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American Fisheries Society Symposium 57:183–203, 2007 © 2007 by the American Fisheries Society Regional Comparisons of Juvenile Salmon Feeding in Coastal Marine Waters off the West Coast of North America Richard D. Brodeur* Northwest Fisheries Science Center, National Marine Fisheries Service 2030 South Marine Science Drive, Newport, Oregon 97365, USA Elizabeth A. Daly CIMRS, Oregon State University, Hatfield Marine Science Center Newport, Oregon 97365, USA Molly V. Sturdevant Alaska Fisheries Science Center, National Marine Fisheries Service Auke Bay Laboratory, Juneau, Alaska 99801, USA Todd W. Miller CIMRS, Oregon State University, Hatfield Marine Science Center Newport, Oregon 97365, USA Jamal H. Moss Alaska Fisheries Science Center, National Marine Fisheries Service Auke Bay Laboratory, Juneau, Alaska 99801, USA Mary E. Thiess and Marc Trudel Fisheries and Oceans Canada, Science Branch 3190 Hammond Bay Road, Nanaimo, British Columbia V9T 6N7, Canada Laurie A. Weitkamp Northwest Fisheries Science Center, National Marine Fisheries Service 2030 South Marine Science Drive, Newport, Oregon 97365, USA Janet Armstrong School of Aquatic and Fishery Sciences, University of Washington Box 355020, Seattle, Washington 98195, USA Elizabeth C. Norton1 Southwest Fisheries Science Center, National Marine Fisheries Service 110 Shaffer Road, Santa Cruz, California 95060, USA * Corresponding author: [email protected] 1 Present address: NOAA Ecosystem Goal Team Office, 1315 East-West Highway, Silver Spring, Maryland 20910, USA. 183 brodeur et al. 184 Abstract.—Upon entering marine waters, juvenile Pacific salmon Oncorhynchus spp. depend on feeding at high and sustained levels to achieve growth necessary for survival. In the last decade, several concurrent studies have been examining the food habits and feeding intensity of juvenile Pacific salmon in the shelf regions from California to the northern Gulf of Alaska. In this paper, we compared results from feeding studies for all five species of juvenile salmon (Chinook salmon O. tshawytscha, coho salmon O. kisutch, chum salmon O. keta, sockeye salmon O. nerka, and pink salmon O. gorbuscha) between 2000 and 2002, years when these regions were sampled extensively. Within these years, we temporally stratified our samples to include early (May–July) and late (August–October) periods of ocean migration. Coho and Chinook salmon diets were most similar due to a high consumption of fish prey, whereas pink, chum, and sockeye salmon diets were more variable with no consistently dominant prey taxa. Salmon diets varied more spatially (by oceanographic and regional factors) than temporally (by season or year) in terms of percentage weight or volume of major prey categories. We also examined regional variations in feeding intensity based on stomach fullness (expressed as percent body weight) and percent of empty or overly full stomachs. Stomach fullness tended to be greater off Alaska than off the west coast of the United States, but the data were highly variable. Results from these comparisons provide a large-scale picture of juvenile salmon feeding in coastal waters throughout much of their range, allowing for comparison with available prey resources, growth, and survival patterns associated with the different regions. Introduction The largest component of natural mortality of Pacific salmon Oncorhynchus spp. in the marine environment is believed to occur during the first few months at sea (e.g., Pearcy 1992). This period, commonly referred to as the postsmolt or juvenile period, is considered critical in the life history of salmon because of the magnitude and variability in mortality that can occur (Pearcy 1992). Once they leave their natal rivers, juvenile salmon occupy habitats predominantly on the continental shelf throughout their range in the Northeast Pacific (Hartt and Dell 1986; Fisher et al. 2007, this volume). In many instances, the juveniles head offshore into the Gulf of Alaska (GOA) in the fall (Welch et al. 2002), although some populations in the California Current (CC) are known to reside on the shelf throughout their first winter (Pearcy 1992; Brodeur et al. 2003). Upon entering marine waters, juvenile Pacific salmon depend on feeding at high and sustained levels to achieve necessary growth for survival. The high growth rates observed in the field (e.g., 1.3 mm/d in juvenile coho salmon O. kisutch; Fisher and Pearcy 2005) require consumption of large quantities of suitable prey during the first summer at sea (Orsi et al. 2004). Yet, during this time salmon are also relatively small and less able to evade the numerous predators present in coastal waters. Since much predation is sizeselective, with higher predation pressure on the smaller individuals (Sogard 1997; Willette 2001; Moss et al. 2005), a substantial advantage is accrued to individuals that experience fast and/or sustained growth rates. During this period, juvenile salmon may also transit from nearshore marine to more openwater, neritic habitat, which may influence mortality rates through changes in prey quality and availability (Healey 1982). Salmon species in the North Pacific have shown marked differences in growth, survival, and production at various spatial scales (Coronado and Hilborn 1998; Hare et al. 1999; Hobday and Boehlert 2001; regional comparisons of juvenile salmon feeding in coastal marine waters Mueter et al. 2002; Pyper et al. 2005). The coastal GOA and CC systems are quite distinct oceanographically and in terms of production, representing the downwelling and upwelling domains, respectively (Ware and McFarlane 1989). Some evidence exists that the two domains respond inversely to climate regime shifts for both zooplankton and salmon production (Brodeur et al. 1996; Hare et al. 1999; Peterson and Schwing 2003); yet, the highest ecosystem productivity along the coast appears to be centered in the transition zone between the two systems off the west coast of Vancouver Island (Ware and Thompson 2005). Much is known about the feeding ecology of juvenile salmon in coastal waters of the northeast Pacific Ocean, and this information has been summarized by Beamish et al. (2003) and Brodeur et al. (2003) for Canadian and U.S. waters, respectively. The last few decades have witnessed a substantial increase in sampling effort throughout the distributional range of juvenile salmon (Fisher et al. 2007), and many individual studies have provided detailed descriptions of the spatial, temporal, and size-related variability in juvenile salmon diets (Brodeur 1990, 1991; Brodeur and Pearcy 1990; Perry et al. 1996; Landingham et al. 1998; Boldt and Haldorson 2003; Sturdevant et al. 2004; Armstrong et al. 2005). However, these papers summarize the diets from a single region or sampling program and do not extend over a broad geographic area. Our main objective in this study was to examine the broad-scale variability in the diets of five species of juvenile salmon throughout much of their range in the GOA and CC ecosystems. To accomplish our objective, we assembled one of the largest data sets available on the stomach contents of juvenile coho salmon, Chinook salmon O. tshawytscha, chum salmon O. keta, pink salmon O. gorbuscha, and sockeye salmon O. nerka 185 salmon from central California to the western Gulf of Alaska. When data were available, we compared the diets among years (2000– 2002), seasons (early and late summer), 10 geographic regions, and 4 oceanographic domains. Using multivariate analyses, we assessed the differences among species within the same year, season, and region as well as differences among regions for the same species, year, and season. This type of analysis provides a unique opportunity to differentiate between speciesand region-specific differences in food habits, which can only be accomplished by comparing diets across studies in diverse ecosystems. Because of the large geographic range from which fish were collected, this analysis also provides unique insight into regional variation in marine habitat partitioning among the five salmon species. Methods Field Sampling and Laboratory Analysis Stomach data for this study were collected during seven sampling programs conducted by several different federal agencies and academic institutions from April to November of 2000–2002 (Figure 1). All studies used finemesh, large-opening surface trawls to collect juvenile salmon in coastal waters (Brodeur et al. 2004; Orsi et al. 2007, this volume). Although there were slight differences in the trawls used for the different programs (Fisher et al. 2007), the sampling strata were very similar, and gear differences are not believed to affect our results. Stations were generally located along transects perpendicular to the coasts across the continental shelf, although some inside waters within Prince William Sound, southeast Alaska, and northern British Columbia were also included (Figure 1). The vast majority of the collections were made during the daylight hours. Once the salmon were brought aboard, brodeur et al. 186 60 Alaska 58 56 WGOA 54 52 50 48 46 NGOA SEAK Ocean Carrying Capacity, NMFS Auke Bay GLOBEC, University of Alaska, Fairbanks EGOA NBC SBC WCVI Southeast Alaska Coastal Monitoring (SECM), NMFS Auke Bay Laboratory 44 High Seas Salmon program, DFO Canada, Pacific Biological Station, Nanaimo, BC 42 Columbia River Plume Habitat, NMFS NWFSC, Oregon State University 40 GLOBEC, NMFS, Oregon State University 38 British Columbia SECM SL NGOA NOR NCC Calif. SCC NMFS SWFSC, Tiburon/Santa Cruz Laboratory 160 155 150 145 140 OR SOR NCA 36 165 WA WAC 135 130 125 Figure 1. Location of sampling program (different symbol types), regions, and major geographic domains (boxes) where salmon diet samples were collected, 2000–2002. Refer to Table 1 for region and domain names. Symbols represent agencies and sampling programs through which these independent samples were collected. they were identified, measured (mm fork length) and generally frozen for later stomach analyses but, in some cases, were preserved at sea in buffered formalin. Juvenile salmon were distinguished from adults based on size frequency or scale analyses. However, we were not able to adequately differentiate subyearling from yearling Chinook salmon in all regions, and these two life history types were combined in our analysis, despite some differences in feeding habits (Schabetsberger et al. 2003). Frozen fish were thawed in the laboratory and measured; stomachs were then dissected and preserved in 10% buffered formalin. Stomach contents were removed and examined under a dissecting microscope. In all studies, prey items were identified to the lowest possible taxonomic level. Each prey taxon was blotted on absorbent paper to remove excess moisture and weighed to the nearest milligram or else the volume that each taxon represented was assessed relative regional comparisons of juvenile salmon feeding in coastal marine waters to the total volume of the stomach content. In some cases, direct prey weights were not available, and we instead used literature values and data on file by species and size-class to estimate weights. For the purposes of this study, we summarized the individual prey taxa into major taxonomic groupings (subclass, order, etc.) for statistical analyses, although information was retained to interpret any finer-scale differences that may have been observed. For coho and Chinook salmon, the prey species were pooled to derive total biomass or volume for eight major prey categories. These categories were Fish, Decapods, Euphausiids, Hyperiids, Pteropods, Copepods, Insects, and Other. The latter category was composed of polychaetes, gammarids, cephalopods, cirripede larvae, mysids, isopods, and miscellaneous gelatinous zooplankton. For chum, pink, and sockeye salmon, which tend to be more planktivorous than Chinook or coho salmon (Brodeur 1990; Landingham et al. 1998), we modified the prey categories to distinguish tunicates (mostly larvaceans), a major prey of these three salmon species, and we eliminated the Insect category, since insects are not commonly found in guts of these species. We calculated the contribution of each prey taxon to individual salmon stomach contents as percent weight or percent volume of total diets and then summarized as mean diet composition per species. To assess how stomach fullness varied across regions, we used a more direct indication of feeding success, the percent body weight (% BW) made up of food items: stomach content weight % BW = ¥100. total fish weight-stomach content weight We could not calculate this index for NCA stations where only stomach volumes were measured. For graphical and statistical comparisons of the diet composition by major prey cat- 187 egories, we grouped our data in a number of ways. First, we examined year as a possible source of variability by partitioning the data into the 3 years. Second, because salmon can undergo substantial ontogenetic changes in their diets as they grow, and because prey resources change seasonally (e.g., Brodeur and Pearcy 1990; Sturdevant et al. 2004; Armstrong et al. 2005), we grouped our data into seasons, which were classified as early (May through July) and late (August through October) to account for this variability (Table 1). Third, data were grouped into 10 geographic regions throughout the range sampled (Figure 1; Table 1), with three of the broad sampling programs subdivided into smaller, more physically homogeneous subareas. Finally, we partitioned the data into four broader oceanographic domains (northern GOA, eastern GOA, northern CC, and southern CC; Figure 1) based on differences in upwelling, current regimes, and productivity (Ware and McFarlane 1989). We used the software PRIMER (Plymouth Routines in Multivariate Ecological Research, version 5; Clarke and Green 1988; Clarke and Warwick 2001) to conduct multivariate analyses on the diet composition data for each species by year and season, using all prey types except Other. We applied a fourth root transformation on percent prey composition to reduce the dominance of abundance prey taxa and then calculated Bray-Curtis similarity coefficients. For each salmon species, nonmetric multidimensional scaling (NMDS) analysis was conducted in two dimensions to visually assess the prey species representative of year, season, and region and to represent similarities among samples as relative distances. To see which groupings differed significantly in their dietary composition, an analysis of similarity (ANOSIM) was run using year, season, geographic region, and oceanographic domain as factors. The calculated R statistic shows the relative brodeur et al. 188 Table 1. Sample size (n) and mean fork length (FL, mm) and standard deviation (in parentheses) of juvenile salmon examined for each species/season combination within regions for all years combined. Refer to Figure 1 for locations of geographic regions. Oceanographic domains are shown in bold type. The sample sizes refer to the number of fish with % BW information. Note that the sample sizes of the fish with detailed prey information shown in Figures 2 through 6 may be smaller than that given in this table. Chinook salmon Domain/area Early Late Coho salmon Early Late Pink salmon Early Late Chum salmon Early Late Sockeye salmon Early Late Northern Gulf of Alaska Western Gulf of Alaska n 732 444 105 63 131 20 FL 133 (25) 147 (31)133 (11) 140 (24) 181 (35) 132 (30) Northern Gulf of Alaska n 384 136 132 114 FL 115 (21) 139 (24)131 (18) 175 (38) Southeast Alaska Coastal Monitoring n 10 34 137 110 146 99 194 60 FL 183 (39) 259 (35)174 (24) 218 (55) 79 (37) 183 (24) 89 (31) 173 (28) Eastern Gulf of Alaska Southeast Alaska n 8 525 280 10 5 137 57 353 FL 259 (58) 269 (33) 292 (35)131 (11) 147 (5) 230 (21) 145 (21) 193 (32) Northern British Columbia n 16 135 54 274 120 230 191 65 232 FL 201 (20) 227 (48)169 (37) 284 (26)118 (23) 221 (18) 217 (20) 137 (20) 191 (17) Southern British Columbia n 119 466 280 483 139 296 191 281 43 FL 191 (46) 174 (38)203 (32) 272 (35)121 (12) 133 (21) 208 (22) 127 (13) 155(14) Northern California Current Washington Coast n 517 179 635 248 28 64 37 7 FL 170 (34) 220 (59)166 (26) 284 (29) 156 (20) 95 (15) 117 (19) 179 (41) Northern Oregon n 332 257 269 68 7 FL 150 (46) 175 (50)172 (27) 286 (35) 79 (7) Southern Oregon n 97 166 151 83 147 FL 216 (35) 202 (63)173 (34) 315 (62) 111 (11) Southern California Current Northern California n 199 90 FL 119 (41) 215 (25) separation between groups; R ranges from 0 to 1, with a value of 1 indicating complete separation. To identify which prey taxa were most likely responsible for the patterns detected by ANOSIM, we used the similarity percentages (SIMPER) procedure in PRIMER to determine which were the discriminating species (Clarke 1993). To test for differences in % BW, we grouped the fish by early and late season (combining years) and then used analysis of variance (ANOVA) on arcsine square root transformed data to examine regional differences in feeding intensity. The arcsine transformation was used to normalize the response data. Where significant differ- regional comparisons of juvenile salmon feeding in coastal marine waters 189 Figure 2. Diet composition by major prey categories of juvenile Chinook salmon from different regions of the eastern North Pacific for early and late summer sampling from 2000 to 2002. ences were observed, we used Fisher’s least significant difference (LSD) procedure to discriminate among the mean responses. We also investigated regional patterns of feeding for the most successful and least successful juvenile salmon by examining spatial variation in the percentages of total stomachs that were empty (% BW < 0.04) or were overly full or distended (% BW > 5.0). 190 brodeur et al. Results General Diet Composition Juvenile Chinook salmon had the broadest distribution of diet samples available, with all but the two Gulf of Alaska (northern Gulf of Alaska [NGOA] and western Gulf of Alaska [WGOA]) areas represented (Figure 2). Fish prey generally comprised the majority of prey by weight or volume, but there were some notable exceptions. For example, off northern British Columbia (NBC) and southern British Columbia (SBC) diets were highly variable, with decapods, hyperiids, euphausiids, and insects being equally or even more important than fish at times (Figure 2). Similarly, off California (NCA), the diets tended to also be highly variable and showed a lesser reliance on fish. The major prey in half (3 of 6) year/season combinations for this region was Other, which consisted mainly of cephalopods, mostly juvenile market squid (also known as opalescent inshore squid) Loligo opalescens. Juvenile coho salmon were sampled from nearly as broad a geographical area as Chinook salmon and consumed similar main prey. Fish were again the dominant prey consumed, but euphausiids, decapods, and hyperiids were also relatively important for coho salmon during some cruises (Figure 3). With the exception of early 2000 diets, there was a general increase in fish prey in the more southern regions. Other prey taxa were less important in juvenile coho salmon than in juvenile Chinook salmon and included mysids, gammarid amphipods, other crustaceans, and some gelatinous zooplankton. The remaining three species of juvenile salmon were less represented in terms of geographical areas, although the sample size within a particular region was quite high in some cases. Juvenile pink salmon were primarily examined from Vancouver Island northward and had highly variable diets by year and region (Figure 4). Pteropods, fishes, and copepods were the dominant prey taxa north of southeast Alaska (WGOA, NGOA, and Southeast Alaska Coastal Monitoring [SECM]), whereas euphausiids and hyperiids were dominant off southeast Alaska down to British Columbia. A similar north–south dichotomy was observed for chum salmon, but pteropods were replaced somewhat with tunicates in the north (Figure 5). Off Washington and Oregon, chum salmon diets were often heavily dominated by a single prey group such as copepods, tunicates, or fishes (off southern Oregon). Latitudinal variation was not as pronounced in juvenile sockeye salmon, but different years were dominated by specific prey (Figure 6). For example, euphausiids and decapods were important in 2000, while copepods and fish were much more evident in the 2001 diets. Statistical Comparisons For all salmon species except coho salmon, prey composition differed significantly by the two spatial factors: large oceanographic domain and sampling region (ANOSIM, p < 0.026; Table 2), suggesting that most species’ diets varied depending on where the fish were collected. Few differences were observed at either temporal scale. Year was significant for pink and chum salmon, but no significant difference in diet composition was found between early and late summer fish for any species (Table 2). The latter result was particularly surprising given the substantial size differences between early and late fish for most salmon species (Table 1). The SIMPER dissimilarities among regions were low to moderate for Chinook salmon juveniles, and the only values that marginally exceeded 50% occurred between NCA and several other regions (Table 3). This was due mainly to the lack of fish and the high volume of other prey (mainly squid) in the NCA. regional comparisons of juvenile salmon feeding in coastal marine waters 191 Figure 3. Diet composition by major prey categories of juvenile coho salmon from different regions of the eastern North Pacific for early and late summer sampling from 2000 to 2002. As suggested by the nonsignificant ANOSIM results, juvenile coho salmon were relatively similar among regions in this analysis (none of the SIMPER dissimilarities >50%). Conversely, for pink, chum, and sockeye salmon, most dissimilarity pairs exceeded 50% (Table 3). For pink salmon, the most discriminating taxon was euphausiids, followed by pteropods. Many different taxa accounted for the differences seen in chum salmon diets, but 192 brodeur et al. Figure 4. Diet composition by major prey categories of juvenile pink salmon from different regions of the eastern North Pacific for early and late summer sampling from 2000 to 2002. fish and tunicates were found to be most responsible. Finally, fish and tunicates were identified as the most discriminating taxa related to the dissimilarities observed for sockeye salmon among regions. The NMDS of all salmon species showed that Chinook and coho salmon diets were most similar overall likely due to their mutual consumption of mainly fish prey, particularly among coho salmon diets, compared to regional comparisons of juvenile salmon feeding in coastal marine waters 193 Figure 5. Diet composition by major prey categories of juvenile chum salmon from different regions of the eastern North Pacific for early and late summer sampling from 2000 to 2002. the other species (Figure 7). The three other salmon species were less piscivorous, and their diets were more variable by year, season, and region. Sockeye salmon diet varied the most, as suggested by the spread of their NMDS scores (Figure 7). The overall stress value was high, indicating little differentiation among the salmon species, at least with prey grouped at the relatively high taxonomic level we utilized in our analysis. ANOSIM tests between all possible species pairs grouped by year and region showed that 194 brodeur et al. Figure 6. Diet composition by major prey categories of juvenile sockeye salmon from different regions of the eastern North Pacific for early and late summer sampling from 2000 to 2002. coho and Chinook salmon did not have significantly different diets (P = 0.133 and P = 0.180 for early and late comparisons, respec- tively). Similarly, all pairings of pink, chum and sockeye salmon showed no significant differences in prey consumed in early (all 195 regional comparisons of juvenile salmon feeding in coastal marine waters Table 2. Results of multivariate analysis of similarities (ANOSIM) showing the p-values resulting from the test of significant variations in diet composition of juvenile salmon species by the spatial and temporal factors. P-values less than 0.05 are bolded. Factor Chinook salmon Coho salmon Pink salmon Chum salmon Sockeye salmon Oceanographic domain Sampling region Year Season 0.001 0.008 0.688 0.227 0.079 0.646 0.185 0.832 P > 0.622) and late (all P > 0.242) seasons. However, all pairings of coho and Chinook salmon with the other three salmon species showed significantly different feeding habits during both seasons (all P < 0.02) Feeding Intensity For all five species in both early and late seasons, there were highly significant regional differences in % BW (ANOVA, all P < 0.001). For Chinook and coho salmon juveniles, the LSD test distinguished the northern areas (SECM, SEAK, NBC, and SBC) from the regions off Washington and Oregon, with the exception of late coho salmon where the pattern in feeding intensity was not well defined (Figure 8). For pink, chum, and sockeye salmon, often one or two regions were either significantly higher or lower in % BW than the remaining regions, but the geographic locality of these outliers showed no consistent latitudinal pattern (Figure 8). In terms of the geographic distribution of the nearly full or nearly empty stomachs, juvenile coho and Chinook salmon generally exhibited a strong latitudinal trend, with more overly full stomachs to the north and more empty stomachs to the south (Figure 9). Late coho salmon was an exception with both the highest and lowest feeding intensities occurring off WAC and NOR. An opposite pattern was evident for early pink, chum, and sockeye salmon, whereas the patterns for late pink and sockeye salmon were 0.001 0.001 0.020 0.398 0.020 0.002 0.018 0.570 0.026 0.021 0.156 0.606 more similar to those of coho and Chinook salmon (Figure 9). Discussion Our analysis of regional variation in juvenile salmon stomach contents and feeding success represents the largest collection of such data yet assembled (>10,000 stomachs) and for the first time compares feeding from several highly contrasting oceanographic regions. We know that many important life history parameters of salmon, such as marine growth and survival, vary among these regions (Pyper et al. 2005) and may also be linked to early ocean feeding. Although we do not have complementary prey sampling representing all these regions, the taxonomic composition, abundance, and timing of major prey groups present, and thus their availability to fish, vary markedly among regions and years (Landingham et al. 1998; Schabetsberger et al. 2003; Park et al. 2004; Cross et al. 2005; Mackas and Coyle 2005). There is also substantial variation in caloric values, digestibility, and ease of capture, and thus in profitability, among the major prey groups we examined. For example, larger fish prey generally require a higher foraging and handling time but have a much higher nutritional value than pteropods and tunicates (larvaceans), which are more abundant and easier to capture. Therefore, juvenile salmon must consume more of the less-nutritious, but abundant prey to compensate for lower con- brodeur et al. 196 Table 3. Results of similarity percentages multivariate analysis (SIMPER) of juvenile salmon dietary composition by species for all years combined. Values below the diagonal are the dissimilarities between geographic regions. Prey codes above the diagonal refer to the taxa that account for the most difference when regional diets were more than 50% dissimilar (values in bold text). Chinook NCA SOR NOR WAC SBC NBC SEAK SECM NCA SOR NOR WAC SBC NBC SEAK SECM – 48.4 51.3 50.4 42.7 52.3 47.0 36.9 – 27.0 25.5 43.0 41.8 21.3 30.3 Fish – 24.0 45.1 42.2 25.1 32.5 Fish – 45.9 43.3 25.6 32.5 – 48.8 40.8 37.4 Other – 37.3 42.7 – 27.8 – Coho SOR NOR WAC SBC NBC SEAK SECM SOR NOR WAC SBC NBC SEAK SECM – 33.5 33.5 35.9 38.9 31.4 38.1 – 28.3 34.5 38.1 32.1 37.2 – 32.9 37.0 30.6 36.6 – 37.9 30.1 32.7 – 34.0 36.2 – 32.3 – Pink WAC SBC NBC SEAK WAC SBC NBC SEAK SECM WGOA NGOA – 33.2 58.7 35.9 55.4 56.1 63.3 – 58.5 28.9 40.8 54.6 54.0 Euph Euph – 61.0 60.3 67.1 71.5 Euph – 44.8 54.6 65.1 Euph Tun – 39.0 39.7 Euph Ptero Ptero Euph – 30.1 Euph Euph Ptero Euph Chum SOR NOR WAC SBC NBC SEAK SECM WGOA NGOA SOR NOR WAC SBC NBC SEAK SECM WGOA NGOA – 60.6 61.1 74.4 78.4 59.0 50.4 36.8 37.6 Fish – 54.7 79.3 74.5 84.5 48.5 54.2 48.2 Fish Tun – 54.7 52.6 59.7 45.7 44.3 40.0 Fish Tun Cop – 32.0 39.5 52.1 69.9 61.6 Fish Tun Cop Fish – 42.4 47.7 68.4 71.2 Euph Tun Cop – 58.6 63.6 63.7 Fish Tun Tun – 36.0 42.1 Tun Euph Hyp Fish – 20.7 Fish Fish Fish Sockeye WAC SBC NBC WAC SBC NBC SEAK WGOA NGOA – 59.3 71.6 57.7 50.0 41.0 Fish – 57.7 43.0 60.8 67.9 Tun Tun – 66.4 76.2 76.2 SECM WGOA SEAK WGOA NGOA Cop Tun – 54.6 64.5 Euph Fish Tun Fish – 39.6 Fish Fish Fish – NGOA – – regional comparisons of juvenile salmon feeding in coastal marine waters Stress: 0.17 197 Chinook Tunicates Pteropods Coho Fish Pink Copepods Euphausiids Chum Sockeye Figure 7. Nonmetric multidimensional scaling plot of diet data for the first two axes showing each year/ season/region for each salmon species as a different data point. Species are coded by the different symbol types. The strength and relative directionality of the important prey taxa are shown as vectors. sumption of fish. Nutritional value varies even within the prey categories examined in this study, but this variation is generally less than the variation between categories (Davis et al. 1998). An important conclusion derived from our study is that, with the possible exception of juvenile coho salmon, the geographic variability in diets was generally much greater than the temporal (seasonal and interannual) variability. Part of this may stem from the period of our study in which the California Current exhibited a shift in higher ocean productivity after the 1998 El Niño (Peterson and Schwing 2003). Prior to this time, the California Current was considered to be in a warm phase associated with poor ocean survival of salmonids (Mantua et al. 1997). An intrusion of cool, nutrient-rich subarctic water onto the Oregon–California shelf during 2001 and 2002 led to higher primary production on the shelf from British Columbia to northern California (Thomas et al. 2003) and caused localized near-bottom hypoxic condi- tions (Wheeler et al. 2003), which may have affected trophic dynamics between juvenile salmon and their preferred prey. Interannual and interdecadal effects of the environment on the feeding ecology of juvenile coho salmon were clearly observed in a study that used similar methods, examining 12 oceanographically variable years of diet data, which included both extremely warm and cold years off Oregon and Washington (Brodeur et al. 2007). Although some variation probably exists between laboratory methodologies and classification of prey items in our study, these differences are not likely to account for such substantial differences in diets and feeding intensity observed among regions, especially since we grouped the data by higher taxonomic categories. Also worthy of note is the finding that diet differences between species were consistent across geographically distant and biologically dissimilar ecosystems. Chinook and coho salmon had similar diets regardless of year or region, as did the group consisting of 198 brodeur et al. Figure 8. Boxplots of the feeding intensity (percent body weight) for all years combined within regions for each species/season combination. The solid line in the box is the median value and the dotted line is the mean. Top and bottom of the box represents the 75th and 25th percentiles, the error bar represents the 90th and 10th percentiles, and the points represent the 95th and 5th percentiles. regional comparisons of juvenile salmon feeding in coastal marine waters 199 Figure 9. Percentages of relatively empty or relatively full stomachs in each area by species and season species for all years combined. 200 brodeur et al. pink, chum, and sockeye salmon, although the two groups were quite different in all comparisons. These consistent patterns suggest partitioning of marine resources between the two species groups, and this partitioning is maintained, despite potentially large differences in prey resources between years and/or regions. Although similar species partitioning has been observed in numerous studies examining juvenile salmon diets at smaller spatial scales (e.g., Brodeur and Pearcy 1990; Perry et al. 1996; Landingham et al. 1998), this is the first study to demonstrate that these differences are maintained across ocean basins. Habitat partitioning by Pacific salmon in freshwater is well known (Quinn 2005); our findings suggest that it may be equally universal in marine environments. An interesting finding from the SIMPER analysis was that the most geographically distant sampling areas were not always the most different in terms of major prey composition (e.g., for Chinook salmon in Table 3, NCA versus SECM), although specific prey were likely different in many instances. Chinook salmon diet in the NCA area was found to be distinct from diets in most other regions due to the high consumption of squid prey compared to the other regions. The squid prey most commonly found in Chinook salmon diets in the NCA, market squid, is more abundant off central California than other areas sampled (Brodeur et al. 2003; Orsi et al. 2007). This region is also geographically isolated from the other regions by hundreds of kilometers of continental shelf, suggesting that a more gradual transition between NCA and SOR may have been observed had we sampled between these two regions. Although coho salmon and, to a lesser extent, Chinook salmon were feeding on similar major prey groups throughout their range, the species consumed in different regions were often quite different. Off southeast Alaska, common fish prey were capelin Mallotus villosus and juvenile walleye pollock Theragra chalcogramma, and a common euphausiid prey was Thysanoessa raschii, whereas off Oregon and Washington, the dominant fishes were northern anchovy Engraulis mordax and rockfishes Sebastes spp., and the dominant euphausiids were Euphausia pacifica and T. spinifera (Brodeur and Pearcy 1990; Weitkamp 2004). Even more striking were the differences in feeding intensity (% BW) among regions. Most species showed higher feeding intensities and a lower percentage of empty stomachs off Alaska compared to off the west coast of the United States. Weitkamp (2004) had reported similar results for juvenile coho and Chinook salmon, which also showed substantially higher marine survival rates off southeast Alaska. However, many factors may have led to variability in feeding intensity besides region of capture, including time of day, prey patchiness, and the intensity of interspecific competition within the system (Brodeur 1992). Interspecific competition may have been higher within the CC than in the GOA. Many more potential competitors of juvenile salmon, such as small pelagic fish and squid, inhabit the CC system, with salmonids only consisting of 2–13% of the total community compared to 35–83% in the GOA (Orsi et al. 2007). Competition with small pelagic fishes might be more important for pink, chum, and sockeye salmon than for Chinook and coho salmon, as pelagic fish typically feed on zooplankton instead of prey fishes. However, even in areas without abundant nonsalmonid pelagic fish stocks, the densities of pink salmon may be of sufficient magnitude that intraspecific and interspecific competition with other juvenile salmonids could be occurring in coastal waters (Ruggerone and Nielsen 2004). The CC and the GOA systems are substantially different oceanographically and biologically, with a transition area off Can- regional comparisons of juvenile salmon feeding in coastal marine waters ada (Ware and McFarlane 1989). Ware and Thompson (2005) have found that the highest chlorophyll levels and fishery biomass occurs off the west coast of Vancouver Island and Washington coast within the CC system, but our study shows that this area was often not where juvenile salmon showed the highest feeding rates. Our results indicate that there is substantial variability in feeding success of juvenile salmon among geographic regions of the northeast Pacific, but a more detailed comparison between regional variations in feeding intensity and prey availability in relation to survival patterns is clearly warranted. Acknowledgments The authors thank their numerous colleagues who went to sea to collect the salmon examined in this study. Although the authors examined many of the stomachs included in this study, a large team of support personnel helped out and their contributions are keenly appreciated. Hal Batchelder and two anonymous reviewers provided helpful comments on the manuscript. We thank the Northwest, Alaska, and Southwest Fisheries Science Centers, Fisheries and Oceans Canada, Bonneville Power Administration, and the U.S. GLOBEC program for providing funding to undertake the field sampling and processing of samples. This is contribution number 306 to the U.S. GLOBEC program. 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