Understanding the fluctuations in marine fish and ecosystem production is a pressing research goal as scientists and policymakers address climate change forecasts (Hollowed et al. 2011; Link et al. 2012). Commercial fishing records and stock assessment surveys provide a wealth of observational data that are needed to understand climatic drivers of fish production in continental shelf systems (Hare and Mantua 2000; Hollowed et al. 2001; Mueter et al. 2009; Noakes and Beamish 2009; Litzow and Mueter 2014), but these data sources are not available for every species or every system. Nearshore systems are economically important for local, small-scale commercial and recreational fishing, diving, and wildlife viewing. However, they seldom support large-scale commercial fisheries and thus tend to lack adequate catch, stock assessment, and recruitment data, which are needed to estimate production or to understand climatic drivers across a wide geographic area (Cooke and Cowx 2004, 2006; Agardy et al. 2005). Nearshore systems are very productive; they function as critical spawning and rearing habitat for commercial and noncommercial species, and they support high biodiversity (Kruse and Tyler 1989; Dean et al. 2000; Agardy et al. 2005; Laurel et al. 2007; Doyle et al. 2009). A lack of available data relating environmental conditions to productivity in nearshore systems is compounded by complex interactions of atmospheric, oceanographic, watershed, and human influences at the marine—terrestrial interface (Cloern and Jassby 2008). To provide insights about nearshore biological responses to basin- and local-scale conditions, we developed an annual index of nearshore production from the growth rates of two nearshore-resident fishes at nine sites in the California Current and Alaska Coastal Current. “Basin scale” refers to the Pacific Ocean basin, and “local scale” refers to conditions at sample sites and their adjacent areas (thousands to tens of thousands of square kilometers).

Relationships between basin-scale environmental indices and nearshore fish growth would imply strong linkages between global environmental dynamics and local biology. Basin-scale conditions could influence nearshore systems through their linkages to offshore or terrestrial systems, as basin indices correlate well with offshore sea surface temperature (SST), salinity, and upwelling (Di Lorenzo et al. 2008; Ainley and Hyrenbach 2010) and with terrestrial indicators such as freshwater discharge (Royer et al. 2001; Papineau 2001; Neal et al. 2002; Hickey et al. 2010). The Pacific Decadal Oscillation (PDO), North Pacific Gyre Oscillation (NPGO), and El Niño—Southern Oscillation (ENSO) represent both decadal (e.g., PDO and NPGO) and interannual (e.g., ENSO) scales of climate variability in the northeast Pacific Ocean basin (Hollowed et al. 2001) and are among the most consistent predictors of marine and terrestrial ecosystem production in the North Pacific Ocean and western United States, respectively (Neal et al. 2002; Mundy 2005; Spies 2007; Black 2009; Menge et al. 2009; Di Lorenzo et al. 2013; Sydeman et al. 2013). Interpretation of basin-scale relationships and their linkages to nearshore responses could be improved by a complementary analysis of organismal growth responses to local conditions.

Local-scale conditions (e.g., SST, upwelling, and freshwater discharge) influence nearshore fish growth through bottom-up shifts in prey availability and prey quality. At the lowest levels of the food web, local physical conditions control the rate of production for phytoplankton and other primary producers (e.g., kelp) by modifying the availability of the light and nutrients that are required for photosynthesis (Steneck et al. 2002; Cury et al. 2003). This energy is consumed first by herbivores and other primary consumers (e.g., detritivores consuming plant material) and is later transferred to predators by way of changes in the abundance and quality of their prey (Cury et al. 2003).

Time lags must be considered when linking predator production with environmental conditions through trophic interactions (sensu Post 2004), especially when predators are limited by the availability of prey that are at least 1 year old and when prey abundance is determined by conditions experienced early in life history (Miller and Sydeman 2004; Frederiksen et al. 2006). Analyses spanning multiple seasons at plausible biological time lags are helpful in identifying whether conditions that are present during a specific window of months or during the transition from one seasonal climate state to another are particularly important to biological function. For instance, variations in primary production, recruitment of benthic invertebrates, zooplankton abundance, rockfish Sebastes spp. growth, and seabird reproduction occur when the onset of upwelling in the California Current is delayed, whether or not normal upwelling conditions prevail later in the summer (Barth et al. 2007; Shanks and Roegner 2007; Black et al. 2011).

Black Rockfish Sebastes melanops and Kelp Greenling Hexagrammos decagrammus are common nearshore-resident fishes with similar geographic distributions that span the California Current and the Alaska Coastal Current. Individuals of both species occupy small (<1 km²) home ranges, often in rocky reef habitats with canopy kelp (giant kelp Macrocystis pyrifera and bull kelp Nereocystis luetkeana; Freiwald 2009; Love 2011; Pirtle et al. 2012). Black Rockfish are pelagic-feeding generalists that target forage fishes, including Pacific Herring Clupea pallasii, Pacific Sand Lances Ammodytes hexapterus, and juvenile salmon Oncorhynchus spp., as well as invertebrates such as crab megalopae (Rosenthal 1983; Love et al. 2002; Love 2011; Sturdevant et al. 2012). Kelp Greenlings are benthic-feeding generalists that forage on a variety of benthic invertebrates, including amphipods, snails, sea cucumbers, decorator crabs, and brittle stars (Moulton 1977; Hines 1982; Rosenthal 1983; Love 2011).

We explored the influence of basin- and local-scale environmental indices across seasons and years on the growth of two nearshore fishes (Black Rockfish and Kelp Greenling) in the (1) California Current, which fluctuates seasonally between upwelling (summer) and downwelling (winter); and (2) Alaska Coastal Current, a predominantly downwelling system. A priori, we posited that fish growth would be related to basin- and localscale indices (Figure 1), and we categorized relationships in terms of either “warm” water-column-stabilizing effects or “cool” water-column-destabilizing effects. More specifically, we hypothesized that nearshore pelagic Black Rockfish would benefit from cooler conditions in the California Current and from warmer conditions in the Alaska Coastal Current (Polovina et al. 1995; Gargett 1997; von Biela et al. 2015), whereas nearshore benthic Kelp Greenlings would benefit from warmer conditions in both of the current systems (Phillips 2005; Blanchette et al. 2006; von Biela et al. 2015). In our analysis, we examined the time lags for which basin- and local-scale indices were related to nearshore fish growth and production. Lagged relationships were intended to reflect changes in prey quantity through trophic interactions, while current-year relationships were taken to indicate changes in (1) the prey quality associated with feeding conditions, and (2) the quantity of age-0 prey. Lags of up to 2 years are considered to match the age-classes of the likely forage fish and invertebrate prey for both of our focal fish species (Hatch and Sanger 1991; Yang 1993 ; Van Pelt et al. 1997).

METHODS

Nearshore production was indexed by using annual growth increments recorded in the otoliths of Black Rockfish and Kelp Greenlings that were collected at nine sites in the California Current and Alaska Coastal Current (Table 1; Figure 2). Study sites were characterized by rocky reef habitat and by the presence of macrophytes (kelp) and sea otters Enhydra lutris. A keystone predator in nearshore North Pacific systems, the sea otter is known to increase community diversity and kelp production via top-down control of major kelp grazers, such as sea urchins Strongylocentrotus spp. (Steneck et al. 2002). Details of collections, otolith sectioning, otolith measuring, and crossdating procedures were described previously (von Biela et al. 2015). We provide a brief summary here. Fish were collected by using a combination of hook-and-line sampling, trammel-netting, and spearfishing in shallow (<15 m) rocky reef habitats from 2009 to 2011. Otoliths were removed, sectioned, and mounted on slides to measure annual increment widths on high-resolution digital images that were captured with a digital camera (Leica DFC Model 425 or 450; 5-megapixel resolution) mounted on a stereomicroscope (Leica Model MZ6 or M60) under 20–40× magnification following the methods of Black et al. (2005). These polishing and photographing procedures were sufficient to clearly reveal growth increment structure in most of the samples; only otoliths with clearly defined growth increment boundaries were used in the study. Dendrochronology crossdating procedures were used to verify that all increments were assigned the correct calendar year of formation (Black et al. 2005) and to assess measurement error. If measurement error was high, visual crossdating and the statistical interseries correlation results from the software COFECHA (Grissino-Mayer 2001) were used to determine whether there was low synchrony among individuals, indicative of high error rates or weak environmental signals. Crossdating identifies missing or incorrectly added growth increments most easily in relatively old fish (age > 15 years), which have more years of data from which to assess coherence among individuals. Error rates in year assignments for younger fish were almost certainly low given their rapid growth rates and correspondingly wide increments, which are difficult to miss; although there are few cases in a short time series, conspicuously narrow (or wide) increments also corresponded among individuals collected from the same site. Only fish older than age 5 at capture were included in this study, and the measured increments spanned the subadult and adult growth history (i.e., increments represented age-1 growth and beyond). Annual growth increments spanned the period 1972–2010 for Black Rockfish and spanned 1994–2010 for Kelp Greenlings; however, the years 2000–2010 were best represented because younger fish only provided data from these more recent years (see von Biela et al. 2015 for the number of otolith increments plotted by growth year). The interseries correlations ranged from 0.37 to 0.70 (von Biela et al. 2015) and were comparable with those of other rockfish chronologies (Black et al. 2005, 2008, 2009), suggesting that increment growth boundaries were correctly delineated with minimal measurement error and good signal-to-noise ratios.

Growth was compared to basin-scale conditions and local conditions across seasons with time lags of up to 2 years. Seasons were defined as autumn (October–December), winter (January–March), spring (April–June), and summer (July–September) following Cummins and Masson (2014). The PDO, NPGO, and the multivariate ENSO index (MEI) were selected as indicators of basin-scale conditions. The PDO is the leading principal component of monthly SST, and the NPGO is the second dominant mode of sea surface height anomalies (SSHa) in the North Pacific Ocean (Mantua et al. 1997; Di Lorenzo et al. 2008). Positive values of PDO indicate warm coastal SSTs throughout the northeast Pacific Ocean, weaker upwelling and decreased precipitation in the California Current, and stronger downwelling and increased precipitation in the Alaska Coastal Current (Mantua et al. 1997; Royer 2005). Positive values of NPGO indicate enhanced transport of the North Pacific Current as well as increased transport of the Alaska Coastal Current and California Current (Di Lorenzo et al. 2008). Increased transport of the California Current is associated with stronger upwelling, higher sea surface salinity and nutrient concentrations, weaker thermoclines, decreased stability of the water column, and cool conditions in the California Current (Di Lorenzo et al. 2008, 2009). Increased transport of the Alaska Coastal Current is associated with an intensified Subarctic Gyre, which draws warm waters from the south into the Gulf of Alaska (Di Lorenzo et al. 2008; Danielson et al. 2011). The MEI is the leading principal component of six variables over the tropical Pacific: sea level pressure, meridional and zonal wind components, cloudiness, surface air temperature, and SST (Wolter and Timlin 1998). Positive MEI values are associated with ENSO conditions, including a warmer, fresher, more stable water column with low nutrient concentrations in the eastern Pacific Ocean (Wolter and Timlin 1998). The three basin-scale indices interact with ENSOs centered over the eastern Pacific, thereby modifying the Aleutian low-pressure system and PDO, whereas ENSOs that are centered over the central Pacific modify the North Pacific Oscillation and the NPGO (Di Lorenzo et al. 2013). Monthly values for the PDO, NPGO, and MEI were obtained from the Joint Institute for the Study of the Atmosphere and Ocean at the University of Washington, Seattle (jisao.washington.edu/pdo); monthly NPGO values were from the Department of Ocean Climate and Ecosystem Science at Georgia Tech University, Atlanta ( www.o3d.org/npgo); and monthly MEI values were from the National Oceanic and Atmospheric Administration's Earth System Research Laboratory ( www.esrl.noaa.gov/psd/enso/mei).

FIGURE 1.

Conceptual diagram of food web responses to basin- and local-scale conditions in the northeast Pacific Ocean. Basin-scale variables are represented by the Pacific Decadal Oscillation (PDO), the North Pacific Gyre Oscillation (NPGO), and the El Niño—Southern Oscillation (ENSO), which is indexed by the multivariate ENSO index (MEI). Local-scale conditions are indicated by sea surface temperature (SST), sea surface height anomalies (SSHa), the Bakun upwelling index (UW), photosynthetically active radiation (PAR), and freshwater discharge (FW). Solid lines represent conceptual relationships, and dotted lines represent indirect relationships that are analyzed. Other relationships (e.g., direct effects of temperature on fish growth) are excluded for simplicity.

TABLE 1.

Collection sites, collection dates, and sample sizes for Black Rockfish and Kelp Greenlings from which otoliths were obtained; the areas of the marine study sites, buffered study sites, and associated watersheds are also presented. The buffered site area includes a 100-km buffer around the site and was used to calculate mean sea surface temperature.

FIGURE 2.

Map of nearshore fish collection sites (blue), associated watersheds (green), and stream gauge locations (black-and-white circles; California Current sites only) along the Pacific coast (PWS = Prince William Sound). The blue-shaded area represents the largest possible extent of a study site, but fish were only captured in depths less than 15 m and therefore were generally closer to shore than indicated here.

Local-scale environmental indices included SST, SSHa, photosynthetically active radiation (PAR), the Bakun upwelling index, and freshwater discharge. These environmental variables were selected because they are either used to derive (i.e., SST and SSHa) or track basin-scale conditions and are useful for predicting biological responses (Mantua et al. 1997; Papineau 2001; Royer et al. 2001; Neal et al. 2002; Di Lorenzo et al. 2008; Ainley and Hyrenbach 2010; Hickey et al. 2010). The SST measures the heat near the surface of the ocean. Winds, currents, and the heat content of the water column all influence SSHa, with lower values indicating offshore water movement during periods of upwelling and reduced heat content as heat causes water column expansion (Wolf et al. 2009). We used PAR as a measure of the energy available for photosynthesis at the ocean's surface within the waveband used by primary producers (400–700 nm). Coastal upwelling indices are derived from wind stress, with positive values indicating upwelling and negative values indicating downwelling. In the California Current, upwelling index values are generally positive such that increasing values are associated with more upwelling and cooler, less-stable conditions. In the Alaska Coastal Current, upwelling index values are typically negative so that relatively high (near zero) values are associated with the relaxation of downwelling and a lack of vertical mixing that promotes stability and “warm” conditions. Freshwater discharge is an estimate of the freshwater input to the marine study sites, and high rates of discharge are associated with greater water column stability (Royer et al. 2001). Warmer, more stable conditions were assumed to be associated with higher SST, SSHa, PAR, and freshwater discharge in both current systems; increased upwelling (i.e., relaxed downwelling) in the Alaska Coastal Current; and decreased upwelling (i.e., relaxed upwelling) in the California Current. Categorization of the relationships for each environmental variable in terms of warm and cool effects recognizes that (1) environmental variables act in concert, and (2) there is an inherent lack of independence among environmental indices.

An index of primary production could not be included for two reasons. First, the time series of phytoplankton data was too short for an analysis with lagged relationships. Second, recent evidence from stable isotopes in Black Rockfish and Kelp Greenlings suggests that a substantial proportion of energy is provided by kelp and other macroalgae (von Biela et al., in press), but systematic long-term data sets on production and standing stocks of macrophytes across the study region do not exist. Our analysis assumes that the physical environment controls the total amount of primary production available, but we do not differentiate or make specific assumptions about phytoplankton and kelp production patterns.

Gridded environmental data (SST, SSHa, and PAR) were averaged over an area spanning a 100-km buffer around each study site to increase the number of grid cells sampled (buffered site area in Table 1; range = 14,000–60,000 km²). In all cases, the spatial extent of calculations was truncated at the 200-m isobath. Monthly SST averages for each site from 1982 to the year prior to fish collection were extracted from satellite SST data via AVHRR (Advanced Very High Resolution Radiometer) PathFinder software (version 5.0;  www.nodc.noaa.gov/SatelliteData/pathfinder4km/userguide.html). Monthly SSHa values were obtained via satellite altimetry measurements from the AVISO (Archiving, Validation, and Interpretation of Satellite Oceanographic Data) product (coastwatch.pfeg.noaa.gov/erddap/griddap) for each site from 1993 to the year prior to fish collection. Monthly PAR averages were obtained from the MODIS (Moderate Resolution Imaging Spectroradiometer) Terra satellites (ocean data.sci.gsfc.nasa.gov/MODIST/Mapped/Monthly/4km/par) from 2000 to the year prior to fish collection. In the northern part of our study range, seasonally low light conditions prevented PAR detection by satellites and resulted in a data gap for November–January. Therefore, there are no models for autumn PAR, and the PAR values for the winter season were averaged over February and March only. Monthly averaged upwelling indices for a location offshore of each study site were obtained from the National Marine Fisheries Service's Pacific Fisheries Environmental Laboratory (PFEL;  www.pfeg.noaa.gov; latitude and longitude rounded to the nearest 0.5° and at least 1° offshore following the recommendations of PFEL) for all years with increment growth data.

Freshwater discharge was considered as an additional localscale variable representing a terrestrial influence on water column stratification and was estimated using either a spatially explicit discharge model for sites in the Alaska Coastal Current (Hill et al. 2015; except the Alaska Peninsula site, which is beyond the domain of the discharge model) or stream gauge data for sites in the California Current. In each case, the watershed for a given study site was delineated by identifying all of the coastal pour points in the marine study site and associated watersheds via use of a digital elevation model (2-arc-seconds' resolution; data available at ned.usgs.gov for U.S. sites and gdex.cr.usgs.gov/gdex for Canadian sites) following established methods for defining hydrography (Jenson and Domingue 1988). When the discharge model was used to estimate monthly freshwater discharge, the mean monthly discharge from a study watershed was extracted from the model (Hill et al. 2015) for the years 1980–2010.

When stream gauge data were used to estimate freshwater discharge, monthly values were obtained from stream gauges within the watershed corresponding to the study site (Figure 2). If no streams in the study watershed were gauged, discharge from the nearest gauge with adequate data was obtained. Because gauged watersheds are much smaller than the study watersheds, discharge values were scaled to estimate the total discharge from the larger study watershed. Scaled discharge values were calculated by multiplying the area of the study watershed by the measured discharge per unit area of the gauged watershed. The stream gauges used to estimate freshwater discharge for sites in the California Current were located in Big Creek (U.S. Geological Survey [USGS] 11143000; within the Big Sur [California] study watershed, 1951–2010), the Hoko River (USGS 12043300; adjacent to the Neah Bay study watershed, 1996–2010), Tofino Creek (Water Survey of Canada 08HB086; within the Clayoquot Sound [British Columbia] study watershed, 1996–2010), and the Zeballos River (Water Survey of Canada 08HE006; within the Nuchatlitz [British Columbia] study watershed, 1972–2010). The combination of modeled discharge and scaled gauge estimates provided the best possible approach for estimating discharge at each study site. Sites in Alaska were covered by a spatially explicit discharge model but no river gauges, and sites in the California Current system were associated with gauged watersheds but were not included in a spatially explicit discharge model. This approach provided some indication for the potential of freshwater discharge to stratify the nearshore water column across years and sites, although a direct measure of stratification would have been preferred if available.

Models were formulated to (1) allow the relationships between annual otolith increment width and each basin- or local-scale indicator to vary between current systems, and (2) recognize that growth increment width is related to the fish's age during increment formation and that these relationships may vary across sites and across individual fish. All models included the age at increment formation to account for the faster growth of younger fish (Morrongiello et al. 2011). Annual otolith increment widths and ages were log transformed prior to analysis to achieve homoscedasticity and a linear relationship between these two variables. In addition to an overall growth intercept (increment width at age 0) across all sites, increment widths were allowed to vary across individual fish by including random intercepts that were specific to each individual fish, nested within random site-specific intercepts. We included a within-individual, autocorrelated error structure for growth increment width to account for any biological processes that might result in growth rates from the previous year being related to the current year's growth or to accommodate any remaining autocorrelated measurement error. Because the measurements within an individual are successive, overestimating the width of a given growth increment results in underestimation of the next growth increment's width (Morrongiello et al. 2015). Black Rockfish models also included a random slope term in addition to the age effect that modifies the slope describing the decline in growth increment width as fish age by allowing the rate of decline to be faster or slower for each individual—essentially fitting an individual growth trajectory to each fish, as modified by environmental effects that are shared among all individuals. However, models for predicting Kelp Greenling annual growth increments did not converge when random slopes were included for each individual; this is likely due to the younger ages and shorter within-individual growth records, which resulted in less data for fitting slopes to each individual. Therefore, Kelp Greenling models included random intercepts—but not random slope terms—for each individual. The random intercepts allowed for some individuals to have overall wider or narrower growth increments; however, the absence of a random slope term for age equates to the assumption that all individuals grow at the same rate after environmental influences on growth are taken into account. Only one environmental index was considered at a time, and the indices were scaled (mean = 0; SD = 1) prior to analysis so that model coefficients would be comparable across analyses, such that coefficients of larger magnitude indicated stronger relationships.

The log-transformed width of an annual increment in year t at site k for individual i (y_tki) was estimated as

Model diagnostics were examined by reviewing plots of the observed and expected growth increment widths for individual fish and the residuals across years and collection sites to assess fit. Models were initially fitted using maximum likelihood for model comparisons, and the best model was refitted by using restricted maximum likelihood to obtain unbiased coefficients (Pinheiro and Bates 2000). Nested model formulations with and without each environmental effect were compared by using Akaike's information criterion (AIC) to determine the best fit (Burnham and Anderson 2002). Basin- and local-scale effects were considered significant if the AIC value decreased by 2.0 units or more relative to the same model without the basin- or local-scale effect and if the coefficient describing the effect was statistically significant (P < 0.05). All statistical analyses were conducted by using the package nlme (Pinheiro and Bates 2000) in R version 3.1.2 (R Development Core Team 2013). Otolith growth indices were not converted to changes in somatic size for any analysis because otolith indices likely reflect overall body condition rather than simply changes in length (Black et al. 2013).

RESULTS

Black Rockfish and Kelp Greenling growth across the California Current system and Alaska Coastal Current system appeared to be related to conditions indexed by basin- and local-scale environmental variables based on improvements in model AIC values (Tables 2, 3; Supplemental Tables S.1–S.4 available separately online). The best single growth model for Black Rockfish included the spring PDO from 2 years prior (AIC difference for the null model [ΔAIC_null] ∼ 41; Table S.1). The best growth model for Kelp Greenlings included the PDO from the prior winter (ΔAIC_null ∼ 26; Table S.3). For both Black Rockfish and Kelp Greenlings, AIC scores indicated that basin-scale models including the PDO outperformed those that contained the MEI, which in turn outperformed those that included the NPGO (Tables S.1, S.3).

Local-scale environmental variables were related to the growth of Black Rockfish and Kelp Greenlings in both current systems (Tables 2, 3). Among the Black Rockfish growth models, the best models included the SST for the current summer (ΔAIC_null ∼ 23; Table S.2), freshwater discharge for the current winter (ΔAIC_null ∼ 20), the upwelling index for the current autumn (ΔAIC_null ∼ 19), PAR for the previous spring (ΔAIC_null ∼ 17), or SSHa for the previous spring (ΔAIC_null ∼ 11; Table S.2). Among the Kelp Greenling growth models, the best models included the upwelling index for the current winter (ΔAIC_null ∼ 29), PAR for the summer 2 years prior (ΔAIC_null ∼ 25), SST for the current summer (ΔAIC_null ∼ 20), SSHa for the current summer (ΔAIC_null ∼ 20), or freshwater discharge for the winter 2 years prior (ΔAICnull = 6.5; Table S.4). Model diagnostics provided no evidence that model assumptions were violated. Seasonal SST had little to no overlap between current systems (Alaska Coastal Current sites versus California Current sites) in the fall (5–10°C versus 10–15°C), winter (2–7°C versus 7–14°C), or spring (2–10°C versus 8–14°C). However, considerable overlap occurred in the summer (9–15°C versus 12–17°C), with warm years at Alaska Coastal Current sites overlapping the SST range from cool and average years at the California Current sites.

Black Rockfish in the California Current

Current-specific coefficients indicated that cool conditions at the basin scale were generally associated with faster Black Rockfish growth in the California Current (17 of 18 significant coefficients; Table 2; Supplemental Figure S.1). Specifically, Black Rockfish growth was inversely related to the PDO and MEI and was positively related to the NPGO with and without lags (Table 2). Among local-scale conditions, improved Black Rockfish growth was more commonly associated with cooler conditions (15 of 23 significant coefficients; Table 2; Figure S.2) that were primarily lagged (11 of 15 cool localscale relationships). Growth was inversely related to SST; growth relationships with SSHa, the upwelling index, and freshwater discharge were mostly inverse, while relationships with PAR were mostly positive. Compared to the consistent association of cool basin-scale conditions with increased growth, the relationships with local-scale conditions were more variable.

TABLE 2.

Relationships between Black Rockfish growth and environmental indices at the basin scale (PDO = Pacific Decadal Oscillation; NPGO = North Pacific Gyre Oscillation; MEI = multivariate El Niño–Southern Oscillation index) and local scale (SST = sea surface temperature; SSHa = sea surface height anomalies; UW = Bakun upwelling index; PAR = photosynthetically active radiation; FW = freshwater discharge). Growth rates are based on the annual growth increment width in otoliths. Environmental indices are represented for each season (Aut = autumn; Win = winter; Spr = spring; Sum = summer) in the year of growth and up to 2 years prior (L1 = 1-year lag; L2 = 2-year lag). Blank cells indicate nonsignificant relationships from mixed models. An effect was considered significant if (1) the Akaike's information criterion value for the model was at least 2.0 units lower than that of the same model without the environmental effect and (2) the coefficient describing the effect was statistically significant (P < 0.05). The sign of the coefficient is noted in each cell as either positive (Pos) or negative (Neg). Light-blue and dark-blue cells indicate relationships between cool conditions and increased fish growth (P < 0.05 and P < 0.01, respectively). Pink and red cells indicate relationships between warm conditions and increased fish growth (P < 0.05 and P < 0.01, respectively).

TABLE 3.

Relationships between Kelp Greenling growth and environmental indices at the basin and local scales (index abbreviations are defined in Table 2). Growth rates are based on the annual growth increment width in otoliths. Environmental indices are represented for each season (abbreviations defined in Table 2) in the year of growth and up to 2 years prior (L1 = 1-year lag; L2 = 2-year lag). Blank cells indicate nonsignificant relationships from mixed models. An effect was considered significant if (1) the Akaike's information criterion value of the model was at least 2.0 units lower than that of the same model without the environmental effect and (2) the coefficient describing the effect was statistically significant (P < 0.05). The sign of the coefficient is noted in each cell as either positive (Pos) or negative (Neg). Light-blue and dark-blue cells indicate relationships between cool conditions and increased fish growth (P < 0.05 and P < 0.01, respectively). Pink and red cells indicate relationships between warm conditions and increased fish growth (P < 0.05 and P < 0.01, respectively).

DISCUSSION

Growth rates of Black Rockfish and Kelp Greenlings in nearshore habitats of the California Current and Alaska Coastal Current were related to basin- and local-scale indices of environmental conditions. In general, pelagic-feeding Black Rockfish grew faster during cool basin-scale conditions in the California Current and warm local-scale conditions in the Alaska Coastal Current. The results of this study generally support the notion that California Current pelagic production is bottom-up limited by nutrients and that Alaska Coastal Current production is bottom-up limited by light, as water column stability is generally higher than optimal in the California Current and lower than optimal in the Alaska Coastal Current (Gargett 1997).

Benthic-feeding Kelp Greenlings grew faster during and subsequent to warm basin- and local-scale conditions in the Alaska Coastal Current. In the California Current, the Kelp Greenling growth response to environmental conditions was complex, with both warm and cool conditions relating to increases in growth at different time lags. Thus, we suggest that benthic production is highest (1) during warm years in the Alaska Coastal Current, and (2) when cool and warm years alternate in the California Current.

Otolith chronologies likely indicate biologically relevant species and ecosystem conditions. At the species level, otolith size correlates with somatic size (Campana 1990) and suggests that chronologies are related to interannual differences in somatic size and condition. In a recent study, Black et al. (2013) found that annual body mass indices (weight/length) of Yellowfin Sole Limanda aspera were well correlated with prior otolith growth at the population level. At the ecosystem level, otolith chronologies of Yelloweye Rockfish Sebastes ruberrimus and Splitnose Rockfish Sebastes diploproa were observed to be synchronous with bivalve and tree-ring chronologies (Black 2009) as well as seabird reproductive success (Black et al. 2011), implying that otolith growth does reflect broad ecosystem conditions. Climatic events are particularly useful for identifying links between otoliths and biological responses at the species and ecosystem levels. For example, the 1983 El Niño was associated with very narrow otolith growth increments (Black 2009), reduced levels of visceral fat (Lenarz and Wyllie Echeverria 1986), and recruitment failures (Lenarz et al. 1995) in several rockfish species as well as a general reduction in ecosystem production (Lenarz et al. 1995).