1
Effects of Sea Surface Temperature Fluctuations on the Occurrence of Small
Cetaceans off Southern California: Implications for Climate Change
E. Elizabeth Henderson1, Karin A. Forney2, Jay P. Barlow3, John A. Hildebrand4, Annie
B. Douglas5, John Calambokidis5 and William J. Sydeman6
1
National Marine Mammal Foundation
222 Shelter Island Dr. #200
San Diego, CA 92106
Elizabeth.henderson@nmmpfoundation.org
2
Southwest Fisheries Science Center
Marine Mammal and Turtle Division
National Marine Fisheries Service, NOAA
Santa Cruz, CA 95060
3
Southwest Fisheries Science Center
National Marine Fisheries Service, NOAA
La Jolla, CA 92093
4
Scripps Institution of Oceanography
University of California, San Diego
La Jolla, CA 92093
5
Cascadia Research Collective
Olympia, WA 98501
6
Farallon Institute for Advanced Ecosystem Research
Petaluma, CA 94952
2
Abstract
This study examines the link between ocean temperature and spatial and temporal
distribution patterns for eight species of small cetaceans off southern California for the
period 1979-2009. Sea surface temperature (SST) anomalies are used as proxies for sea
surface temperature fluctuations on three temporal scales: seasonal, El Niño/Southern
Oscillations (ENSO), and Pacific Decadal Oscillations (PDO). The hypothesis that
cetacean species assemblages and habitat associations in southern California waters
would co-vary with these periodical changes in SST was tested using generalized additive
models. Seasonal SST anomalies were included as a predictor in the models for Dall’s
porpoise (Phocoenoides dalli), and common (Delphinus spp.) and Risso’s dolphins
(Grampus griseus). The ENSO index was included as a predictor for Pacific white-sided
(Lagenorhynchus obliquidens), northern right whale (Lissodelphis borealis), and Risso’s
dolphins. The PDO index was selected as a predictor for Pacific white-sided, common,
and bottlenose dolphins (Tursiops truncatus). A bathymetric depth metric was included
in every model, indicating a distinctive spatial distribution for each species that may
represent niche or resource partitioning in a region where multiple species have
overlapping ranges. While the temporal changes in distribution are likely a response to
changes in prey abundance or dispersion, these patterns associated with SST variation
may be predictive of future, more permanent range shifts due to global climate change.
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Introduction
Cetaceans are apex marine predators whose movement patterns and habitat preferences
are typically related to the distribution of their prey (e.g., Gowans et al., 2008; Wishner et
al., 1995). Unlike baleen whales, small cetaceans (porpoises, dolphins, and small toothed
whales) generally do not undertake ocean-scale annual migrations tracking prey or
moving between breeding and feeding grounds. Rather, small cetaceans may display a
high degree of site fidelity, or may move seasonally inshore and offshore or along
coastlines (Dohl et al., 1986; Forney and Barlow, 1998; Leatherwood et al., 1984; Shane
et al., 1986). While many species may overlap in total range in any one region, they will
often differ in their occurrence or habitat-use patterns, perhaps reflecting competitive
exclusion or niche partitioning. This separation of habitat and resources often occurs
along depth, slope, and sea surface temperature (SST) gradients (Ballance et al., 2006;
Forney, 2000; MacLeod et al., 2008; Reilly, 1990). Habitat preferences are likely
reflections of differences in preferred prey, and dolphins track prey habitats or water
masses as they shift not only seasonally but through climate-driven changes such as the
El Niño/Southern Oscillation (ENSO) or the Pacific Decadal Oscillation (PDO) (Ballance
et al., 2006; Benson et al., 2002; Defran et al., 1999; Shane, 1995). This study examines
the distribution and relative abundance of multiple species of small cetacean across
shifting temperature regimes off southern California using a unique coupled cetaceanoceanographic long-term dataset, which enables the assessment of inter-decadal changes
in cetacean distribution.
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The southern California region represents the convergence of warm and cold
water regimes, and supports populations of both warm- and cold-water small cetacean
species (Dohl et al., 1981; Forney and Barlow, 1998) This area undergoes seasonal
temperature fluctuations as the cold, equator-ward flowing California Current and warm,
pole-ward flowing California Undercurrent shift in dominance from spring to fall
(Caldeira et al., 2005; Hickey, 1993; Hickey et al., 2003). Strong El Niño years have been
linked to increased downwelling, warmer SST’s, and a depression of the thermocline
observed off southern California (McGowan, 1985; Sette and Isaacs, 1960). During the
warm phase of the PDO, the California Current is weakened and the Countercurrent is
strengthened, bringing warmer waters farther north and west into and beyond the
southern California region and creating warm SST anomalies along the California coast.
In contrast, during the cool PDO phase the California Current is stronger, bringing cool
water farther south and east into the region (Mantua and Hare, 2002). A PDO regime
shift from cool to warm occurred around 1977, and a shift back to a cool PDO occurred
in the last decade (Wang et al., 2010; Zhang and McPhaden, 2006).
Two long-term sets of ship-based surveys have been conducted in southern
California waters, making it an ideal region for this investigation. California Cooperative
Oceanic Fisheries Investigations (CalCOFI) have been conducting quarterly cruises that
have sampled a breadth of oceanographic and biological measurements since 1949, with
marine bird and mammal observations added in 1987. The Southwest Fisheries Science
Center (SWFSC), an agency of NOAA, has also regularly carried out marine mammal
abundance surveys that included this region since 1979. In addition to the availability of
these 2 long-term data sets, the co-occurrence in overall range of cold- and warm-water
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species makes this the ideal location to examine potential impacts of climate variation on
small cetacean distribution patterns at different temporal scales (inter-annual, annual and
decadal). Changes in SST have been linked to changes in all levels of the food web, from
immediate phyto- and zooplankton responses to lagged alterations in numbers, diet and
even reproductive success of organisms at higher levels (Hubbs, 1948; McGowan, 1985;
McGowan et al., 2003; Tibby, 1937). It follows that small cetacean populations are
expected to respond to such variations, likely as a response to the movements of their
prey. In addition, animals’ responses to these fluctuations in temperature may be
predictive of their reaction to future ocean conditions as global ocean temperatures rise.
We investigated such responses by 8 species of small cetaceans across 30 years, using
SST anomaly indices as a proxy for environmental variation on three time scales:
seasonal (yearly), ENSO (2-7 years) and PDO (~30 years). Following similar work that
has been conducted for sea birds (Hyrenbach and Veit, 2003; Yen et al., 2006) and other
cetaceans (Becker et al., 2012; Forney and Barlow, 1998), we predict that 1) species
assemblages in southern California waters will differ dependent on the dominant SST
regime, such that 2) when cold-water conditions prevail, cold-water associated species
will be more abundant and broadly distributed, while 3) in warm-water conditions, warmwater associated species will dominate the region, and 4) when SST fluctuations co-occur
on multiple scales, these results will be compounded.
Methods and Materials
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Study Area and Survey Methods - Our study area is between 117° W and 125°W
longitude and from 30° N to 35° N latitude (Fig. 1). The Southern California Bight is a
region of complex bathymetric features, including the Channel Islands and a series of
deep basins and shallow ridges (Dailey et al., 1993). Beyond the steep 2000-m slope lies
the ocean basin, with a mean depth over 3500-m (see Fig. 1 for further description of
depth regions used for analysis).
Marine mammal visual sighting data were used from 105 separate survey cruises
from 1979 through 2009 conducted by both CalCOFI and SWFSC (Fig. 2). On CalCOFI
surveys from May 1987 to April 2004, marine mammals were recorded as part of
standardized CalCOFI top predator surveys which were focused primarily on marine
birds and used the strip transect methods of Tasker et al. (1984). Observations were made
by a single observer with the naked eye stationed on the flying bridge or outside the main
bridge. Marine mammals were recorded if they occurred within the 300-m strip transect
used for birds, or up to 1000-m of the vessel for large cetaceans; encounter rates rather
than densities were reported. Marine bird and mammal data, while continuously obtained,
were summarized into 3-km bins, with the latitude and longitude determined for the
centroid of each bin. Details of field methods can be found in Veit et al. (1997; 1996),
Hyrenbach and Veit (2003) and Yen et al. (2006).
In July 2004, 2 dedicated marine mammal visual observers were added to the
CalCOFI cruises, using standard line-transect protocol (Buckland et al., 2001; Burnham
et al., 1980). A complete description of survey methods can be found in Soldevilla et al.
(2006). Each observer monitored a 90° field of view from bow to abeam, alternating
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between scanning with Fujinon 7x50 bionoculars and the naked eye. Survey effort was
calculated based on the latitude and longitude at the start and end of each trackline.
For all CalCOFI surveys, observations were made on daytime tracklines between
stations, with no visual observation effort conducted at station, and all visual effort was
conducted in sea state conditions of Beaufort 5 or less. Data for this analysis are generally
from 4 surveys per year from 1987 to 2009. In 5 of these years only 3 surveys were
conducted, and in 1998 surveys were carried out monthly to capture a time series of
oceanographic measures in a strong El Niño year. However, for analysis purposes these
cruise data were combined into 4 quarters, to be consistent with all other years. A full
summary of surveys, along with total effort (in km) and sightings per year for all species
can be found in Appendix I.
SWFSC has conducted a number of cruises that have included southern California
waters; data for this analysis came from 10 different cruises (Appendix I) conducted
primarily in the summer and fall (July through November) from 1979 through 2005.
SWFSC cruises also used standard line-transect protocols, details of which can be found
elsewhere (Barlow and Forney, 2007; Kinzey et al., 2000). These cruises had 3 observers
on the flying bridge, 2 of whom used 25 x 150 big-eye binoculars to scan 90° from bow
to abeam on either side of the flying bridge, while the third observer monitored the entire
forward 180° using 7x50 binoculars and the naked eye. Survey effort (in km) was
calculated either from the latitude and longitude positions at the start and end of each
trackline (1979-1984 surveys) or from latitude and longitude positions recorded
approximately every 10 minutes along the track (1991-2005 surveys).
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Eight species of small cetacean were examined in this analysis. There were 3
warm-temperate and tropical species: short-beaked common dolphin (Delphinus delphis;
Dd), long-beaked common dolphin (D. capensis; Dc), and striped dolphin (Stenella
coeruleoalba; Sc); 3 cold-temperate species: Pacific white-sided dolphin
(Lagenorhynchus obliquidens; Lo), northern right whale dolphin (Lissodelphis borealis;
Lb), and Dall’s porpoise (Phocoenoides dalli; Pd); and 2 cosmopolitan species located in
cold-temperate, warm-temperate, and tropical waters: Risso’s dolphin (Grampus griseus;
Gg) and common bottlenose dolphin (Tursiops truncatus; Tt) (Reeves et al., 2002). All
bottlenose dolphin sightings in this study were presumed to be offshore animals, as most
coastal animals remain within about 1 km of the shore (Hanson and Defran, 1993), and
no surveys were conducted that close to the coast. A Delphinus species (Dsp) category
was also used that combined both short-beaked and long-beaked common dolphin
species, which were not formally recognized as distinct species until 1994 (Heyning and
Perrin, 1994) and were not distinguished on SWFSC cruises prior to 1991, nor on
CalCOFI cruises prior to August 2004. Therefore the Dc and Dd datasets are smaller than
the datasets for all other species, and the Dsp dataset consists of all combined common
dolphin sightings from all cruises.
Environmental data - Three variables were used to represent variation in SST on different
time scales: quarterly SST anomalies, ENSO indices, and PDO indices. Monthly
averaged SST data from 1985 through 2009 were taken from NOAA Advanced Very
High Resolution Radiometer (AVHRR) Pathfinder satellite data, with a spatial resolution
of ~4.1-km (http://podaac.jpl.nasa.gov/DATA_CATALOG/sst.html). For 1981-1984,
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NOAA AVHRR data were also used, using a multi-channel averaged SST with a 5.7-km
resolution. There were no satellite data available prior to 1981, so a missing data filter
was used to replace the missing 1979 and 1980 values with the mean of the remainder of
SST data using a single imputation method (Hastie, 1991; Nakagawa et al., 2001). Using
Windows Image Manager (WIM, M. Kahru, Scripps Institution of Oceanography), a
seasonal SST anomaly value was calculated from the monthly SST data as the difference
from the overall seasonal mean. These SST anomalies were estimated for each quarter
and each grid cell (see below) from 1981-2009 (spring: February-April; summer: MayJuly; fall: August-October; winter: November-January). NOAA ENSO anomaly data,
derived from the Oceanic Niño Index (ONI) as a 3-month running mean of SST
anomalies from 1971 through 2009 in the Niño 3.4 region around the equator
(http://www.cpc.ncep.noaa.gov) were used as a proxy for ENSO for 1979-2009. The
Niño 3.4 is centered on the equator, and so the index indicates the relative strength of the
ENSO event rather than SST anomaly values for southern California waters. PDO
anomaly data averaged from 1900 through 2009 from the University of Washington
(http://jisao.washington.edu/pdo) were used as a proxy for the PDO regime from 19792009. The PDO Index is derived from a monthly averaged SST for North Pacific waters
poleward of 20° N.
Modeling cetacean sighting rates - Generalized additive models (GAM) of species
sighting rates as a function of the temperature anomalies and depth values were created
using the package mgcv in R (www.r-project.org) (Hastie and Tibshirani, 1990; Wood,
2006). GAMs use a link function to relate the predictor variables to the mean of the
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response variable. GAMs also allow nonparametric functions to be fit to the predictor
variables using a smoothing function to describe the relationship between the predictor
and the response variables (Hastie and Tibshirani, 1990).
For model development, the study region was divided into 52 1-degree latitude by
1-degree longitude grid sections, leading to grid cell areas ranging from 2940 to 3120km2. These grid cells were then used as data units, with all effort, sighting, and seasonal
SST data calculated for each cell, thereby normalizing spatial and temporal differences in
survey data. The type of survey (Survey Type: SWFSC; CalCOFIa: 1987-2004;
CalCOFIb: 2004-2009) was included as a categorical variable to account for differences
in sighting rates due to survey method and platform. For each survey type, the number of
group sightings of each species within each 1-degree cell, offset by the log of the amount
of effort per cruise (in km), was modeled assuming a Poisson distribution with a log link
function. The potential predictor variables in the model included: seasonal SST anomalies
of each grid section (SeasAnom); ENSO Index (ENSO); PDO Index (PDO); the mean
(DepthMean), minimum (DepthMin), maximum (DepthMax) and standard deviation
(DepthSD) of depth (in m) for each grid section; the quarter (Quarter) as a categorical
variable to look for inter-annual patterns; and the year (Year) to look for trends in
abundance over time. Although Beaufort sea state has been demonstrated to be an
important predictor of sighting rates in other cetacean habitat and trend models (Becker,
2007), this was not recorded in early CalCOFI observations and so was not included in
this analysis. Instead, only data recorded in Beaufort sea state 0-3 were used in order to
standardize for differences in survey effort, making the different platforms as comparable
as possible.
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We used the number of group sightings, rather than the number of individuals, as
our measure of relative encounter rate, essentially making this an encounter rate model of
group sightings per unit (km) of survey effort (SPUE). Instead of using a traditional
stepwise method to select predictor variables for inclusion in each model, a likelihood
based smoothness selection method was used, using the Restricted Maximum Likelihood
(REML) criterion (Patterson and Thompson, 1971; Wood, 2006). Each predictor variable
was tested for inclusion in the model using a tensor product approach coupled with a
cubic spline regression smoothing function with shrinkage. The best model was selected
using a combination of the information-theoretic (IT) descriptor Akaike’s Information
Criterion (AIC, Akaike, 1976) and REML. Next an interactive term selection method was
applied to sequentially drop the single term with the highest non-significant p-value and
then refit the model until all terms were significant. The best-fit model was therefore one
that minimized AIC and maximized REML and included only significant predictor
variables. In addition, the ENSO, PDO, and Year variables, as well as each of the Depth
metrics, were tested for correlation if more than one was included in a model as a
significant predictor and were only included together if they were not correlated. If the
variables were correlated, only the most significant variable remained in the final model.
Results
The SST for the study region over this period ranged from 12.7° to 20.1° C, with a mean
of 16.2° C; overall averaged seasonal anomalies ranged from -1.5 to 1.1° C around the
mean (Fig. 3), while seasonal anomalies by grid section ranged from -3.8° to 3.4°. Years
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with a strong positive PDO (Index > 1) were 1983, 1987, 1993, 1997 and 2003, while a
strong negative PDO (Index < -1) occurred in 1999 and 2008 (Fig. 3). Strong positive
ENSO years were 1982-83, 1987-88, 1991-92, 1997-98 and 2002-03, while strong
negative ENSO years were 1988-89 and 1999-2000 (Fig. 3). No long-term trends in SST
are apparent in our data given the levels of seasonal and ENSO variation seen. However,
a linear regression of PDO anomaly data shows an overall negative trend in the last 30
years (R2 = 0.215, P = 0.009). This pattern is likely a result of the PDO regime switch in
the last decade (Hodgkins, 2009; Overland et al., 2008).
The best fit models are shown in Table 1, with values for explained deviance
ranging between 18% and 53.7% across species, while a summary of group sighting rates
is given in Table 2. Seven of the 9 models included quarter while 5 included the Year
variable, indicating both seasonal/intra-annual and inter-annual variation in the SPUE for
each species. Six models included the Survey Type variable, with the 1987-2004
CalCOFI cruises ranked lowest in sighting numbers while the SWFSC cruises had the
highest number of observations for most species. Four models included the seasonal SST
anomaly variable, and 6 models also included either the PDO or ENSO index,
demonstrating the importance of those temperature fluctuations on small cetacean
distribution. All models also included at least 1 depth metric, which has been shown to
be an important predictor variable (e.g., Becker, 2007).
Common dolphin - Three different models were used for common dolphins: short-beaked
commons (Dd), long-beaked commons (Dc), and Delphinus spp. (Dsp). The similarities
in the model results suggest that the Dsp data are likely dominated by Dd sightings.
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Common dolphins were associated with seasonal SST’s near or above the mean in the
Dsp and Dd models, with possible avoidance of extreme anomalies (Fig. 4). For all
common dolphin groups, most sightings occurred in the summer, and the fewest sightings
occurred in the spring. Year was included in the Dsp and Dc models; there was high
annual variability in sighting data in the Dsp model, while the Dc model showed a slight
increase in sightings across time. Depth was an important predictor of common dolphin
distribution in all three models, with Dc found almost exclusively inshore while Dd/Dsp
were found both inshore and offshore. The Dsp and Dd models also included PDO, and
while the response is fairly flat both showed a slight increase in sightings with negative
PDO anomalies.
Risso’s dolphin - Risso’s dolphins (Gg) were largely observed inshore, although they
were occasionally observed offshore (Fig. 5). Sightings peaked slightly during slightly
warmer seasonal SST’s and during the warm, California Countercurrent-dominated fall
quarter, while sightings occurred least frequently in the summer. ENSO was also
included in the model; however, while it was significant it was not a very strong
predictor.
Bottlenose dolphin - Bottlenose dolphin (Tt) groups tended to display a strong inshore
and island association. They were generally sighted over the continental shelf, although
they were occasionally observed more offshore (Fig. 5). While both the Year and PDO
variables were significant, neither were very strong predictors, although a slight increase
in sightings over time has occurred.
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Striped dolphin - Striped dolphins (Sc) are a tropical and warm-temperate species
associated with warm water masses and were predominantly observed offshore of the
2000-m depth contour (Fig. 5). Due to this strong offshore distribution, only 28 groups
were sighted during 22 cruises. This is in part due to the limitation of including only
sightings made in Beaufort sea state 3 or less; as most striped dolphin sightings occurred
offshore, many were made in higher sea states and were therefore not included. Due to
that exclusion, most sightings included for analysis came from later SWFSC (1991-2005)
cruise data, making Survey Type an important predictor variable.
Northern right whale dolphin - Northern right whale dolphins (Lb) are one of three cold
temperate species strongly associated with the California Current and therefore whose
extent into the southern California study region was expected to correlate with cold water
intrusions. Northern right whale dolphin groups demonstrated a strong slope association,
with most sightings located along the 2000-m depth contour (Fig. 6). Sightings peaked in
spring, when the California Current dominates the region and SST’s are coolest.
However, sightings were also associated with both cool and warm ENSO phases.
Dall’s porpoise - Dall’s porpoises (Pd), another cold temperate species, had peak
sightings during the fall and spring (Fig. 6), and were associated with both warm and cold
seasonal SST anomalies. They were distributed largely inshore, although with some
offshore presence as well. Year was also included as an ordinal variable; over the 30-year
study period, encounter rates first decreased and then increased.
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Pacific white-sided dolphin - As the final cool temperate water species whose sighting
rates were expected to increase in cooler temperatures, the Pacific white-sided dolphin
(Lo) results were unexpected. Although sightings peaked slightly during the spring
quarter when the water temperature is cooler, they also exhibited a bi-modal association
with ENSO and PDO indices (Fig. 6), with sightings peaking in moderately cool and
warm ENSO periods and in extreme PDO phases. This species was distributed largely
inshore. Finally, their encounter rate fluctuated over the years, with peaks in the early
1980’s and late 1990’s and a strong decline since 2000.
Discussion
Seasonal SST patterns – Patterns of encounter rate related to seasonal SSTs were largely
consistent with past studies within this region (e.g., Barlow, 1995; Barlow and Forney,
2007; Becker, 2007; Dohl et al., 1986; Forney, 2000; Forney and Barlow, 1998).
Consistent with our hypotheses, Risso’s, common, and striped dolphins preferred
intermediate and warmer water (Becker, 2007; Forney, 2000; Reeves et al., 2002), and
Dall’s porpoise, Pacific white-sided dolphins, and northern right whale dolphin sightings
peaked in the cool spring season (Becker, 2007). However, Dall’s porpoise sightings
peaked in warm and cool SSTs, corresponding with the peak in sightings in fall and
spring. This pattern may also be related to their distance offshore; in the fall the
California Current has been pushed offshore (Hickey, 1993), while in the spring the
current is closer to the coast, and so the increase in fall sightings may indicate Dall’s
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porpoises are tracking the California Current. Otherwise, the seasonal distribution
patterns here are consistent with those found by Forney and Barlow (1998) for temperate
species, although Forney and Barlow (1998) observed an increase in common dolphin
sightings in winter rather than summer. In contrast, a summer peak in sightings for
common dolphins was found by Dohl et al. (1986). Nevertheless, both of those findings
are supported by the results of this longer-term study. A strong El Niño occurred in 199192, which may explain the increase in winter sightings for short-beaked common
dolphins by Forney and Barlow (1998). In contrast, the 1975-78 surveys conducted by
Dohl et al. (1986) overlap with the 1976/77 PDO regime shift from cool to warm, which
could account for the increase in common dolphins during the warmer months. In
addition, long-beaked common, bottlenose, and Risso’s dolphins and Dall’s porpoise
demonstrated a preference for inshore and/or island-associated waters; short-beaked
common and Pacific white-sided dolphins were observed both in- and offshore; northern
right whale dolphins were associated with the slope; and striped dolphins were observed
only in deep offshore waters. While the relationship between SST and depth is complex
and difficult to separate, and these models are likely oversimplifying the observed trends,
these results support some habitat or resource partitioning as these small cetacean species
seasonally track preferred water conditions and prey.
ENSO and PDO patterns – Temperature fluctuation patterns like ENSO, PDO, and the
North Atlantic Oscillation (NAO) have been documented to affect the prey of marine
mammals. An example of this is the strong relationship between the NAO, the life cycle
of the copepod Calanus finmarchicus, and recruitment of larval cod (Gadus morhua) that
17
prey on copepods (Stenseth et al., 2002). Atlantic cod in turn are a major food source for
grey seals (Halichoerus grypus), while Calanus are an important North Atlantic right
whale (Eubalaena glacialis) prey (Mohn and Bowen, 1996; Wishner et al., 1995).
Calanoid copepods in the California Current have also demonstrated population-level
step changes in response to strong ENSO events and PDO shifts (Rebstock, 2002).
Population fluctuations of small pelagic fish such as anchovy (Engraulis spp.) and
sardine (Sardinops sagax) are strongly correlated with both ENSO and PDO indices
(Hubbs, 1948; Lehodey et al., 2006; Ñiquen and Bouchon, 2004; Tibby, 1937); these fish
species are prey for many species of cetaceans in the California Current (e.g., Heise,
1997; Osnes-Erie, 1999; Walker and Jones, 1993). Isolated occurrences have also been
noted of dolphins changing their distribution patterns after strong climatic events, such as
an expansion of the northern extent of the coastal bottlenose dolphin range along the
California coast during the 1982-83 El Niño (Defran et al., 1999). SST fluctuations have
been shown to impact the distribution and community composition of sea birds as well
(Hyrenbach and Veit 2003; Yen et al. 2006).
Most species’ models included the PDO and/or ENSO indices as significant
variables, although in most cases they were not strong predictors. An increase in
sightings occurred for Pacific white-sided dolphins during positive and negative PDO
anomalies, while bottlenose and common dolphins were associated with slightly negative
PDO anomalies. Pacific white-sided dolphins and northern right whale dolphins were
associated with both positive and negative ENSO indices, and Risso’s dolphins had an
almost flat but slightly positive ENSO function. During positive PDO and ENSO phases,
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upwelling waters are reduced and productivity decreases throughout the California
Current System, while water temperatures increase, particularly as warm equatorial
waters are pushed pole-ward and the California Current is found closer inshore
(McGowan, 1985; Sette and Isaacs, 1960). This may prompt some of the normally coolwater-associated species to further contract their ranges inshore and poleward in search of
prey, while warm-water species extend their ranges poleward as temperatures rise and
warm-water endemic prey expand their range (e. g. Forney and Barlow, 1998).
Implications for climate change - While this study demonstrates changes in distributions
of small cetaceans on scales of months to decades, with a limited understanding of the
mechanisms behind those changes, the model results may help create a basis for
understanding the potential impact of climate change upon these species. Studies of
climate change in the California Current have found that in addition to increasing
temperatures, a rise in CO2 levels is predicted to lead to more intense upwelling (Bakun,
1990; Snyder et al., 2003), stronger thermal stratification and a deepening of the
thermocline (Roemmich and McGowan, 1995), and alter large-scale circulation patterns
(Harley et al., 2006). Changes in these physical mechanisms will lead to changes in
ecosystem dynamics and biodiversity from primary producers to top predators (Harley et
al., 2006; Hooff and Peterson, 2006; Sydeman et al., 2001). For example, Keiper et al.
(2005) noted that in 1998 off central California, a local relaxation event occurred, with
high chlorophyll concentrations and retention of plankton and fish larvae. Coinciding
with these local conditions was the strong El Niño of 1998, which led to a deep
thermocline, a narrow, inshore distribution of sardine eggs, and an overall decrease in
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abundance of macrozooplankton. Our model results support other research that has
found that Dall’s porpoises and Pacific white-sided dolphins dominated the odontocete
species assemblage in the decade before this period, whereas during the El Niño,
sightings of Dall’s porpoises were greatly reduced, while common and Risso’s dolphin
sightings increased (Benson et al., 2002; Keiper et al., 2005). Our model results further
show Pacific white-sided dolphin sightings decreased after this period, while sightings of
common (particularly the long-beaked species) and bottlenose dolphins increased.
However, Dall’s porpoise sightings have also increased since the 1998 El Niño, and both
Pacific white-sided dolphin and northern right whale dolphin sightings have a bimodal
relationship with ENSO and/or PDO. Therefore, while the ranges of common dolphins,
Risso’s dolphins, and bottlenose dolphins are predicted to expand as ocean temperatures
warm, especially as seasonal and ENSO/PDO events are compounded, and Pacific whitesided dolphins, northern right whale dolphins, and Dall’s porpoise ranges are predicted to
contract poleward and inshore, our model results show a more complicated relationship
between distribution patterns and sea surface temperature than these straightforward
predictions suggest.
Globally, species associated with sea-ice and those with highly limited ranges are
the most obvious species to be affected by changing ocean temperatures and sea levels
(Moore and Huntington, 2008). However, even pelagic species such as those presented
here are likely to be affected (Learmonth et al., 2006; Simmonds and Eliott, 2009). For
example, as water temperatures off Scotland increased, the abundance of common
dolphins increased, while the number of white-beaked dolphins (Lagenorhynchus
20
albirostris) decreased, possibly indicating a poleward shift in range for both species
(MacLeod et al., 2005; Simmonds and Isaac, 2007).
Temperature shifts related to both global climate changes and regime shift
changes have also been linked to reproductive success in a number of marine mammals,
including North Atlantic right whales, humpback whales (Megaptera novaeangliae),
sperm whales (Physeter macrocephalus), dusky dolphins (Lagenorhynchus obscurus),
(Learmonth et al., 2006), and gray whales (Eschrichtius robustus) (Perryman et al.,
2002). Mass strandings of bottlenose dolphins in the Gulf of Mexico have been linked to
anomalous cold-water events (Carmichael et al., 2012; IWC, 1997). Indirect effects of
increasing temperature also include impacts on prey resources, leading not only to a shift
in prey availability, but increase the reliance on blubber reserves, which could mobilize
contaminants and lead to disruptions in immunization and reproductive systems
(Learmonth et al., 2006). Since the PDO regime was in a positive, warm phase for most
of the study period, and there were more strong positive ENSO events than strong
negative ones during this time, the occurrence patterns observed here may be predictive
of future patterns as the oceans continue to warm. Therefore some of these indirect
effects may already be occurring in these species, and continued monitoring efforts
should be made to ensure that changes in distribution or reproductive success are
documented.
Model considerations – The results presented here provide insight into long-term
distribution trends of small cetaceans and are both supported by and build upon the
21
current knowledge base for these species. Nonetheless, there are some caveats to this
study that should be acknowledged.
The PDO and ENSO indices were developed using broad regions of the Pacific
and may not precisely reflect the dynamics of the southern California study region. The
seasonal SST’s, while averaged for each grid section and quarter, are also still quite broad
and may not capture local variability in the form of fronts or eddies. In addition, the Year,
ENSO, and PDO variables have the potential to be correlated, as the indices are similar
over time and the Year variable could capture the same long-term trends. A correlation
analysis was conducted and some correlations between ENSO and PDO and between
seasonal SSTs and PDO were detected. However, when each of these variables was
excluded from models where they were both present, no change in the functional form of
the other was detected.
There was only 1 cruise per year prior to 1987, and so to tease apart Year effects
from Survey Type effects, we repeatedly re-ran each model while randomly dropping out
data from different years. The results demonstrated that the models were robust to
missing years of data and that the Year effect was real and separate from the Survey Type
effect. The apparent increasing yearly trend of long-beaked common dolphins could be a
result of the separation of common dolphin species in the southern California Bight
region in 1994 (Heyning and Perrin, 1994) and a subsequent increase in sightings
attributed to the long-beaked species.
The survey methods from each Survey Type were quite different, making it a
challenge to combine these datasets. However, by only using the group SPUE and by
limiting our sightings to those made in Beaufort sea state of 3 or less, we tried to make
22
the data as comparable as possible. The inclusion of the Survey Type variable in most
models is a reflection of some of those differences in survey effort. The 1987-2004
CalCOFI cruises consistently ranked lowest in sighting numbers for all species even
though those surveys had the most effort (except for the Dall’s porpoise model, which
had a high sighting rate during the period of the early CalCOFI cruises). This was likely
due to the use of a single observer on those cruises, covering both birds and mammals
with a smaller effective strip width, as compared to the multiple dedicated marine
mammal observers for the other two survey types. In contrast, the SWFSC cruises had the
highest number of observations for four of the six species while having the least amount
of effort. This may be due to the fact that these cruises were largely conducted during the
summer and fall when sighting conditions are optimal. In addition, big eye binoculars
were used on SWFSC but were not used regularly on CalCOFI cruises, and CalCOFI
surveys were always conducted in passing mode whereas SWFSC ships could deviate
from the transect line to confirm species.
Finally, we used the number of groups sighted rather than the number of
individuals observed as our metric of encounter rate and acknowledge that our models
could be misidentifying trends if group size changes in response to any of our
explanatory variables. However, an analysis of mean group size per season and year was
conducted and verified that no patterns existed that may have confounded our results.
Conclusions
23
The models presented in this study demonstrate that fluctuations in sea surface
temperature regimes do influence the distribution of small cetaceans, although the
relationships were not as straightforward as predicted, and it is likely that these
associations represents an effect on prey and a subsequent cetacean response. Dolphins
have previously been shown to be sensitive to changes in SST and to shift their
distributions in response to regime oscillations like ENSO. However, this is the first
study to model responses to multiple temperature shifts over a long time period for a
variety of species. The resulting models were unique to each species, indicating that each
demonstrates a distinct habitat occurrence pattern related to SST dynamics despite the
overlap in their overall distributions in the southern California study region. These results
can be used to begin to predict the future distribution of these small cetaceans throughout
southern California waters and as a tool to understand potential responses of these species
to rising ocean temperatures as global climate change intensifies.
24
Acknowledgments
We are grateful to SWFSC and CalCOFI for the use of their datasets, without which this
analysis could not have been conducted, and to all of the visual observers over the years
who gathered the data. Records of marine mammals on seasonal CalCOFI surveys was
collected and maintained by Farallon Institute (2007-present), PRBO Conservation
Science (2000-2006), and Scripps Institution of Oceanography (1987-present). Funding
for marine mammal observations during CalCOFI cruises was provided by the Chief of
Naval Operations N45, for which we thank F. Stone and E. Young. WJS thanks the
National Science Foundation (CCE-LTER) and NOAA-Integrated Ocean Observing
System via the Southern California Coastal Ocean Observing System (SCCOOS) for
recent support, R. Veit and J. McGowan for the vision to initiate the project in the 1980s,
D. Hyrenbach for sustaining the project through the 1990s. Thanks also to Nate Mantua
and Steven Hare for permission to use their PDO Index and to NOAA for permission to
use their ENSO Index. Thanks to M. Ferguson, E. Archer, J. Moore, and E. Becker for
assistance with the modeling, and to M. Kahru for help with the satellite sea surface
temperature data and WIM.
25
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35
Table 1 –The final best-fit models are presented here along with the REML score,
explained deviance, and residual degrees of freedom (DF) for each model. Dd: D.
delphis; Dc: D. capensis; Dsp: Delphinus sp.; Gg: Grampus griseus; Lb: Lissodelphis
borealis; Lo: Lagenorhynchus obliquidens; Pd: Phocoenoides dalli; Sc: Stenella
coeruleoalba; Tt: Tursiops truncatus.
Species
Final Model
REML
Expl.
Dev.
Residual
DF
Dd
Quarter + DepthMean + PDO + SeasAnom
724.5
18%
642
Dc
Quarter + Year + DepthMax
185.9
53.7%
652
Dsp
Quarter + Year + DepthMean + PDO + SeasAnom
2538.4 25.7%
2415
Gg
Quarter + SurveyType + DepthSD + DepthMean +
ENSO + SeasAnom
611.1
32.8%
2421
Lb
Quarter + SurveyType + DepthMean + ENSO
256.6
28%
2428
Lo
Quarter + SurveyType + Year + DepthMean + ENSO +
PDO
642.2
26.3%
2419
Pd
Quarter + SurveyType + Year + DepthMean +
SeasAnom
671.3
29.7%
2423
Sc
SurveyType + DepthMean
85.5
35.9%
2437
Tt
SurveyType + Year + DepthSD + DepthMean + PDO
334.2
47.0%
2429
36
Table 2 – Summary of group encounter rates for each species, including the number of
cruises in which each species was encountered, and the total number of groups
sighted.
Species
Dd
Number of
Cruises
29
Number of
Groups
387
Dc
22
93
Dsp
105
1537
Gg
74
227
Lb
32
71
Lo
62
217
Pd
64
240
Sc
22
28
Tt
50
180
37
Figures
Figure 1 – The Southern California study area, located in the Eastern North Pacific
Ocean, south of Point Conception and incorporating the Channel Islands. 500-m depth
contours are plotted. The blue area (mean depth < 1100 m, maximum depth < 2000 m)
was considered the inshore and island region; the green area (mean depth 1000-3200 m,
depth range 500-3500 m) was considered the slope region; the yellow area (mean depth >
3500 m, maximum depth > 4000 m) was considered the offshore region.
Figure 2 – Transect lines surveyed for all studies. CalCOFI surveys from 1987 through
2004 are in orange, CalCOFI surveys from 2004 through 2009 are in green, and all
SWFSC surveys are in purple. Black lines indicate latitude and longitude in 1 degree
increments, used to create the grid sections utilized in the GAM analysis.
Figure 3 - ENSO and PDO SST anomalies from 1979-2009, and seasonal SST anomalies
from southern California waters from 1981 to 2009. PDO SST anomalies were calculated
relative to data from 1900-2009, while ENSO anomalies were calculated using a three
month running mean from 1950-2009. Seasonal SST anomalies were calculated using
AVHRR data and averaged per quarter.
Figure 4 – GAM functions of short-beaked (Delphinus delphis - Dd) and long-beaked
(Delphinus capensis - Dc) common dolphin SPUE from 1991 to 2005 for SWFSC cruises
and from 2004-2009 for CalCOFI cruises, and of all common dolphins (Delphinus spp. Dsp) from 1979 to 2009. Estimated degrees of freedom of the smooth function are given
(in parentheses on the y-axis) for all included variables from the best fit model. Solid
lines represent the marginal effect of the given variable after controlling for the other
variables in the model. Dashed lines are bands of two standard errors.
Figure 5 – GAM functions of Risso’s dolphin (Grampus griseus - Gg), bottlenose
dolphin (Tursiops truncatus - Tt), and striped dolphin (Stenella coeruleoalba - Sc) SPUE
from 1979 to 2009 in relation to SST indices and depth variables for the best models.
Estimated degrees of freedom of the smooth are given (in parentheses on the y-axis) for
all included variables. Solid lines represent the marginal effect of the given variable after
controlling for the other variables in the model. Dashed lines are bands of two standard
errors.
Figure 6 – GAM functions of northern right whale dolphin (Lissodelphis borealis - Lb),
Dall’s porpoise (Phocoenoides dalli - Pd), and Pacific white-sided dolphin
(Lagenorhynchus obliquidens – Lo) sightings from 1979 to 2009 in relation to SST
indices and depth variables for the best models. Estimated degrees of freedom of the
smooth are given (in parentheses on the y-axis) for all included variables. Solid lines
represent the marginal effect of the given variable after controlling for the other variables
in the model. Dashed lines are bands of two standard errors.
38
Appendix I – Search effort (linear km) and number of groups seen for each species on
each of the surveys included in this analysis. El Niño cruises were combined into seasons
for analysis. Seasons are defined as follows: spring: February-April; summer: May-July;
fall: August-October; winter: November-January.
CalCOFI
Cruise
CC198705
CC198709
CC198711
CC198801
CC198804
CC198808
CC198810
CC198901
CC198904
CC198907
CC198911
CC199003
CC199004
CC199007
CC199011
CC199101
CC199103
CC199107
CC199109
CC199201
CC199204
CC199207
CC199209
CC199301
CC199303
CC199308
CC199310
CC199401
CC199403
CC199410
CC199501
CC199504
CC199507
CC199510
CC199604
CC199608
CC199610
CC199701
CC199707
CC199709
CC199712
Year
1987
1987
1987
1988
1988
1988
1988
1989
1989
1989
1989
1990
1990
1990
1990
1991
1991
1991
1991
1992
1992
1992
1992
1993
1993
1993
1993
1994
1994
1994
1995
1995
1995
1995
1996
1996
1996
1997
1997
1997
1997
Quarter
Spring
Summer
Fall
Winter
Spring
Summer
Fall
Winter
Spring
Summer
Fall
Winter
Spring
Summer
Fall
Winter
Spring
Summer
Fall
Winter
Spring
Summer
Fall
Winter
Spring
Summer
Fall
Winter
Spring
fall
Winter
Spring
Summer
Fall
Spring
Summer
Fall
Winter
Summer
Fall
El Niño 1
Dsp Gg Lb Lo Pd Sc Tt
5
1
0
0
4
0
3
9
4
0
5
0
0
3
3
1
0
1
2
0
3
3
2
0
2
3
0
3
3
1
4
0
0
0
3
15
0
0
0
3
0
3
3
7
0
0
9
0
3
2
0
1
0
2
0
3
1
0
0
3
7
0
3
25
3
1
1
1
0
3
11
4
1
1
4
0
3
1
0
1
0
1
0
3
13
0
0
5
3
1
3
18
2
0
0
1
0
3
5
3
0
1
4
0
3
3
1
0
1
3
0
3
7
2
0
1
5
0
3
28
0
0
2
0
0
3
12
2
0
0
0
0
3
5
1
2
3
1
0
3
5
2
0
1
2
0
3
18
1
1
2
1
0
3
5
0
0
0
2
0
3
10
1
0
1
1
0
3
9
2
0
0
0
0
0
9
0
0
0
0
0
0
2
1
0
0
2
0
0
12
2
2
0
4
0
1
2
0
0
0
0
0
0
15
6
0
2
0
0
2
15
2
0
0
1
0
0
12
2
0
0
2
0
0
26
1
0
2
1
0
0
9
1
0
1
0
0
0
6
1
0
0
1
0
1
8
0
0
3
0
0
0
4
0
0
0
0
0
0
7
8
1
5
3
0
0
25
3
0
0
1
0
2
9
1
0
2
0
0
1
2
3
0
0
0
0
0
Dd
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
Dc
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
Effort
(km)
1559
1704
1468
1501
1346
1810
1420
1338
1596
1932
1496
407
1509
1887
1349
1332
1162
1668
1635
1265
2427
1437
1625
1249
1630
1843
1549
1369
1552
1590
1331
1629
1900
1589
1214
1729
1434
1442
1724
1511
361
39
CC199801
CC199803
CC199804
CC199805
CC199806
CC199807
CC199809
CC199810
CC199904
CC199908
CC199910
CC200004
CC200007
CC200010
CC200101
CC200104
CC200107
CC200110
CC200201
CC200203
CC200207
CC200211
CC200301
CC200304
CC200307
CC200310
CC200401
CC200403
CC200407
CC200411
CC200501
CC200504
CC200507
CC200511
CC200602
CC200604
CC200607
CC200610
CC200707
CC200711
CC200701
CC200704
CC200801
CC200803
CC200808
CC200810
CC200901
CC200903
CC200907
CC200911
1998
1998
1998
1998
1998
1998
1998
1998
1999
1999
1999
2000
2000
2000
2001
2001
2001
2001
2002
2002
2002
2002
2003
2003
2003
2003
2004
2004
2004
2004
2005
2005
2005
2005
2006
2006
2006
2006
2007
2007
2007
2007
2008
2008
2008
2008
2009
2009
2009
2009
Winter
El Niño 2
Spring
El Niño 3
El Niño 4
Summer
Fall
El Niño 5
Spring
Summer
Fall
Spring
Summer
Fall
Winter
Spring
Summer
Fall
Winter
Spring
Summer
Fall
Winter
Spring
Summer
Fall
Winter
Spring
Summer
Fall
Winter
Spring
Summer
Fall
Winter
Spring
Summer
Fall
Winter
Spring
Summer
Fall
Winter
Spring
Summer
Fall
Winter
Spring
Summer
Fall
10
6
13
14
14
25
9
21
9
33
17
9
9
9
7
5
16
25
7
6
23
7
14
6
16
12
16
13
21
19
16
7
64
32
4
6
53
17
42
22
20
9
15
19
31
30
30
14
34
12
1
2
1
0
1
0
1
0
1
2
1
0
0
0
2
2
0
3
4
0
1
0
2
3
4
0
1
6
2
2
2
4
0
5
0
3
0
0
7
0
1
4
4
2
1
2
1
0
7
2
0
0
0
0
1
0
0
0
3
0
0
0
0
2
0
1
0
0
3
0
0
0
0
1
1
0
0
3
0
0
1
6
0
1
0
2
0
1
0
2
0
1
1
2
0
0
0
0
0
1
0
4
2
1
2
1
0
1
3
0
0
3
10
4
1
1
0
5
0
5
2
0
1
7
0
0
0
7
6
6
4
13
3
1
4
3
0
3
1
2
1
2
5
6
1
2
0
0
0
1
0
1
0
1
0
0
0
0
1
0
1
5
1
1
1
2
0
0
3
4
2
0
2
12
1
0
4
14
1
0
3
4
0
1
0
8
0
1
0
1
7
9
4
22
0
0
13
2
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
1
0
0
1
1
2
1
1
0
0
0
1
0
2
3
2
0
0
0
0
1
0
4
0
0
0
0
0
5
0
0
2
0
2
0
1
7
3
0
4
0
1
0
2
0
2
6
1
4
1
7
0
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
16
8
11
0
16
10
6
1
41
11
14
12
14
2
8
13
10
21
18
5
9
6
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
0
8
1
4
18
7
4
1
3
2
10
0
0
1
0
2
3
1
3
4
9
1
696
701
1491
818
812
1652
1499
1308
1633
1457
1212
1667
1754
1425
1434
1428
1547
1322
1172
1454
1741
1443
1712
3503
1680
1542
1380
2301
2003
1552
1376
2024
2264
1357
1292
2070
1964
1731
2180
1630
1454
900
1264
1182
1224
1505
1273
707
931
713
40
SWFSC
Cruise Name
Year
Duration
Dsp
Gg
Lb
Lo
Pd
Sc
Tt
Dd
Dc
564
646
798
674
905
CAMMS
PODS
ORCAWALE
1979
1980
1982
1983
1984
1991
1993
1996
Sept-Oct
June-July
April
Dec
Dec
July-Oct
July-Oct
Aug-Nov
17
8
16
19
42
50
23
30
8
0
15
7
13
8
3
6
1
0
11
0
1
10
0
1
1
0
8
18
10
0
0
9
2
2
16
4
3
0
0
0
1
0
0
0
0
6
4
6
3
3
3
3
3
3
1
4
NA
NA
NA
NA
NA
45
21
24
NA
NA
NA
NA
NA
2
0
2
ORCAWALE
CSCAPE
2001
2005
July-Dec
Aug-Dec
20
42
7
2
0
0
2
0
0
6
1
5
7
4
16
29
1
6
Effort
(km)
1662
2045
1842
562
1179
4210
2610
3936
2540
2951