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. 3 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. 4 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 5 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 6 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 7 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). 8 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, 9 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 10 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. 11 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 12 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. 13 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. 14 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. 15 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 16 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, 18 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 19 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 Literature Cited Akaike H. 1976. An information criterion (AIC). Math Science. 14:5-9. Bakun A. 1990. Global climate change and intensification of coastal ocean upwelling. Science. 247:198-201. Ballance L. T., Pitman R. L., Fiedler P. C. 2006. Oceanographic influences on seabirds and cetaceans of the eastern tropical Pacific: A review. Prog Oceanogr. 69:360-390. 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Decadal variability of the shallow Pacific meridional overturning circulation: Relation to tropical sea surface temperatures in observations and climate change models. Ocean Modelling. 15:250-273. 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