søreide et al., 2008; Darnis and Fortier, 2012). Among several adaptations to the extreme seasonality of the arctic pelagic ecosystem, C. hyperboreus and C. glacialis extract and accumulate large lipid reserves from ice microalgae and phytoplankton during a short grazing season in late spring and summer (Falk-Petersen et al., 2007; Søreide et al., 2010; Wassmann, 2011; Daase et al., 2013). By making the energy captured during the short microalgal bloom available to higher trophic levels over the rest of the year, this build-up of lipid reserves by copepods is a pivotal process in arctic ecosystems (e.g., Falk-Petersen et al., 2009). By feeding fish, marine mammals and seabirds, copepod lipids underpin much of the ecosystem services provided to northern communities (Darnis et al., 2012).
Like many arctic zooplankton species, Calanus hyperboreus and C. glacialis complete a seasonal vertical migration (SVM) from their autumn-winter position at depth towards the productive surface layer in spring and summer (Dawson, 1978; Hirche, 1997; Ashjian et al., 2003; Darnis and Fortier, 2014). In ice-covered waters and in open waters during the period of day-night succession in spring and autumn, limited diel vertical migrations (DVM) superimpose on the SVM of the two species (e.g., Fortier et al., 2001; Daase et al., 2015; Darnis et al., 2017). Consistent with the Predator Avoidance Hypothesis (e.g., Lampert, 1989), feeding at night in the food-rich surface layer and migrating to depth in daytime would enable Calanus copepods to avoid visual predators such as seabirds and fish (Runge and Ingram, 1991; Fortier et al., 2001).
The interactions among zooplankton grazers, their microalgal food and their predators, at scales of decimeters to several meters during the short feeding migration to the surface layer in spring–summer, likely dictate the efficiency of lipid transfer in the arctic marine food web (Darnis et al., 2012; Durham and Stocker, 2012; Schmid et al., 2018). Elucidating these interactions may provide crucial insights into how ongoing changes in the sea-ice, turbulence, and temperature regimes of the summer surface layer may disrupt the pelagic ecosystem of Arctic seas (Falk-Petersen et al., 2007; Søreide et al., 2010; Darnis et al., 2012). The vertical resolution of traditional zooplankton sampling systems is generally insufficient to describe zooplankton distribution at these scales. Using ground-breaking technologies at the time, Herman (1983) showed how, in northwestern Baffin Bay in late July and early August, the copepodite stage C5 of Calanus hyperboreus distributed in the subsurface chlorophyll maximum (SCM), while C. glacialis C5 and C. finmarchicus C5 on average distributed above the SCM, presumably at the depth of maximum phytoplankton productivity.
The Lightframe Onsight Key-species Investigation (LOKI) optical profiler (Schultz et al., 2010; Schmid et al., 2016) captures the fine-scale vertical distribution of mesozooplankton. The optical resolution of images is sufficient for either visual (Schulz et al., 2010; Hirche et al., 2014) or computer-assisted (Schmid et al., 2016, 2018) taxonomic identification of zooplankton organisms. Computer-assisted identification has the advantage that large quantities of plankton images (tens to hundreds of millions) can be identified efficiently (Luo et al., 2018) when human expert identification is no longer practical. Some imagers, such as LOKI, make it possible to estimate the lipid reserves of Calanus spp. (Schmid et al., 2018).
In the present study, the LOKI profiler was deployed from 10 m above the seafloor to the surface at six stations in northern Baffin Bay to investigate the fine-scale vertical co-distribution (1 m resolution) of Calanus hyperboreus, C. glacialis and chlorophyll a at different hours of the day, at the end of the grazing season in August. Zooplankton images were identified automatically by a classifier developed using machine learning (Schmid et al., 2016). The observed distributions of Calanus in relation to its microalgal food at different light intensities were then compared to the predictions of the Predator Avoidance Hypothesis. The Ideal Free Distribution model for phenotypes of unequal competitive abilities was used to interpret the co-distribution of actively grazing C4 and C5 copepodites of the two species in the subsurface chlorophyll maximum (SCM).
The North Water (NOW, Figure 1) is a large, recurrent and biologically productive polynya between Greenland and Ellesmere Island (Muench, 1971; Stirling, 1980; Barber et al., 2001). Typically, the polynya forms in late April or early May when the flux of Arctic ice through Nares Strait is blocked by the formation of an ice bridge in Smith Sound, and northerly winds push the remaining ice south (Muench, 1971; see April et al., 2019, for recent climate-driven changes to the polynya). The ice-free region reaches its maximum extent (ca. 70,000 km2) in July. The polynya sensu stricto ceases to exist in August when the tongue of ice that separates it from the rest of Baffin Bay melts and all of Baffin Bay becomes free of ice. Arctic Surface Water enters the North Water through Nares Strait. By comparison to the adjacent Canadian Archipelago, the early removal of the ice in the NOW (April–May versus July–August in the Archipelago) results in an early phytoplankton bloom, the early development of the zooplankton community, and strong recruitment of juvenile polar cod Boreogadus saida (Fortier et al., 2002; Ringuette et al., 2002; LeBlanc et al., 2019).
Concurrent vertical profiles of temperature, salinity, light, fluorescence, and mesozooplankton abundance were obtained by deploying the Lightframe On-sight Keyspecies Investigation (LOKI) profiler at six stations in the North Water and Nares Strait (Figure 1) between 15 August and 28 August during the 2013 ArcticNet expedition of the research icebreaker CCGS Amundsen. The LOKI profiler (Schultz et al., 2010) captures images of the particles funneled into a photographic chamber by a 0.28-m2 aperture, 1.5-m long, 200-μm mesh conical net. At each station (Table 1) the LOKI was deployed to 10 m above the seafloor and then hauled back to the surface at a constant speed of 24 m min–1. During the ascent, images of mesozooplankton were stored automatically on an internal solid-state drive. Ancillary sensors simultaneously recorded temperature and oxygen (Aanderaa Oxygen Optode 4330F), conductivity (Aanderaa Conductivity Sensor 3919), chlorophyll fluorescence (TriOS MicroFlu – chl) and pressure (Aanderaa Pressure Sensor 4017D) every second. Particles passing through the photographic chamber were collected in a 200-μm mesh cod-end and preserved in a 4% formaldehyde-seawater solution buffered with sodium borate. For full information on LOKI hardware and software settings see Schmid et al. (2016).
|Station||Date (m/d/y)||Local time||Latitude N||Longitude W||Depth (m)|
|NOW West||8/16/2013||2:40||76° 17’ 37”||77° 45’ 30”||275|
|NOW East||8/18/2013||10:40||76° 12’ 57”||71° 07’ 31”||639|
|Petermann Glacier||8/22/2013||15:30||80° 32’ 39”||61° 07’ 05”||838|
|Kane Basin||8/25/2013||3:15||79° 10’ 38”||71° 10’ 36”||185|
|NS East||8/27/2013||3:40||77° 12’ 24”||73° 15’ 21”||329|
|NS West||8/28/2013||23:00||77° 11’ 36”||77° 01’ 27”||449|
Images of 179,270 zooplankton and particles were identified automatically using a Random Forests machine learning model (Breiman, 2001), which is efficient at correctly identifying the copepodite stages of C. hyperboreus and C. glacialis (Schmid et al., 2016). Details of the protocol for image preparation, the development of the classifier, and its application to the automatic identification of mesozooplankton are given in Schmid et al. (2015, 2016). From the set of 179,270 images, 41,231 were identified as Calanus copepodites (C1 to females and males). Of these, 18,974 were identified as C. hyperboreus and 17,637 as C. glacialis (Figure 2). Due to their morphological similarities and size overlaps, C. glacialis C2 and C. hyperboreus C1 as well as C. glacialis C3 and C. hyperboreus C2 cannot be discriminated by the classifier (Schmid et al., 2016). The classifier identified 2203 images as C. glacialis C2/C. hyperboreus C1 and 2417 as C. glacialis C3/C. hyperboreus C2.
In addition, the classifier cannot distinguish C. finmarchicus from other Calanus. Taxonomic analysis of the cod-end collections based on prosome length and morphometric criteria found 213 C. finmarchicus m–2 at station NOW East (0.64% of Calanus) and 142 m–2 at NOW West (0.57% of Calanus). Based on the same criteria, C. finmarchicus was absent at stations further north. Given the overlap in size of C. finmarchicus and C. glacialis, especially in the southern reaches of their sympatric distribution, the reliability of discriminating the two species based on size and morphometrics has been questioned (e.g., Parent et al., 2011; Choquet et al., 2018). However, consistent with our identification, Parent et al. (2011) found none and few C. finmarchicus, respectively, at two stations in NW Baffin Bay and the Canadian Archipelago using molecular techniques. The classifier would most likely identify the few C. finmarchicus present at the southernmost stations as C. glacialis.
Counts of each Calanus taxon were binned for each 1 m of the water column, prior to correcting counts for the likelihoods of incorrect identifications (Solow et al., 2001). These likelihoods were determined previously based on visual validations of automatic classifier identifications (Schmid et al., 2016). Corrected counts were used to estimate the abundance (number m–3) of the copepodite stages (or stage combinations) for the two species.
The lipid fullness (LF) of Calanus hyperboreus and C. glacialis in the SCM was estimated from LOKI images of copepods in a suitable lateral orientation following Schmid et al. (2018). LF was calculated as the ratio of the lipid sac area to prosome area times 100 (Vogedes et al., 2010) for 44 C4 and 57 C5 C. glacialis, and 72 C4 and 43 C5 C. hyperboreus.
Water samples collected with the main CTD-Rosette profiler of the ship were analyzed to determine chlorophyll a (Chl a) concentrations at a minimum of 6 depths at each station. Phytoplankton pigments were extracted and analyzed with a Thermo Scientific HPLC system as described in Thaler et al. (2017). The fluorescence signals (FS) recorded by the fluorometers of the CTD-Rosette and the LOKI profiler deployed within the same 30-min period at the same station were strongly correlated (FSLOKI = 0.007 + 0.96 FSCTD-Rosette, r2 = 0.87, n = 2743). Hence, the HPLC-derived Chl a values were used to transform the fluorescence signal of the LOKI into Chl a concentration. Photosynthetically active radiation (EPAR, μmole photons m–2 s–1) at the surface and in the water column was recorded with a Biospherical QCP-2300 mounted on the CTD-Rosette.
To provide background information on the seasonal-spatial development of the surface phytoplankton bloom in the study area, surface Chl a concentration was mapped monthly from April to September 2013 using MODerate resolution Imaging Spectroradiometer (MODIS) level 3 data from the Aqua satellite. This chl a concentration was calculated at a resolution of 4 km/pixel using NASA’s standard algorithms (Hu et al., 2012). Sea ice concentrations at a resolution of 25 km/pixel were derived from Nimbus-7 SMMR and DMSP SSM/I-SSMIS passive microwave data (https://nsidc.org/data/nsidc-0051).
Patchiness and spatial autocorrelation of abundance estimates invalidate the use of traditional parametric statistics to compare the vertical distribution of planktonic organisms sampled simultaneously by nets, pumps, or profilers (Venrick, 1986). W’, a modification of the Kolmogorov-Smirnov statistic insensitive to patchiness (Solow et al., 2000), was used to test for differences between the vertical distributions of Calanus hyperboreus and C. glacialis copepodites. The significance of W’ was tested by randomization (1000 iterations).
Ice break-up and the first detection of surface chlorophyll occurred in April on the Greenland side of the North Water (Figure 3). The surface phytoplankton bloom developed in May and June in the center of the polynya and reached maximum extent in July. Northern Baffin Bay cleared of ice in August. At that time significant concentrations of surface chlorophyll were detected primarily in the open waters of the partially ice-covered Nares Strait (Figure 3). The ice cover started to form again by September.
Copepodites of Calanus were more abundant and at a more advanced developmental stage in the North Water and Nares Strait than at the northernmost stations of Kane Basin and Petermann Glacier (Table 2). Calanus hyperboreus C3, C4 and C5 and C. glacialis C4 and C5 dominated numerically at the four stations in the North Water and Nares Strait (Table 2). C1, C2 and females (F) were the most abundant taxa in Kane Basin and at the Petermann Glacier.
|Calanus hyperboreus C3||1886||1680||2620||2824||868||626|
|C. hyperboreus C4||8802||6002||3496||5778||657||502|
|C. hyperboreus C5||6614||3864||2542||4020||637||350|
|C. hyperboreus F||722||982||1838||1684||1534||2422|
|C. hyperboreus M||–b||–||–||–||234||442|
|Calanus glacialis C1||–||550||1202||428||1304||2312|
|C. glacialis C4||7156||5962||3358||5220||692||438|
|C. glacialis C5||6802||3518||2978||5378||911||622|
|C. glacialis F||888||730||1682||1996||1624||2632|
|C. glacialis M||–||–||–||–||277||482|
|C. hyperboreus C1/C. glacialis C2||–||658||1242||682||1765||3042|
|C. hyperboreus C2/C. glacialis C3||424||942||1394||756||1910||2680|
The vertical distribution of Calanus copepods in relation to the subsurface chlorophyll maximum (SCM) and incident photosynthetic active radiation (EPAR) levels was documented for three different cases.
Case 1: Low Chl a concentration in low light. At station Kane Basin, Chl a concentration was low (≤1 mg m–3) with a weak SCM at 40-m depth (Figure 4). Incident EPAR was low (18 μE m–2 s–1) at the time of the LOKI profile. The abundance of Calanus glacialis C1 peaked in the SCM, with the bulk of this stage distributed between the SCM and 80 m (Figure 4). C. hyperboreus C3–C5 and C. glacialis C4–C5 were distributed between 40 and 120 m with peak abundance immediately under the SCM. Females of the two species presented a similar but slightly deeper (60–140 m) distribution than younger copepodite stages. The dicothermal thermocline and the strong halocline had no obvious influence on the vertical distribution of the copepods (Figure 4). The vertical distributions of C. hyperboreus and C. glacialis males are presented in Figure S1.
Case 2: High Chl a concentration in daylight. Station Peterman Glacier with a well-developed SCM (>5 mg Chl a m–3 between 10 and 50 m) was profiled in daytime (15h30, 697 μE m–2 s–1). While some of the younger copepodite stages (C1 to C3) of both Calanus species were found in the SCM, most of them and the larger stages (e.g., C. hyperboreus C3, C. glacialis C4) were distributed at the base of the SCM and below (Figure 5). Similar patterns of copepod daytime (10h40, 652 μE m–2 s–1) vertical distribution in relation to a strongly marked SCM (3 mg Chl a m–3, at 30 m) were observed at station NOW East (Figure S2).
Case 3: Intermediate Chl a concentration in low light. Stations NOW West, NS West and NS East were sampled during polar twilight (23h00 to 03h40, EPAR 2–18 μE m–2 s–1), with Chl a ranging from 1.5 mg m–3 to 3.4 mg m–3 in the well-developed SCM located between 20 and 40 m. At station NS East, for example, the abundance of Calanus copepodites C1 to C5 tracked the Chl a profile, peaking in or around the SCM (Figure 6). Females remained below the SCM. Similar patterns of copepod vertical distribution were observed at stations NOW West and NS West (Figures S3 and S4, respectively).
Vertical co-distributions of Calanus hyperboreus and C. glacialis at Case 3 stations (NOW West, NS West and NS East) showed that the numerically dominant C4 and C5 copepodites (Table 2) were actively grazing at night in the well-developed SCM. The large C. hyperboreus occupied the core of the SCM, while the smaller C. glacialis distributed preferably above and below maximum Chl a concentration (Figure 7). For instance, at both NOW West and NS West, C. hyperboreus C4 abundance peaked in the SCM, while C. glacialis C4 abundance was maximum at intermediate Chl a concentration both above and below the SCM (Figure 7). The same patterns were observed for C. hyperboreus and C. glacialis C5 at Station NS East. These vertical distributions of same-stage C. hyperboreus and C. glacialis in the SCM differed significantly, in all instances (W’, p ≤ 0.006; Figure 7 and Table S1).
The lipid fullness (LF) of Calanus hyperboreus in the core SCM reached higher values than those of C. glacialis above or under the core SCM (Figure 8). For a given station or when pooled among the three stations (Figure S5), the mean LF of C. hyperboreus C4 and C5 in the core SCM was significantly higher than that of C. glacialis C4 and C5 at the periphery of the SCM (Welch Two Sample t-test: C4: t = –3.70, p < 0.001; C5: t = –4.77, p < 0.0001).
The stations sampled in mid- to late August covered the south–north gradient in decreasing ecosystem maturity often seen in arctic seas in midsummer (e.g., Rabindranath et al., 2010; Ardyna et al., 2013; Gosselin and Poulin, 2016). A deep (25–35 m) SCM with relatively low standing stocks of small microalgae (80 mg m–2 Chl a within the top 100 m, 10% of cells > 20 μm; Gosselin and Poulin, 2016) grazed primarily by the advanced (C4 and C5) copepodite stages of Calanus characterized the southern stations in the North Water (Table 2). Female Calanus of both species were already distributed below the SCM even at night, indicating the start of the migration to diapause at depth. By contrast, the northern Petermann Glacier station presented an intense phytoplankton bloom (250 mg m–2 Chl a within the top 100 m) of relatively large cells (46% of cells > 20 μm; Gosselin and Poulin, 2016) grazed by younger Calanus C1–C3 copepodites and females (Table 2). Consistent with previous studies (Klein et al., 2002; Ringuette et al., 2002), the northward propagation of the ice break-up from the North Water in April–May to Kane Basin and beyond in August, explains the late-summer gradient from post-bloom conditions at southern stations to early-bloom conditions in Nares Strait.
At our sampling latitudes (76–81°N) in mid- to late August, the midnight sun is ending as the sun increasingly descends on the horizon at night, and some twilight develops. The resulting daily variations in irradiance at the depth of the SCM were sufficient to trigger a DVM in actively grazing C4 and C5 stages of Calanus that are completing their lipid reserves before overwintering at depth (e.g., Schmid et al., 2018). At any one time, only part of the populations of Calanus copepodites partake in the grazing diel migration. The non-migrating fraction of the population is interpreted as satiated individuals remaining at depth in low Chl a concentration and where predation pressure is low (e.g., Pearre, 2003; Ringelberg, 2010).
All three types of vertical distributions observed at the different stations were consistent with the Predator Avoidance Hypothesis which predicts that if, and only if, the energy gain from grazing in high microalgal concentrations offsets the cost of vertical migrations, grazers will migrate up into the food-rich surface waters at night and migrate down and out of the euphotic zone in daytime to avoid visual predators (Lampert, 1989; DeMeester et al., 1999; Fortier et al., 2001). At station Kane Basin at night (Case 1) the Chl a gradient between the SCM and the deeper layers was likely insufficient to trigger a feeding migration (Gliwicz and Pijanowska, 1988; Lampert, 1989; Hays, 2003). At stations NOW East and Petermann Glacier sampled during the day (Case 2), the large C. hyperboreus and C. glacialis remained at depth despite higher phytoplankton concentrations in the SCM, likely to avoid visual predators, in particular the abundant planktivorous seabirds nesting and foraging in the area in August (e.g., Karnovsky et al., 2008). In agreement with previous reports (Brooks and Dodson, 1965; Fortier et al., 2001; Hays, 2003; Daase et al., 2015; Schmid et al., 2018), the largest Calanus developmental stages, most susceptible to predation, showed the strongest avoidance behavior by moving deeper where illumination is further reduced, while smaller and less conspicuous taxa remained in the SCM.
Conditions of low light and abundant food in the SCM (Case 3) conducive to active nighttime grazing by herbivorous copepods (Daase et al., 2008, 2015; Falk-Petersen et al., 2008; Rabindranath et al., 2010; Baumgartner et al., 2011; Berge et al., 2014) prevailed at stations NS East, NS West and NOW West. At these stations, the distributions of all Calanus taxa, except females, generally aligned with the Chl a profile, with copepod abundances peaking in the SCMs. The resulting distributions again were consistent with the predictions of the Predator Avoidance Hypothesis (Gliwicz and Pijanowska, 1988; Lampert, 1989; DeMeester et al., 1999; Fortier et al., 2001). At this stage in the maturation of the ecosystem, Calanus females, the exception that confirms the rule, had acquired the full lipid load necessary to overwinter and had stopped migrating to the SCM to feed (Schmid et al., 2018).
Using an electronic counter based on the Coulter principle and carried by a horizontally-towed, vertically-oscillating vehicle, Herman (1983) showed how Calanus hyperboreus C5 distributed in the subsurface chlorophyll maximum (SCM), while C. glacialis and C. finmarchicus C5 distributed on average above the SCM, presumably at the calculated depth of maximum phytoplankton productivity. Our results confirm the concentration of grazing C. hyperboreus C4 and C5 in the core SCM. C. glacialis C4 and C5, however, were found both above and below the peak SCM. This pattern suggests some foraging interference, with the large C. hyperboreus excluding the smaller C. glacialis from peak Chl a concentration in the center of the SCM and relegating its congener to medium food availability above and below the SCM.
The Ideal Free Distribution (IFD) model predicts that under density-dependent competition (or interference) animals of equal competitive abilities foraging on a continuously renewed food resource (continuous input situation) will spread spatially in proportion to the available resource so as to minimize competition and maximize individual gain in energy (Fretwell and Lucas, 1969). However, when phenotypes of unequal competitive abilities exploit such a food source and the payoff of a given competitor is reduced by the addition of other competitors to the patch, the best phenotypes should occupy the best patches of food and therefore gain some fitness advantage (Parker and Sutherland, 1986). In the present study, continuous phytoplankton production at the nitracline replenished the SCM (Martin et al., 2010), thus maintaining the sub-surface maximum in the microalgal food of Calanus congeners (a continuous input situation). While the two Calanus congeners are morphologically nearly identical (Figure 2), C4 and C5 of C. hyperboreus are 4.4 and 3.2 times heavier, respectively, than the corresponding C. glacialis (for C4: 457 vs 104 μg C, for C5: 1022 vs 320 μg C; Forest et al., 2011). Assuming that a larger size provides some competitive advantage, the monopolization of the richer core of the SCM by the larger C. hyperboreus is consistent with the first prediction of the IFD model for two phenotypes of unequal competitive abilities (Parker and Sutherland, 1986). Because their food is diluted, the larger the copepod, the more food limited it tends to be in situ (Saiz and Calbet, 2007; Kiørboe, 2011). As well, the amplitude of diel vertical migrations of copepods increases with size (Fortier et al., 2001; Eiane and Ohman, 2004). This dependence of feeding and migrations on size led Kiørboe (2011) to conclude that “Large zooplankters may compensate for the declining specific clearance rate by being better able to find and utilize patches of food on a larger scale than smaller zooplankters — hence increasing their feeding rates — or by being better able to avoid predation, e.g. through diurnal vertical migration — hence decreasing their mortality rate”. The observed co-distribution of grazing C. hyperboreus and C. glacialis in the SCM is consistent with this conclusion.
A second prediction of the IFD model is that the large phenotype C. hyperboreus grazing in the core SCM will gain some fitness advantage over the small phenotype C. glacialis grazing at the periphery of the SCM (Parker and Sutherland, 1986). C. hyperboreus grazing in the SCM attained a higher relative lipid load than C. glacialis grazing at the periphery. On average, C. hyperboreus starts to migrate to diapause earlier and at lower lipid fullness (~50%) than C. glacialis (~60%) of the same developmental stage (Schmid et al., 2018). Grazing in the rich core SCM may enable C. hyperboreus to initiate the seasonal migration to depth earlier than C. glacialis. An earlier migration to depth would reduce exposure to visual predators such as seabirds and fish in the surface layer. Hence, C. hyperboreus could achieve some fitness advantage over C. glacialis by monopolizing the rich core SCM, although the smaller size and thus lesser vulnerability of C. glacialis to predation would compensate some of this advantage.
Alternatively, the vertical partitioning of grazing Calanus hyperboreus and C. glacialis in the SCM could reflect some differential distribution of their respective preferred food. Calanus copepods exhibit a strong selectivity for larger phytoplankton cells and some selectivity for phytoplankton species (e.g., Mullin, 1963; Frost, 1972). Moreover, Calanus will readily feed on microzooplankton (see Campbell et al., 2016, for a review). Recent research has shown that different phytoplankton taxa occupy different vertical niches within the SCM (Monier et al., 2015; Latasa et al., 2016). Thus, grazing C. hyperboreus and C. glacialis may be choosing their vertical position in the SCM according to the distribution of a preferred cell size, phytoplankton taxon or microzooplankton prey. Health and nutritional quality, for instance, the lipid content of the different prey, may also influence the distribution of the grazers. Advances in the development of microplankton underwater imaging systems (e.g., Orenstein et al., 2015) should soon allow a taxonomic comparison of the fine-scale vertical distribution of zooplankton grazers and their food across the SCM.
Parametric statistics cannot be used to compare the vertical distribution of patchy variables sampled simultaneously by the same instrument (Venrick, 1986). Non-parametric tests robust to patchiness have been proposed for both the case of un-replicated (Solow et al., 2000) and replicated (Beet et al., 2003) profiles. In the present exploratory study, the three stations representing Case 3 cannot be considered replicates as the SCM differed in vertical position and width (Figure 7). Hence, W’ for un-replicated profiles (Solow et al., 2000) was used to confirm that the vertical distributions of C. glacialis and C. hyperboreus in the SCM were different. Unfortunately, W’ does not test for the precise hypothesis of exclusion (negative correlation or contingency) of C. glacialis from the SCM by C. hyperboreus. However, given the general agreement of the co-distribution of Calanus congeners in the SCM reported here and by Herman (1983), and the repetition of the inverse distribution at the three stations where the two species actively grazed in the SCM, we believe that the observed exclusion patterns warrant further investigation to distinguish between competitive grazing, size-dependent fitness advantage, and prey specificity as the underlying explanations for the observed distributions of these key species in the northern Baffin Bay ecosystem. In particular, climate change would likely affect the aforementioned three possible scenarios differently. In a scenario where the observed distribution patterns are due to the prey preference of Calanus, climate change-induced shifts in the phytoplankton cell size spectrum could lead to changes in copepod co-distributions, with unknown consequences. Where the observed co-distributions are driven by competition and size, copepod co-distributions would likely be affected more indirectly through their feeding success and growth. Ultimately, further study of the fine-scale distributions of these key species will improve understanding of climate change impacts on Arctic marine ecosystems.
The supplemental files for this article can be found as follows:
We thank the officers and crew of the CCGS Amundsen for their dedication and professionalism at sea. Marcel Babin and Atsushi Matsuoka provided advice on ocean color remote sensing and HPLC data. Figure 3 by courtesy of A. Matsuoka. We are grateful to Jordan Grigor and Cyril Aubry for technical support throughout the project.
Shiptime was funded in part by Amundsen Science thanks to grants from the Canada Foundation for Innovation (CFI) and by the Network of Centres of Excellence ArcticNet. Discovery and Northern Supplement grants from the Natural Sciences and Engineering Research Council to L.F. supported this research. M.S. received postgraduate scholarships from the Canada Excellence Research Chair (CERC) in Remote Sensing of Canada’s New Arctic Frontier and stipends from Québec-Océan. This is a joint contribution to Québec-Océan, ArcticNet, the Green Edge project, and the Canada Research Chair on the response of marine arctic ecosystems to climate warming.
The authors have no competing interests to declare.
April, A, Montpetit, B and Langlois, D. 2019. Linking the open water area of the North Water Polynya to climatic parameters using a multiple linear regression prediction model. Atmos-Ocean 57: 91–100. DOI: 10.1080/07055900.2019.1598332
Ardyna, M, Babin, M, Gosselin, M, Devred, E, Bélanger, S, Matsuoka, A and Tremblay, JE. 2013. Parameterization of vertical chlorophyll a in the Arctic Ocean: impact of the subsurface chlorophyll maximum on regional, seasonal, and annual primary production estimates. Biogeosciences 10(6): 4383–4404. DOI: 10.5194/bg-10-4383-2013
Ashjian, CJ, Campbell, RG, Welch, HE, Butler, M and Van Keuren, D. 2003. Annual cycle in abundance, distribution, and size in relation to hydrography of important copepod species in the western Arctic Ocean. Deep Sea Res Pt I 50(10–11): 1235–1261. DOI: 10.1016/S0967-0637(03)00129-8
Barber, DG, Hanesiak, JM, Chan, W and Piwowar, J. 2001. Sea-ice and meteorological conditions in Northern Baffin Bay and the North Water polynya between 1979 and 1996. Atmos Ocean 39(3): 343–359. DOI: 10.1080/07055900.2001.9649685
Baumgartner, MF, Lysiak, N, Schuman, C, Urban-Rich, J and Wenzel, FW. 2011. Diel vertical migration behavior of Calanus finmarchicus and its influence on right and sei whale occurrence. Mar Ecol Prog Ser 423: 167–184. DOI: 10.3354/meps08931
Beet, A, Solow, AR and Bollens, SM. 2003. Comparing vertical plankton profiles with replication. Mar Ecol Prog Ser 262: 285–287. DOI: 10.3354/meps262285
Berge, J, Cottier, F, Varpe, Ø, Renaud, PE, Falk-Petersen, S, Kwasniewski, S, Griffiths, C, Søreide, JE, Johnsen, G, Aubert, A, Bjærke, O, Hovinen, J, Jung-Madsen, S, Tveit, M and Majaneva, S. 2014. Arctic complexity: a case study on diel vertical migration of zooplankton. J Plankton Res 36(5): 1279–1297. DOI: 10.1093/plankt/fbu059
Breiman, L. 2001. Random Forests. Mach Learn 45(1): 5–32. DOI: 10.1023/A:1010933404324
Brooks, JL and Dodson, SI. 1965. Predation, body size, and composition of plankton. Science 150(3692): 28–35. DOI: 10.1126/science.150.3692.28
Campbell, RG, Ashjian, CJ, Sherr, EB, Sherr, BF, Lomas, MW, Ross, C, Alatalo, P, Gelfman, C and Van Keuren, D. 2016. Mesozooplankton grazing during spring sea-ice conditions in the eastern Bering Sea. Deep-Sea Res Pt II 134: 157–172. DOI: 10.1016/j.dsr2.2015.11.003
Choquet, M, Kosobokova, K, Kwasniewski, S, Hatlebakk, M, Dhanasiri, AKS, Melle, W, Daase, M, Svensen, C, Søreide, JE and Hoarau, G. 2018. Can morphology reliably distinguish between the copepods Calanus finmarchicus and C. glacialis, or is DNA the only way? Limnol Oceanogr Methods 16: 237–252. DOI: 10.1002/lom3.10240
Daase, M, Eiane, K, Aksnes, DL and Vogedes, D. 2008. Vertical distribution of Calanus spp. and Metridia longa at four Arctic locations. Mar Biol Res 4(3): 193–207. DOI: 10.1080/17451000801907948
Daase, M, Falk-Petersen, S, Varpe, Ø, Darnis, G, Søreide, JE, Wold, A, Leu, E, Berge, J, Philippe, B and Fortier, L. 2013. Timing of reproductive events in the marine copepod Calanus glacialis: a pan-Arctic perspective. Can J Fish Aquat Sci 70(6): 871–884. DOI: 10.1139/cjfas-2012-0401
Daase, M, Hop, H and Falk-Petersen, S. 2015. Small-scale diel vertical migration of zooplankton in the High Arctic. Polar Biol 39(7): 1213–1223. DOI: 10.1007/s00300-015-1840-7
Darnis, G and Fortier, L. 2012. Zooplankton respiration and the export of carbon at depth in the Amundsen Gulf (Arctic Ocean). J Geophys Res Oceans 117(C4): C04013. DOI: 10.1029/2011JC007374
Darnis, G and Fortier, L. 2014. Temperature, food and the seasonal vertical migration of key arctic copepods in the thermally stratified Amundsen Gulf (Beaufort Sea, Arctic Ocean). J Plankton Res 36(4): 1092–1108. DOI: 10.1093/plankt/fbu035
Darnis, G, Hobbs, L, Geoffroy, M, Grenvald, JC, Renaud, PE, Berge, J, Cottier, F, Kristiansen, S, Daase, ME, Søreide, J, Wold, A, Morata, N and Gabrielsen, T. 2017. From polar night to midnight sun: Diel vertical migration, metabolism and biogeochemical role of zooplankton in a high Arctic fjord (Kongsfjorden, Svalbard). Limnol Oceanogr 62(4): 1586–1605. DOI: 10.1002/lno.10519
Darnis, G, Robert, D, Pomerleau, C, Link, H, Archambault, P, Nelson, RJ, Geoffroy, M, Tremblay, J-É, Lovejoy, C, Ferguson, SH, Hunt, BPV and Fortier, L. 2012. Current state and trends in Canadian Arctic marine ecosystems: II. Heterotrophic food web, pelagic-benthic coupling, and biodiversity. Clim Change 115(1): 179–205. DOI: 10.1007/s10584-012-0483-8
Dawson, JK. 1978. Vertical Distribution of Calanus hyperboreus in the Central Arctic Ocean. Limnol Oceanogr 23: 950–957. DOI: 10.4319/lo.1978.23.5.0950
DeMeester, L, Dawidowicz, P, Van Gool, E and Loose, CJ. 1999. Ecology and evolution of predator-induced behaviour of zooplankton: Depth selection behaviour and diel vertical migration. In Tollrian, R, Harvell, CD (eds.). The ecology and evolution of inducible defences . The United States of America: Princeton Univ Press.
Durham, WM and Stocker, R. 2012. Thin phytoplankton layers: characteristics, mechanisms, and consequences. Annu Rev Marine Sci 4(1): 177–207. DOI: 10.1146/annurev-marine-120710-100957
Eiane, K and Ohman, MD. 2004. Stage-specific mortality of Calanus finmarchicus, Pseudocalanus elongatus and Oithona similis on Fladen Ground, North Sea, during a spring bloom. Mar Ecol Prog Ser 268: 183–193. DOI: 10.3354/meps268183
Falk-Petersen, S, Leu, E, Berge, J, Kwasniewski, S, Nygård, H, Røstad, A, Keskinen, E, Thormar, J, von Quillfeldt, C, Wold, A and Gulliksen, B. 2008. Vertical migration in high Arctic waters during autumn 2004. Deep Sea Res Pt II 55(20–21): 2275–2284. DOI: 10.1016/j.dsr2.2008.05.010
Falk-Petersen, S, Mayzaud, P, Kattner, G and Sargent, JR. 2009. Lipids and life strategy of Arctic Calanus. Mar Biol Res 5(1): 18–39. DOI: 10.1080/17451000802512267
Falk-Petersen, S, Pavlov, V, Timofeev, S and Sargent, JR. 2007. Climate variability and possible effects on arctic food chains: The role of Calanus. In Ørbæk, JB, Kallenborn, R, Tombre, I, Hegseth, EN, Falk-Petersen, S and Hoel, AH (eds.). Arctic alpine ecosystems and people in a changing environment . Germany: Springer.
Forest, A, Galindo, V, Darnis, G, Pineault, S, Lalande, C, Tremblay, J-É and Fortier, L. 2011. Carbon biomass, elemental ratios (C:N) and stable isotopic composition (∂13C, ∂15N) of dominant calanoid copepods during the winter-to-summer transition in the Amundsen Gulf (Arctic Ocean). J Plankton Res 33(3): 547–547. DOI: 10.1093/plankt/fbr003
Fortier, M, Fortier, L, Hiroshi, H, Hiroaki, S and Legendre, L. 2001. Visual predators and the diel vertical migration of copepods under Arctic sea ice during the midnight sun. J Plankton Res 23(11): 1263–1278. DOI: 10.1093/plankt/23.11.1263
Fortier, M, Fortier, L, Michel, C and Legendre, L. 2002. Climatic and biological forcing of the vertical flux of biogenic particles under seasonal Arctic sea ice. Mar Ecol Prog Ser 225: 1–16. DOI: 10.3354/meps225001
Fretwell, SD and Lucas, HL, Jr. 1969. On territorial behavior and other factors influencing habitat distribution in birds. Acta Biotheor 19(1): 16–36. DOI: 10.1007/BF01601953
Frost, BW. 1972. Effects of size and concentration of food particles on the feeding behavior of the marine planktonic copepod Calanus pacificus. Limnol Oceanogr 17(6): 805–815. DOI: 10.4319/lo.1972.17.6.0805
Gliwicz, MZ and Pijanowska, J. 1988. Effect of predation and resource depth distribution on vertical migration of zooplankton. Bull Mar Sci 43: 695–705.
Gosselin, M and Poulin, M. 2016. Phytoplankton and primary production – Legs 1a, 1b and 2a. In Merzouk, A and Levesque, K (eds.). ArcticNet 2013 Expedition Report . Canada: ArcticNet Inc.
Hays, GC. 2003. A review of the adaptive significance and ecosystem consequences of zooplankton diel vertical migrations. Hydrobiologia 503(1–3): 163–170. DOI: 10.1023/B:HYDR.0000008476.23617.b0
Herman, AW. 1983. Vertical distribution patterns of copepods, chlorophyll, and production in northeastern Baffin Bay. Limnol Oceanogr 28(4): 709–719. DOI: 10.4319/lo.1983.28.4.0709
Hirche, HJ. 1997. Life cycle of the copepod Calanus hyperboreus in the Greenland Sea. Mar Biol 128: 607–618. DOI: 10.1007/s002270050127
Hirche, HJ, Barz, K, Ayon, P and Schulz, J. 2014. High resolution vertical distribution of the copepod Calanus chilensis in relation to the shallow oxygen minimum zone off northern Peru using LOKI, a new plankton imaging system. Deep Sea Res Pt I 88: 63–73. DOI: 10.1016/j.dsr.2014.03.001
Hobson, KA, Fisk, A, Karnovsky, N, Holst, M, Gagnon, J-M, Fortier, M. 2002. A stable isotope (δ13C, δ15N) model for the North Water food web: implications for evaluating trophodynamics and the flow of energy and contaminants. Deep Sea Res Pt II 49: 5131–5150. DOI: 10.1016/S0967-0645(02)00182-0
Hu, C, Lee, Z and Franz, B. 2012. Chlorophyll a algorithms for oligotrophic oceans: A novel approach based on three-band reflectance difference. J Geophys Res Oceans 117(c): C01011. DOI: 10.1029/2011JC007395
Karnovsky, NJ, Hobson, KA, Iverson, S and Hunt, GL, Jr. 2008. Seasonal changes in diets of seabirds in the North Water Polynya: a multiple-indicator approach. Mar Ecol Prog Ser 357: 291–299. DOI: 10.3354/meps07295
Klein, B, Leblanc, B, Mei, Z-P, Beret, R, Michaud, J, Mundy, CJ, von Quillfeldt, CH, Garneau, M-È, Roy, S, Gratton, Y, Cochran, JK, Bélanger, S, Larouche, P, Pakulski, JD, Rivkin, RB and Legendre, L. 2002. Phytoplankton biomass, production and potential export in the North Water. Deep Sea Res Part II Top Stud Oceanogr 49(22–23): 4983–5002. DOI: 10.1016/S0967-0645(02)00174-1
Kiørboe, T. 2011. How zooplankton feed: mechanisms, traits and trade-offs. Biol Rev Camb Philos Soc 86(2): 311–339. DOI: 10.1111/j.1469-185X.2010.00148.x
Lampert, W. 1989. The adaptive significance of diel vertical migration of zooplankton. Funct Ecol 3(1): 21–27. DOI: 10.2307/2389671
Latasa, M, Cabello, AM, Morán, XAG, Massana, R and Scharek, R. 2016. Distribution of phytoplankton groups within the deep chlorophyll maximum. Limnol Oceanogr 62(2): 665–685. DOI: 10.1002/lno.10452
LeBlanc, M, Geoffroy, M, Bouchard, C, Gauthier, S, Majewski, A, Reist, JD and Fortier, L. 2019. Pelagic production and the recruitment of juvenile polar cod Boreogadus saida in Canadian Arctic Seas. Polar Biol . DOI: 10.1007/s00300-019-02565-6
Luo, JY, Irisson, J-O, Graham, B, Guigand, C, Sarafraz, A, Mader, C and Cowen, RK. 2018. Automated plankton image analysis using convolutional neural networks. Limnol Oceanogr Methods 16: 814–827. DOI: 10.1002/lom3.10285
Martin, J, Tremblay, J-E, Gagnon, J, Tremblay, G, Lapoussière, A, Jose, C, Poulin, M, Gosselin, M, Gratton, Y and Michel, C. 2010. Prevalence, structure and properties of subsurface chlorophyll maxima in Canadian Arctic waters. Mar Ecol Prog Ser 412: 69–84. DOI: 10.3354/meps08666
Monier, A, Comte, J, Babin, M, Forest, A, Matsuoka, A and Lovejoy, C. 2015. Oceanographic structure drives the assembly processes of microbial eukaryotic communities. ISME J 9(4): 990–1002. DOI: 10.1038/ismej.2014.197
Muench, RD. 1971. The physical oceanography of the northern Baffin Bay region. The Baffin Bay-North Water Project Science Report 1 . The United States of America: Arctic Institute of North America. 150 pp.
Mullin, MM. 1963. Some factors affecting the feeding of marine copepods of the genus Calanus. Limnol Oceanogr 8(2): 239–250. DOI: 10.4319/lo.1963.8.2.0239
Orenstein, EC, Beijbom, O, Peacock, EE and Sosik, HM. 2015. WHOI-Plankton – A large scale fine grained visual recognition benchmark dataset for plankton classification. arXiv 15010: arXiv:1510.00745.
Parent, GJ, Plourde, S and Turgeon, J. 2011. Overlapping size ranges of Calanus spp. off the Canadian Arctic and Atlantic Coasts: impact on species’ abundances. J Plank Res 33(11): 1654–1665. DOI: 10.1093/plankt/fbr072
Parker, GA and Sutherland, WJ. 1986. Ideal free distributions when individuals differ in competitive ability: phenotype-limited ideal free models. Anim Behav 34(4): 1222–1242. DOI: 10.1016/S0003-3472(86)80182-8
Pearre, S, Jr. 2003. Eat and run? The hunger/satiation hypothesis in vertical migration: History, evidence and consequences. Biol Rev 78(1): 1–79. DOI: 10.1017/S146479310200595X
Rabindranath, A, Daase, M, Falk-Petersen, S, Wold, A, Wallace, MI, Berge, J and Brierley, AS. 2010. Seasonal and diel vertical migration of zooplankton in the High Arctic during the autumn midnight sun of 2008. Mar Biodiv 41(3): 365–382. DOI: 10.1007/s12526-010-0067-7
Ringelberg, J. 2010. Diel vertical migration of zooplankton in lakes and oceans. Causal explanations and adaptive significances. Germany: Springer. 356 pp. DOI: 10.1007/978-90-481-3093-1
Ringuette, M, Fortier, L, Fortier, M, Runge, JA, Bélanger, S, Larouche, P, Weslawski, JM and Kwasniewski, S. 2002. Advanced recruitment and accelerated population development in Arctic calanoid copepods of the North Water. Deep Sea Res Pt II 49(22–23): 5081–5099. DOI: 10.1016/S0967-0645(02)00179-0
Runge, JA and Ingram, RG. 1991. Under-ice feeding and diel migration by the planktonic copepods Calanus glacialis and Pseudocalanus minutus in relation to the ice algal production cycle in southeastern Hudson Bay, Canada. Mar Biol 108(2): 217–225. DOI: 10.1007/BF01344336
Saiz, E and Calbet, A. 2007. Scaling of feeding in marine calanoid copepods. Limnol Oceanogr 52(2): 668–675. DOI: 10.4319/lo.2007.52.2.0668
Schmid, MS, Aubry, C, Grigor, J and Fortier, L. 2015. ZOOMIE v1.0 (Zooplankton Multiple Image Exclusion) [software]. Available at: https://zenodo.org/record/17928.
Schmid, MS, Aubry, C, Grigor, J and Fortier, L. 2016. The LOKI underwater imaging system and an automatic identification model for the detection of zooplankton taxa in the Arctic Ocean. Methods Oceanogr 15–16: 129–160. DOI: 10.1016/j.mio.2016.03.003
Schmid, MS, Maps, F and Fortier, L. 2018. Lipid load triggers migration to diapause in Arctic Calanus copepods—insights from underwater imaging. J Plankton Res 40(3): 311–325. DOI: 10.1093/plankt/fby012
Schulz, J, Barz, K, Ayon, P, Lüdtke, A, Zielinski, O, Mengedoht, D and Hirche, HJ. 2010. Imaging of plankton specimens with the lightframe on-sight keyspecies investigation (LOKI) system. J Eur Opt Soc Rapid Publ A 5: 10017s. DOI: 10.2971/jeos.2010.10017s
Solow, A, Davis, C and Hu, Q. 2001. Estimating the taxonomic composition of a sample when individuals are classified with error. Mar Ecol Prog Ser 216: 309–311. DOI: 10.3354/meps216309
Solow, AR, Bollens, SM and Beet, A. 2000. Comparing two vertical plankton distributions. Limnol Oceanogr 45(2): 506–509. DOI: 10.4319/lo.2000.45.2.0506
Søreide, JE, Falk-Petersen, S, Hegseth, EN, Hop, H, Carroll, ML, Hobson, KA and Blachowiak-Samolyk, K. 2008. Seasonal feeding strategies of Calanus in the high-Arctic Svalbard region. Deep Sea Res Pt II 55(20–21): 2225–2244. DOI: 10.1016/j.dsr2.2008.05.024
Søreide, JE, Leu, E, Berge, J, Graeve, M and Falk-Petersen, S. 2010. Timing of blooms, algal food quality and Calanus glacialis reproduction and growth in a changing Arctic. Glob Chang Biol 16(11): 3154–3163. DOI: 10.1111/j.1365-2486.2010.02175.x
Stirling, I. 1980. The biological importance of polynyas in the Canadian Arctic. Arctic 33(2): 303–315. DOI: 10.14430/arctic2563
Thaler, M, Vincent, WF, Lionard, M, Hamilton, AK and Lovejoy, C. 2017. Microbial community structure and interannual change in the last epishelf lake ecosystem in the North Polar Region. Front Mar Sci 3: 275. DOI: 10.3389/fmars.2016.00275
Venrick, EL. 1986. The Smirnov statistic: An incorrect test for vertical distributions patterns. Deep-Sea Res 33: 1275–1277. DOI: 10.1016/0198-0149(86)90024-5
Vogedes, D, Varpe, O, Søreide, JE, Graeve, M, Berge, J and Falk-Petersen, S. 2010. Lipid sac area as a proxy for individual lipid content of arctic calanoid copepods. J Plankton Res 32: 1471–1477. DOI: 10.1093/plankt/fbq068
Wassmann, P. 2011. Arctic marine ecosystems in an era of rapid climate change. Prog Oceanogr 90(1): 1–17. DOI: 10.1016/j.pocean.2011.02.002
Wassmann, P, Reigstad, M, Haug, T, Rudels, B, Carroll, ML, Hop, H, Gabrielsen, GW, Falk-Petersen, S, Denisenko, SG, Arashkevich, E, Slagstad, D and Pavlova, O. 2006. Food webs and carbon flux in the Barents Sea. Prog Oceanogr 71(2–4): 232–287. DOI: 10.1016/j.pocean.2006.10.003