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ICES Journal of
Marine Science
ICES Journal of Marine Science (2012), 69(2), 151 –162. doi:10.1093/icesjms/fsr195
Common large-scale responses to climate and fishing across
Northwest Atlantic ecosystems
Nancy L. Shackell1*, Alida Bundy 1, Janet A. Nye2, and Jason S. Link 2
1
Fisheries and Oceans, Bedford Institute of Oceanography, PO Box 1006, Dartmouth, NS, Canada B2Y 4A2
National Marine Fisheries Service, Northeast Fisheries Science Center, Woods Hole Laboratory, 166 Water Street, Woods Hole, MA 02543, USA
2
*Corresponding Author: tel: +1 902 4077538; fax: +1 902 4269710; e-mail: [email protected].
Shackell, N. L., Bundy, A., Nye, J. A., and Link, J. S. 2012. Common large-scale responses to climate and fishing across Northwest Atlantic
ecosystems. – ICES Journal of Marine Science, 69: 151 – 162.
Received 31 March 2011; accepted 21 November 2011; advance access publication 13 January 2012.
Investigating whether there were common biological responses to climate and fishing across seven Northwest Atlantic ecosystems,
a minimum/maximum autocorrelation factor analysis of biological indicators for each region revealed a common primary multivariate
trend of a rapid change during the 1980s and early 1990s. There was a strong common pattern in the biological indicators responsible
for the primary multivariate temporal trend in the five more northerly regions: an increase in the abundance of phytoplankton,
an increase in biomass at mid-trophic levels, and a decline in predatory groundfish size. The common associations between
patterns and drivers were fishing indices and the Atlantic Multidecadal Oscillation, but all associations weakened when co-varying
drivers were held constant. The results are consistent with known long-term effects of intense fishing, such as a decline in average
fish size and changes in species composition. Less fishing pressure has allowed some regions to recover to former predatory
biomass levels since the late 1990s, but the bulk of the biomass consists of fewer species. However, fishing was not the only driver,
and a more mechanistic understanding of how the climate affects lower trophic levels is needed to contextualize climate effects
in heavily fished ecosystems.
Keywords: Atlantic Multidecadal Oscillation, body size, climate, fishing, fishing-induced evolution, marine ecosystem, Northwest Atlantic.
Introduction
The physical oceanography of a region sets the stage for trophic dynamics by determining base productivity, which in turn influences
the abundance of higher trophic levels. Production of upper trophic
levels in aquatic ecosystems is ultimately determined by productivity at the base of the foodweb (Cushing, 1975; Aebischer et al., 1990;
Ware and Thomson, 2005; Chassot et al., 2010). The variability of
oceanographic parameters can modify the composition and abundance of species (Alheit et al., 2005; Stenseth et al., 2006), and as
such can intensify, or buffer, the effects of intense harvesting
(Daskalov et al., 2007; Casini et al., 2009).
Fishing also influences ecosystems. Direct fishing effects on
ecosystems can be significant through reductions in the biomass
and size of targeted fish. Indirect fishing effects have also been
observed. In several marine systems, overfishing of large-bodied,
dominant predatory fish resulted in increases in their prey and indirect changes in the trophic structure (Worm and Myers, 2003;
Bundy, 2005; Frank et al., 2005; Daskalov et al., 2007; Oguz and
Gilbert, 2007; Casini et al., 2009). Shackell et al. (2010) hypothesized that even a reduction in predator size can influence
# 2012
trophic structure. However, other studies have not fully concurred
with the proposed magnitude of fishing effects and have concluded
that the combined effects of fishing and oceanographic variability
influenced how ecosystem dynamics (such as trophic interactions)
have responded (Link et al., 2002, 2009, 2010; Gaichas et al., 2009).
Frank et al. (2007) hypothesized that colder, species-poor ecoregions are less resilient to overfishing because of the slower
growth rates and a smaller pool of potential predator compensators that could regulate the prey. What is clear from all these
studies, though, is the need to explore regions simultaneously to
identify the processes influencing an ecosystem, particularly
because climate change and fishing influences are anticipated to
continue or escalate (sensu Link et al., 2002).
Comparative ecosystem responses among contiguous ecosystems can reveal whether common, large-scale forcing drives
common ecosystem responses (Alheit et al., 2005). In Northwest
Atlantic marine ecosystems, trophic-level dynamics in some
regions have been examined independently, but not as an
ensemble. Here, therefore, we offer a comparative analysis of
seven contiguous regions of the NW Atlantic with different
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152
N. L. Shackell et al.
Figure 1. Map of the study domain showing seven biogeographical regions: ESS, eastern Scotian Shelf; WSS, western Scotian Shelf; BoF, Bay of
Fundy; GoM, Gulf of Maine; GB, Georges Bank; SNE, southern New England; MAB, Mid-Atlantic Bight. The total area is 409 064 km2, estimated
using an appropriate planar projection. Thick black lines demarcate ecosystem boundaries.
temperature regimes, ranging from the colder eastern Scotian Shelf
(ESS) to the warmer Mid-Atlantic Bight (MAB). The goal was to
explore whether there were common ecological patterns among
the seven regions, then to determine whether climate or fishing,
or both, were associated with those patterns.
Material and methods
Of the seven biogeographic regions examined, three are under
Canadian jurisdiction (ESS; western Scotian Shelf, WSS; and Bay
of Fundy, BoF) and four under US jurisdiction (Gulf of Maine,
GoM; Georges Bank, GB; southern New England, SNE; and
MAB; see Figure 1). Time-series of data on climate, fishing, and
biological indicators were gathered for each of the seven regions
from a range of Canadian and US sources. As the data came
from sources that had used different sampling gear, mesh sizes,
etc., comparison of absolute differences among all regions was
obviously going to be difficult. Therefore, all data were
log-transformed and standardized before analysis (annual standardized anomalies from the long-term mean). In this manner, focus
was on the trends in the time-series among regions and not absolute differences. A list of indicators is provided in Table 1, with
further descriptions provided below.
Climate oceanographic indicators
Four indicators of large temporal- and spatial-scale climate conditions that affect the study domain were examined. Two represented
water mass properties as the percentage of warm slope water (i) in
the Emerald Basin, and (ii) at a standard oceanographic sample
site known as the Halifax line (Therriault et al., 1998; see
Figure 1), which was sampled regularly as part of the Atlantic
zonal monitoring program (AZMP). Water mass indicators were
included because advection has been recognized as an important
determinant of zooplankton composition (Kane, 2007), influencing the study regions included here. Two hemispheric-scale indicators were included, the North Atlantic Oscillation (NAO) and
the Atlantic Multidecadal Oscillation (AMO; see Table 1). The
NAO index represents the difference between the surface pressure
of the subtropical (Azores) high and the subpolar (Iceland) low;
variation influences local sea surface temperature (SST), temperature at depth, and precipitation in the NW Atlantic (Hurrell et al.,
2003). NAO effects are not the same throughout the region, and in
part of the study domain, are weak relative to effects north of 458N
(Petrie, 2007). Following the rationale of Hurrell et al. (2003), we
used the mean winter NAO index. The AMO index is a measure of
warm and cold phases in Atlantic SST at multidecadal time-scales
153
Common large-scale responses to climate and fishing across NW Atlantic ecosystems
Table 1. Summary description of indicators by region, with the years sampled abbreviated, e.g. 60-08 refers to 1960– 2008 (see text for
detail, and the Supplementary material for a list of fish species within functional groups).
Indicator
Description
DRIVER: Climate
Large-scale climate (common to all regions)
AMO
Atlantic Multidecadal Oscillation
NAO
Winter North Atlantic Oscillation
WarmSlope3
% warm slope water on Halifax sampling line
WarmSlopeE
% warm slope water in Emerald Basin
Regional-scale climate (unique to each)
SST
Sea surface temperature
Temp50
Temperature at 50 m
Temp100
Temperature at 100 m
SSTCV
Intra-annual variation in SST (among monthly values)
Temp50CV
Intra-annual variation in temperature at 50 m (among monthly
values)
Temp100CV
Intra-annual variation temperature at 100 m (among monthly
values)
Stratif
Stratification
DRIVER: Fishing
LandingsMT
Total landings
GrFishLands
Main predatory groundfish landings
PlankLands
Planktivore (small pelagic) landings
RelativeMortalityGR Relative exploitation (landings/biomass) of main predators
(groundfish)
RelativeMortalityPL Relative exploitation (landings/biomass) of main planktivores
(small pelagic)
RESPONSE: Biological
Lower trophic levels
Colour
Phytoplankton
Centropage
Centropages typicus
SmallCopes
Small copepods: Paracalanus spp., Pseudocalanus spp.
Metridia
Metridia lucens
Oithona
Oithona spp.
Cal14
Calanus copepodite stages I–IV
LargeCope
Calanus finmarchicus, C. hyperboreus, C. glacialis
Macroinvertebrates biomass (BM)
BM_Decapod
Decapod
BM_Squid
Squid
BM_Bivalve
Bivalve
Fish biomass (BM)
BM_Plankti
Planktivore
BM_NonComm
Non-commercial fish (longhorn sculpin)
BM_MdBenth
Medium-sized benthivore
BM_Zoopisc
Zoopiscivore
BM_LgBenth
Large benthivore
BM_Pisc
Piscivore
Fish size/community structure
SZ_Plankti
Planktivore
SZ_MdBenth
Medium-sized benthivore
SZ_Zoopisc
Zoopiscivore
SZ_LgBenth
Large benthivore
SZ_Pisc
Piscivore
Evenness
Pielou evenness index of all fish species
ESS
WSS
BoF
GoM
GB
SNE
MAB
60-08
60-08
60-08
60-08
60-08
60-08
60-08
60-08
60-08
60-08
60-08
60-08
60-08
60-08
60-08
60-08
60-08
60-08
60-08
60-08
60-08
60-08
60-08
60-08
60-08
60-08
60-08
60-08
60-08
60-08
60-08
60-08
60-08
60-08
60-08
60-08
60-08
60-08
60-08
60-08
60-08
60-08
60-08
60-08
60-08
77-07
77-07
77-07
77-07
70-08
70-08
70-08
70-08
70-08
70-08
70-08
70-08
70-08
70-08
70-08
70-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
70-08
70-08
70-08
67-08
67-08
67-08
67-08
62-73
91-06
62-73
91-06
62-73
91-06
62-73
91-06
62-73
91-06
62-73
91-06
62-73
91-06
61-73
91-06
61-73
91-06
61-73
91-06
61-73
91-06
61-73
91-06
61-73
91-06
61-73
91-06
na
61-08
na
na
na
na
61-08
77-07
77-07
77-07
na
61-08
77-07
77-07
77-07
na
61-08
77-07
77-07
77-07
na
61-08
77-07
77-07
77-07
na
61-08
77-07
77-07
77-07
na
61-08
77-07
77-07
77-07
70-08
70-08
na
70-08
70-08
na
70-08
70-08
na
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
70-08
70-08
70-08
70-08
70-08
70-08
70-08
70-08
70-08
70-08
70-08
70-08
70-08
70-08
70-08
70-08
70-08
70-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
70-08
70-08
70-08
70-08
70-08
70-08
70-08
70-08
70-08
70-08
70-08
70-08
70-08
70-08
70-08
70-08
70-08
70-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
67-08
60-08
60-08
70-08
70-08
“na” represents the indicators that were unavailable (e.g. there were no comparable lower trophic level indicators in the BoF). BM denotes the biomass
(kg tow21). SZ denotes the mean individual weight (kg).
154
(Sutton and Hodson, 2005), although how the AMO influences
local physical conditions (and hence biota) is not completely
known. Following Nye et al. (2010), the detrended Kaplan SST
dataset (58 latitude × 58 longitude grids) from 0 to 708N was
used (Knight et al., 2005; Sutton and Hodson, 2005). The detrending removed the linear effects of anthropogenic climate change.
The resultant index represents natural variation in SST (Sutton
and Hodson, 2005), so a positive AMO reflects a
North-Atlantic-scale warm phase regardless of (or in
addition to) anthropogenic warming.
Seven regional-scale climate indicators (Table 1) were examined. For each, temperature data were obtained from databases
available at http://www.mar.dfo-mpo.gc.ca/science/ocean/
database/data_query.html, processed to correct for differences in
monthly sampling, and expressed as annual standardized anomalies. Data that fell within the boundaries of each region were used.
Mean SST and temperature at 50 and 100 m were selected because
they influence the growth and availability of food at all trophic
levels. The coefficients of variation (CVs) of monthly SST and temperature at depth were also included in the analyses. Any increase
in the variability of temperature (associated with climate change)
may interfere with biological production schedules, e.g. the spring
bloom, or recruitment events. The range of SSTs off the northeastern United States has increased since the 2000s (Friedland
and Hare, 2007). Stratification indices were provided by Roger
Pettipas (BIO, DFO, Dartmouth, NS, Canada) and Jon Hare
(NMFS, NEFSC, Narragansett, RI, USA) and were derived from
the difference in density between 50 m and the surface; positive
values reflect stronger stratification. Stratification was included
in the analysis because it has been hypothesized to influence the
population dynamics of lower trophic levels (Greene and
Pershing, 2007).
Fishing indicators
In all, five indices of fishing pressure were used in the analysis: (i)
total landings of groundfish, small pelagic, and invertebrates,
summed for each region from Canadian and US commercial fisheries landings databases, then further refined into (ii) main predatory groundfish landings, (iii) planktivore (small pelagic) landings,
(iv) relative exploitation of main predatory groundfish (landings/
biomass), and (v) relative exploitation of planktivores.
Biological indicators
The biological data included information for a range of lower to
upper trophic level biota and two community-level indicators:
evenness and the average size of functional groups.
Lower trophic levels
Two major sources of data were used to derive lower trophic level
indices for phytoplankton and zooplankton: broad-scale bongo
surveys throughout the United States, and Continuous Plankton
Recorder (CPR) information for both regions. Zooplankton indicators for US regions were provided fully processed by Jon Hare,
with survey and processing detailed by Kane (2007).
The CPR is a high-speed plankton net used to sample the
surface abundance of phytoplankton and zooplankton
(http://www.sahfos.org). The survey has used ships of opportunity at a sampling interval of one month since 1961. We used
zooplankton data as provided to DFO, Canada, for two regions
(WSS and ESS) and phytoplankton data for three (WSS, ESS,
and GoM). Phytoplankton data were not available for BoF, GB,
N. L. Shackell et al.
SNE, and MAB, and no zooplankton data were available for the
BoF. In the Canadian regions, there is a gap in the series from
1974 to 1990. All CPR data were processed to account for seasonality and expressed as counts per sample. Years when fewer than 5
months had been sampled were omitted, and for those years with
an enough months but with missing samples, the average of the
preceding and following months was taken, following the
approach of Head and Sameoto (2007). An annual index was
calculated by taking the average of all months within a year,
grouping zooplankton species into six functional groups (Table 1).
Mid- and upper trophic levels
Two major sources of data were used to derive upper trophic level
indices: the US and Canadian fishery-independent research vessel
(RV) surveys are designed to monitor the distribution and abundance of commercial and non-commercial species. The US conducts annual multispecies surveys in spring and autumn, but we
used just the autumn time-series for this study. The US surveys
use a #36 Yankee (or similar) bottom trawl towed at
6.5 km h21 for 30 min at each station. Further details of the
sampling methodology are provided by Azarovitz (1981) and
NEFSC (1988). Since 1970, DFO, Canada, has conducted
annual, scientific RV surveys in July over the Scotian Shelf. The
surveys used a #36 Yankee bottom trawl from 1970 to 1981, and
a Western IIA trawl from 1982. The trawl is towed at
5.5 km h21 for 30 min per set. Further details of the sampling
methodology are provided by Simon and Comeau (1994).
Biomass (stratified weight per tow) and abundance (stratified number per tow) time-series (1967–2008 in the United
States and 1970–2008 in Canada) were derived for 46 species
from the RV survey databases (see Supplementary material).
Macroinvertebrates and finfish were divided into functional
groups, macroinvertebrates into decapods, squid, and bivalves.
Although the US survey has consistently enumerated macroinvertebrates and “Cancer” crabs since 1973, the Canadian survey
has done so only since 1999. Therefore, Canadian abundance
information was only available for two invertebrates, Homarus
americanus (American lobster), representing decapods, and
Ilex spp. (squid) from 1970 to present. Note that lobster may
not represent all decapods on the Scotian Shelf. Finfish
species were divided into functional groups based on the
maximum body size ever observed (Froese and Pauly, 2009)
and diet (Shackell and Frank, 2007). Six finfish functional
groups were denoted: medium (,80 cm maximum body size)
and large (≥80 cm maximum body size) benthivores (primarily
consumers of bottom dwellers), piscivores (primarily consumers of fish, i.e. consumers of planktivores and other smaller
fish), zoopiscivores (consumers of amphipods, euphausiids,
and small fish), planktivores (consumers of zooplankton), and
a category with a single species, longhorn sculpin, as a noncommercial functional group. Longhorn sculpin are found in
all regions, but in relatively low abundance in the most southerly region, MAB. Hereafter, piscivores, medium and large
benthivores, and zoopiscivores are referred to collectively as
main predators.
Fish community
Two community-level indicators were included: evenness and the
average size of a functional group. Evenness was measured as
Pielou evenness index (Pielou, 1966) of all fish species in a given
year–region combination (see the Supplementary material for a
Common large-scale responses to climate and fishing across NW Atlantic ecosystems
species list). If total biomass is shared more or less equally by all
member species, the value of evenness is larger. As body size is
recognized as a determinant of trophic structure and energy
flow in size-structured ecosystems (Woodward et al., 2005),
average body size of each functional group was used as a
community-level indicator. We first calculated the total weight/
total abundance per species, then the biomass-weighted (by
species) geometric average body size for each functional group
was estimated.
Statistical analysis
The aim was to explore whether there were common ecological
patterns among the seven regions then to determine whether
climate or fishing, or both, were associated with those patterns.
Biological variables are referred to as response indicators, and
climate and fishing indicators as drivers. The first step was to
extract the primary multivariate temporal trend of response
155
indicators from each region. To do this, we used a data-reduction
technique, comparable with principal component analysis but
designed for ordered time-series, named minimum/maximum
autocorrelation factor analysis (MAFA). MAFA was originally
developed by Solow (1994) and further developed by Zuur et al.
(2007). It uses the autocorrelation structure of each response indicator to extract temporal trends, then tests whether they are significant. In this broad-scale scoping exercise, focus was on the primary
trend (MAF axis 1 or MAF1), because it represents the strongest
temporal signal. As it is for a PC axis, the direction of a MAF
axis is arbitrary and is equivalent to its opposite by reversing the
sign of each coefficient in the linear combination. To ease interpretation among regions, regional primary multivariate trends
were adjusted to have a common direction. Comparable with
the variable loadings on a principal components axis, the sign
and the magnitude of canonical correlations of each response indicator with the primary multivariate temporal trend reflect
Figure 2. Canonical relationship of response indicators with the primary multivariate temporal trend (MAF1) superimposed (dots are annual
values and lines smoothed loess using a span of 0.3) in each region. Horizontal dashed lines indicate significance levels for correlations
(+0.315). The r critical value for the Scotian Shelf was 0.32 and for the United States was 0.31. Their average was used for depiction. Axis
values on the top and the right refer to MAF1 and on the bottom and the left to canonical correlations. The sign and the magnitude of
canonical correlations of each response indicator with the primary temporal trend reflect their influence on that trend. If the correlation is
positive and strong, then the original response variable follows the primary trend closely, and vice versa. Response indicator abbreviations are
as in Table 1.
156
N. L. Shackell et al.
their influence on that trend; if the correlation is positive and
strong, then the original response variable follows the primary
trend closely, and vice versa.
We then quantified the extent to which the external drivers
(climate and fishing) might be influencing the primary trends in
biological characteristics, by conducting a correlation analysis
between each external driver and the primary trend. Note that
unlike the response indicators, the external drivers were not
included in an MAFA.
To account for multicollinearity among drivers, partial correlation analyses (correlation between MAF1 and a driver holding all
other drivers constant) were also used.
Ecological responses may lag behind their drivers owing to
the biological processes of survival, recruitment, and reproduction (Stenseth et al., 2006). In these systems, we would not
expect any correlations .5 –6 years, given the lifetime of the
lower trophic levels as well as the average lifespan for exploited
species (although they may have a much higher natural lifespan). Therefore, some correlation at time-lag 0, though
perhaps not the highest correlation, would be expected.
Recognizing that further exploration into lagged drivers
would be insightful, for this initial study, we present canonical
correlations between extracted trends and drivers without lags,
because different trophic levels would require different lags.
MAFAs were conducted using Brodgar software Version 2.5.6
(Highland Statistics, Inc., http://www.Brodgar.com). Data compilation, scaling, and processing were performed using the
open-source R statistical software Version 2.8.1 (R
Development Core Team, 2008).
Results
Primary temporal trend
The primary multivariate temporal trends (MAF1) were all statistically significant (Figure 2; probabilities for all regions p , 0.001
except for GB, where p , 0.007), with a common monotonic
trend starting roughly in late 1970s/early 1980s to early 1990s in
all ecosystems. This monotonic trend continued in four of the
seven regions: ESS, WSS, BoF, and SNE, abated slightly in the
ESS and reversing in the GoM, GB, and MAB in the early 1990s
(Figure 2). By superimposing the canonical correlations on
MAF1 (Figure 2), patterns within regions can be interpreted: the
response indicators significantly correlated with MAF1 (positive
or negative) are those most responsible for the collective ecological
trend (Table 2).
On the ESS, MAF1 increased steadily starting in 1980 and
abating slightly by 1990. The abundance of phytoplankton and
the biomass of decapods and planktivores were positively associated with that trend, whereas abundance of large copepods
and copepodite stages I –IV, and the biomass of three predator
groups declined. The body size of all fish functional groups
declined (Figure 2, Table 2).
On the WSS, MAF1 was stable until the mid 1980s and
increased steadily thereafter. The response indicators that followed
that trend (strongly and positively correlated) included phytoplankton, the biomass of decapods and planktivores, the
biomass of a non-commercial fish and medium benthivores,
and, to a lesser extent, the biomass of zoopiscivores. The body
size of all fish functional groups declined as did evenness within
the fish community (Figure 2, Table 2).
Table 2. The relationship between response variables and the primary multivariate temporal trend (MAF1) in each region, with significant
correlations of 0.31 (+) for the US regions and 0.32 for the Canadian regions shown emboldened (abbreviations defined in Table 1).
Indicator
Lower trophic
Colour
Centropage
Metridia
Oithona
SmCope
Cal14
LrgCope
Mid-trophic
BM_Bivalve
BM_Decapod
BM_Squid
BM_Plankti
Upper trophic
BM_NonComm
BM_Zoopisc
BM_MdBenth
BM_LgBenth
BM_Pisc
Fish community traits
SZ_Plankti
SZ_Zoopisc
SZ_MdBenth
SZ_LgBenth
SZ_Pisc
Evenness
ESS
WSS
BoF
0.45
0.23
0.27
0.20
20.05
20.28
20.25
0.43
20.04
0.30
20.08
20.23
0.04
20.11
na
na
na
na
na
na
na
na
0.57
20.25
0.77
na
0.71
0.02
0.69
0.06
20.39
20.76
20.16
20.76
20.40
20.74
20.93
20.55
20.81
0.17
GoM
GB
SNE
MAB
0.31
0.55
0.56
0.63
0.81
0.46
0.65
na
0.25
20.21
0.29
20.08
20.31
20.38
na
0.00
0.24
0.59
0.18
0.12
0.06
na
0.31
0.00
0.23
0.03
20.11
20.06
na
0.63
20.07
0.68
0.07
0.43
20.11
0.81
0.22
0.37
0.08
0.69
0.42
0.02
0.34
20.59
0.37
20.04
20.15
0.06
0.69
0.27
0.52
0.04
20.19
0.39
0.37
0.45
20.02
0.55
0.66
0.08
20.70
20.36
20.28
0.18
20.26
20.34
20.17
0.02
20.47
20.74
20.53
0.29
20.10
20.69
20.67
20.68
0.26
20.72
20.54
20.55
20.80
20.63
20.62
20.49
20.76
20.68
20.98
20.45
20.59
20.69
20.35
20.71
20.91
20.74
20.87
20.39
20.04
20.50
20.31
20.03
20.11
20.25
20.52
20.67
20.13
20.06
20.04
20.21
20.66
20.38
20.60
20.39
20.09
20.05
The sign and the magnitude of canonical correlations of each response indicator with the primary temporal trend reflect their influence on that trend; if the
correlation is positive and strong, then the original response variable follows the primary trend closely, and vice versa.
157
Common large-scale responses to climate and fishing across NW Atlantic ecosystems
In the BoF, MAF1 increased linearly over time. There were no
data available for lower trophic levels. The trend reflected an increase in the biomass of decapods, planktivores, non-commercial
fish, and three main predatory groundfish groups. The body size of
all fish functional groups declined, as did evenness within the fish
community (Figure 2, Table 2).
In the GoM, MAF1 revealed a monotonic increase until 1990,
which then reversed. Here, the lower trophic level data were complete, and there were clear increases until 1990 in the abundance of
phytoplankton, six functional groups of zooplankton, and the biomasses of decapods, planktivores, and a non-commercial fish. The
biomass of medium and large benthivores was negatively correlated with the primary trend. The body size of all fish functional
groups declined, as did evenness within the fish community
(Figure 2, Table 2).
On GB, MAF1 declined from the late 1960s to 1980s, after
which it increased before starting to decline in 1990. The response
indicators that followed this trend strongly were the biomasses of
decapods and planktivores. The indicators that responded in the
opposite direction were the abundance of Calanus stages I –IV,
large copepods, the biomass of medium benthivores, and the
body size of medium benthivores and zoopiscivores (Figure 2,
Table 2).
In SNE, MAF1 increased monotonically from the early 1980s
on. The response indicators that followed that trend were the
abundance of Oithona and the biomass of squid and bivalves.
Since the mid 1980s, planktivore biomass has declined, as did
that of a non-commercial fish, medium benthivores, and zoopiscivores. The size of planktivores and zoopiscivores also declined
(Figure 2, Table 2).
In the MAB, MAF1 increased monotonically until 1990. Only
the biomass of Centropages and bivalves was strongly positively
correlated with the trend, whereas the biomass of a noncommercial fish and the biomass of three main predatory groundfish declined. Body size declined in four of the five fish functional
groups (Figure 2, Table 2).
Common response indicators
Common responses are evident among the individual patterns
across the seven regions, particularly for the mid- and upper
trophic levels (Figure 2; Table 2). To reiterate, the response indicators significantly correlated with MAF1 (positive or negative) are
those most responsible for the collective ecological trend. On the
ESS, WSS, BoF, GoM, and GB, there was an increase in decapods
and planktivores, which lessened by the 1990s and even reversed in
the GoM and GB. On the WSS, BoF, and GoM, the noncommercial fish biomass increased at least until the 1990s. In all
regions, body size declined through the 1980s, significantly for
all functional groups in ESS, WSS, BOF, and GoM, significantly
for four groups in MAB and for two groups in GB and SNE.
The decline in body size, until at least the 1990s, was stronger in
the more northerly regions. Pielou evenness index declined in
regions with increasing or no clear trend in predatory groundfish
Table 3. Correlation of MAF1 to drivers and the partial correlation of MAF1 to the suite of significant drivers in each region (abbreviations
defined in Table 1).
Indicator
Driver
AMO
NAO
SST
SSTCV
Stratif
Temp100
Temp100CV
Temp50
Temp50CV
WarmSlope3
WarmSlopeE
LandingsMT
GrFishLands
PlankLands
RelativeMortalityGR
RelativeMortalityPL
Partial
AMO
NAO
SST
SSTCV
Stratif
Temp100
Temp100CV
Temp50
LandingsMT
RelativeMortalityGR
RelativeMortalityPL
ESS
WSS
BoF
GoM
GB
SNE
MAB
0.73
0.17
0.11
0.12
0.55
20.59
0.20
-0.42
0.15
0.20
20.05
20.89
20.86
na
20.72
na
0.77
0.05
20.02
0.27
0.38
20.35
0.26
20.24
0.16
0.08
0.02
20.76
20.93
20.57
20.75
20.72
0.77
0.14
20.11
0.17
0.07
0.09
20.44
20.18
0.00
0.18
20.08
20.20
20.51
20.71
20.71
20.81
0.45
0.40
0.31
20.55
0.03
0.20
20.17
0.25
20.26
0.27
0.01
20.60
20.60
0.35
20.32
20.75
0.47
0.20
20.08
20.04
0.17
20.10
20.04
20.01
20.07
0.27
20.05
20.76
20.72
20.24
20.58
20.82
0.66
0.10
0.38
20.51
0.28
0.01
0.13
0.29
20.22
20.03
0.00
0.32
20.59
20.38
20.41
20.55
0.39
0.25
0.00
0.02
20.06
20.02
20.07
0.00
20.09
0.22
0.00
0.84
20.55
20.23
20.83
20.54
20.02
na
na
na
0.00
20.26
na
0.01
20.71
0.27
na
0.32
na
na
na
20.16
20.16
na
na
20.23
20.37
20.39
0.59
na
na
na
na
na
20.33
na
0.16
20.38
20.50
0.21
0.24
0.45
na
na
na
na
na
20.14
0.24
20.54
20.07
na
na
na
na
na
na
na
20.42
0.25
20.59
0.57
na
0.04
20.26
na
na
na
na
0.33
0.11
20.19
0.06
na
na
na
na
na
na
na
0.56
20.19
20.33
The correlation of driver variables with MAF1 is an independent measure of the association between the two: the driver variables were not included in the
construction of MAF1. Drivers that were significant in the full correlations were used as input to the partial correlation matrices. “na” indicates that a given
driver was not included. Levels for significance are 0.31 (+) for US regions and 0.32 for Canadian regions and are shown emboldened.
158
biomass (WSS, BoF, and GoM), indicating that fewer species now
make up most of the fish biomass.
The emerging picture for the lower trophic levels is less clear,
because some indicators are missing or have data gaps in some
regions, potentially understating the influence of lower trophic
levels on the primary trends. However, where phytoplankton was
measured (ESS, WSS, and GoM), it increased from the beginning
of the time-series to at least the 1990s. The pattern of correlation
between each of the five zooplankton groups and the relevant
primary temporal trend was not consistent across the seven
regions, but the data gaps may have obscured the results. The
zooplankton has been measured since 1961 in the GoM, and all
functional groups were significantly and positively associated
with an increasing trend up to the early 1990s.
Drivers
The correlation between the drivers and MAF1 varied among
regions. The consistent drivers were the AMO, which was
positively correlated in all regions, and fishing indices, which
were generally negatively correlated (Table 3). Available AMO
data date back to the 1850s (Figure 3). It has been increasing
since the start of the RV surveys in 1970, yet was in a negative
phase until around 1995.
In most regions, relative exploitation of both main predatory
groundfish and planktivores declined along with the landings, an
indication that there was less fishing pressure over time. The exception was in the GoM, where the relative exploitation of planktivores increased as landings fell (Figure 3). Total landings (which
N. L. Shackell et al.
include invertebrates) in five regions declined over time and show
no discernible pattern off SNE since the late 1970s, but a modest
increase in MAB that had abated by 1990. These patterns are
reflected in their correlations with MAF1 (Figure 4, Table 3). In
general, total landings were strongly negatively correlated in four
of the seven regions, and positively correlated in the two most
southerly regions (Table 3), whereas predator groundfish landings,
planktivore landings, and relative exploitation indices were negatively correlated in all regions, except planktivore landings in the
GoM (there were no planktivore landings or exploitation on the
ESS).
Within regions, cooler temperature at depth and increasing
stratification were associated with the primary multivariate trend
on the ESS and the WSS. In the BoF, the decline in the
intra-annual variability of temperature was negatively associated
with the primary trend. A decline in SST intra-annual variability
and increasing mean SST, for part of the time-series, were associated with the primary trends in GoM and SNE. On GB and
MAB, only the increasing AMO (and landings) was associated
with the primary multivariate trend (Figure 4, Table 3).
Some of the drivers themselves are correlated with each other,
obscuring the direct link to MAF1. For each region, the drivers
selected were those that were significantly correlated with MAF1,
and a partial correlation matrix was calculated. The partial correlations between MAF1 and selected drivers (Table 3) reflect the
correlation between MAF1 and a given driver, holding all other
drivers constant. This allowed us to gain some insight into
partial associations. Always, the strength of the correlations
Figure 3. AMO (the solid line is the 5-year running mean) and fishing index anomalies. Total landings refer to all fish and invertebrate catches.
GroundfishLands refer to aggregate main predatory groundfish landings. PlankLands refer to aggregate planktivore landings. RelExpGroundfish
refers to relative exploitation of main predatory groundfish (landings/biomass). RelExpPlank refers to relative exploitation of planktivores
(landings/biomass). Lines are smoothed using loess smoothers. Dashed vertical lines in the upper panel indicate the start of the US and
Canadian RV surveys used in this study, 1967 and 1970, respectively.
Common large-scale responses to climate and fishing across NW Atlantic ecosystems
159
Figure 4. Correlation of drivers with primary multivariate temporal trend (MAF1) superimposed (dots are annual values and lines smoothed
loess using a span of 0.3) in each region. Horizontal dashed lines indicate the significance level for correlations (+0.315). The r critical value for
the Scotian Shelf was 0.32 and for the United States was 0.31. Their average was used for depiction. Axis values on the top and the right refer
to MAF1 and on the bottom and the left to correlations. Driver indicator abbreviations are as in Table 1.
decreased, demonstrating that although fishing indices prevail,
there is no single driver responsible for trends.
Discussion
The emergence of a common primary multivariate temporal trend
(MAF1) across all seven ecosystems, shaped by similar changes in
biological indicators over time, suggests that over the whole study
domain, these ecosystems have experienced similar forcing factors
and have responded similarly. The strongest common patterns
(declines in body size of fish functional groups, increase in
biomass of planktivores and macroinvertebrates) were in the
more northerly ecosystems, ESS, WSS, BoF, GoM, and, to a
lesser extent, GB.
Common patterns were associated with observed less fishing
pressure on main predators and planktivores in five of the seven
regions and were also positively correlated with large-scale environmental forcing (AMO) in all ecoregions. The two warmest,
most southerly regions, SNE and MAB, behaved slightly
differently. In those regions, landings were stable or showed no
clear trend, and there were declines in the biomass of all upper
trophic levels, except that of large benthivores. Note also that
the increase in planktivores observed in the five more northerly
regions was not found in those regions.
Species composition differs in SNE and MAB (Supplementary
material), and those regions are biogeographically less similar to
the others (Link et al., 2010). Although those two regions differ
in their patterns of fishing pressure, they have both experienced
declines in fish predator biomass and body size.
In all regions, the strength of correlations between MAF1 and
the drivers decreased in the partial correlation analysis. Fishing
indices dominated, but no singular driver was found to be responsible for the common trends. In all, 11 climate indices were
included in the analysis, yet only the AMO was correlated with
the primary multivariate temporal trends across all ecosystems.
Local environmental indices reflective of climatic conditions
included in this analysis, such as stratification, SST, and warm
slope water, were not common drivers of the primary multivariate
temporal trends among regions, but some were locally important.
The AMO was included in this analysis because it includes SST
variability and is related to thermohaline circulation (Knight
160
et al., 2005). It is not yet clear how the AMO is mechanistically
related to the ecological changes observed, or even if there is a
cause and effect between community structure and broad-scale
climate.
The AMO may have different local effects depending on geography, as has been found with the NAO (Petrie, 2007). Perhaps
persistent “warm” and “cool” phases indicated by the AMO can
drive trends in population size and community dynamics to a
greater extent than local high-frequency climate variability.
However, the multidecadal-scale, low-frequency signal of the
AMO is difficult to interpret relative to the shortness of the biological time-series. Climate, including the AMO, might be
expected to influence recruitment success, vital rates, and spatial
distribution.
In this study, the primary common trend in each ecoregion was
best correlated with changes in the size and biomass of macroinvertebrates and fish, traits more likely to be directly related to
fishing than to climate. The results are consistent with a suite of
studies demonstrating that fishing, through selective temporary
or permanent reductions in biomass or size, and as modulated
by environmental factors, is a dominant force in shaping ecosystems, particularly at a large scale in the area of study.
All seven ecosystems have supported significant commercial
fisheries for centuries (Rosenberg et al., 2005; Rose, 2007). They
have been subjected to considerable fishing pressure, often resulting in sequential stock depletion (Gough, 1993; Fogarty and
Murawski, 1998); on the ESS in fact, there has been a groundfishing moratorium since 1993 (Bundy, 2005). As reflected in this
study, fishing pressure on main predators and planktivores
declined over time in most regions. There have been temporary
reductions in aggregate biomass coinciding with higher levels of
relative exploitation in several of the study regions, and compensation within functional groups by other species south of ESS
(Shackell and Frank, 2007; Auster and Link, 2009). The lower
fishing pressure during the later portion of the time-series, combined with compensation, has allowed for recovery or maintenance of aggregate predatory groundfish biomass south of ESS.
The results support the notion that colder regions (e.g. ESS) are
less resilient to overfishing because of the lower demographic
rates and a smaller pool of species that could compensate (Frank
et al., 2007).
Compensation of aggregate predatory groundfish biomass at
the community level occurred in response to either individual
species declines or to less fishing pressure in most regions
(Shackell and Frank, 2007; Auster and Link, 2009). In contrast,
body-size declines were a much stronger common signal.
Worldwide and locally, declines in average size and size- and
age-at-maturity have been associated with the preferential
harvest of older and larger fish in both commercial fisheries and
their bycatch (Olsen et al., 2004; Swain et al., 2007; Darimont
et al., 2009; Fisher et al., 2010; Shackell et al., 2010). Here, fish
size declined most in the more northerly regions as a consequence
of the relatively “slower” life-history traits for a given species compared with their southern, smaller-bodied, faster maturing counterparts (Fisher et al., 2010).
Climate and fishing have been examined, but trophic interactions only incompletely. Trophic interactions are important on
the ESS, where a decline in predator groundfish biomass has
been related to a planktivore increase (Bundy, 2005; Frank et al.,
2005) as well as on the WSS, where trophic interactions through
changes in body size have seemingly contributed to planktivore
N. L. Shackell et al.
increase (Shackell et al., 2010). However, trophic interactions are
not invoked solely as explanations of planktivore increases
through the GoM and GB (Link et al., 2002, 2009; Gaichas et al.,
2009). The influence of trophic interactions on ecosystem response
cannot be addressed adequately here by comparing regional,
multitrophic ordination axes developed from MAFA, largely
because subtler signals are lost. Here, we have determined
common dynamics at multiple trophic levels among the seven
regions and have suggested that common fishing and/or climate
indices were the drivers. A different approach to addressing the
influence of trophic interactions on system changes within
regions will be pursued in other work.
Summary
Using the joint patterns of relative exploitation, planktivore landings, and total landings as indicators of fishing pressure, fishing
would seem to be the dominant driver of ecosystem response,
although local climate regimes either exacerbate (in northerly
regions) or mitigate (in southerly regions) the response.
Remarkably, common trends in upper trophic levels were observed
across all seven regions spanning 128 of latitude, with some latitudinal differences in species assemblages over an area of almost half
a million square kilometres.
This comparative analysis of the seven ecosystems suggests that
the ecosystem response to perturbation is similar regardless of
species composition. The effects of climate and fishing interact,
and differences in regional lower trophic dynamics ultimately determine upper trophic productivity (Chassot et al., 2010).
At a broad scale, the AMO increased and was well correlated
with all primary multivariate trends. The mechanism is not
clear, and the correlation is confounded by the multidecadal
scale, low-frequency signal of the AMO and the relative shortness
of the biological time-series.
Supplementary material
Supplementary material is available at the ICESJMS online version
of the manuscript as a summary of RV survey species names and
proportions by functional group for each region for two periods,
1967/1970–1985 and 1986–2008.
Acknowledgements
We thank J. Hare, M. Fogarty, R. Pettipas, B. Petrie, T. Horsman,
and K. T. Frank for providing data or assisting with data
exchanges. J. A. Fisher and two anonymous reviewers provided
helpful comments on an earlier version of the manuscript.
Funding for this joint Canadian/US research was provided by
the Canadian Department of Fisheries and Oceans under the
Maritimes ERI (Ecosystem Research Initiative) program and by
the US NOAA NMFS Fisheries under the Environment (FATE)
program.
References
Aebischer, N. J., Coulson, J. C., and Colebrook, J. M. 1990. Parallel
long-term trends across four marine trophic levels and weather.
Nature, 347: 753 –755.
Alheit, J., Möllmann, C., Dutz, J., Kornilovs, G., Loewe, P., Mohrholz,
V., and Wasmund, N. 2005. Synchronous regime shifts in the
central Baltic and the North Sea in the late 1980s. ICES Journal
of Marine Science, 62: 1205 –1215.
Auster, P. J., and Link, J. S. 2009. Compensation and recovery of
feeding guilds in a Northwest Atlantic shelf fish community.
Marine Ecology Progress Series, 382: 163 – 172.
Common large-scale responses to climate and fishing across NW Atlantic ecosystems
Azarovitz, T. R. 1981. A brief historical review of the Woods Hole
Laboratory trawl survey time series. Canadian Special Publication
of Fisheries and Aquatic Sciences, 58: 62– 67.
Bundy, A. 2005. Structure and function of the eastern Scotian Shelf
ecosystem before and after the groundfish collapse in the early
1990s. Canadian Journal of Fisheries and Aquatic Sciences, 62:
1453– 1473.
Casini, M., Hjelm, J., Molinero, J. C., Lövgren, J., Cardinale, M.,
Bartolino, V., Belgrano, A., et al. 2009. Trophic cascades promote
threshold-like shifts in pelagic marine ecosystems. Proceedings of
the National Academy of Sciences of the USA, 106: 197 – 202.
Chassot, E., Bonhommeau, S., Dulvy, N. K., Mélin, F., Watson, R.,
Gascuel, D., and Le Pape, O. 2010. Global marine primary production constrains fisheries catches. Ecology Letters, 13: 495– 505.
Cushing, D. H. 1975. Marine Ecology and Fisheries. Cambridge
University Press, Cambridge, UK.
Darimont, C. T., Carlson, S. M., Kinnison, M. T., Paquet, P. C.,
Reimchen, T. E., and Wilmers, C. C. 2009. Human predators
outpace other agents of trait change in the wild. Proceedings of
the National Academy of Sciences of the USA, 106: 952 – 954.
Daskalov, G. M., Grishin, A. N., Rodionov, S., and Mihneva, V. 2007.
Trophic cascades triggered by overfishing reveal possible mechanisms of ecosystem regime shifts. Proceedings of the National
Academy of Sciences of the USA, 104: 10518– 10523.
Fisher, J. A. D., Frank, K. T., and Leggett, W. C. 2010. Breaking
Bergmann’s rule: truncation of Northwest Atlantic marine fish
body sizes. Ecology, 91: 2499– 2505.
Fogarty, M. J., and Murawski, S. A. 1998. Large-scale disturbance and
the structure of marine systems: fishery impacts on Georges Bank.
Ecological Applications, 8(Suppl. 1): S6 – S22.
Frank, K. T., Petrie, B., Choi, J. S., and Leggett, W. C. 2005. Trophic
cascades in a formerly cod-dominated ecosystem. Science, 308:
1621– 1623.
Frank, K. T., Petrie, B., and Shackell, N. L. 2007. The ups and downs of
trophic control in continental shelf ecosystems. Trends in Ecology
and Evolution, 22: 236– 242.
Friedland, K. D., and Hare, J. A. 2007. Long-term trends and regime
shifts in sea surface temperature on the continental shelf of the
northeast United States. Continental Shelf Research, 27:
2313– 2328.
Froese, R., and Pauly, D. 2009. FishBase. http://www.fishbase.org (last
accessed January 2009).
Gaichas, S., Skaret, G., Falk-Petersen, J., Link, J. S., Overholtz, W.,
Megrey, B. A., Gjøsaeter, H., et al. 2009. A comparison of community and trophic structure in five marine ecosystems based on
energy budgets and system metrics. Progress in Oceanography,
81: 47– 62.
Gough, J. 1993. A historical sketch of fisheries management in Canada.
In Perspective on Canadian Marine Fisheries Management, pp.
5 – 53. Ed. by L. S. Parsons, and W. H. Lear. Canadian Bulletin of
Fisheries and Aquatic Sciences, 226.
Greene, C. H., and Pershing, A. J. 2007. Climate drives sea change.
Science, 315: 1084– 1085.
Head, E. J. H., and Sameoto, D. D. 2007. Inter-decadal variability in
zooplankton and phytoplankton abundance on the
Newfoundland and Scotian shelves. Deep Sea Research II, 54:
2686– 2701.
Hurrell, J. W., Kushnir, Y., Ottersen, G., and Visbeck, M. 2003. An
overview of the North Atlantic Oscillation. In The North Atlantic
Oscillation: Climatic Significance and Environmental Impact, pp.
1 – 35. Geophysical Monograph, 134.
Kane, J. 2007. Zooplankton abundance trends on Georges Bank,
1977– 2004. ICES Journal of Marine Science, 64: 909– 919.
Knight, J. R., Allan, R. J., Folland, C. K., Vellinga, M., and Mann, M. E.
2005. A signature of persistent natural thermohaline circulation
cycles in observed climate. Geophysical Research Letters, 32:
L20708. doi:10.1029/2005GL024233.
161
Link, J. S., Brodziak, J. K. T., Edwards, S. F., Overholtz, W. J.,
Mountain, D., Jossi, J. W., and Smith, T. D. 2002. Marine ecosystem assessment in a fisheries management context. Canadian
Journal of Fisheries and Aquatic Sciences, 59: 1429– 1440.
Link, J. S., Bundy, A., Overholtz, W. J., Shackell, N., Manderson, J.,
Duplisea, D., Hare, J., et al. 2010. Northwest Atlantic ecosystembased management of fisheries. In Ecosystem Based Management
for Fisheries: Linking Patterns to Policy, pp. 32 –112. Ed. by A.
Belgrano, and C. W. Fowler. Cambridge University Press,
New York.
Link, J. S., Col, L., Guida, V., Dow, D., O’Reilly, J., Green, J.,
Overholtz, W., et al. 2009. Response of balanced network
models to large-scale perturbation: implications for evaluating
the role of small pelagics in the Gulf of Maine. Ecological
Modelling, 220: 351 – 369.
NEFSC (Northeast Fisheries Science Center). 1988. An evaluation of
the bottom trawl survey program of the Northeast Fisheries
Science Center. NOAA Technical Memorandum, NMFS-F/
NEC-52. 83 pp.
Nye, J. A., Bundy, A., Shackell, N. L., Friedland, K. D., and Link, J. S.
2010. Coherent trends in contiguous survey time-series of major
ecological and commercial fish species in the Gulf of Maine ecosystem. ICES Journal of Marine Science, 67: 26– 40.
Oguz, T., and Gilbert, D. 2007. Abrupt transitions of the top-down
controlled Black Sea pelagic ecosystem during 1960– 2000: evidence for regime-shifts under strong fishery exploitation and nutrient enrichment modulated by climate-induced variations. Deep
Sea Research I, 54: 220 – 242.
Olsen, E. M., Heino, M., Lilly, G. R., Morgan, M. J., Brattey, J.,
Ernande, B., and Dieckmann, U. 2004. Maturation trends indicative of rapid evolution preceded the collapse of northern cod.
Nature, 428: 932 –935.
Petrie, B. 2007. Does the North Atlantic Oscillation affect hydrographic properties on the Canadian Atlantic continental shelf?
Atmosphere– Ocean, 45: 141 – 151.
Pielou, E. C. 1966. The measurement of diversity in different types of
biological collections. Journal of Theoretical Biology, 13: 131 – 144.
R Development Core Team. 2008. R: a Language and Environment for
Statistical Computing. R Foundation for Statistical Computing,
Vienna, Austria. ISBN 3-900051-07-0, http://www.R-project.org.
Rose, G. A. 2007. Cod. The Ecological History of the North Atlantic
Fisheries. Breakwater, St John’s, Newfoundland. 591 pp.
Rosenberg, A. A., Bolster, W. J., Alexander, K. E., Leavenworth, W. B.,
Cooper, A. B., and McKenzie, M. G. 2005. The history of ocean
resources: modeling cod biomass using historical records.
Frontiers in Ecology and the Environment, 3: 78– 84.
Shackell, N. L., and Frank, K. T. 2007. Compensation in exploited
marine fish communities on the Scotian Shelf, Canada. Marine
Ecology Progress Series, 336: 235– 247.
Shackell, N. L., Frank, K. T., Fisher, J. A. D., Petrie, B., and Leggett,
W. C. 2010. Decline in top predator body size and changing
climate alter trophic structure in an oceanic ecosystem.
Proceedings of the Royal Society of London, Series B: Biological
Sciences, 277: 1353– 1360.
Simon, J. E., and Comeau, P. A. 1994. Summer distribution and abundance trends of species caught on the Scotian Shelf from 1970–
1992, by research vessel groundfish survey. Canadian Technical
Report of Fisheries and Aquatic Sciences, 1953. 145 pp.
Solow, A. R. 1994. Detecting change in the composition of a multispecies community. Biometrics, 50: 556– 565.
Stenseth, N. Ch., Llope, M., Anadon, R., Ciannell, L., Chan, K. S.,
Hjermann, D. O., Bagoien, E., et al. 2006. Seasonal plankton
dynamics along a cross-shelf gradient. Proceedings of the
Royal Society of London, Series B: Biological Sciences, 273:
2831– 2838.
162
Sutton, R. T., and Hodson, D. L. R. 2005. Atlantic Ocean forcing of
North American and European summer climate. Science, 309:
115– 118.
Swain, D. P., Sinclair, A. F., and Hanson, J. M. 2007. Evolutionary response to size-selective mortality in an exploited fish population.
Proceedings of the Royal Society of London, Series B: Biological
Sciences, 274: 1015– 1022.
Therriault, J-C., Petrie, B., Pepin, P., Gagnon, J., Gregory, D., Helbig,
J., Herman, A., et al. 1998. Proposal for a Northwest Atlantic zonal
monitoring program. Canadian Technical Reports of Hydrography
and Ocean Science, 194. vii + 57 pp.
N. L. Shackell et al.
Ware, D. M., and Thomson, R. E. 2005. Bottom-up ecosystem trophic
dynamics determine fish production in the Northeast Pacific.
Science, 308: 1280– 1284.
Woodward, G., Ebenman, B., Emmerson, M., Montoya, J. M., Olesen,
J. M., Valido, A., and Warren, P. H. 2005. Body size in ecological
networks. Trends in Ecology and Evolution, 20: 402 – 409.
Worm, B., and Myers, R. A. 2003. Meta-analysis of cod-shrimp interactions reveals top-down control in oceanic food webs. Ecology, 84:
162– 173.
Zuur, A. F., Leno, E. N., and Smith, G. M. 2007. Analysing Ecological
Data. Springer, New York. 680 pp.
Handling editor: Bill Turrell