Download Regional Comparisons of Juvenile Salmon Feeding in Coastal

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.
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brodeur et al.
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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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