Polar Biol DOI 10.1007/s00300-012-1241-0
ORIGINAL PAPER
Pelagic fish and zooplankton species assemblages in relation to water mass characteristics in the northern Bering and southeast Chukchi seas Lisa Eisner • Nicola Hillgruber • Ellen Martinson Jacek Maselko
•
Received: 18 June 2012 / Revised: 22 August 2012 / Accepted: 23 August 2012 Ó Springer-Verlag 2012
Abstract This research explores the distributions and community composition of pelagic species in the sub-Arctic and Arctic waters of the northern Bering and central and southern Chukchi seas during September 2007 by linking pelagic zooplankton and fish assemblages to water masses. Juvenile saffron cod (Eleginus gracilis), polar cod (Boreogadus saida), and shorthorn sculpin (Myoxocephalus scorpius) were most abundant in warm, low salinity Alaska Coastal Water (ACW) of the central Chukchi Sea, characterized by low chlorophyll, low nutrients, and small zooplankton taxa. Adult Pacific herring (Clupea pallasii) were more abundant in the less stratified Bering Strait waters and in the colder, saltier Bering Shelf Water of the northern Bering and southern Chukchi seas, characterized by high chlorophyll, high nutrients, and larger zooplankton taxa. Juvenile pink (Oncorhynchus gorbuscha) and chum (O. keta) salmon were most abundant in the less stratified ACW in the central Chukchi Sea and Bering Strait. Abundances of large zooplankton were dominated by copepods (Eucalanus bungii, Calanus glacialis/marshallae, Metridia pacifica) followed by euphausiids (juvenile Thysanoessa raschii and unidentified taxa), whereas small zooplankton L. Eisner (&) E. Martinson J. Maselko Auke Bay Laboratories, Alaska Fisheries Science Center, National Marine Fisheries Service (NOAA), Ted Stevens Marine Research Institute, 17109 Pt. Lena Loop Road, Juneau, AK 99801, USA e-mail:
[email protected] N. Hillgruber School of Fisheries and Ocean Sciences, University of Alaska Fairbanks, 17101 Pt. Lena Loop Road, Juneau, AK 99801, USA N. Hillgruber Institute of Fisheries Ecology, Thu¨nen Institut, Wulfsdorfer Weg 204, 22926 Ahrensburg, Germany
were dominated by bivalve larvae and copepods (Centropages abdominalis, Oithona similis, Pseudocalanus sp.). Pelagic community composition was related to environmental factors, with highest correlations between bottom salinity and large zooplankton taxa, and latitude and fish species. These data were collected in a year with strong northward retreat of summer sea ice and therefore provide a baseline for assessing the effects of future climate warming on pelagic ecosystems in sub-Arctic and Arctic regions. Keywords Arctic Bering Sea Chukchi Sea Community composition Water mass characteristics Zooplankton distribution Polar cod Pelagic fish
Introduction In recent years, sub-Arctic and Arctic marine ecosystems have been experiencing the effects of substantial climate change. Under increasing greenhouse gas scenarios, the Arctic is predicted to be ice-free in summer by 2050 and sea surface temperatures (SSTs) to increase by as much as 10 °C from 2000 to 2100 (Arzel et al. 2006; Lin et al. 2006; Stroeve et al. 2008; Wang and Overland 2009). Potential increases in resource extraction and ship travel make it critical to collect baseline data on fisheries resources and their relationships between ocean and ecosystem components in these high-latitude regions (Grebmeier et al. 2010). A better understanding of the water mass characteristics responsible for the distribution and abundance of pelagic fish is an essential first step in interpreting the effects of climate change on the pelagic fish communities in this region. While the distribution and abundance of demersal fish assemblages in the northern (N.) Bering and southeastern
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Chukchi seas have been explored in several disjointed studies (Lowry and Frost 1981; Barber et al. 1997; Cui et al. 2009; Norcross et al. 2010), a similar exploration of the pelagic fish fauna to date is missing. For example, little is known about the ecology and habitat preferences of polar cod (Boreogadus saida) in the N. Bering and southern (S.) and central (C.) Chukchi seas (Quast 1974; Lowry and Frost 1981; Barber et al. 1997; Cui et al. 2009; Norcross et al. 2010). Another gadoid species that has attracted even less scientific attention is the saffron cod (Eleginus gracilis). While in recent years, this species appears to have undergone a remarkable range extension into the northern Gulf of Alaska (Johnson et al. 2009), knowledge about the biology and ecology and even taxonomy of this species is limited or outdated (Wolotira 1985; Johnson et al. 2009). Even fewer studies specifically targeted the pelagic larval and juvenile stages of these ecologically important Arctic taxa (Quast 1974; Welch et al. 1992, 1993; Norcross et al. 2010, Parker-Stetter et al. 2011). A better understanding of these small pelagic fishes, however, is important because of their trophic link to many piscivorous predators, such as seabirds (Springer et al. 1984; Piatt et al. 1989; Gaston et al. 2003) and marine mammals (Seaman et al. 1982). Juvenile stages of Pacific salmon (Oncorhynchus spp.) and whitefish (Coregonus spp.) are also parts of these pelagic fish assemblages in Arctic and sub-Arctic waters and are important subsistence resources of local communities (Jarvela and Thorsteinson 1999). In the N. Bering and the C. Chukchi and S. Chukchi seas, several water masses can be discerned, which are likely to impact the distribution of pelagic zooplankton and fish, namely Alaska Coastal Water (ACW), Bering Shelf Water (BSW), and Anadyr Water (AW). These water masses have a north–south orientation (Coachman et al. 1975), with ACW on the east, BSW in the middle, and AW on the west. The ACW originates along the coast over the inner shelf in the eastern Bering Sea; it develops annually from the input of river water and melting ice from western Alaskan rivers and its temperature increases rapidly through spring and summer from about 0 to 10 °C (Springer et al. 1984). The BSW originates on the middle Bering Shelf, south of St. Lawrence Island. The AW originates from the Gulf of Anadyr at depth along the continental slope of the Bering Sea (Springer et al. 1989). The ACW is less saline (\*31.8–32.2), warmer (2–13 °C), and has lower concentrations of nutrients and chlorophyll a than BSW and AW (Coachman and Shigaev 1992; Weingartner 1997). In contrast, BSW and AW are cooler (0–10 °C), more saline (BSW:*31.8–33; AW:*32.3–33.3), and have substantially higher chlorophyll a and nutrient concentrations (Sambrotto et al. 1984; Walsh et al. 1989; Coachman and Shigaev 1992; Weingartner 1997). While strong frontal gradients separate ACW and BSW, only a gradual interface
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exists between AW and BSW, which promotes the formation of a combined water mass, the Bering Shelf Anadyr Water (BSAW) characterized by high primary and secondary production (McRoy et al. 1972; Alton 1974; Stoker 1978, 1981; Grebmeier 1987; Grebmeier et al. 1988; Springer 1988; Walsh et al. 1989). While high primary production is fueled by a high and continuous supply of nitrogen from AW (Grebmeier et al. 1988), high secondary production is largely due to the transport of oceanic zooplankton northward into the Chukchi Sea (Springer et al. 1989; Weingartner 1997). Zooplankton distributions are generally associated with water masses (e.g., Hopcroft et al. 2010). However, the distribution of pelagic early life stages of fishes may be more closely tied to bathymetry (e.g., Duffy-Anderson et al. 2006), topography and current patterns (Doyle et al. 2002), and to water mass characteristics (e.g., Norcross et al. 2010, Siddon et al. 2011). The strong contrasting physical and biological characteristics of water masses in the northeastern Bering Sea and Chukchi Sea are expected to define distinctly differing habitat characteristics for pelagic zooplankton and fish taxa in these regions. Therefore, this study is directed at identifying the main water masses and characterizing patterns in pelagic zooplankton and fish distributions in response to environmental variables associated with these water masses. Specifically, we examined nutrient concentrations, biomass, size fractionation and production of phytoplankton, light attenuation, large and small zooplankton abundance, and pelagic fish abundance. The main objectives of this study are to (1) characterize the physical and biological properties of the major water masses in the study area; (2) identify single species and community composition of zooplankton and fish in relation to water masses and geographic location; and (3) examine whether the distributional patterns of zooplankton and pelagic fish communities are related to environmental parameters. The data used in this study are the result of a northern extension of an ongoing Bering Aleutian Salmon International Survey (BASIS) program initiated by the North Pacific Anadromous Fisheries Commission to study the effect of climate change and variability on Bering Sea pelagic ecosystems (Farley 2009).
Methods Sample collection, laboratory analysis, and processing A fisheries oceanography survey was conducted aboard the NOAA ship R/V Oscar Dyson in the S. and C. Chukchi Sea and N. Bering Sea, September 4–17 2007 (Fig. 1). Station spacing was 38–55 km from latitude 70°N–64°N and
Polar Biol Fig. 1 Stations sampled by the R/V Oscar Dyson, 4–17 September 2007. Dashed line is the international date line. Bathymetry contours are every 50 m. Latitudinal regions are circled
longitude 164°W–172°W, on the US side of the date line. Bottom depths ranged from 25 to 60 m. The surface mixed layer depth ranged from 10 to 30 m. Oceanographic data were obtained from conductivity– temperature–depth (CTD) vertical profiles from the surface to 5–10 m above the bottom using a SBE (Seabird Electronics Inc.) 911plus CTD with auxiliary sensors for chlorophyll a fluorescence (Wet Labs Wet-star) and light attenuation (Wet Labs Wet-Star and Wet Labs C-Star, used to estimate relative particle concentration). Data were processed using standard SBE processing software, quality checked to remove data spikes, and 1-m binned. To estimate nutrient availability and phytoplankton biomass, size structure, and primary productivity (PP), we collected seawater samples from Niskin bottles attached to the CTD. Water was analyzed for nutrients (nitrate, nitrite, phosphate, silicate, and ammonium), chlorophyll a (totals using Whatman GF/Fs, and size fractions [10 lm using Millipore Isopore polycarbonate membrane filters), and phytoplankton carbon uptake (on-deck incubation experiments). Nutrient samples were immediately filtered with a 0.2-lm polycarbonate filter, stored at -20 °C, and analyzed at a shore-based facility using colorimetric protocols
(Gordon et al. 1994). Chlorophyll a samples were stored at -70 °C and analyzed with a Turner Designs (TD-700) laboratory fluorometer (Parsons et al. 1984). In situ fluorometric data were calibrated with discrete chlorophyll a samples to estimate chlorophyll a concentrations (r2 = 0.78). At a subset of stations, we conducted stable isotope (13C) primary production experiments following standard protocols (Dugdale and Goering 1967). Zooplankton samples were collected with two gear types and mesh sizes to estimate biomass of large and small zooplankton taxa. For small taxa, zooplankton samples were collected with a 160-lm mesh 50 cm diameter Juday net equipped with a General Oceanics flowmeter. The net was cast and retrieved vertically at 1 m s-1 to within 2 m of the bottom, retrieved and rinsed. Zooplankton samples were sorted on board to the lowest taxonomic level and developmental stage feasible (Volkov and Murphy 2007), and water column densities (No. m-2) were determined using flow meter counts. Zooplankton biomass (wet weight in mg m-3) for each taxon was estimated from densities using mean weights from the literature (Volkov and Murphy 2007). For large taxa, zooplankton samples were collected with a 505-lm mesh, 60 cm diameter bongo net
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equipped with a General Oceanics flowmeter located above the bridle. Double oblique tows were conducted from surface to 5–10 m off the bottom, nets rinsed, and the contents preserved in 5 % buffered formalin–seawater solution. At a shore-based facility, samples were sorted to the lowest possible taxonomic level and species-specific wet weights were measured (Coyle et al. 2008). For subsequent data analysis, zooplankton taxa were designated as ‘‘large’’ if individual wet weights were C0.25 mg or ‘‘small’’ if individual wet weights were \0.25 mg. Abundance for large taxa was determined from bongo net samples, while small taxa abundance was determined from Juday net samples. Large taxa primarily included large copepods, larvaceans (Oikopleura sp.), chaetognaths, euphausiids (juveniles and furcilia), amphipods, and cnidarians. Small taxa primarily consisted of small copepods, larvaceans (Fritillaria sp.), cladocerans, pteropods (Limacina helicina), polychaetes, and various meroplankton taxa (e.g., bivalve larvae, cirripedia). For small taxa, we removed one outlier located at 70°N, 168°W, the first station sampled, since raw abundances in the Juday sample were very low at this station and sample collection was considered questionable. Pelagic fish were captured at each station with a Cantrawl 300 midwater trawl with a mean horizontal spread of 54 m, mesh size of 1.2 cm, rigged to sample the top 12 m of the water column. Trawls were towed at 7.8–8.5 km h-1 for 30 min and sampled a mean area of 0.224 km2. Upon retrieval of the trawl, the whole catch was immediately sorted. Fish were identified to species, counted, and weighed to the nearest 1.0 g wet weight. For large catches, a random subsample was sorted to taxa, counted, weighed, and the results were extrapolated to estimate the total catch by taxa. All fish were measured in fork length to the nearest 1.0 mm. Abundances (No. km-2) were estimated for all fish taxa. Statistical analyses We conducted several nonparametric analyses using PRIMER-E Version 6.1 (Clarke and Warwick 2001; Clarke and Gorley 2006) as well as standard parametric analyses. Water masses and natural groupings of zooplankton and fish were defined using PRIMER CLUSTER analysis. Differences in environmental variables between water masses and latitudinal regions were analyzed with the analysis of variance (ANOVA) followed by Tukey’s tests. Relationship between water mass, geographic location, and zooplankton and pelagic fish community composition was evaluated with PRIMER analysis of similarity routine (ANOSIM). To determine the environmental parameters that best explain distributional patterns of zooplankton and fish communities, we used PRIMER BIO-ENV analysis.
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Temperature (T) and salinity (S) were used to determine water mass cluster groups. We extracted surface (mean for top 8 m) and bottom (mean for bottom 8 m) T and S measurements from CTD profiles, normalized T and S data separately, then split data into four columns (surface and bottom T and S). CLUSTER analysis with SIMPROF (similarity profile) tests was used to group the normalized surface and bottom T and S data. Within each cluster group, the surface and bottom water masses were characterized based on their T and S ranges as ACW, BSW, and AW as defined in prior studies (Coachman and Shigaev 1992; Weingartner 1997). Differences in physical and biological oceanographic parameters among water mass cluster groups and latitudinal groups (C. Chukchi Sea, S. Chukchi Sea, and N. Bering Sea) were compared using ANOVA followed by Tukey’s tests for multiple comparisons. Latitudinal separations were set at 64.0–65.5°N, 66–68°N, and 68.5–70°N to stratify the sampling area into the N. Bering Sea, S. Chukchi Sea, and C. Chukchi Sea, respectively (Fig. 1). Oceanographic parameters included surface and bottom T, S, dissolved inorganic nitrogen (DIN), phosphate (PO4), silicate (SiO4), surface chlorophyll a, water column integrated chlorophyll a, mean fraction chlorophyll a [ 10 lm, and mean light attenuation. Contour maps of oceanographic characteristics were produced using the inverse distance routine in Geostatistical Analyst in ArcMap (version 9.3.1). Distributions of the most common zooplankton and fish taxa were plotted. Mean abundance of large zooplankton, small zooplankton, and fish for each water mass cluster grouping was listed (Tables 1, 2). We used ArcMap with natural breaks (Jenk’s classification) to produce distribution plots (bubble plots) of common zooplankton and fish taxa (taxa making up [95 % of total abundances) and PP. Significant differences in community composition between water masses were determined with ANOSIM based on Bray-Curtis similarity indices. For pairs of water mass cluster groups, we computed an ANOSIM R value, a measure of the overall difference between groups based on a given distance measure matrix. For R = 0, there is no difference, whereas R = 1 indicates groups are non-overlapping. These analyses were conducted on square root (sqrt) transformed abundance data to balance the influence of rare and abundant species (Clarke and Warwick 2001). Abundances of large zooplankton, small zooplankton, and fish taxa were compared between pairs of water mass groups. Similarities in community composition within water mass groups were compared using SIMPER (similarity percentages routine) with similarities between stations within a group ranging from 0 for no overlap to 100 % for complete overlap. We also examined natural species
Polar Biol Table 1 Statistical differences in oceanographic characteristics between water mass cluster groups (A–F) Water mass cluster Surface Bottom N
A ACWlowS ACWlowS 2
D ACWhighS ACWhighS
B ACWlowS BSW
F ACWlowS BSAW 10
E BSW BSAW
C BSAW BSAW
8
10
Ts
10.83
8.73
11.23
9.70
8 7.38
2.58
Tb Ss
10.68 30.10
6.40 31.44
6.27 30.10
2.56 31.54
3.47 32.31
1.97 32.55
Sb
ANOVA F
Tukey P
Sig. at P \ 0.05
E [ B, C [ BDEF
1
30.37
31.67
32.07
32.44
32.59
32.56
DINs
3.66
1.09
0.44
0.70
3.17
14.96
7.23
0.0001
DINb
0.56
2.53
2.97
10.42
15.60
21.36
16.57
0.0001
CEF [ ABD
Ps
0.50
0.47
0.29
0.36
0.57
1.44
5.8
0.001
CE [ B, C [ F
Pb
0.55
0.74
0.70
1.36
1.63
1.94
14.37
0.0001
CEF [ ABD
Sis
8.27
8.04
4.38
6.11
14.40
40.22
5.34
0.001
E [ B, C [ BF
Sib
8.92
11.17
7.40
23.02
33.18
46.76
8.7
0.0001
CEF [ B, E [ D
0.85
1.07
1.05
1.19
4.70
1.12
8.59
0.0001
E [ ABDF
IntChwc
16.75
39.55
25.94
36.58
67.25
35.44
3.19
0.001
E [ CDF
Ch10wc
0.46
0.53
0.24
0.38
0.41
0.60
4.08
0.005
D[B
Attwc
1.75
0.78
0.36
0.40
0.77
0.39
3.73
0.009
A [ BF
Chs
Mean values (untransformed) of oceanographic parameters shown for each water mass cluster group (ACWlowS:Alaska Coastal Water, low salinity, ACWhighS:Alaska Coastal Water, high salinity, BSW: Bering Shelf Water, BSAW: Bering Shelf Anadyr Water). Prior to statistical analysis, transformations (lnX?1) were conducted for DIN (dissolved inorganic nitrogen), Si (silicate), Ch (chlorophyll a), IntCh (integrated chlorophyll a), and ln(x) for Att (light attenuation), but not for T (temperature) and S (salinity) or P (phosphate). Lower case italic s indicates surface data, b indicates bottom, and wc indicates water column. Differences in oceanographic characteristics were tested with the analysis of variance (ANOVA), displaying F values and probability (P). N number of samples
Table 2 Statistical differences in oceanographic characteristics between latitude regions: central Chukchi Sea (CCh), southern Chukchi Sea (SCh), and northern Bering Sea (NBer) Regions
CCh
SCh
NBer
ANOVA F
15
Tukey P
Sig. at P \ 0.05
N
12
Ts
10.75
9.31
12 8.12
8.49
0.001
CCh [ NBer
Tb Ss
4.82 30.79
5.51 31.20
4.44 31.69
0.58 3.84
0.567 0.031
NBer [ CCh
Sb
32.21
32.14
32.03
0.33
0.719
DINs
0.48
0.95
3.37
6.73
0.003 0.611
NBer [ CCh, SCh
DINb
4.82
7.82
9.99
0.5
Ps
0.36
0.31
0.61
11.87
0.0001
Pb
0.94
1.03
1.27
1.2
0.313
Sis
3.31
8.18
13.55
20.33
0.0001
NBer, SCh [ CCh
Sib
9.45
18.83
25.61
5.66
0.007
NBer [ CCh SCh [ CCh
Chs
NBer [ CCh, SCh
0.79
2.81
1.88
3.17
0.054
IntChwc
22.79
47.37
47.11
6.66
0.003
NBer, SCh [ CCh
Ch10wc
0.30
0.38
0.48
3.91
0.029
NBer [ CCh
Attwc
0.21
0.74
0.83
21.65
0.0001
NBer, SCh [ CCh
Mean values (untransformed) of oceanographic parameters shown for each latitudinal region. Prior to statistical analysis, transformations (lnX ? 1) were conducted for DIN (dissolved inorganic nitrogen), Si (silicate), Ch (chlorophyll a), IntCh (integrated chlorophyll a), and ln(x) for Att (light attenuation), but not for T (temperature) and S (salinity) or P (phosphate). Lower case italic s indicates surface data, b indicates bottom, and wc indicates water column. Differences in oceanographic characteristics were tested with analysis of variance (ANOVA), displaying F values and probability (P). N number of samples
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composition of groupings of zooplankton and fish taxa using the CLUSTER analysis with SIMPROF tests, which allowed us to describe spatial variations in community composition over the whole survey region, irrespective of water mass. The environmental factors that best explained the community composition of zooplankton and fish abundance were determined with BIO-ENV analysis within the BEST routine, which searches over subsets of environmental variables to determine ones that best explain the spatial variations in community composition. Spearman rank correlation coefficients (q), which estimate the measure of agreement between the environmental and taxonomic data sets (with 0 indicating no similarity and 1 perfect agreement), were computed for all combinations of variables. Environmental variables included latitude, longitude, station depth, and the oceanographic parameters listed above that were used for water mass and latitude comparisons. Nutrients, chlorophyll a, and light attenuation were ln(x ? 1) or ln(x) transformed, and all data were normalized prior to BIO-ENV analysis.
Results Physical characterization of water masses in the N. Bering and Chukchi seas Six separate water masses were identified from the cluster analysis (SIMPROF test at 5 % significance) within the N. Bering Sea and the S. and C. Chukchi Sea regions. Cluster groups were classified by surface and bottom water masses including two ranges of ACW, one with lower salinity (ACWlowS) and one with higher salinity (ACWhighS), BSW and BSAW (AW, Anadyr water and BSW combined). Surface/bottom water mass cluster groups (Table 1) included three groups with high water column stratification (B = ACWlowS/BSW, F = ACWhighS/BSAW, and E = BSW/BSAW) and three groups with low stratification (A = ACWlowS/ACWlowS, D = ACWhighS/ACWhighS, and C = BSAW/BSAW) (Fig. 3a). ACWhighS was characterized by T of *6–11 °C (with two outliers at 4–5 °C) and S of *31–32. BSW had T of *5–9 °C and S of *31.8–32.5 with one outlier at 31.6. BSAW had T of -1 to 4 °C and S of 32.3–33.0 with one outlier at T = 5, S = 32.1. Over the survey area, SST ranged from 2.6 to 11.9 °C and sea surface salinity (SSS) from 29.5 to 32.6; bottom T ranged from -0.9 to 10.8 °C and bottom S from 30.0 to 32.9 (Fig. 2). Higher T was observed in the lower S waters and vice versa (Figs. 2a, b,3b; Table 1). At both the surface and bottom, temperature generally decreased and salinity increased from onshore to offshore (Figs. 2,4). In addition, mean surface T decreased and S increased from north to
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south with significantly warmer and less saline surface water in the C. Chukchi Sea; however, no significant latitudinal differences were seen for bottom T and S (Table 2). Latitudinal variations were partially reflected in variations in water mass distribution. ACWlowS/BSW (group B) was primarily seen at inshore stations in the Chukchi Sea, but was not found in the N. Bering Sea. ACWlowS/ ACWlowS (group A) was detected at only two stations (Figs. 2a, b, 3a, c). ACWhighS/BSAW (group F) was seen at several offshore stations throughout the survey area, whereas ACWhighS/ACWhighS (group D) was found primarily nearshore in the N. Bering Sea and Bering Strait. BSW/BSAW (group E) was observed offshore in the S. Chukchi and N. Bering seas, but not further north in the C. Chukchi Sea. Finally, BSAW/BSAW (group C) was detectable only at one station north of St. Lawrence Island. Overall, for surface and bottom combined, ACWlowS was seen only in the Chukchi Sea with the exception of one station inshore in the NBS, whereas ACWhighS, BSW, and BSAW were seen throughout the study region. Vertical sections of T and S were used to visualize the vertical structure of surface and bottom water masses within each cluster group (Fig. 4). These plots show that surface mixed layer depths were shallow and increased from onshore (*10 m depth) to offshore (*20 m depth) (Fig. 4a–c). Longitudinal variations occurred between surface and deepwater masses, with fronts located further offshore (westward) for surface compared to deepwater masses (Fig. 4a–c). By latitude, lower salinity and higher temperature surface waters occurred between 66–67°N and 69–70°N (Fig. 4d) possibly due to closer proximity to shore. Biological characterization of water masses in the N. Bering and Chukchi seas The main surface water masses not only differed significantly in their physical characteristics, but also displayed large differences in biological properties, such as nutrients, chlorophyll a, and particle concentrations (Table 1). Surface nutrients increased from onshore to offshore with DIN values above limiting levels ([1 lM) in water mass cluster groups C and E located along the western edges of our survey area (Figs. 2, 3a). Water mass cluster group C with surface BSAW had the highest DIN, followed by group E with surface BSW and groups B, D, and F with surface ACW (Table 1). As with T and S, surface nutrients (DIN, SiO4, PO4) showed latitudinal gradients, with increases in nutrient concentrations from north to south (Table 2). Bottom nutrients had a similar spatial pattern as surface nutrients, with highest values further offshore in bottom BSAW (clusters C, E, F); bottom nutrients throughout our survey area were always above 1 lM (Fig. 2). Bottom DIN
Polar Biol
Fig. 2 Contours of surface a temperature (°C), b salinity, c dissolved inorganic nitrogen (DIN, lM), and d silicate (lM); bottom e temperature, f salinity and g DIN, h silicate; i surface chlorophyll a (chla, mg m-3) with surface primary productivity (mg C m-3 d-1); water column j integrated chlorophyll a (mg m-2), k mean percent large chla (ratio [10 lm/total chla), and l mean light attenuation coefficient (m-1). Water mass cluster group is shown for each station.
Water mass designations are Alaska Coastal Water low S (ACW low S) and high S (ACW high S), Bering Shelf Water (BSW) and Bering Shelf Anadyr Water combined (BSAW). Surface/Bottom water B = ACWlowS/BSW, masses are A = ACWlowS/ACWlowS, C = BSAW/BSAW, D = ACWhighS/ACWhighS, E = BSW/BSAW, F = ACWhighS/BSAW
and SiO4 were higher in cluster groups C, E, and F than in groups A, B, and D (Table 1), indicating that bottom BSAW had higher nutrient concentrations than other water masses. DIN covaried with PO4 and SiO4, with higher
correlations seen for bottom compared to surface nutrients and for PO4 compared to SiO4 (Pearson correlation for DIN compared to PO4 and SiO4 = 0.87, 0.69 for surface and 0.95 and 0.88 for bottom nutrients).
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Polar Biol Fig. 3 a Water mass groupings from cluster analysis of surface (top 8 m) and bottom (bottom 8 m) temperature and salinity (TS) data. Water mass designations are Alaska Coastal Water low S (ACW low S) and high S (ACW high S), Bering Shelf Water (BSW), and Bering Shelf Anadyr Water combined (BSAW). Surface/Bottom water masses are A = ACWlowS/ ACWlowS, B = ACWlowS/BSW, C = BSAW/BSAW, D = ACWhighS/ACWhighS, E = BSW/BSAW, and F = ACWhighS/BSAW. b Surface and bottom water TS characteristics for all stations. Cluster groups and water mass designations (ovals) are indicated
Latitudinal variations were only significant for bottom silicate with decreasing concentrations observed from N. Bering Sea to the C. Chukchi Sea (Table 2). Surface and integrated water column chlorophyll a and PP were also relatively high in areas with high surface nutrients, particularly in water mass group E, where surface chlorophyll a was significantly higher than in all other groups (Fig. 2; Table 1). Only stations located northwest of St. Lawrence Island (Groups C, F, and D) represented exceptions with relatively high surface nutrients and low chlorophyll a (Table 1; Fig. 2). Over the survey area, moderate correlations were seen for surface chlorophyll a with surface DIN and SiO4 (Pearson correlation = 0.33 and 0.51, respectively). High correlations between surface and integrated chlorophyll a (Pearson correlation = 0.70) suggest that phytoplankton peak concentrations were mainly in surface waters. Based on the mean water column ratios of [10 lm/total chlorophyll a, a higher percentage of large phytoplankton were located nearshore in the N. Bering Sea, at the innermost station at 70°N (group D, ACWhighS/ACWhighS), and in the high chlorophyll a region in the S. Chukchi Sea (group E, BSW/BSAW) (Fig. 2). Phytoplankton particle sizes were
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larger in surface ACWhighS (group D) than in surface ACWlowS (group B) (Table 1). The smallest phytoplankton were in group B, which also had low mean concentrations of surface DIN (\1 lM). Phytoplankton also showed latitudinal variations with larger phytoplankton found in the N. Bering than in the S. and C. Chukchi and higher chlorophyll a concentrations found in the N. Bering or S. Chukchi than in C. Chukchi (Table 2). Mean water column light attenuation was highest, indicating more particles in the water, in the N. Bering and S. Chukchi seas than in the C. Chukchi Sea (Table 2), with significantly higher values in group A than in B and F (Table 1). The high chlorophyll a in the offshore regions of the S. Chukchi (group E) likely account for the higher attenuation of light in these regions, whereas high sediment loads associated with river input may account for high attenuation in the nearshore regions in the N. Bering Sea (group A and D) (Yukon River input) and to a lesser extent in the S. Chukchi Sea (Noatak and Kobuk River input) (Figs. 1, 2; Table 1). Light attenuation was positively correlated with integrated chlorophyll a and surface SiO4 (Pearson correlation = 0.54 and 0.53, respectively) and negatively correlated with latitude (Pearson correlation = -0.57).
Polar Biol
(a)
ACW H
ACW H
ACW L ACW H
ACW H
ACW H
ACW H BSW
BSW BSAW
BSAW
(b)
ACW H
BSW
BSAW
(c)
ACW L
ACW L
BSW
BSAW BSW ACW L ACW H ACW H
ACW H
BSW
BSAW
ACWL
BSW
BSAW BSW ACW L ACW H ACW H
ACW L
ACW L
ACW H
ACW H
BSAW
(d)
BSAW
BSW ACW L ACW L ACW H ACW H
ACW L BSW ACW H
ACW L
ACW L BSW
BSW BSW
BSW BSAW
ACW L ACW H
ACW H
BSAW
ACW H
Fig. 4 Vertical slices of temperature (T) and salinity (S) for east–west transects along a 70°N, b 67.5°N, c 64.5°N and d north–south transect along *168°W, graphed in Ocean Data View. Surface and bottom water masses are labeled
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Polar Biol
Single species abundances in relation to water masses and geographic location Zooplankton sampling yielded copepods, larvaceans, chaetognaths, euphausiids, amphipods, cnidarians, ctenophores, polychaetes, and meroplankton (Table 3). Taxa groups responsible for [90 % of the total abundance for large zooplankton included copepods (59 %), euphausiids (25 %), and larvaceans (6 %), and for small zooplankton meroplankton (52 %) and copepods (39 %) (Table 4) with meroplankton making up 49 % of the total abundance, followed by copepods (40 %) for large and small taxa combined. In contrast, large and small copepods accounted for the highest overall wet weight biomass (62 %), followed by euphausiids (22 %). Large zooplankton taxa accounted for almost twice as much of the total biomass as small taxa (63 % large compared to 37 % small), although small taxa were slightly more abundant (45 % large and 55 % small) (Table 4). Among large taxa, copepods were most abundant in the N. Bering Sea followed by C. Chukchi and S. Chukchi, whereas euphausiids were most abundant in the S. Chukchi Sea followed by C. Chukchi and N. Bering (Table 4). The ten most abundant large zooplankton taxa making up 95.7 % of the total abundance were large copepods (Eucalanus bungii, Calanus glacialis/ marshallae, Metridia pacifica), euphausiids (juveniles of Thysanoessa raschii and unidentified furcilia and juveniles), chaetognaths (Sagitta elegans), amphipods (Parathemisto sp.), cnidarians (Aglantha digitale), and larvaceans (Oikopleura sp.). The six most abundant small taxa making up 95.7 % of the total abundance were small copepods (Centropages abdominalis, Oithona similis, Pseudocalanus sp., and unidentified naupliar stages), polychaetes (unidentified trochophores), and bivalve larvae. Zooplankton taxa varied along north/south and onshore/offshore gradients and between water mass cluster groups (Table 3; Fig. 5). Large taxa were concentrated further offshore in higher salinity water masses (Fig. 5a–j). The dominant large zooplankton taxa were in highest abundances in water mass cluster groups with bottom BSAW (C: BSAW/BSAW, E: BSW/BSAW, and F: ACWhighS/BSAW) and lowest in group A (surface and bottom ACWlowS), which only had one large taxon, S. elegans. Large copepods (E. bungii, M. pacifica, and C. marshallae) and the larvacean Oikopleura sp. had the highest concentrations in cluster groups C, E, and F (bottom BSAW), although E. bungii was also present in medium levels in group D (surface and bottom ACWhighS) (Fig. 6; Table 1). For euphausiids, unidentified furcilia and T. raschii had relatively high abundances in groups E and F, whereas unidentified juveniles were observed in relatively high numbers in group E. The cnidarian A. digitale had highest abundance in group D. The
123
chaetognath S. elegans was the most widespread species with moderate abundances in all water mass cluster groups, while the amphipod Parathemisto sp. was least prevalent with low abundances in groups C, E, F, and D; it was absent in groups A and B. Small zooplankton taxa were more evenly distributed across water masses with distributions generally highest inshore in the C. and S. Chukchi Sea, although high concentrations of O. similis, C. abdominalis, and copepod nauplii were also observed in the N. Bering Sea (Fig. 5k– p). The dominant small zooplankton taxa had the highest abundances in groups with surface ACW (B: ACWlowS/ BSW, D: ACWhighS/ACWhighS and F: ACWhighS/BSAW) and lowest in group C (surface and bottom BSAW) (Fig. 6; Table 3). Small copepods, O. similis and C. abdominalis, had the highest concentrations in group B (ACWlowS/BSW) with O. similis also in high concentrations in group D (surface and bottom ACWhighS). Pseudocalanus sp. occurred in moderate abundances in E, F, B, and D. Polychaetes were most abundant in groups B, F, and E, but not present in group C. Bivalve larvae, the most numerous meroplankton, were most abundant in group F (ACWhighS/ BSAW) and B (ACWlowS/BSW), followed by groups E, D, and A. Copepod nauplii were seen only in low abundances in groups E, F, B, D and absent in other groups. Fish surface trawls yielded mostly juvenile stages of fish species, resulting in a total of 120,515 individuals belonging to 29 taxa (Table 5). Only seven fish species made up 97.2 % of the total abundance, namely, in descending order, juvenile saffron cod (E. gracilis, 55.9 % of total), adult Pacific herring (13.7 %), juvenile shorthorn sculpin (Myoxocephalus scorpius, 9 %), juvenile polar cod (7.6 %), juvenile pink salmon (O. gorbuscha, 4.3 %), adult Pacific sand lance (3.9 %), and juvenile chum salmon (3.1 %) (Table 5). All other fish species made up \1 % of the total catch and were therefore excluded from further distributional analysis. Horizontal distribution of the major seven fish taxa varied notably with latitude and water mass cluster. Fish were captured in surface water masses, so fish distributions are expected to be more strongly associated with surface rather than bottom water masses. Both gadoid species, saffron cod and polar cod, as well as juvenile shorthorn sculpins and adult Pacific sand lance were captured mostly above 68°N (Fig. 7), but species distribution also varied with water mass cluster (Fig. 6; Table 5). Saffron cod juveniles were widely distributed in nearshore waters, with highest mean abundances in water mass groups with surface ACW (B: ACWlowS/BSW, D: ACWhighS/ACWhighS, and F: ACWhighS/BSAW), similar to small zooplankton (Fig. 6). In contrast, polar cod was most abundant in group F (ACWhighS/BSAW; Table 5). Virtually, no juvenile gadoids occurred in groups E and C (BSW/BSAW and
Polar Biol Table 3 Mean zooplankton abundances (No. m-2) by water mass structure groupings for large (lg) and small (sm) taxa and sums of mean abundance for each taxonomic group (bold data) Taxa group
Size
Water mass cluster Surface Bottom Taxa
Copepod
lg
Calanus glacialis/mar. Epilabidocera amphitrites
D ACWhighS ACWhighS
B ACWlowS BSW
F ACWlowS BSAW
212
1,703
1,208
2,565
2,205
505
960
283
51
0
0
Eucalanus bungii
94
13,108
6,979
21,124
37,055
37,485
Metridia pacifica
0
1,843
394
13,053
10,599
29,988
Neocalanus cristatus
0
0
2
131
163
10
Neocalanus flemingeri
0
0
0
49
105
469
Neocalanus plumchrus
0
37
15
386
553
1,718
Neocalanus sp.
0
128
157
175
235
625
800
17,800
9,000
37,535
50,915
72,800
0 0
83 0
5,619 0
0 258
0 0
0 0
19,831
54,934
94,947
58,581
65,810
11,096
3,059
27,660
18,655
13,696
17,847
0
293
0
361
0
0
0
Metridia sp. (copepodites)
0
1,435
0
1,533
4,649
46,313
Microcalanus pygmaeus
0
0
622
925
536
50,172
Microsetella sp.
0
344
361
1,370
2,521
0
Neocalanus sp. (copepodites)
0
1,742
0
228
1,905
483
Oithona plumifera
0
0
602
0
0
0
Oithona similis
25,121
154,208
223,268
91,322
73,113
77,188
Oncea borealis
0
1,926
0
932
5,218
0
5,956
27,125
38,505
36,947
41,249
9,166
Large copepods sm
Acartia hudsonica Acartia longiremis Centropages abdominalis Copepoda (nauplii) Eurytemora pacifica
Pseudocalanus sp.
Larvacean
Cladoceran
Chaetogn.
Euphausiid
A ACWlowS ACWlowS
E BSW BSAW
C BSAW BSAW 2,499
Racovitzanus antarcticus
0
0
0
488
0
0
Scolecithricella sp.
0
0
0
116
0
0
54,000 0
269,000 1,839
383,000 334
206,000 3,109
213,000 6,382
194,000 8,747
lg
Small copepods Oikopleura sp.
sm
Fritillaria sp.
0
25,715
903
369
0
11,578
Larvaceans
0
27,600
1,200
3,500
6,400
20,300
Evadne sp.
0
921
1,516
229
0
0
Podon sp.
3,522
1,220
2,005
688
0
0
Cladocerans
3,500
2,100
3,500
900
0
0
0
32
18
156
312
156
Parasagitta elegans
2,464
2,076
1,039
2,083
1,899
2,811
Chaetognaths
2,500
2,100
1,100
2,200
2,200
3,000
0
0
0
0
62
0
sm
lg
lg
sm
Eukrohnia hamata
Euphausiacea (calyptopis) Euphausiacea (furcilia)
52
645
2,720
16,155
10,683
3,124
Euphausiacea (juv)
37
888
86
1,071
4,788
2,499 0
Thysanoessa inermis
0
16
8
110
15
Thysanoessa raschii
0
711
121
7,704
2,212
0
Thysanoessa sp.
0
0
0
225
1,466
0
0 100
0 2,300
0 2,900
2,880 28,100
0 19,200
0 5,600
Euphausiacea eggs Euphausiids
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Polar Biol Table 3 continued Taxa group
Size
Water mass cluster Surface Bottom Taxa
Amphipod
lg
Aceroides sp.
53
0
0
0
0
0
Ampelisca sp.
0
1
0
0
0
0
lg
D ACWhighS ACWhighS
B ACWlowS BSW
F ACWlowS BSAW
E BSW BSAW
C BSAW BSAW
Amphipoda
186
22
0
0
0
0
Monoculodes sp.
106
77
365
107
0
0
Parathemisto sp.
0
242
222
608
720
781
Themisto libellula
0
0
3
4
66
20
Themisto pacifica
0
34
9
23
205
0
Stenothoidae
0
0
0
30
0
0
Hyperia medusarum
0
0
0
0
7
0
Hyperoche medusarum
0
0
0
0
1
0
300
400
600
800
1,000
800
Amphipods Cnidarian
A ACWlowS ACWlowS
Aegina sp. Aglantha digitale
0
0
0
110
0
0
201
3,948
500
855
833
937
Cnidaria
0
2
3
2
0
0
Coryne principes
0
0
62
0
0
0
Cormorpha flammea Leptomedusae (unident.)
0 0
8 1
0 7
0 0
0 1
0 0
Melicertum octocostatum
0
2
8
5
2
0
Melicertum sp.
0
1
0
1
0
0
42
0
0
0
0
0
0
0
2
0
0
0 900
Obelia sp. Proboscidactyla flavicirrata
200
4,000
600
1,000
800
Ctenophore
lg
Cnidarians Ctenophora (unident.)
0
0
10
8
22
0
Pteropod
lg
Clione limacina
0
0
5
6
18
156
sm
Limacina helicina (juv)
0
2,408
2,839
414
1,447
19
Pteropods
0
2,400
2,800
400
1,500
200
Polynoidae
0
0
0
0
0
0
Polychaete
Meroplank.
lg
Syllidae
0
0
2
0
0
0
Tomopteris sp.
0
0
0
1
0
0
sm
Polychaeta (troch)
13,456
12,015
56,898
63,080
60,422
0
lg
Polychaetes Ammodytes hexapterus
13,500 0
12,000 0
56,900 0
63,100 1
60,400 0
0 0
Argis lar Chionoecetes sp. Cottidae
0
0
0
0
0
172
96
161
230
49 0
0
0
0
1
0
Crangonidae
383
0
111
0
0
0
Diastylis sp.
7
0
0
0
0
0
Eudorellopsis sp.
123
35 178
27
0
0
0
0
0
Fish eggs
0
1
0
0
0
0
Fish (juvenile)
0
0
1
0
0
0
Fish (larvae)
260
49
19
3
16
0
Flatfish (juv)
0
0
1
0
0
0
Hippolytidae (juv)
0
1
0
0
8
0
Hippolytidae (zoea)
0
0
2
4
0
0
Hyas sp. (megalopa)
21
3
0
43
7
0
Polar Biol Table 3 continued Taxa group
Size
Water mass cluster Surface Bottom Taxa
A ACWlowS ACWlowS
B ACWlowS BSW
F ACWlowS BSAW
E BSW BSAW
C BSAW BSAW
Mysida (juv)
0
0
1
0
0
0
Neomysis rayii
7
0
0
0
0
0
Paguridae (glaucothoe)
0
0
8
6
7
0
Paguridae (zoea)
74
100
52
25
1
0
Pandalidae (zoea)
0
0
0
15
0
0
Pandalus sp.
5
1
0
0
0
0
Perigonimus sp. Pleuronectidae Asteroidea/bipinnaria sm
D ACWhighS ACWhighS
0
0
0
0
0
0
31
7
9
3
1
0 0
0
3,521
1,882
0
0
Cirripedia (cyprid)
587
3,884
5,845
2,851
198
0
Cirripedia (nauplii)
8,203
8,748
2,792
2,399
1,516
11,578
Echinodermata (larvae)
0
5,297
2,783
705
0
0
Bivalve larvae
134,908
157,679
561,429
426,551
227,053
23,156
Meroplankton
145,000
179,000
575,000
433,000
229,000
35,000
Table 4 Percentages of zooplankton abundance (No. m-2) by taxa group for large, small, and all taxa combined (total)
Abundance
Total (%)
Large (%)
Small (%)
Combined biomass Large (%)
Small (%) 32
Copepods
59
39
40
30
Euphausiids
25
\1
2
22
Chaetognaths
4
0
\1
8
Meroplankton
2
52
49
Amphipods
1
0
\1
1
Cnidarians
3
0
\1
1
Larvaceans
6
1
1
1
Polychaetes
\1
7
6
Column total
100
100
100
CCh (%)
4
1 63 SCh (%)
37 NBer (%)
Percent of large taxa abundance by region Percentages of total biomass for all taxa combined are shown for comparison. Percentages of large taxa abundance by geographic region (central Chukchi Sea (CCh), southern Chukchi Sea (SCh), and northern Bering Sea (NBer)) are included
Copepods
46
40
73
Euphausiids
25
51
10
Chaetognaths
8
2
4
Meroplankton
2
1
2
Amphipods
\1
2
1
Cnidarians
11
1
2
Larvaceans Column total
BSAW/BSAW, respectively). Shorthorn sculpin juveniles were primarily caught in water mass groups B (ACWlowS/ BSW) and F (ACWhighS/BSAW), while adult Pacific sand lance were virtually absent in all groups but F (Fig. 6). Adult Pacific herring distribution differed markedly from
7
3
8
100
100
100
gadoid distribution, with peak abundance below 68°N (Fig. 7). Adult herring occurred mostly offshore within water mass groups D (surface and bottom ACWhighS) and E, and other than juvenile Chinook salmon (O. tshawytscha), was the only taxon caught in group C (Fig. 6;
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Polar Biol
Fig. 5 Zooplankton abundance (No. m-2) for common large taxa a Eucalanus bungii and b Thysanoessa raschii, c Sagitta elegans, d Euphausiacea furcilia, e Euphausiacea juveniles, f Calanus glacialis/marshallae, g Parathemisto sp., h Metridia pacifica, i Aglantha
digitale, j Oikopleura sp., and small taxa, k Centropages spp. and l Oithona similis, m Pseudocalanus sp., n bivalve larvae, o Polychaete, and p Copoda nauplii
Table 3). In contrast to the above latitudinal distributions, juvenile pink and chum salmon were widely distributed throughout our study area with highest concentrations in less stratified ACW water of groups A and D (Figs. 3,4,6).
between water mass cluster groups were seen between group A (ACWlowS/ACWlowS) and all other groups (ANOSIM, R from 0.67 to 1.00) and between B (ACWlowS/BSW) and E (BSW/BSAW) (ANOSIM, R = 0.65). Significant differences were also found between groups B and D, B and F, D and E (ANOSIM, R = 0.23–0.44, Table 6). Similarity of large taxa within groups (among stations within a water mass group) ranged from 20 % (group A) to 44–51 % (groups D, B, F) to 60 % (group E). In contrast, the abundance of small zooplankton taxa was more evenly distributed across water masses with the largest differences between water mass cluster group B
Community composition in relation to water masses and geographic location Zooplankton community composition for large taxa (reflected by the abundance and relative proportion of each taxon) varied among water mass cluster groups (Table 6). For large zooplankton, the largest differences
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Polar Biol
Fig. 5 continued
(ACWlowS/BSW) and other water mass groups, with B and A showing the largest differences, followed by B and E, then B and D (ANOSIM R = 0.60, 0.36 to 0.29, respectively, Table 6). For small zooplankton taxa, similarity within water mass groups ranged from 49–50 % (groups D and F) to 58–59 % (group A and E) to 70 % (group B). Fish community composition varied with water mass group. Significant differences in fish community composition occurred only between water mass cluster group B (ACWlowS/BSW) and other groups, with large differences between B and A, B and E followed by B and D (ANOSIM, R = 0.73, 0.64 0.44, respectively, Table 6). Similarity within water mass groups ranged from
24–29 % (group F, A, and D) to 37 % (group E) and 52 % (group B). The natural groupings of the zooplankton and fish taxa determined using cluster analysis (SIMPROF test at 5 % level of significance) showed a likeness to water mass cluster groupings or latitudinal gradients. Large zooplankton taxa had seven groups that showed cross-shelf gradients corresponding to water mass grouping and distinct latitudinal variations (Figs. 3b, 8a). Small zooplankton taxa had six groups, with less distinct longitudinal and latitudinal gradients than seen for large zooplankton (Fig. 8b). Fish taxa had five groups (Fig. 8c). The geographic location of fish groups suggests that communities
123
Polar Biol
Fig. 5 continued
varied primarily along latitudinal gradients with water masses being only of secondary importance (Fig. 8c). Distribution of zooplankton and pelagic fish in relation to environmental factors Large zooplankton community composition was clearly related to bottom water mass. For large zooplankton abundances, the highest correlation of zooplankton community composition with environmental variables (BEST routine) was with bottom salinity, bottom SiO4, and longitude (Spearman rank coefficient, q = 0.65, Table 7). The highest single variable correlation was with bottom salinity
123
(q = 0.59) indicating that salinity could explain 59 % of the variability in large zooplankton community composition. Surface salinity was also correlated with large zooplankton community composition, albeit to a lesser extent (q = 0.37, Table 7). Separate BEST analyses for bottom salinity within each geographic region yielded even higher correlations, q = 0.76, 0.80, and 0.68, for N. Bering Sea, S. Chukchi Sea, and C. Chukchi Sea, respectively. Small zooplankton community composition did not correlate well with our suite of environmental variables. The highest correlation for small zooplankton abundances was with bottom salinity, surface DIN, mean water column light attenuation, water column mean ratio of[10 lm/total
Polar Biol
Fig. 6 Mean abundance of large zooplankton, small zooplankton, and fish for water mass cluster groups (a–f). Taxa shown account for 96, 96, and 97 % of total abundance over our survey grid for large zooplankton, small zooplankton, and fish, respectively
123
Polar Biol Table 5 Mean abundance (No. km-2) of fish by water mass cluster groups (A–F) with surface and bottom water masses shown Common name
Water mass group Surface over bottom Scientific name
Saffron cod
Eleginus gracilis
Pacific herring (adult)
Clupea pallasii
Shorthorn sculpin
Myoxocephalus scorpius
6
Polar cod
Boreogadus saida
Pink salmon
Oncorhynchus gorbuscha
Pacific sand lance
Ammodytes hexapterus
Chum salmon
Oncorhynchus keta
Slender eelblenny
Lumpenus fabricii
Capelin
Mallotus villosus
Pacific herring Rainbow smelt
Clupea pallasii Osmerus mordax
Longhead Dab (larvae) Sockeye salmon Chinook salmon
Oncorhynchus tshawytscha
Bering flounder (larvae)
A ACWlowS ACWlowS
D ACWhighS ACWhighS
B ACWlowS BSW
F ACWhighS BSAW
E BSW BSAW
C BSAW BSAW
Total caught
Length (mm)
98
8,727
17,624
8,133
0
0
67,535
79
892
4,231
262
349
3,867
82
16,502
200
265
1,813
2,736
43
0
10,412
51
120
550
634
3,304
2
0
9,230
68
1,076
1,541
442
248
197
0
5,169
175
0
0
10
2,108
2
0
4,769
75
685
1,034
278
110
412
0
3,784
196
0
3
277
287
0
0
1,124
75
0
32
148
24
117
0
638
102
831 652
0 0
0 0
0 0
0 0
0 0
381 299
92 101
Limanda proboscidea
2
5
58
22
7
0
199
34
Oncorhynchus nerka
2
3
0
13
49
0
125
210
21
38
0
0
0
5
80
228
Hippoglossoides robustus
0
0
3
27
0
0
63
37
Three-spined stickleback (adult)
Gasterosteus aculeatus
0
0
19
0
0
0
42
39
Coho salmon
Oncorhynchus kisutch
47
7
0
0
0
0
35
302
Arctic lamprey (adult)
Lethenteron camtschaticum
0
3
0
1
6
0
20
383
Chum salmon (immature)
Oncorhynchus keta
0
2
0
3
6
0
20
653
Chum salmon (maturing)
Oncorhynchus keta
0
1
0
0
8
0
17
691
Crested sculpin (adult)
Blepsias bilobus
0
2
5
0
0
0
13
107
Bering wolfish
Anarhichas orientalis
0
0
4
0
1
0
9
176
Slender eelblenny (adult)
Lumpenus fabricii
19
0
0
0
0
0
9
169
Chinook salmon (immature)
Oncorhynchus tshawytscha
2
1
0
0
2
0
6
677
Greenland halibut (larvae)
Reinhardtius hippoglossoides
0
1
0
2
0
0
5
72
Arctic Cod (larvae)
Boreogadus saida
0
0
0
2
0
0
4
38
Nine-spined stickleback (adult)
Pungitius pungitius
9
0
0
0
0
0
4
59
Pacific Sand lance (adult)
Ammodytes hexapterus
0
0
0
1
0
0
4
146
Crested Sculpin
Blepsias bilobus
0
1
1
0
0
0
3
92
Sockeye salmon (immature)
Oncorhynchus nerka
0
0
0
1
1
0
3
373
Prowfish
Zaprora silenus
0
0
0
0
0
0
2
117
Shorthorn Sculpin (adult)
Myoxocephalus scorpius
0
0
1
0
0
0
2
177
Atka mackerel
Pleurogrammus monopterygius
0
0
0
0
1
0
1
161
Pond Smelt
Hypomesus olidus
2
0
0
0
0
0
1
110
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Polar Biol Table 5 continued Common name
Water mass group Surface over bottom Scientific name
A ACWlowS ACWlowS
D ACWhighS ACWhighS
Rainbow Smelt (adult) Saffron Cod (adult)
B ACWlowS BSW
F ACWhighS BSAW
E BSW BSAW
C BSAW BSAW
Total caught
Length (mm)
Osmerus mordax
2
0
0
0
0
0
1
Eleginus gracilis
2
0
0
0
0
0
1
180
Salmon shark
Lamna ditropis
0
1
0
0
0
0
1
1,854
Starry flounder (adult) Walleye pollock
Platichthys stellatus Theragra chalcogramma
2 0
0 1
0 0
0 0
0 0
0 0
1 1
330 115
220
Total number of fish caught for all stations combined and mean length. Fish taxa are listed in the order of their total abundance. All fish listed were juveniles, unless stated differently
chlorophyll a (chla10), and station depth (Spearman rank coefficient, q = 0.39, Table 7). The highest single variable correlation was with chla10 (q = 0.23). The highest twovalue correlation included chla10 and surface DIN (q = 0.31). These data suggest that there may be a moderate relationship between small zooplankton community composition and surface DIN and phytoplankton taxa variations (reflected by changes in chlorophyll a size fraction ratios). Within each geographic region, separate BEST analysis of water mass properties (T and S) with small zooplankton showed that bottom salinity had correlations of q = 0.37, 0.14, and 0.37 for N. Bering Sea, S. Chukchi Sea, and C. Chukchi Sea, respectively. By region, the highest single value correlation for small zooplankton was for light attenuation (q = 0.44) for the N. Bering, surface SiO4 (q = 0.48) for the S. Chukchi, and surface PO4 (q = 0.46) for the C. Chukchi Sea. Thus, correlations of small zooplankton abundances with environmental factors were higher by region than for all regions combined. Pelagic fish community composition was highly correlated with latitude suggesting that the distributional ranges of fish taxa were primarily the result of geographic location and only secondarily due to water masses and associated habitat preferences. For fish abundances, the highest correlation was gained for three variables namely latitude, mean water column light attenuation, and surface SiO4 (q = 0.68) (Table 7). Latitude alone could explain 59 % of the variability in fish community composition (q = 0.59). For SST alone (data not shown), a moderate correlation (q = 0.29) was obtained, suggesting a secondary relationship with surface water mass TS characteristics. For mean water column light attenuation alone, a moderate correlation (q = 0.39) was also found, suggesting that water clarity may be associated with fish community composition. Separate BEST analyses within each geographic region yielded single correlations with surface temperature or salinity of q = 0.37, 0.21, and 0.41, for N. Bering Sea, S. Chukchi Sea, and C. Chukchi Sea, respectively.
Discussion Characteristics of water masses in the N. Bering and Chukchi seas Four separate water masses (within six water mass cluster groups) were identified within the N. Bering Sea and the S. and C. Chukchi Sea regions. These results are in contrast to previous studies that concluded that the N. Bering Sea and southeastern Chukchi Sea regions are generally influenced by only three dominant water masses, including the ACW, the BSW, and the AW (Coachman et al. 1975; Springer et al. 1984). Our analysis of surface water detected two components of the ACW, a nearshore low S component (ACWlowS) and more offshore high S component (ACWhighS), in addition to the BSW and BSAW, with the latter being generally located the furthest offshore in the N. Bering Sea and S. Chukchi Sea. Similarly, an intermediate water mass between ACW and BSW, termed transitional water (TW), was described for the Chukchi Sea (Hopcroft et al. 2010) with the mean over top 50 m for S ranging from 31.3 to 32.0 and for T from 4.5 to 8.0. Thus, the TW has similar S but lower T ranges than our ACWhighS. The ACW originates along the Alaskan coast over the inner shelf in the southeastern Bering Sea and moves northward through Bering Strait, and into the Chukchi Sea, generally hugging the Alaska coastline. The low S component of ACW is most likely due to coastal river discharges with large contributions from the Yukon River (Weingartner 1997), which provides most of the freshwater from late May through September (USGS 2008). In contrast, the BSW (and BSAW) most likely represents a mix of winterformed Bering Sea shelf water and deepwater from the Gulf of Anadyr (Weingartner 1997). Water masses encountered in our survey showed considerable variability in biological (nutrients, chlorophyll a, PP, and light attenuation) as well as physical characteristics. Surface nutrients, surface and integrated chlorophyll
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Polar Biol
Fig. 7 Fish abundance (No. m-2) of a saffron cod, b polar cod, c shorthorn sculpin, d adult sand lance, e adult herring, f chum salmon, and g pink salmon
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Polar Biol Table 6 Differences between water mass cluster groups for communities of large and small zooplankton (No. m-2) and fish (No. km-2) using PRIMER analysis of similarity routine (ANOSIM) on square root transformed (sqrt) abundance data
Water mass cluster pairs
Large zooplankton
Surface
A: ACWlowS
B: ACWlowS
Bottom
ACWlowS
BSW
Small zooplankton
Fish
0.87*
0.60*
0.67*
0.00
-0.04
0.77*
0.00
-0.01
1.00*
0.21
0.23
0.30*
0.29*
0.44*
0.09
0.06
0.03
0.44*
0.17*
0.02
F: ACWhighS BSAW
0.23*
0.14*
0.13
E: BSW
0.65*
0.36*
0.64*
D: ACWhighS
0.73*
ACWhighS F: ACWhighS BSAW E: BSW BSAW D: ACWhighS
B: ACWlowS
ACWhighS
BSW F: ACWhighS
The ANOSIM test statistic, R, is shown. R varies roughly from 0 (no difference) to 1 (all dissimilarities between groups are larger than any dissimilarities within groups). BSAW/BSAW, a single station, was not shown and was not significantly different among groups
B:ACWlowS BSW
F: ACWhighS
E: BSW
* Significant differences (P \ 0.05)
BSAW
BSAW
BSAW E: BSW BSAW
BSAW -0.03
-0.05
0.12
Fig. 8 Natural groupings of taxa from CLUSTER routine in PRIMER for sqrt transformed abundances of a large zooplankton, b small zooplankton, and c fish
a concentrations, and PP were highest in regions with surface BSW (cluster group E) in the N. Bering Sea and S. Chukchi Sea. These regions located downstream of the Anadyr Strait are characterized by decreased turbulences and high phytoplankton biomass (Springer and McRoy 1993). Previous studies indicated that in BSAW, the
nutrients advected northward from Anadyr Strait continuously fuel PP after ice melt in June until the onset of winter storm mixing in September (Sambrotto et al. 1984), thus yielding high yearly PP estimates of 250–300 g C m-2 y-1 in BSAW in the 1980s (Sambrotto et al. 1984; Grebmeier et al. 1988; Springer 1988; Walsh et al. 1989). Surface
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Polar Biol Table 7 Correlation factors between environmental variables and the observed community structure for large zooplankton sqrt (No. m-2), small zooplankton sqrt (No. m-2), and fish sqrt (No. km-2) using BEST BIO-ENV analysis (Spearman Rank correlation) No. of variables
Highest corr.
Large zooplankton 1
Sb
0.59
Tb
0.46
DINb
0.46
Ss
0.37
2
Sb, Sib
0.62
Sb, Lon
0.62
Sb, DINb
0.60
Sb, Ss
0.59
3
Sb, Sib, Lon
0.65
Sb, DINb, Lon
0.64
Sb, Tb, Sib
0.62
Sb, Tb, Lon
0.61
Small zooplankton 1
Ch10
0.23
Sb
0.20
Att
0.17
DINs
0.17
2 3
DIN, Ch10 Att, Ch10, DINs
0.31 0.35
Ch10, Sb DINs, Ch10, Sb
0.31 0.35
Ch10, Ps Att, Ch10, Ps
0.29 0.34
Ch10, Att Ps, Ch10, Sb
0.28 0.34
5
Att, Ch10, DINs, Depth, Sb
0.39
1
Lat
0.59
Att
0.39
Sis
0.39
Lon
0.31
2
Lat, Att
0.63
Lat, Sis
0.60
Lat, Ts
0.58
Lat, DINs
0.55
3
Lat, Att, Sis
0.66
Lat, Att, Ts
0.64
Lat, Lon, Att
0.64
Lat, Att, DINs
0.62
Fish
Variables shown include temperature at the surface (Ts), bottom (Tb), salinity at the surface (Ss) and bottom (Sb), latitude (Lat), longitude (Lon), mean water column ratio chlorophyll a [10 lm/total (Ch10), mean water column light attenuation (Att), phosphate at surface (Ps), silicate at surface (Sis) and bottom (Sib), DIN at surface (DINs) and bottom (DINb), and bottom depth (Depth). The top four correlations are shown for 1, 2, and 3 variable combinations. The best set of variables, out of a possible 10, that explain community composition are in bold. The numbers indicate the strength of the correlation for each set of variables. All correlations are significant (P \ 0.01). Station at 70°N 168°W removed from analysis
nutrient concentrations, surface and integrated chlorophyll a concentrations, and PP were lowest in ACW, which is not unexpected as nutrients are stripped from the water column by the PP during spring in ACW and outside of the Anadyr plume region in BSW; mean PP here was 0.53 g C m-2 d-1 with a yearly estimate of 78 g C m-2 y-1 for 1985–1989 (Springer and McRoy 1993). In addition to differences in PP, the composition of phytoplankton taxa also varied between BSW and ACW in the Chukchi Sea. Large chain-forming diatoms have been observed within high chlorophyll a regions, while smaller taxa such as phytoflagellates observed in low nutrient waters outside of the Anadyr plume region (Springer and McRoy 1993). Our surface and water column size-fractionated chlorophyll a data partially support these observations with larger particles in BSW than ACW in the S. Chukchi Sea (Fig. 2). River inputs also impacted water mass properties. High light attenuation in the N. Bering and S. Chukchi Sea nearshore ACW is likely related to high sediment loads from the Yukon River that flow into Norton Sound in the N. Bering Sea and possibly from the Noatak and Kobuk rivers that flow into Kotzebue Sound in the S. Chukchi Sea (Fig. 1). In contrast, the high light attenuation in the S. Chukchi BSW is due at least partly to high concentrations of phytoplankton indicated by the high chlorophyll a values in this area. The observed variations in water clarity may have ecological implications for pelagic taxa as they
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may affect the foraging behavior and success of visual predators, such as zooplanktivorous fish. Species and community composition in relation to water mass and geography Distributions of large zooplankton species in this study were related to water masses in the southeastern Chukchi Sea, and similar results were also shown previously (Lane et al. 2008; Hopcroft et al. 2010; Matsuno et al. 2011). For example, copepods made up large percentages of the total zooplankton abundance in 2004, with the large oceanic copepod taxa E. bungii, M. pacifica, and Neocalanus spp. dominating the offshore, more saline water masses (Hopcroft et al. 2010). In this study, we also found E. bungii and M. pacifica to be most abundant in BSAW. Since all these taxa represent sub-Arctic Pacific species that are common to the Bering Sea ecosystem, their distribution suggests a northward advection with BSAW. While in the current study E. bungii and M. pacifica were also among the most abundant large zooplankton taxa, Neocalanus spp. were substantially less abundant, suggesting that these taxa had already settled out of the Bering Sea and AW and were therefore not transported northwards. In contrast to the large oceanic copepods, small copepod taxa were more evenly distributed across water masses (Pseudocalanus sp.) or were found in higher concentrations in ACW and TW than in BSW (C. abdominalis and
Polar Biol
O. similis). Bivalve larvae were also found in high concentrations in ACW, but were absent in other water masses in 2004 (Hopcroft et al. 2010). Euphausiids contributed significantly to community biomass (21 %) and abundance (2 %) in our study with highest relative abundances found in the S. Chukchi Sea, while they occurred only in low concentrations (10 % biomass and 0.1 % of total abundance) in 2004 (Hopcroft et al. 2010); as in the current study, however, euphausiids were concentrated in higher salinity water masses and absent from ACW (Hopcroft et al. 2010). It should also be noted that abundances presented here are likely underestimated, since our sampling was restricted to daytime only, when euphausiids are known to form a layer near the bottom (Coyle and Pinchuk 2002). Prior studies observed high and variable abundances of barnacle larvae in the southeastern Chukchi Sea (Hopcroft et al. 2010; Matsuno et al. 2011). In contrast, no barnacle larvae were collected in this study, possibly because previous studies were conducted one to two months earlier (July–August) and barnacle larvae might have already settled out at the time of our sampling. Also, the year 2007 was exceptional due to an increased annual mean transport and water temperatures of Pacific water through Bering Strait (Woodgate et al. 2010). This high volume transport might have been responsible for moving the barnacle larvae distribution further northwards and thus out of our study area (Matsuno et al. 2011). Community composition of zooplankton varies with water mass (Hopcroft et al. 2010; Matsuno et al. 2011). Large zooplankton taxa, in particular, were clearly related to water mass, with a stronger relationship to bottom than surface water mass characteristics (q = 0.59 and 0.37, for bottom and surface S, respectively), suggesting that larger zooplankton species may have been concentrated in bottom water masses. The strong relationship with bottom water mass characteristics also suggests that large Bering Sea taxa, such as Eucalanus bungii, were advected in BSAW into more northern habitats (Hopcroft et al. 2010; Matsuno et al. 2011). During August 2004, zooplankton communities were also correlated with environmental variables over the upper 50 m, namely temperature and density (q = 0.75) (Hopcroft et al. 2010). The higher correlations between water mass and zooplankton community composition found in the 2004 study may be partially due to differences in geographic coverage, since sampling in 2004 extended to marine waters well west of 170°W and north of 70°N with a southern limit at Bering Strait (*66°N). In contrast, our sampling was focused on nearshore waters east of 170°W and south of 70°N, but extended further south to St. Lawrence Island (64°N) into the N. Bering Sea. For the current study, we found improved correlations between community composition and bottom salinity (q = 0.68–0.80) when the N. Bering Sea, S. Chukchi Sea,
and C. Chukchi Sea were evaluated separately. Natural zooplankton cluster groups varied with both latitude and longitude in the current study. Matsuno et al. (2011) also found that different natural zooplankton cluster groups were located in the S. Chukchi compared to the N. Chukchi Sea (i.e., clusters varied with latitude) and secondarily from offshore to onshore (with longitude). Hopcroft et al. (2010) found onshore to offshore variations in zooplankton cluster groups, and these variations mimicked spatial variations in water mass over the top 50 m. Zooplankton size varied with water mass. Larger zooplankton taxa were found in BSAW, whereas smaller zooplankton taxa were generally found in the ACW or more evenly distributed across water masses for the current study and in prior research (Lane et al. 2008; Hopcroft et al. 2010). Small phytoplankton generally prevalent in ACW in the Chukchi Sea may be grazed on by small zooplankton taxa, but may be unable to sustain large zooplankton taxa (Kobari et al. 2008). Accordingly, the large zooplankton taxa may be partially sustained by larger phytoplankton in BSAW. Previous research examining zooplankton data collected during our survey indicates that biomass and size structure varied by geographic region. Total biomass was 50 % lower in the C. Chukchi Sea compared to regions further south (Volkov and Murphy 2007). The biomass of large zooplankton taxa [3.3 mm, primarily copepods (E. bungii), chaetognaths (S. elegans), and euphausiids (T. raschii), was highest in the N. Bering Sea where it made up 75 % of the total biomass, compared to 50 % in the C. and S. Chukchi Sea (Volkov and Murphy 2007), with differences due partially to variations in water mass coverage between regions. If distributions of water masses change with climate (e.g., if ACW moves northward or covers more spatial area as the climate warms), then the associated zooplankton communities may also change, with potential for an increase in the abundance of small taxa and a decrease in large taxa. A reduction in phytoplankton cell size with warming was observed in Arctic waters (Li et al. 2009), due to increased surface temperature and freshwater input leading to increased stratification and a reduction in surface nutrient availability. This may be similar to an increase in areal extent of ACW and would further limit prey availability for large zooplankton taxa. These changes in water mass distribution could reduce the abundances or spatial extent of large lipidrich zooplankton and would likely disrupt Arctic food webs and limit prey availability for larger or later stages of planktivorous fishes, marine mammals, and seabirds. In the SE Bering Sea, warm climate conditions were associated with smaller zooplankton in the water and in the prey base for juvenile salmon and age-0 pollock compared to cold climate conditions when larger lipid-rich zooplankton were more prevalent (Coyle et al. 2008, 2011). Accordingly,
123
Polar Biol
during cold years, forage fish such as age-0 walleye pollock had higher energy density going into winter that likely allowed higher overwinter survival and increased recruitment (Heintz pers. comm. 2012). Pelagic fish community composition correlated highly with latitude suggesting that the distributional ranges of fish taxa were primarily the result of geographic location and only secondarily due to water masses and associated habitat preferences. Specifically, we found the highest concentrations of age-0 polar cod, saffron cod, shorthorn sculpin, and adult sand lance in the C. Chukchi Sea. Polar cod and sand lance were least widespread across water masses (high numbers in group F) followed by shorthorn sculpin (high numbers in groups F and B) and saffron cod (high numbers in groups F, B, and D); all cluster groups had surface ACW. In contrast, no age-0 saffron cod and shorthorn sculpin and only very few age-0 polar cod were caught in the N. Bering Sea and S. Chukchi Sea, with lowest polar cod counts in groups E and C (surface BSW and BSAW), saltier, colder, offshore water masses. Juvenile polar cod are known to associate in dense schools with sea ice or to be dispersed in the midwater and move into deeper water as they grow (Frost and Lowry 1983; Rand and Logerwell 2011) assuming a more demersal life style. The association of polar cod with surface ACW in our study is notably different from the observed absence of demersal polar cod and pelagic larval polar cod in ACW in the summer of 2004 (Norcross et al. 2010); however, as mentioned above, in 2004, the station grid was located mainly west of 170°W and only three stations were identified as ACW. In contrast, all our sampling in the Chukchi Sea was east of 170°W suggesting that we targeted a very different area of the Chukchi Sea. In addition, demersal fish in 2004 were sampled with a modified beam trawl with a comparatively small opening of \3.0 m 9 1.0 m, originally designed for the capture of crabs and juvenile flatfish taxa (Gunderson and Ellis 1986). While this sampling device has shown to be effective in sampling juvenile gadoids (Gunderson and Ellis 1986; Abookire and Rose 2005; Norcross et al. 2010), it is clear that this gear targets a very different fish assemblage than was sampled in this study. Also, the occurrence of polar cod in the ACW component is not surprising, because this species is widely abundant in Arctic waters and has previously been documented to also occur in coastal, nearshore, and even brackish waters (Craig et al. 1982; Jarvela and Thorsteinson 1999). Previous studies found the highest (late summer 1989–1991) concentrations of age-0 polar cod near stations with cold Resident Chukchi seawater (RCW) (Wyllie-Echeverria et al. 1997). The southern extent of RCW is often observed in bottom waters near 70°N–71°N with a semipermanent front formed between ACW and RCW (Weingartner 1997). Since we did not
123
encounter RCW during our study, it is impossible to determine whether we were close to the southern extent of this water mass. The most abundant fish taxon during our survey was another juvenile gadoid, namely saffron cod. Saffron cod is a shallow water species that is widely distributed in the coastal waters of the Arctic, but can also range as far south as the northern Gulf of Alaska (Wolotira 1985; Johnson et al. 2009). While it has been suggested that this wideranging distribution may be the result of two, externally very similar species, to date no conclusive taxonomic study has been conducted (Wolotira 1985). Saffron cod spawn demersal eggs under coastal ice in very shallow water. Larvae hatch in early spring (April–May), metamorphose after 2–3 months, and descend to the bottom by midsummer (Wolotira 1985). Juvenile saffron cod are able to tolerate low salinity water and do not undergo seasonal migration (Wolotira 1985 and the literature cited therein), thus explaining their predominance in nearshore water mass groups with surface ACW. The large abundance of saffron cod during our study was noteworthy but might in part be explained by the coastal extent of our sampling grid. In addition, other studies have also noted an increase in the abundance of saffron cod in 2007, namely large numbers of saffron cod in the coastal waters of Prince William Sound, northern Gulf of Alaska (Johnson et al. 2009); occurrence of this species in PWS had previously never been documented. In contrast to polar cod, saffron cod, and shorthorn sculpin, the abundances of adult Pacific herring were highest in surface BSW offshore in the N. Bering Sea and S. Chukchi Sea. Since Pacific herring were concentrated in the colder BSW, higher abundances might be found in colder, higher salinity water masses in the Chukchi Sea, outside of our survey area. Adult Pacific herring sampled during BASIS (2002–2007) in the eastern Bering Sea were concentrated in colder, higher salinity water masses (BASIS unpublished data). Pink and chum salmon juveniles were observed throughout the survey area, with high abundances in ACW with low stratification: ACWlowS/ACWlowS in the C. Chukchi Sea and ACWhighS/ACWhighS in Bering Strait. Genetic information indicates that these salmon originated from different stocks. Juvenile pink and chum salmon captured in C. Chukchi Sea originated from Kotzebue Sound (69 %) and the Seward Peninsula to Norton Sound (29 %) in western Alaska, while fish in Bering Strait originated primarily from northeastern Russia (77 %) (Kondzela et al. 2009). Thus, the higher salinity ACW in the Bering Strait may serve as a migration corridor for Russian pink and chum salmon stocks, whereas Yukon River pink and chum salmon juveniles may be migrating northward in the inshore ACWlowS. These northward
Polar Biol
migrations may be substantial, for example, for the entire eastern Bering Sea and Southeast Chukchi Sea combined (54.5–70°N), half of the total catch for juvenile pink and chum salmon came from the N. Bering Sea and Chukchi Sea (64–70°N) (Moss et al. 2009). Distribution of zooplankton and pelagic fish in relation to environmental factors The community compositions of large zooplankton were strongly associated with water masses with the highest correlations with bottom salinity, whereas fish composition had the highest correlation with latitude. Bottom salinity or surface temperature alone could explain 59 and 29 % of the community variability for large zooplankton and pelagic forage fish, respectively, while small zooplankton had weaker relationships to environmental parameters. Large zooplankton taxa are known to be advected northward into the Chukchi Sea (Springer et al. 1989; Weingartner 1997). In contrast, forage fish distributions can be viewed as the result of an interplay between spawning location and nursery area and active migration in response to habitat preferences. Similarly, the benthic epifaunal community composition on the Chukchi Sea shelf was also related to latitude and substrate type, whereas pelagic zooplankton and fish larvae communities were related to water mass (Bluhm et al. 2009; Hopcroft et al. 2010; Norcross et al. 2010). Lower trophic level components may have a more direct link or a shorter response time to water mass variations than higher trophic organisms such as fish, although, ultimately, we expect all trophic levels to be affected by changes in lower trophic level productivity within a marine ecosystem. Interactions between trophic levels also can vary by water mass and latitude as indicated by pelagic fish diet studies in 2007 (Volkov and Murphy 2007). The C. Chukchi Sea nearshore regions with surface ACW (cluster B and F, D) characterized by low nutrients, low phytoplankton biomass, and a higher relative percentage of small zooplankton, polar and saffron cod, and shorthorn sculpins fed primarily on small copepods (C. abdominalis and Pseudocalanus sp.) and chum and pink salmon fed on small fish (primarily pricklebacks, a taxon captured in similar locations as salmon, BASIS unpublished data) (Volkov and Murphy 2007). In contrast, in offshore waters of the N. Bering Sea and S. Chukchi Sea and Bering Strait regions with surface BSW or ACWhighS (cluster E and D) characterized by high nutrients, high phytoplankton biomass, and large zooplankton, chum and pink salmon and adult herring fed primarily on euphausiids and other large zooplankton (Volkov and Murphy 2007; Moss et al. 2009). Thus, pelagic fish generally preyed upon the available food resources in the system, which in turn were influenced by water mass and geographic variations.
Baseline data for understanding climate change Under scenarios of climate change, alterations in water mass characteristics and spatial extent are to be expected and may greatly impact the Arctic and sub-Arctic pelagic ecosystem. This study provides a baseline for assessing potential future effects of climate change. The year 2007 was a year with exceptionally fast ice melt and record minimum ice coverage in the Arctic (NCAR 2007). In addition, this year was characterized by exceptionally warm water temperatures and significantly increased annual mean water transport through Bering Strait (Woodgate et al. 2010). The high water volume transport and the high water temperatures might have been responsible for some of the distributional patterns of pelagic taxa observed in this study, for example, the increased numbers of pink and chum salmon in the C. Chukchi Sea. In the late 1980s and early 1990s, sockeye (O. nerka), pink, chum, and coho salmon (O. kisutch) were also observed in the Canadian Arctic, outside their previously known distributional range and these range extensions were suggested to have been related to temperature increases in Arctic waters (Babaluk et al. 2000). While it is not clear what might have been the cause for the high abundances of saffron cod, it is noteworthy that this species also experienced a range extension in 2007, albeit to the south (Johnson et al. 2009). The exceptionally warm year of 2007 might exemplify some of the physical and biological changes to be expected for Arctic waters under warming climate scenarios and therefore may provide not only necessary baseline data against which to measure future change, but might also already allow some insight into the mechanisms through which change will be manifested in the Arctic waters of the northern Bering and Chukchi seas. Acknowledgments We thank the Alaska Fisheries Science Center, Ecosystem Monitoring and Assessment program scientists Alex Andrews, Kristin Cieciel, Ed Farley, Jeanette Gann, Jennifer Lanksbury, Jim Murphy, and Bruce Wing, Fisheries Oceanography Coordinated Investigations program scientist Morgan Busby, TINRO Center Vladivostok scientist Anatoly Volkov, and student volunteers Lauren Kuehne and Jenefer Bell for collecting and processing BASIS fisheries and oceanography data. We are grateful to the captain and crew of the NOAA ship R/V Oscar Dyson for their assistance during our field sampling. Funding was provided by the Bering Sea Fisherman’s Association, Arctic-Yukon-Kuskokwim-Sustainable-SalmonInitiative, and NOAA National Marine Fisheries Service. We also thank Mike Sigler and two anonymous reviewers for their helpful suggestions for the improvements of this manuscript. Any mention of trade names is for descriptive purposes only and does not reflect endorsement by the US government.
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