Effects of fluctuations in sea-surface temperature on the occurrence of small cetaceans off Southern California.
Cetaceans are higher-trophic-level marine predators whose movement patterns and habitat preferences are typically related to the distribution of their prey (Wishner et al., 1995; Gowans et al. 2007). Unlike baleen whales, small cetaceans (porpoises, dolphins, and small-toothed whales) generally do not undertake oceanscale annual migrations to track prey or to move between breeding and feeding grounds. Rather, small cetaceans may display a high degree of site fidelity, or they may move seasonally inshore and offshore or along regional-scale coastlines (Leatherwood et al., 1984; Dohl et al., 1986; Shane et al., 1986; Forney and Barlow, 1998).
Although many small cetacean species may overlap in any one region of their total range, they 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 (Reilly, 1990; Forney, 2000; Ballance et al., 2006; MacLeod et al., 2008). Habitat preferences likely reflect differences in preferred prey. Dolphins may follow prey habitats as they shift not only seasonally but through large-scale climate-driven changes such as the El Nino-Southern Oscillation (ENSO) or the Pacific Decadal Oscillation (PDO) (Shane, 1995; Defran, 1999; Benson et al., 2002; Ballance et al., 2006).
We examined the distribution and relative abundance of multiple species of small cetaceans across shifting temperature regimes off Southern California by using a unique coupled cetaceanoceanographic long-term data set. This data set enables a rare opportunity to assess interdecadal changes in cetacean distribution over a broad spatial extent. The co-occurrence of cold- and warm-water cetacean species makes this location an ideal one at which to examine potential effects of climate variation on regional distribution patterns at different temporal scales (intraannual, annual, and decadal).
The Southern California region represents the convergence of warm- and cold-water masses and supports populations of both warm- and cold-water, small cetacean species (Forney and Barlow, 1998). During the summer, the cold, equatorward flowing California Current system has a seasonal maximum (7.8 Sverdrups [Sv], ~7.8 million [m.sup.3] [s.sup.-1]). The California Current turns shoreward (poleward) at approximately 32[degrees]N and becomes the California Countercurrent. The California Countercurrent and California Undercurrent also have a seasonal maximum in late s--ummer and into the fall and, therefore, dominate the Southern California Bight, with a combined maximum transport in October of 1.8 Sv. The California Undercurrent reaches its minimum (0.8 Sv) and turns equatorward in the spring. The California Countercurrent turns equatorward then as well; therefore, all flow through the Southern California region becomes equatorward in the spring, allowing the California Current to dominate and transport cooler water farther south (Hickey, 1993; Hickey et al., 2003).
In the California Current system, strong El Nino years in the positive ENSO phase have been linked to increased downwelling, warmer SSTs, and a deepening of the thermocline observed off Southern California (Sette and Isaacs, 1960; McGowan, 1985; Caldeira et al., 2005). During the warm, positive phase of the PDO, the California Current is weakened and the Countercurrent is strengthened. This intensified current brings warmer waters farther north and west into and beyond the Southern California region, creating warm SST anomalies along the California coast. In contrast, during the cool, negative 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, before our study, and a shift back to a cool PDO may have occurred during the last decade starting in 1998-99 (Peterson and Schwing, 2003; Zhang and McPhaden, 2006; Wang et al., 2010).
Two long-term sets of ship-based surveys have been conducted in Southern California waters, making it an ideal region for this investigation. The California Cooperative Oceanic Fisheries Investigations (CalCOFI) has been conducting quarterly cruises that have sampled a breadth of oceanographic and lower-trophic-level biological data since 1949. Marine bird and mammal observations were added in 1987 (Hyrenbach and Veit, 2003; Sydeman, et al., in press). The NOAA Southwest Fisheries Science Center (SWFSC) also regularly has conducted marine mammal abundance surveys that have included this region since 1979.
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 higher-level organisms, such as fishes, seabirds, and marine mammals (Tibby, 1937; Hubbs, 1948; McGowan, 1985; McGowan et al., 2003; Sydeman et al., in press). It follows that small cetacean populations would respond to such variations in SST, likely as a response to changes in prey populations, as has been shown for seabirds (Hyrenbach and Veit, 2003). In addition, population-level responses to these fluctuations in temperature may predict 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 averages and anomaly indices as a proxy for environmental variation on 3 temporal scales: seasonal (yearly), ENSO (2-7 years) and PDO (~30 years). We predicted that patterns in small cetacean occurrence and distribution within Southern California waters would follow similar trends reported for seabirds (Hyrenbach and Veit, 2003; Yen et al., 2006; Sydeman et al., in press) and other cetaceans (Forney and Barlow, 1998; Becker et al., 2012). For small cetaceans off Southern California, the following trends were predicted: 1) species assemblages will differ depending on the dominant SST regime, 2) cold-water-associated species will be more abundant and broadly distributed when cold-water conditions prevail, 3) warm-water-associated species will dominate during warm-water conditions, and 4) the latter 2 patterns will be compounded when SST fluctuations co-occur on multiple scales.
Materials and methods
Study area and survey methods
Our study area was situated between 117[degrees]W and 125[degrees]W longitude and from 30[degrees]N to 35[degrees]N latitude (Fig. 1) and includes the Southern California Bight as well as deeper offshore waters. 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 of >3500 m. Three regions, associated with depth, were defined in the analyses for this study (Fig. 1): 1) the inshore and island region (with a mean depth <1100 m and a maximum depth <2000 m; 2) the slope region (with a mean depth of 1000-3200 m and a depth range of 500-3500 m); and the offshore region (with a mean depth >3500 m and a maximum depth >4000 m). The terms for these three regions will be used throughout the study.
We analyzed data from visual sightings of marine mammals from 105 separate survey cruises conducted by both CalCOFI and SWFSC from 1979 to 2009 (Fig. 2). During CalCOFI cruises from May 1987 to April 2004 (CalCOFIa) marine mammals were recorded as part of standardized CalCOFI top predator surveys that were focused primarily on marine birds. The strip-transect methods of Tasker et al. (1984) were followed. Observations were made with the naked eye by a single observer stationed on one side of the flying bridge or outside the main bridge. Marine mammals were recorded only if they occurred within the 300-m strip transect used for birds or within 1000 m of the vessel for large cetaceans. Each CalCOFI transect line extended from directly in front of the ship to 90[degrees] on the observation side. Group sightings of marine birds and mammals were summarized into 3-km bins, with the latitude and longitude determined for the centroid of each bin. Additional details of field methods are provided in Veit et al. (1996; 1997), Hyrenbach and Veit (2003), and Yen et al. (2006).
In July 2004, 2 dedicated marine mammal visual observers were added to the CalCOFI cruises (CalCO-FIb), and a standard line-transect protocol replaced the strip-transect protocol (Burnham et al., 1980; Buckland et al., 2001). A complete description of survey methods can be found in Soldevilla et al. (2006). Each observer monitored a 90[degrees] field of view from bow to abeam, one on each side of the ship, and alternated between scanning with Fujinon (1) 7x50 binoculars (Fujifilm Corp., Tokyo) and with the naked eye. Survey effort was calculated on the basis of latitude and longitude at the start and end of each trackline.
For all CalCOFI surveys, observations were made on daytime tracklines between stations, and no visual observation effort was conducted while the vessel was stationary. All visual effort was conducted in sea state conditions rated 5 or less on the Beaufort scale. Data used for analyses were generally from 4 surveys per year from 1987 to 2009, 1 survey per season (typically in the same month but with some variation). In 5 of these years, only 3 surveys were conducted. In 1998, surveys were carried out monthly to capture a time series of oceanographic measures in a strong El Nino year. However, to be consistent across all years for purposes of analysis, these cruise data were combined into 4 quarters (winter, spring, summer, and fall; see the next section, Environmental data, for details). A full summary of surveys, along with total effort (in kilometers) and sightings per year for all species is provided in Appendix I.
Data for analyses also came from 10 different SWFSC cruises, conducted primarily in the summer and fall (from July through November) from 1979 through 2005 and covering an area that included Southern California waters (Appendix I). For SWFSC cruises, standard line-transect protocols were followed, as described in Barlow and Forney (2007) and Kinzey et al. (2) The latter cruises had 3 observers on the flying bridge, 2 of whom used "big eye" 25 x 150 binoculars to scan 90[degrees] from bow to abeam on either side of the flying bridge. The third observer monitored the entire forward 180[degrees] with 7x50 binoculars and the naked eye. Survey effort (in kilometers) was calculated either from the latitude and longitude positions at the start and end of each trackline (1979-84 surveys) or from latitude and longitude positions recorded approximately every 10 min along the track (1991-2005 surveys).
Eight species of small cetaceans were examined in this analysis. The 3 warm-temperate and tropical species were short-beaked common dolphin (Delphinus delphis), long-beaked common dolphin (D. capensis), and striped dolphin (Stenella coeruleoalba). The 3 coldtemperate species were Pacific white-sided dolphin (Lagenorhynchus obliquidens), northern right whale dolphin (Lissodelphis borealis), and Dali's porpoise (Phocoenoides dalli). The remaining 2 species were considered cosmopolitan, distributed globally in tropical and temperate waters: Risso's dolphin (Grampus griseus) and bottlenose dolphin (Tursiops truncatus) (Reeves et al., 2002).
All bottlenose dolphin sightings in this study were presumed to be offshore animals because most coastal animals remain within about 1 km from the shore (Hanson and Defran, 1993) and surveys were conducted at least 5-10 km from the coast. In addition to their individual species' models, short- and long-beaked common dolphins were combined into an additional Delphinus species category because the 2 species were not recognized formally as distinct until 1994 (Heyning and Perrin, 1994). Furthermore, they were not distinguished on SWFSC cruises before 1991 or on CalCOFI cruises before August 2004. Therefore, the data sets for long-beaked and short-beaked common dolphin are smaller than the data sets for all other species, and the data set for Delphinus spp. consists of all combined common dolphin sightings from all cruises.
Three variables were used to represent variations in SST on different temporal scales: quarterly SST averages, ENSO indices, and PDO indices. Monthly averaged SST data from 1985 to 2009 were from NOAA Advanced Very High Resolution Radiometer (AVHRR) Pathfinder satellite data, which have a spatial resolution of ~4.1-km (http://www.nodc.noaa.gov/SatelliteData/pathfinder4km). For 1981-84, NOAA AVHRR data (multichannel averaged SST with a 5.7-km resolution) were also used. No satellite data were available before 1981; therefore, a missing data filter and a single imputation method were used to create values for 1979 and 1980 with the mean of the SSTs for the other years (Hastie, 1991; Nakagawa et al., 2001).
With Windows Image Manager, vers. 6 (WimSoft, San Diego, CA), seasonal SST averages were calculated from the monthly SST data. These SST averages were estimated for each quarter and each grid cell (see the following paragraph) for the period 1979-2009 (spring: February-April; summer: May-July; fall: August-October; winter: November-January). NOAA ENSO anomaly data, derived from the Oceanic Nino Index as a 3-month running mean of SST anomalies from 1971 to 2009 in the Nino 3.4 region (http://www.cpc.ncep. noaa.gov/products/analysis_monitoring/ensostuff/ ensoyears.shtml), were used as a proxy for ENSO for 1979-2009. The Nino 3.4 region is centered on the equator; therefore, the index indicates the relative strength of the ENSO event rather than SST anomaly values for Southern California waters. PDO anomaly data, averaged for the period from 1900 to 2009, from the University of Washington (http://jisao.Washington. edu/pdo) were used as a proxy for the PDO regime from 1979 to 2009. The PDO index is derived from a monthly averaged SST for North Pacific waters poleward of 20[degrees]N.
Depth data were taken from the NOAA National Geophysical Data Center's ET0P02 2-min global relief database (http://www.ngdc.noaa.gov/mgg/ fliers/06mgg01.html). The study area was divided into 52 grid cells of Io (111 km or 60 nmi) latitude by 1[degrees] longitude, leading to grid cell areas that ranged from 2940 to 3120 km2. The gridded depth data were then assigned to each of the grid cells, and minimum, maximum, and mean depth values were calculated for each grid cell, along with the maximum seafloor slope per cell. These large grid cells correspond to approximately one day of effort for each of the surveys and were designed to be large enough to smooth out the mesoscale features that occur on shorter temporal and spatial scales than were of interest here. Although mesoscale features, such as fronts or eddies, are often observed to be hotspots for marine mammals, the multidecadal data set used in our study allowed for a synoptic examination of changing distribution patterns throughout the study area.
Modeling cetacean sighting rates
Generalized additive models (GAMs) of species sighting rates as a function of the temperature data and depth values were created with the mixed GAM computational vehicle (mgcv) package in R software, vers. 2.14.2 (R Core Team, 2012) (Hastie and Tibshirani, 1990; Wood, 2006). GAMs use a link function to relate the predictor variables to the mean of the response variable. GAMs also allow nonparametric functions to be fitted to the predictor variables through the use of a smoothing function to describe the relationship between the predictor and the response variables (Hastie and Tibshirani, 1990).
For model development, the grid cells described previously were used as data units, and all effort, sighting, and seasonal SST data were calculated for each cell. This approach allowed for the normalization of spatial and temporal differences in survey data. The type of survey was included as a categorical variable to account for differences in sighting rates due to survey method and platform. For example, because many vessels of different heights were used and heights for some vessels were not reported, standardization of observations for platform heights was not possible. Survey types included SWFSC (1979-2005), CalCOFIa (1987-2004), and CalCOFIb (2004-09). For each survey type, the number of group sightings of each species within each 1[degrees] cell, standardized by the log of the amount of effort per cruise (in kilometers), was modeled by assuming a Poisson distribution with a log link function.
Potential predictor variables in the model were the following: seasonal SST averages of each grid section (SeasAv); ENSO index (ENSO); PDO index (PDO); the mean (DepthMean), minimum (DepthMin), and maximum (DepthMax) depth (in meters) for each grid section; the maximum slope for each grid section (Slope); and the quarter (Quarter) as a categorical variable for identification of interannual patterns. Although sea state has been shown to be an important predictor of sighting rates in other cetacean habitat and trend models (Becker, 2007), the condition of the sea surface was not recorded in early CalCOFI observations and, therefore, sea state was not included in this analysis. Instead, only data recorded when the sea state was rated 0-3 on the Beaufort scale during SWFSC cruises and later CalCOFI cruises were used to standardize for differences in survey effort and, thus, make the different platforms as comparable as possible.
We used the number of group sightings, rather than the number of individuals, as our measure of relative encounter rate, essentially creating encounter rate models of group sightings per unit (kilometer) of survey effort (SPUE) (Bordino et al., 1999; Stockin, 2008). A correlation analysis of annual rates of group sightings in relation to mean group size per year also was conducted to determine whether group size correlated with the number of groups encountered.
To select predictor variables for inclusion in each model, a likelihood-based smoothness selection method, instead of a traditional stepwise method, was applied with the restricted maximum likelihood (REML) criterion (Patterson and Thompson, 1971; Wood, 2006). Each predictor variable was tested for inclusion in the model with a tensor product approach coupled with a smoothing function defined by a cubic regression spline with shrinkage. The best model was selected on the basis of a combination of the information-theoretic 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 nonsignificant 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 the explained deviance and that included only significant predictor variables. In addition, the ENSO, PDO, and seasonal SST averages, as well as each of the depth metrics, were tested for correlation if more than one of them was included in a model as a significant predictor. These variables were then included together only if they were not correlated. If the variables were correlated, then only the most significant variable remained in the final model.
Sea-surface temperature for the study area over the period 1979-2009 ranged from 12.7[degrees]C to 19.4[degrees]C, with a mean of 16.2[degrees]C. Overall averaged seasonal anomalies ranged from -1.5[degrees]C to 1.1[degrees]C around the mean (Fig. 3). In comparison, seasonal anomalies by grid section ranged from -3.8[degrees]C to 3.4[degrees]C. Years with a strong positive PDO (index>1) were 1983, 1987, 1993, 1997, and 2003, and 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, and strong negative ENSO years were 1988-89 and 1999-2000 (Fig. 3). No long-term trends in SST were apparent in our data given the levels of seasonal and ENSO variation observed. However, a linear regression of PDO anomaly data shows an overall negative trend in the last 30 years: coefficient of multiple determination ([R.sup.2])=0.215, P=0.009. This pattern is likely a result of the PDO regime switch in the last decade (Overland et al., 2008; Hodgkins, 2009).
The correlation analysis revealed that annual sighting rates and mean group size were not correlated for any of the species examined. This finding indicates that, although species may be encountered with varying frequency across years, the number of individual animals per group does not change in a correlated way. For example, if more groups of a given species were encountered in a year, the group size would not necessarily also increase or decrease.
The best-fit models are shown in Table 1. Values for explained deviance ranged between 21.2% and 57.4% across species. A summary of group sighting rates is given in Table 2. Six of the 9 models included the Quarter variable, indicating intra-annual variation in the SPUE for each species. Of the 9 models, 7 models included the SurveyType variable; the 1987-2004 CalCOFI cruises ranked lowest and the SWFSC cruises ranked highest in sighting numbers for most species. Of the 9 models, 6 models included the seasonal SST average variable, and 7 models also included either the PDO or ENSO index. The latter results indicate the importance of those temperature fluctuations on small cetacean distribution. All models also included at least one depth metric, previously shown to be an important predictor variable for Southern California cetaceans (e.g., Becker, 2007). Finally, 5 of the 9 models included slope as a predictor.
Three different models were used for common dolphins: both species of common dolphin in a single combined category, short-beaked common dolphin, and long-beaked common dolphin. The similarities in the model results for both common dolphins and the short-beaked common dolphin indicate that the data for the combined category likely are dominated by sightings of short-beaked common dolphins. Common dolphins were associated with seasonal SSTs of about 14-18[degrees]C in all 3 models, indicating possible avoidance of extremely warm or cold temperatures (Fig. 4). For all common dolphin groups, most sightings occurred in the summer and fall, and generally the fewest sightings occurred in the spring. Depth was an important predictor of common dolphin distribution in all 3 models, and slope was included in the models for the combined category and the short-beaked common dolphin. Long-beaked common dolphins were found almost exclusively inshore, and sightings of short-beaked common dolphins and dolphins in the combined group were recorded both inshore and offshore in areas with shallow slopes. The model for both common dolphins combined showed a very slight increase in sightings with negative PDO anomalies, although the overall response was fairly flat (Fig. 4).
Risso's dolphins were largely observed inshore, although they were occasionally observed offshore and in areas of shallow depths and steep slope, as shown in the partial residuals plots for depth and slope (Fig. 5). Sightings peaked slightly during warmer seasonal SSTs, around 18[degrees]C, but occurred least frequently in the summer. ENSO also was included in the model and indicated slightly more sightings during positive ENSO phases.
Striped dolphins are a tropical and warm-temperate species associated with warm water masses, and dolphins of this species were predominantly observed offshore of the 2000-m depth contour with a deep minimum depth (Fig. 5). Because of this strong offshore distribution, only 28 groups were sighted during 22 cruises. This low number of sightings is in part due to the limitation of including only sightings made in sea states rated 3 or less on the Beaufort scale; because most striped dolphin sightings occurred offshore, many were made in higher-rated sea states and were, therefore, not included. Because of that exclusion, most sightings included for analyses came from data collect ed during later SWFSC (1991-2005) cruises, making Survey Type an important predictor variable.
Bottlenose dolphin groups tended to display a strong inshore and island association. They generally were sighted over the continental shelf, although they were occasionally observed farther offshore, as shown in the depth residuals plots (Fig. 5). The PDO variable was significant, indicating that a slight increase in sightings occurred with negative PDO anomalies.
Northern right whale dolphin
Northern right whale dolphin is 1 of 3 cold-temperate species strongly associated with the California Current system. Therefore, the extent of this species into the Southern California study area was expected to correlate with cold-water intrusions. Sightings were associated with cool SSTs as expected. However, sightings were associated also with both positive and negative ENSO anomalies. Groups of northern right whale dolphins showed a strong association with the slope region, with most sightings located at depths between 2000 and 4000 m, as shown in the depth residuals plot (Fig. 6).
Sightings of Dali's porpoise, another cold-temperate species, peaked during the spring, fall, and winter (Fig. 6), and groups of Dali's porpoises were associated with cool SSTs. However, they were associated with slightly positive PDO phases, as well. They were distributed inshore and offshore, in areas of slightly shallower slopes, as shown in the depth and slope residuals plots.
Pacific white-sided dolphin
Results were unexpected for Pacific white-sided dolphin, the final cold-temperate species the sighting rates of which were anticipated to increase in cooler temperatures. Sightings peaked slightly during the spring quarter when the water temperature was cooler. However, they also exhibited an association with slightly positive PDO indices (Fig. 6). This species was distributed largely inshore, as shown in the depth residuals plot.
Patterns of seasonal sea-surface temperatures
Patterns of encounter rate related to seasonal SSTs were largely consistent with past studies within this region (e.g., Dohl et al., 1986; Barlow, 1995; Forney and Barlow, 1998; Forney, 2000; Barlow and Forney, 2007; Becker, 2007). Risso's and common dolphins preferred waters of intermediate and warmer temperature (14-20[degrees]C) (Forney, 2000; Reeves et al., 2002; Becker, 2007). In contrast, sightings of Dali's porpoises, Pacific white-sided dolphins, and northern right whale dolphins peaked in the cool spring season or with cool SSTs. In addition, long-beaked common, bottlenose, and Risso's dolphins and Dali's porpoises showed a preference for inshore or island-associated waters. Short-beaked common and Pacific white-sided dolphins were observed both inshore and slightly offshore. Northern right whale dolphins were associated with the slope region, and striped dolphins were observed only in deep offshore waters. The relationship between SST and depth is complex and difficult to separate, and these models likely oversimplify the observed trends. However, these results do seem to indicate some habitat or resource partitioning is occurring because these small cetacean species presumably follow preferred water conditions and prey.
Although the seasonal distribution patterns here are generally consistent with those found by Forney and Barlow (1998) for temperate species, an increase in common dolphin sightings was observed in that study in winter rather than in summer for 1991-92. In contrast, a summer peak in sightings for common dolphins was found by Dohl et al. (1986). Our results, however, support the findings of both of these studies. ENSO was included as a predictor in the model for the long-beaked common dolphin. The strong El Nino that occurred in 1991-92 may explain the increase in winter sightings for common dolphins in the surveys conducted by Forney and Barlow (1998) over that time period. If the winter of 1991-92 was uncharacteristically warm, then there may have been more common dolphins present than usual at that time of year. In contrast, the 1975-78 surveys conducted by Dohl et al. (1986) overlapped with the 1976-77 PDO regime shift from cool to warm; this shift could account for the increase in common dolphins during the warmer summer months of 1975-78.
Patterns of temperature oscillation
Temperature fluctuation patterns like ENSO, PDO, and the North Atlantic Oscillation have been documented to affect the prey of marine animals. An example of this effect is the strong relationship between the North Atlantic Oscillation, the life cycle of the copepod Calanus finmarchicus, and the recruitment of larval Atlantic Cod (Gadus morhua) that prey on copepods (Stenseth et al., 2002). Atlantic Cod in turn are a major food source for the gray seal (Halichoerus grypus), and Calanus spp. are an important prey for the North Atlantic right whale (Eubalaena glacialis) (Wishner et al., 1995; Mohn and Bowen, 1996). Calanoid copepods in the California Current system also have exhibited population-level step changes in abundance in response to strong ENSO events and PDO shifts (Rebstock, 2002).
For example, during the PDO phase switch in the late 1970s, 28% of the copepod species sampled increased in abundance. In contrast, around 1990 a biological step change occurred in copepod populations, when 28% of the species declined in abundance.
Population fluctuations of small pelagic fishes, such as anchovies (Engraulis spp.) and Pacific Sardine (Sardinops sagax), are also correlated strongly with both ENSO and PDO indices in the California Current system and in the Peru-Chile Current (Tibby, 1937; Hubbs, 1948; Niquen and Bouchon, 2004; Lehodey et al., 2006). These fish species are prey for many species of cetaceans in the California Current, including the short- and long-beaked common dolphins, bottlenose dolphin, Pacific white-sided dolphin, and Dali's porpoise (e.g., Stroud et al., 1981; Walker and Jones, 1993; Heise, 1997; Amano et al., 1998; Osnes-Erie, 1999).
Isolated instances of cetaceans changing their distribution patterns have been noted during and after strong climatic events. One example is the permanent expansion of the northern extent of the range of coastal bottlenose dolphins along the California coast during the 1982-83 El Nino (Defran et al., 1999). Another example is the increased abundance of humpback whales (Megaptera novaeangliae) in Monterey Bay during the 1997-98 El Nino (Benson et al., 2002). SST fluctuations have been shown to affect the distribution and community composition of seabirds in the California Current system as well (Hyrenbach and Veit, 2003; Yen et al., 2006). A decline of 2% per year in overall seabird density was recorded for the last 25 years--a drop that was attributed to declines in nearshore abundance of forage fishes (Sydeman et al., in press).
The models for most species included the PDO and ENSO indices as significant variables, although they were not strong predictors in most cases. During positive PDO and ENSO phases, upwelling and productivity decrease while water temperature increases, particularly as warm equatorial waters are pushed poleward and the California Current system is found closer inshore (Sette and Isaacs, 1960; McGowan, 1985). These conditions may explain the apparent association of the Dali's porpoise and Pacific white-sided dolphin with positive PDO indices. These species may be pushed closer to shore by the contraction of the California Current, or they could be concentrating in the remaining areas of productivity, as has been hypothesized for the increase in rorquals in Monterey Bay during the 1997-98 El Nino (Benson et al., 2002).
Alternately, the patterns observed here may reflect changes that occur in other parts of these species' ranges. For example, during negative, cool PDO phases, the overall range of warm-temperate species may contract southward; therefore, a slight increase in the number of common dolphins and even bottlenose dolphins may occur during this phase. Likewise, if the cold-temperate species range as far south as Baja during negative PDO and ENSO periods, then their ranges may contract northward during positive PDO phases, leading to an increase in sightings of Dali's porpoises and Pacific white-sided dolphins in Southern California waters.
Implications in regard to climate change
We have demonstrated changes in distributions of small cetaceans on scales of months to decades. Despite a limited understanding of the mechanisms behind those changes, the model results may help create a basis for understanding the potential effect of climate change upon these species. Studies of climate change in the California Current system indicate that, in addition to increasing temperatures, a rise in atmospheric carbon dioxide 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). These changes may alter large-scale circulation patterns (Harley et al., 2006). Fluctuations in these physical mechanisms will lead to changes in ecosystem dynamics and biodiversity from primary producers to top predators (Sydeman et al., 2001; Harley et al., 2006; Hooff and Peterson, 2006).
Globally, species associated with sea ice or 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 the ones discussed 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, whereas the number of white-beaked dolphins (Lagenorhynchus albirostris), which are associated with cold water, decreased. Such trends could indicate a poleward shift in range for both species (MacLeod et al., 2005; Simmonds and Isaac, 2007). In addition, an influx of cold freshwater in the northern Gulf of Mexico in 2011 may have contributed to an unusually high mortality rate in bottlenose dolphins (Charmichael, et al. 2012).
We predicted that the ranges of the common dolphins, Risso's dolphin, and bottlenose dolphin would expand northward as ocean temperatures warmed, especially as seasonal, ENSO, and PDO events were compounded (e.g., a positive PDO with a positive ENSO). Conversely, we predicted that the ranges of the Pacific white-sided dolphin, northern right whale dolphin, and Dali's porpoise would contract poleward and inshore. These patterns have held true for observations made during previous shorter-term studies. For example, Dali's porpoises and Pacific white-sided dolphins dominated the odontocete species assemblage off central California in the decade before the strong El Nino of 1997-98 (Benson et al., 2002; Keiper et al., 2005).
Keiper et al. (2005) noted that during the strong El Nino of 1997-98 there was a deepened thermocline, a narrow, inshore distribution of Pacific Sardine eggs, and an overall decrease in abundance of macrozooplankton.
During that El Nino, sightings of Dali's porpoises were greatly reduced, whereas common and Risso's dolphin sightings increased. Furthermore, Pacific white-sided dolphin sightings decreased after this period, while sightings of common (particularly the long-beaked species) and bottlenose dolphins increased (Keiper et al., 2005).
However, over the longer-term, our study showed an association of the Pacific white-sided dolphin and Dali's porpoise with positive PDO indices, of common and bottlenose dolphins with negative PDO indices, and of the northern right whale dolphin with positive ENSO indices. These results indicate a more complicated relationship between distribution patterns and SST than we allowed for in our initial predictions or that has been observed on shorter temporal scales. Continued monitoring efforts should be made to ensure that future changes in distribution or reproductive success are documented.
The results presented here provide insight into long-term distribution trends of small cetaceans over several decades. The results are both supported by and build upon the current knowledge base for these species. Nonetheless, we recognize some caveats to this study that warrant discussion.
The PDO and ENSO indices were developed with the use of broad regions of the Pacific. Therefore, they may not reflect precisely the specific dynamics of the Southern California study area. The seasonal SSTs, although averaged for each grid section and quarter, were also still quite broad, as was the selected size of grid cells.
However, this scope was used intentionally to capture the large temporal- and spatial-scale dynamics of these changing SST patterns, rather than to examine mesoscale dynamics on shorter temporal scales. In addition, the SST, ENSO, and PDO variables have the potential to be correlated, as the indices are similar over time. A correlation analysis was conducted, and correlations between ENSO and PDO and between seasonal SSTs and PDO were detected for some species. In those cases, they were not included together, and only the most significant predictors were included.
Only one cruise occurred per year before 1987. To account for potential differences between Survey Types, we repeatedly reran each model while randomly dropping out data from different years. The results indicated that the models were robust against missing years of data, and the variation in the number of surveys per year did not affect the results. The survey methods from each Survey Type were quite different, making it a challenge to combine these data sets. However, by using only the group SPUE and by limiting our sightings to the ones made in sea states of 3 or less on the Beaufort scale, we tried to make the data as comparable as possible.
The inclusion of the Survey Type variable in most models reflects some of those differences in survey effort. The CalCOFI cruises in 1987-2004 consistently ranked lowest in sighting numbers for all species although those surveys had the most effort. This ranking was likely due to a single observer who covered both birds and mammals with a smaller effective strip width rather than to the multiple observers dedicated to monitoring marine mammals for the other 2 types of surveys.
The SWFSC cruises had the highest number of observations for 6 of the 7 models in which they were included, although those cruises had less effort than the CalCOFI cruises. The high number of observations may have been due to optimal sighting conditions during the SWFSC cruises, which were largely conducted in summer and fall. In addition, big eye binoculars were used on SWFSC cruises but were not used regularly on CalCOFI cruises. In another difference in Survey Type, CalCOFI surveys always were conducted in passing mode in which the survey vessel does not leave the transect line when animals are sighted, but SWFSC ships operated in closing mode and 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 for encounter rate. The correlation analysis did not indicate a strong relationship between the number of groups encountered and the size of the group for any of the modeled species. Therefore, our models may have misidentified trends if a change in group size as a response to any of these variables had better explanatory power than the overall encounter rates.
The models presented in this study indicated that fluctuations in SST regimes influenced the distribution of small cetaceans. However, the relationships were not as straightforward as predicted. The observed complexities likely are related to effects of SSTs on prey and subsequent responses by cetaceans. Dolphins have been shown previously to be sensitive to changes in SST and to shift their distributions in response to regime oscillations like ENSO. However, this study is the first one to model responses to multiple temperature shifts over a long time period for a variety of cetacean species in this region of the California Current system.
The resulting models were unique to each of the 8 species studies. This finding indicates that each species is characterized by a distinct pattern in habitat occurrence related to SST dynamics in this study area, despite the overlap in the overall distributions of the examined species in the Southern California study area. Results herein can be used to begin to predict the future distribution of these small cetaceans throughout the waters off Southern California. Results also provide a tool to understand, as global climate change intensifies, potential responses of these species to rising ocean temperatures and the ecological mechanisms responsible for those responses.
Search effort (in linear kilometers) and number of groups seen for each species on each of the surveys conducted by the NOAA Southwest Fisheries Science Center (SWF- SC) and the California Cooperative Oceanic Fisheries Investigations (CalCOFI) and included in the analyses for this study. El Nino cruises were combined into seasons for analyses. Seasons are defined as follows: spring was February-April, summer was May-July, fall was August-October, and winter was November-January. Species abbreviations are as follows: Dsp=Delphinus sp.; Dd=Delphinus delphis; De=Delphinus capensis-, Gg=Grampus griseus; bh=Lissodelphis borealis-, ho=Lagenorhynchus obliquidens; Pd=Phocoenoides dalli; Sc=Stenella coeruleoalba-, Tt=Tursiops truncatus. NA=not available. The SWFSC cruises are as follows: CAMMS=The California Marine Mammal Survey; PODS =Population of Delphinus Stocks; ORCAWALE=Oregon, California, Washington Line-Transect and Ecosystem cruise; CSCAPE=The Collaborative Survey of Cetacean Abundance and the Pelagic Ecosystem.
Cruise Year Quarter Dsp Gg Lb Lo Pd CalCOFI CC198705 1987 Spring 5 1 0 0 4 CC198709 1987 Summer 9 4 0 5 0 CC198711 1987 Fall 3 1 0 1 2 CC198801 1988 Winter 3 2 0 2 3 CC198804 1988 Spring 3 1 4 0 0 CC198808 1988 Summer 15 0 0 0 3 CC198810 1988 Fall 3 7 0 0 9 CC198901 1989 Winter 2 0 1 0 2 CC198904 1989 Spring 1 0 0 3 7 CC198907 1989 Summer 25 3 1 1 1 CC198911 1989 Fall 11 4 1 1 4 CC199003 1990 Winter 1 0 1 0 1 CC199004 1990 Spring 13 0 0 5 3 CC199007 1990 Summer 18 2 0 0 1 CC199011 1990 Fall 5 3 0 1 4 CC199101 1991 Winter 3 1 0 1 3 CC199103 1991 Spring 7 2 0 1 5 CC199107 1991 Summer 28 0 0 2 0 CC199109 1991 Fall 12 2 0 0 0 CC199201 1992 Winter 5 1 2 3 1 CC199204 1992 Spring 5 2 0 1 2 CC199207 1992 Summer 18 1 1 2 1 CC199209 1992 Fall 5 0 0 0 2 CC199301 1993 Winter 10 1 0 1 1 CC199303 1993 Spring 9 2 0 0 0 CC199308 1993 Summer 9 0 0 0 0 CC199310 1993 Fall 2 1 0 0 2 CC199401 1994 Winter 12 2 2 0 4 CC199403 1994 Spring 2 0 0 0 0 CC199410 1994 fall 15 6 0 2 0 CC199501 1995 Winter 15 2 0 0 1 CC199504 1995 Spring 12 2 0 0 2 CC199507 1995 Summer 26 1 0 2 1 CC199510 1995 Fall 9 1 0 1 0 CC199604 1996 Spring 6 1 0 0 1 CC199608 1996 Summer 8 0 0 3 0 CC199610 1996 Fall 4 0 0 0 0 CC199701 1997 Winter 7 8 1 5 3 CC199707 1997 Summer 25 3 0 0 1 CC199709 1997 Fall 9 1 0 2 0 CC199712 1997 El Nino 1 2 3 0 0 0 CC199801 1998 Winter 10 1 0 0 0 CC199803 1998 El Nino 2 6 2 0 4 1 CC199804 1998 Spring 13 1 0 2 0 CC199805 1998 El Nino 3 14 0 0 1 1 CC199806 1998 El Nino 4 14 1 1 2 0 CC199807 1998 Summer 25 0 0 1 0 CC199809 1998 Fall 9 1 0 0 0 CC199810 1998 El Nino 5 21 0 0 1 0 CC199904 1999 Spring 9 1 3 3 1 CC199908 1999 Summer 33 2 0 0 0 CC199910 1999 Fall 17 1 0 0 1 CC200004 2000 Spring 9 0 0 3 5 CC200007 2000 Summer 9 0 0 10 1 CC200010 2000 Fall 9 0 2 4 1 CC200101 2001 Winter 7 2 0 1 1 CC200104 2001 Spring 5 2 1 1 2 CC200107 2001 Summer 16 0 0 0 0 CC200110 2001 Fall 25 3 0 5 0 CC200201 2002 Winter 7 4 3 0 3 CC200203 2002 Spring 6 0 0 5 4 CC200207 2002 Summer 23 1 0 2 2 CC200211 2002 Fall 7 0 0 0 0 CC200301 2003 Winter 14 2 0 1 2 CC200304 2003 Spring 6 3 1 7 12 CC200307 2003 Summer 16 4 1 0 1 CC200310 2003 Fall 12 0 0 0 0 CC200401 2004 Winter 16 1 0 0 4 CC200403 2004 Spring 13 6 3 7 14 CC200407 2004 Summer 21 2 0 6 1 CC200411 2004 Fall 19 2 0 6 0 CC200501 2005 Winter 16 2 1 4 3 CC200504 2005 Spring 7 4 6 13 4 CC200507 2005 Summer 64 0 0 3 0 CC200511 2005 Fall 32 5 1 1 1 CC200602 2006 Winter 4 0 0 4 0 CC200604 2006 Spring 6 3 2 3 8 CC200607 2006 Summer 53 0 0 0 0 CC200610 2006 Fall 17 0 1 3 1 CC200707 2007 Winter 42 7 0 1 0 CC200711 2007 Spring 22 0 2 2 1 CC200701 2007 Summer 20 1 0 1 7 CC200704 2007 Fall 9 4 1 2 9 CC200801 2008 Winter 15 4 1 5 4 CC200803 2008 Spring 19 2 2 6 22 CC200808 2008 Summer 31 1 0 1 0 CC200810 2008 Fall 30 2 0 2 0 CC200901 2009 Winter 30 1 0 0 13 CC200903 2009 Spring 14 0 0 0 2 CC200907 2009 Summer 34 7 0 0 0 CC200911 2009 Fall 12 2 1 1 1 SWFSC 564 1979 Sept-Oct 17 8 1 1 2 646 1980 June-July 8 0 0 0 2 798 1982 April 16 15 11 8 16 674 1983 Dec 19 7 0 18 4 905 1984 Dec 42 13 1 10 3 CAMMS 1991 July-Oct 50 8 10 0 0 PODS 1993 July-Oct 23 3 0 0 0 ORCAWALE 1996 Aug-Nov 30 6 1 9 0 ORCAWALE 2001 July-Dee 20 7 0 2 0 CSCAPE 2005 Aug-Dec 42 2 0 0 6 Effort Cruise Sc Tt Dd Dc (km) CalCOFI CC198705 0 3 NA NA 1559 CC198709 0 3 NA NA 1704 CC198711 0 3 NA NA 1468 CC198801 0 3 NA NA 1501 CC198804 0 3 NA NA 1346 CC198808 0 3 NA NA 1810 CC198810 0 3 NA NA 1420 CC198901 0 3 NA NA 1338 CC198904 0 3 NA NA 1596 CC198907 0 3 NA NA 1932 CC198911 0 3 NA NA 1496 CC199003 0 3 NA NA 407 CC199004 1 3 NA NA 1509 CC199007 0 3 NA NA 1887 CC199011 0 3 NA NA 1349 CC199101 0 3 NA NA 1332 CC199103 0 3 NA NA 1162 CC199107 0 3 NA NA 1668 CC199109 0 3 NA NA 1635 CC199201 0 3 NA NA 1265 CC199204 0 3 NA NA 2427 CC199207 0 3 NA NA 1437 CC199209 0 3 NA NA 1625 CC199301 0 3 NA NA 1249 CC199303 0 0 NA NA 1630 CC199308 0 0 NA NA 1843 CC199310 0 0 NA NA 1549 CC199401 0 1 NA NA 1369 CC199403 0 0 NA NA 1552 CC199410 0 2 NA NA 1590 CC199501 0 0 NA NA 1331 CC199504 0 0 NA NA 1629 CC199507 0 0 NA NA 1900 CC199510 0 0 NA NA 1589 CC199604 0 1 NA NA 1214 CC199608 0 0 NA NA 1729 CC199610 0 0 NA NA 1434 CC199701 0 0 NA NA 1442 CC199707 0 2 NA NA 1724 CC199709 0 ] NA NA 1511 CC199712 0 0 NA NA 361 CC199801 0 0 NA NA 696 CC199803 0 1 NA NA 701 CC199804 0 1 NA NA 1491 CC199805 0 2 NA NA 818 CC199806 0 1 NA NA 812 CC199807 0 1 NA NA 1652 CC199809 0 0 NA NA 1499 CC199810 0 0 NA NA 1308 CC199904 0 0 NA NA 1633 CC199908 0 1 NA NA 1457 CC199910 0 0 NA NA 1212 CC200004 0 2 NA NA 1667 CC200007 0 3 NA NA 1754 CC200010 0 2 NA NA 1425 CC200101 0 0 NA NA 1434 CC200104 0 0 NA NA 1428 CC200107 0 0 NA NA 1547 CC200110 0 0 NA NA 1322 CC200201 0 1 NA NA 1172 CC200203 0 0 NA NA 1454 CC200207 0 4 NA NA 1741 CC200211 0 0 NA NA 1443 CC200301 0 0 NA NA 1712 CC200304 0 0 NA NA 3503 CC200307 0 0 NA NA 1680 CC200310 0 0 NA NA 1542 CC200401 0 5 NA NA 1380 CC200403 0 0 NA NA 2301 CC200407 2 0 16 0 2003 CC200411 0 2 8 8 1552 CC200501 0 0 11 1 1376 CC200504 0 2 0 4 2024 CC200507 0 0 16 18 2264 CC200511 0 1 10 7 1357 CC200602 0 7 6 4 1292 CC200604 0 3 1 1 2070 CC200607 0 0 41 3 1964 CC200610 1 4 11 2 1731 CC200707 0 0 14 10 2180 CC200711 0 1 12 0 1630 CC200701 0 0 14 0 1454 CC200704 0 2 2 1 900 CC200801 0 0 8 0 1264 CC200803 0 2 13 2 1182 CC200808 0 6 10 3 1224 CC200810 0 1 21 1 1505 CC200901 0 4 18 3 1273 CC200903 0 1 5 4 707 CC200907 1 7 9 9 931 CC200911 0 0 6 1 713 SWFSC 564 1 3 NA NA 1662 646 0 3 NA NA 2045 798 0 3 NA NA 1842 674 0 3 NA NA 562 905 0 3 NA NA 1179 CAMMS 6 3 45 2 4210 PODS 4 1 21 0 2610 ORCAWALE 6 4 24 2 3936 ORCAWALE 1 7 16 1 2540 CSCAPE 5 4 29 6 2951
The effective degrees of freedom (EDF) and P-values for each of the parameters included in the generalized additive model of sightings per unit effort in Southern California waters in 1979-2009 for each studied species of small cetacean: short-beaked common dolphin (Delphinus delphis), long-beaked common dolphin (D. capensis), Risso's dolphin (Grampus griseus), striped dolphin (Stenella coeruleoalba), bottlenose dolphin (Tursiops truncatus), northern right whale dolphin (Lissodelphis borealis), Pacific white-sided dolphin (Lagenorhynchus obliquidens), and Dali's porpoise (Phocoenoides dalli). Because the short- or long-beaked common dolphins were not recognized formally as distinct until 1994, data for both species were used in a combined category in analyses. Note that no EDF was available for the 2 parametric variables (Quarter and SurveyType). SurveyType is the variable for the cruises, which were conducted by the NOAA Southwest Fisheries Science Center and the the California Cooperative Oceanic Fisheries Investigations. Variable abbreviations: DepthMin=minimum depth (m), DepthMean=mean depth (m), MaxDepth=maximum depth (m), SeasAv=seasonal averaged sea-surface temperature ([degrees]C), ENSO=El Nino-Southern Oscillation, and PDO=Pacific Decadal Oscillation. NA=not available.
Species Parameter EDF P-value Both common Quarter NA <0.01 dolphins SurveyType NA <0.01 Slope 6.97 <0.01 DepthMax 2.09 <0.01 SeasAv 5.87 <0.01 PDO 1.97 <0.01 Short-beaked Quarter NA <0.01 common dolphin Slope 3.12 <0.01 DepthMean 5.32 <0.01 SeasAv 7.1 <0.01 Long-beaked Quarter NA 0.02 common dolphin DepthMax 1.98 <0.01 SeasAv 2.46 0.03 ENSO 3.82 0.03 Risso's dolphin Quarter NA <0.01 SurveyType NA <0.01 Slope 5.33 <0.01 DepthMean 5.09 <0.01 ENSO 2.43 <0.01 SeasAv 3.39 0.01 Striped dolphin SurveyType NA <0.01 DepthMin 1.73 <0.01 Bottlenose SurveyType NA <0.01 dolphin DepthMean 4.97 <0.01 PDO 1.4 0.03 Northern right SurveyType NA <0.01 whale dolphin DepthMax 2.51 <0.01 ENSO 3.32 <0.01 SeasAv 2.19 <0.01 Pacific white- Quarter NA <0.01 sided dolphin SurveyType NA <0.01 Slope 1.57 <0.01 DepthMean 4.06 <0.01 PDO 1.84 0.01 Dali's porpoise Quarter NA <0.01 SurveyType NA <0.01 Slope 1.61 <0.01 DepthMean 3.81 <0.01 PDO 1.74 0.01 SeasAv 2.83 <0.01
Manuscript submitted 1 April 2013.
Manuscript accepted 28 March 2014.
Fish. Bull. 112:159-177 (2014).
The views and opinions expressed or implied in this article are those of the author (or authors) and do not necessarily reflect the position of the National Marine Fisheries Service, NOAA.
We are grateful to SWFSC and CalCOFI for the use of their data sets, without which this analysis could not have been conducted, and to all of the visual observers over the years who gathered that data. We thank N. Mantua and S. Hare for permission to use their PDO index and NOAA scientists for permission to use their ENSO index. We also thank M. Ferguson, E. Archer, J. Moore, and E. Becker for assistance with the modeling and M. Kahru for help with the satellite data of sea-surface temperatures and WimSoft software.
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E. Elizabeth Henderson 
Karin A. Forney 
Jay P. Barlow 
John A. Hildebrand 
Annie B. Douglas 
John Calambokidis 
William J. Sydeman 
Email address for contact author: firstname.lastname@example.org
 Scripps Institution of Oceanography University of California, San Diego 9500 Gilman Drive Mailcode 0905 La Jolla, California 92093
Present address for contact author: National Marine Mammal Foundation 2240 Shelter Island Drive, Suite 200 San Diego, California 92106
 Marine Mammal and Turtle Division Southwest Fisheries Science Center National Marine Fisheries Service, NOAA 110 Shaffer Road Santa Cruz, California 95060
 Marine Mammal and Turtle Division Southwest Fisheries Science Center National Marine Fisheries Service, NOAA 8901 La Jolla Shores Drive La Jolla, California 92037
 Cascadia Research Collective 218 1/2 W. 4th Ave. Olympia, Washington 98501
 Farallon Institute for Advanced Ecosystem Research 101 H Street, Suite Q Petaluma, California 94952 Highlands, New Jersey 07732
(1) Mention of trade names or commercial companies is for identification purposes only and does not imply endorsement by the National Marine Fisheries Service, NOAA.
(2) Kinzey, D., P. Olson, and T. Gerrodette. 2000. Marine mammal data collection procedures on research ship line-transect surveys by the Southwest Fisheries Science Center. NOAA Southwest Fisheries Science Center, Admin. Rep. LJ-00-08, 32 p.
Table 1 The final best-fit generalized additive models are presented here for each of the 8 species of small cetaceans investigated for this study in Southern California waters in 1979-2009. Also included are the restricted maximum likelihood (REML) score, explained deviance (Expl. dev.), and residual degrees of freedom (df) for each model. See Appendix 2 for the P-values of each variable in these models. The 8 species were the short-beaked common dolphin (Delphinus delphis), long-beaked common dolphin (D. capensis), Risso's dolphin (Grampus griseus), northern right whale dolphin (Lissodelphis borealis), Pacific white-sided dolphin (Lagenorhynchus obliquidens), Dali's porpoise (Phocoenoides dalli), striped dolphin (Stenella coeruleoalba), and bottlenose dolphin (Tursiops truncatus); a third model for common dolphins incorporated data for both the short-and long- beaked common dolphins. Variable abbreviations: DepthMin=minimum depth (m), DepthMean=mean depth (m), MaxDepth=maximum depth (m), SeasAv=seasonal averaged sea-surface temperature, ENSO=El Nino- Southern Oscillation, and PDO=Pacific Decadal Oscillation. Expl. Residual Species Final model REML dev. df Short-beaked Quarter + Slope + 754.0 23.9% 642 common dolphin DepthMean + SeasAv Long-beaked Quarter + DepthMax + ENSO 211.7 57.4% 652 common dolphin + SeasAv Both common Quarter + SurveyType + 2751.8 32.5% 2415 dolphins Slope + DepthMax + PDO + SeasAv Risso's dolphin Quarter + SurveyType + 644.7 36.6% 2421 Slope + DepthMean + ENSO + SeasAv Northern right SurveyType + DepthMax + 270.3 26.1% 2428 whale dolphin ENSO + SeasAv Pacific white- Quarter + SurveyType + 706.2 21.2% 2419 sided dolphin Slope + DepthMean + PDO Dall's porpoise Quarter + SurveyType + 726.8 27.5% 2423 Slope + DepthMean + PDO + SeasAv Striped dolphin SurveyType + DepthMin 88.3 41.8% 2437 Bottlenose SurveyType + Slope + 376.0 46.4% 2429 dolphin DepthMean + PDO Table 2 Summary of sightings, including the number of cruises conducted by the California Cooperative Oceanic Fisheries Investigations and the NOAA Southwest Fisheries Science Center in which each species was encountered and the total number of groups sighted in 1979-2009 in Southern California waters for each studied species of small cetacean: short-beaked common dolphin (Delphinus delphis), long-beaked common dolphin (D. capensis), Risso's dolphin (Grampus griseus), northern right whale dolphin (Lissodelphis borealis), Pacific white-sided dolphin (Lagenorhynchus obliquidens), Dali's porpoise (Phocoenoides dalli), striped dolphin (Stenella coeruleoalba), and bottlenose dolphin (Tursiops truncatus). Because the short- and long-beaked common dolphins were not recognized formally as distinct until 1994, data for both species were used in a combined category in analyses. Number of Number of Species cruises groups Short-beaked common dolphin 29 387 Long-beaked common dolphin 22 93 Both common dolphins 105 1537 Risso's dolphin 74 227 Northern right whale dolphin 32 71 Pacific white-sided dolphin 62 217 Dali's porpoise 64 240 Striped dolphin 22 28 Bottlenose dolphin 50 180
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|Author:||Henderson, E. Elizabeth; Forney, Karin A.; Barlow, Jay P.; Hildebrand, John A.; Douglas, Annie B.; C|
|Date:||Apr 1, 2014|
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