Influence of ocean and freshwater conditions on ColumbiaRiver sockeye salmon Oncorhynchus nerka adult return rates
JOHN G. WILLIAMS,1*,† STEVEN G. SMITH,1
JEFFREY K. FRYER,2 MARK D. SCHEUERELL,1
WILLIAM D. MUIR,1,† TOM A. FLAGG,1
RICHARDW. ZABEL,1 JOHNW. FERGUSON1,†
AND EDMUNDO CASILLAS1,†
1NOAA Fisheries, Northwest Fisheries Science Center, 2725
Montlake Blvd. East, Seattle, WA, 98112-2097, U.S.A.2Columbia Inter-Tribal Fish Commission, 729 NE Oregon St,Ste. 200, Portland, OR, 97232, U.S.A.
ABSTRACT
In recent years, returns of adult sockeye salmonOncorhynchus nerka to the Columbia River Basin havereached numbers not observed since the 1950s. Tounderstand factors related to these increased returns,we first looked for changes in freshwater productionand survival of juvenile migrants. We then evaluatedproductivity changes by estimating smolt-to-adultreturn rates (SAR) for juvenile migration years 1985–2010. We found SAR varied between 0.2 and 23.5%,with the highest values coinciding with recent largeadult returns. However, the largest adult return, in2012, resulted not from increased survival, but fromincreased smolt production. We evaluated 19 differentvariables that could influence SARs, representing dif-ferent facets of freshwater and ocean conditions. Weused model selection criteria based on small-samplecorrected AIC to evaluate the relative performance ofall two- and three-variable models. The model withApril upwelling, Pacific Northwest Index (PNI) in themigration year, and PNI in the year before migrationhad 10 times the AICc weight as the second-best-sup-ported model, and R2 = 0.82. The variables of Aprilocean upwelling and PNI in the migration year hadhigh weights of 0.996 and 0.927, respectively, indicat-ing they were by far the best of the candidate variablesto explain variations in SAR. While our analyses wereprimarily correlative and limited by the type andamount of data currently available, changes in ocean
conditions in the northern California Current system,as captured by April upwelling and PNI, appeared toplay a large role in the variability of SAR.
Key words: adult returns, Columbia River Sockeyesalmon, freshwater influences, modeling, ocean influ-ences, smolt-to-adult returns
INTRODUCTION
Within the Columbia River basin, sockeye salmon(Oncorhynchus nerka) historically spawned in a numberof freshwater systems in Oregon, Idaho, Washington,and British Columbia (Gustafson et al., 1997). Chap-man (1986) estimated that Columbia River adult sock-eye runs ranged from 2.25 to 2.62 million fish in thelate 1800s; Fryer (1995) suggested abundance duringthis same period ranged from 3 to 4 million. Adultabundance crashed in the late 19th and early 20thcenturies due to intense fisheries and habitat destruc-tion, with dam construction on headwater reacheseliminating access to spawning grounds for nearly allsockeye salmon populations, and thus preventing anychance of recovery of fish upstream of most dams(Rich, 1935; Fryer, 1995; Gustafson et al., 1997; Selbieet al., 2007). From 1939 to 1943, adult sockeyetrapped at Rock Island Dam were relocated to LakeWenatchee and Osoyoos Lake, which had muchdepleted sockeye populations but no dams preventingaccess to spawning areas (Fig. 1), or were taken forartificial propagation to one of three national fishhatcheries (Leavenworth, Entiat, and Winthrop)located on tributaries to the Columbia River basinabove Rock Island Dam. Numerous descendants ofartificially propagated sockeye salmon trapped at RockIsland and Bonneville Dams, together with progeny ofLake Quinault sockeye salmon, were also stocked intoLake Wenatchee and Osoyoos Lake between 1940 and1968 (Gustafson et al., 1997). Because results werepoor, hatchery production of sockeye from nationalfish hatcheries was terminated by the early 1960s.After that time, all smolts exiting from LakeWenatchee and Osoyoos Lake were natural migrantsup until the early 1990s, when a new hatchery at RockIsland Dam was constructed and juvenile sockeye
*Correspondence. e-mail: [email protected]†These authors retired from NOAA Fisheries.
raised there were transferred to net pens for furtherrearing in Lake Wenatchee before release. Based onsmolt monitoring at McNary Dam between 1993 and2010, the median annual percentage of naturallyreared smolts in the juvenile migration was 95.5%.
Coincident with construction of numerous main-stem dams on the lower and mid-Columbia River,adult returns from the remnant populations showed adownward trend between the 1950s and mid-1970s,followed by wide fluctuations through the mid-2000s(Fig. 2). Presently, >99% of sockeye salmon in theColumbia River Basin spawn in Lake Wenatchee andOsoyoos Lake, which are located on tributaries thatenter the Columbia River on the east side of the Cas-cade mountain range. The remaining fish are fromremnant populations mostly spawning in several lakesin the Salmon River basin in Idaho, primarily RedfishLake (Fig. 1). The large and unforeseen return ofapproximately 386 000 adults to Bonneville Dam onthe Columbia River in 2010 led salmon managers toask about reasons for the return and whether it wasrelated to changes in hydropower operation.
It is presumed that very few Columbia River sock-eye are caught in the ocean, as there is no directedfishery. Although harvest rates on adults between themouth of the river and Bonneville Dam were some-times >50% historically, in recent decades little to noharvest has occurred in the zone (Fig. 2). Thus, in
recent years adult counts at Bonneville Dam repre-sented nearly 100% of adult returns to the ColumbiaRiver.
In recent years there have been extensive efforts toimprove sockeye production from the Okanagan Basinin Canada. These have included a flow managementtool to allow water managers to better balance theneeds of sockeye salmon smolt and adults with the rec-reation, irrigation, flood control, and kokanee interests(Hyatt and Stockwell, 2009, 2010). Sockeye passagehas been provided at McIntyre Dam, opening up addi-tional spawning and rearing habitat. Hatchery produc-tion has been used to re-introduce sockeye salmoninto Skaha Lake upstream of Osoyoos Lake, with thegoal of ultimately restoring passage of migrants to andfrom this lake at all flows (Wright et al., 2011).Already in years of high flow such as 2011, adults cansuccessfully migrate upstream through the Skaha Damspillway and juveniles can pass the spillway at all flowlevels. Finally, restoration has begun in parts of theriver channelized in the 1950s through restoration ofmeanders by setting back dikes and opening up accessto previously cut-off meanders.
After the Endangered Species Act (ESA) listing ofUpper Columbia River spring Chinook salmon andsteelhead in the mid-1990s, changes to the hydropowersystem were made to improve passage facilities at damsand to modify flow and spill to improve timing of
Figure 1. Map of the Columbia RiverBasin noting the location of extant majorsockeye salmon spawning lakes (Osoyoos,Wenatchee, and Redfish Lakes) andmainstem dams.
juvenile migrants and to increase survival of juvenilesand adults. Presumably, improved conditions for ESA-listed Chinook and steelhead also benefited sockeyesalmon. An internal preliminary evaluation by scien-tists at the Northwest Fisheries Science Center regard-ing changes in adult sockeye salmon counts atBonneville Dam since its completion in 1938 did notsuggest a strong periodicity related to ocean regimeshifts in 1947 and 1977, as reflected in changes in thePacific Decadal Oscillation (PDO) (Mantua et al.,1997).
The pattern of adult sockeye salmon returns to theColumbia River did not match a decadal period ofgood returns in the Fraser River reported for the late1970s to late 1980s (Beamish et al., 2004) but didhave a similar trend as sockeye returns to BarkleySound on the west coast of Vancouver Island (DFO,2011). Although Columbia River sockeye populationsizes were not related to PDO shifts, Hyatt et al.(2003) found that duration and timing of adult returnsthrough the Okanogan River were related to oceanicregime shifts. Above-average and below-average adultsockeye salmon migration delays within the OkanoganRiver occurred with warmer and colder water tempera-tures within the river, and these temperatures corre-sponded with, respectively, warm and cold phases ofthe PDO and the Pacific Northwest Index (PNI). Fur-ther, Hyatt et al. (2003) speculated these delays mightlead to lower or higher spawning success and viabilityof gametes.
Adult abundance alone, however, does not providesufficient information to provide insight into factorsthat have caused variability in adult returns. Therecent increased adult returns could have resulted froman increased number of smolts successfully migrating to
the ocean from rearing lakes or from increased survivalof the smolts that did reach the ocean, or a combina-tion of the two. Again, an internal preliminary evalua-tion by scientists at the Northwest Fisheries ScienceCenter regarding changes in the sockeye smolt passageindex at McNary Dam did not suggest that an increasein number of sockeye smolts migrating from the river in2008 explained the large adult return in 2010.
Thus, to systematically address adult returns relatedto numbers of juveniles, we developed annual esti-mates of smolts and the number of adults they subse-quently produced to provide annual smolt-to-adultreturn rates (SARs), a measure of stock productivity.We analyzed these data in conjunction with a numberof riverine and oceanic variables to assess which fac-tors were associated with Columbia River sockeye sal-mon SARs.
We then compared our Columbia River SAR esti-mates to similar indices for Chilko stocks in the FraserRiver and Barkley Sound stocks on Vancouver Islandto determine whether the wide variability in annualColumbia River sockeye salmon SAR estimates is pos-sibly related to general ocean conditions experiencedby other nearby sockeye salmon stocks from the FraserRiver and the outer coast of Vancouver Island. Finally,we also looked at how management actions in theriver may have influenced overall numbers or qualityof juveniles in recent migrations, as the quality ofjuveniles might affect subsequent survival of smolts.
METHODS
Population demographics and juvenile survival
To estimate adult returns from each year’s smoltmigration, we first obtained data on the annual adult
Figure 2. Annual adult sockeye salmonreturn to the Columbia River (BonnevilleDam count plus harvest below BonnevilleDam), 1938–2012.
sockeye salmon return at Bonneville Dam (BON;Fig. 2) for calendar years 1986–2012 from the Colum-bia River DART web site maintained by the Colum-bia Basin Research group at the University ofWashington (http://www.cbr.washington.edu/dart/query/adult_graph_text). To estimate total adultreturn, we also added the estimated annual catch ofadults downstream of BON (WDFW/ODFW, 2012)to the dam counts.
We estimated the proportion of fish in each age-class based on scale analyses of a sample of returningadults collected at BON by the Columbia River Inter-tribal Fish Commission (CRITFC; Table 1). Fromscale samples, ages were assigned to fish based on theEuropean method of fish aging described by Koo(1962). Age-class patterns have the form of ‘x.y’, with‘x’ denoting the number of annuli in juvenile years(x = 1, 2, 3, or 4 in our data), and ‘y’ the number ofannuli in adult years (y = 1, 2, or 3). For each adultreturn year, we multiplied the estimated proportion offish in each ‘x.y’ age class by the total adult return toassign adult returns to the appropriate juvenile migra-tion year. These estimates were then summed to esti-mate total adult returns from each juvenile migrationyear from 1985 to 2009. For juvenile migration year2010, adult returns will not be complete until late
2013. To estimate adults for 2010, we projected x.3returns in 2013 assuming that average historical(brood years 1982–2006) age-class patterns will holdfor all adults that eventually return from the 2007 and2008 brood years.
We used McNary Dam for our estimation of smoltnumbers because it was the only river location forwhich we could develop a long-term data set of esti-mated population abundance of sockeye smolts.Because our starting point for smolts is MCN, ourSAR estimate includes a component of juvenilemigrant survival between MCN and the river’s mouthwhere, arguably, survival from smolt to adult begins.We lack the data that would be necessary to use astarting point for smolts anywhere downstream ofMCN.
Migrant smolts arriving at MCN can pass down-stream either through the spillways (when operating)or via the powerhouse. Of those entering the turbineintakes at the powerhouse, some percentage are inter-cepted by screens and diverted to the juvenile collec-tion/bypass system, and the remainder pass directlythrough the turbines to the tailrace. To estimate thetotal number of smolts passing MCN, we needed esti-mates of the number of smolts passing through thejuvenile collection/bypass system, and of the
Table 1. Variables assessed in models fitted to Columbia River sockeye salmon SARs.
Number Variables assessed Abbreviations
Freshwater 1 Index of tributary (Upper Columbia) flow trib.fl2 Index of tributary (Upper Columbia) air temperature trib.tp3 Index of tributary (Upper Columbia) precipitation trib.prec4 Median passage date for smolts at McNary Dam med.date5 Index of Lower Columbia River flow lowCR.fl6 Index of Lower Columbia River spill lowCR.sp7 Index of Lower Columbia River water temperature lowCR.tp8 PNI for year before migration year PNI.my-1Ocean 9 Pacific Northwest Index (PNI) for migration year – from DART PNI.my10 North Pacific Index for migration year –- from NCAR GCD NPI.my11 Spring transition date (CBR Mean method – from DART) spr.tran12 Average upwelling index at 45N for April during migration year upw.apr13 Average upwelling index at 45N for June during migration year upw.jun14 Average monthly Pacific Decadal Oscillation (PDO) for
January–December of year before migration yearPDO.my-1
15 Average monthly PDO for April-July of migration year PDO.apr-jul16 Average monthly PDO for ‘first winter’ (November of migration
year to April of year after migration year)PDO.1stwtr
17 Average monthly North Pacific Gyre Oscillation (NPGO) forJanuary–December of year before migration year
NPGO.my-1
18 Average monthly NPGO for April–July of migration year NPGO.apr-jul19 Average monthly NPGO for “first winter” (November of migration
year to April of year after migration year)NPGO.1stwtr
proportion of the total run passing the dam that thisrepresented.
We estimated the annual number of smolts thatentered the juvenile collection/bypass system by com-bining daily collection counts of hatchery and wildsmolts from the Smolt Monitoring Program (SMP;data obtained from the Fish Passage Center Website,http://www.fpc.org/) and summing across the season.In earlier years of the data set, the SMP sampled dailyat MCN throughout the season, but since 2003, sam-pling has been done every other day in the springtimeand daily during the summer. Thus, to estimate thetotal-season smolt collection we needed to account fordays not sampled. To do this, we identified the periodof every-other-day sampling within each year and dou-bled the total count during that period. The summa-tion of these adjusted counts provided an estimate ofthe annual total number of juvenile sockeye thatpassed through the collection/bypass system at MCN.
To estimate the proportion of the total run thatentered the juvenile collection/bypass system, we usedstatistical methods for capture-recapture data (Cor-mack, 1964; Jolly, 1965; Seber, 1965) applied to PIT-tagged fish. The SMP has yearly sampled sockeyejuveniles at Rock Island Dam and PIT-tagged them forrelease in the tailrace. These PIT-tagged fish providethe basis for estimates of travel time and survival prob-ability of sockeye smolts migrating from Rock IslandDam to MCN. The statistical model used to estimatesurvival also provides an estimate of ‘detection proba-bility’; the proportion of fish that that survived toMCN that were detected at the dam. The collection/bypass system contains PIT-tag detector units thatidentify PIT-tagged fish as they pass. The detectorsidentify each individual tag code and store the infor-mation in a computer data base. For the period 1996–2001, 97–99% of PIT-tagged fish that passed throughthe MCN collection/bypass system were detected, andfrom 2002 to present (with the installation of newdetection equipment on the large bypass flume) theproportion has been >99% (Axel et al., 2005). Forsimplicity, we assumed 100% of PIT-tagged fish pass-ing through the collection/bypass system weredetected. Thus, the detection probability estimatefrom the capture–recapture model was equivalent toan estimate of the proportion of PIT-tagged fish pass-ing MCN that passed via the collection/bypass system.Because the PIT-tagged fish were a representative sam-ple of the total untagged population passing RockIsland Dam, we assumed that PIT-tagged and untaggedfish used the various passage routes at MCN in thesame proportions. To estimate the annual total num-ber of smolts passing McNary Dam, we divided the
estimated annual total of fish passing through the col-lection/bypass system by the estimated detection prob-ability derived from PIT-tagged fish. Because almostall sockeye smolts passing MCN were wild (95.5% ofthe annual juvenile migration from 1995 to 2009) andbecause no hatchery fish were PIT tagged in mostyears, we used the detection probability efficiencyderived from PIT-tagged wild fish.
Although smolt monitoring data at MCN are avail-able since 1985, we were not able to use the above pro-cedure until migration year 1996, the first year forwhich PIT-tag data were sufficient. We also lack datafrom migration year 2003, because no fish were PIT-tagged that year. To extend the time series of smoltabundance estimates back to 1985, we noted that oursmolt abundance estimates described above were veryhighly correlated (r = 0.98, P < 0.001) with theannual sum of the daily ‘passage index’ from the SMPsampling reports. We used simple linear regression ondata from 1996 to 2012 (excluding 2003) to derive anequation to estimate the total number of smolts pass-ing McNary Dam in migration years 1985–1995 and2003:
Smolts ¼ 2:83 � PIwhere PI is the annual sum of daily passage indices
for hatchery and wild sockeye smolts.We lacked estimates of smolt abundance migrating
from Lake Wenatchee and Osoyoos Lake that enteredthe Columbia River, or how they varied among years.However, we did have reasonably precise survival esti-mates derived by NOAA Fisheries for the period1997–2011 (with the exception of 2003) for smoltsmigrating in the Columbia River from Rock IslandDam to McNary Dam (Faulkner et al., 2011). Forsomewhat fewer years, and with much lower precision,we also had survival estimates for smolts migratingfrom McNary Dam to Bonneville Dam (Faulkneret al., 2011). The estimates were based on sockeyesmolts sampled, PIT-tagged, and released at RockIsland Dam and detected at downstream samplingsites. We compared these estimates with adult returnsand SARs as described below.
Smolt-to-adult return rate (SAR)
We estimated annual SAR for juvenile migration years1985–2010 as the percent of the estimated number ofsmolts passing McNary Dam each year that ultimatelyreturned as adults to the Columbia River. SAR repre-sents the multiplicative effects of a number of survivalevents. Also, the range in estimated SARs was wide(two orders of magnitude). Thus, we used a logarith-mic transformation of SAR as the response variable in
our models, both to linearize the equation and to stabi-lize the variance across the range of the response.
Comparison of Columbia River, Fraser River and BarkleySound SARs
The Department of Fisheries and Ocean Canada(DFO) has for a number of years used data derivedfrom sockeye salmon from the Chilko Lake system inthe Fraser River Basin to estimate smolt-to-adultrecruitment as an index of marine survival. Likewise,they have made estimates of pre-smolt to adult recruitsin several lake systems emptying into Barkley Soundon the western coast of Vancouver Island. Similar toour estimates of Columbia River SARs, their estimatesinclude mortality to smolts in freshwater. Thus, smolt-to-adult recruitment of Fraser River and BarkleySound sockeye provide the same relative life-stage sur-vival as SAR for Columbia River sockeye becausereturning adults to the Columbia are at the recruitstage similar to British Columbia stocks before marinefisheries occur.
We derived an annual SAR index for the Chilkosystem for the 1985–2009 juvenile outmigration yearsby transforming annual ln(recruit/smolt) estimatesplotted in the Canadian Science Advisory SecretariatResearch Document 2012/011 (MacDonald andGrant, 2012), and compared the Chilko index withour annual estimates of Columbia River sockeye sal-mon SARs. We note that estimates for the 2007–2009Chilko Lake smolt migration years were based onincomplete adult returns and are thus preliminary andsubject to change.
We also compared averaged annual estimates of‘marine survival’ for Barkley Sound sockeye stocks(from Sprout Lake and Grand Central Lake) to ourColumbia River SARs for juvenile migration years1985–2008. Data for Barkley Sound pre-smolt to adultrecruits are unpublished (K. Hyatt, DFO – Pacific Bio-logical Station, Nanaimo, BC, Canada, personalcommunication)
Relating SARs to environmental factors
We evaluated a suite of variables we considered likelyto influence the growth and survival of juvenile sock-eye salmon and thus, their eventual return as adults.We categorized these as potential effects in (1) fresh-water rearing and migratory phases of the life-cycle,and (2) the ocean environment (Table 2). Variableswere aligned according to smolt migration year. Foruse in the regression analysis, each variable describedbelow was normalized as follows: we calculated themean (�X and standard deviation (Sx) across the years1985–2010 and then calculated the normalized
variable as: X0i ¼ Xi�ðXÞ
Sx. All resulting variables had
mean 0 and variance 1.While our estimates of SAR begin with smolts at
McNary Dam, conditions experienced by smolts beforethey arrive at McNary Dam (i.e., in juvenile rearingareas or in tributary systems) may affect their size orquality upon arrival at the dam and, therefore, theirsubsequent SAR. We had no information on size offish arriving at McNary Dam, but a preliminary analy-sis of smolt length at Rock Island Dam found no rela-tionship between annual median length and SAR(R2 = 0.05, P = 0.43). Because size of fish often relatesto conditions in the rearing area, we derived indices oftributary flow, air temperature, and precipitation fromnearest possible sites to lakes where fish spawn. ForOsoyoos Lake fish, we collected monthly data on mean
Table 2. Summary of age-class percentage, based on scalepattern analysis from adult sockeye salmon sampled yearly atBonneville Dam, 1985–2013.
air temperature (°C) and precipitation (cm) at Pentic-ton, B.C. (http://www.tutiempo.net/en/Climate/Pen-ticton/04-2008/718890.htm), and river flow (cfs) inthe Okanogan River near Oroville, WA [http://water-data.usgs.gov/WA/nwis/current/?type = flow [see12439500)]. For Lake Wenatchee fish, we usedmonthly mean air temperature (°C) and precipitation(cm) data at Leavenworth, WA (http://www.ncdc.noaa.gov/cdo-web/datasets/GHCNDMS/locations/ZIP:98826/detail), and river flow at Peshastin, WA [http://waterdata.usgs.gov/WA/nwis/current/?type = flow (see12459000)]. For each index we averaged the monthlyvalues for September of the year preceding migrationthrough April of the migration year. We then com-bined the indices for the two tributaries into a singleweighted mean with weights in proportion to the rela-tive contribution of smolts from each tributary (80%Okanogan, 20% Wenatchee), resulting in tributaryindices of river flow (trib.fl), air temperature (trib.tp),and precipitation (trib.prec).
Because timing of arrival to the ocean influencedeventual SAR for Chinook salmon and steelhead(Scheuerell et al., 2009), we developed an index forthe timing of the smolt migration at MCN from theannual smolt passage index (see estimation of smoltpassage above). We calculated the median date of pas-sage at MCN as the date on which the 50th percentileof the cumulative smolt index occurred (med.date).Although in some years the distribution past MCNwas bimodal (smolts from Lake Wenatchee migrateearlier than those from Osoyoos Lake), this variableprovided an index of migration timing, particularlyindicating when migration occurred early or late.Migration timing related generally to flow, with higherflows from tributaries and the mainstem ColumbiaRiver leading to earlier migration.
Because of particular concerns by managers abouthydropower operations and their effects on adultreturns, we developed indices for daily average flow(lowCR.fl), percentage of spill (lowCR.sp), and watertemperature (lowCR.tp) in the lower mainstemColumbia River. For each of the three variables ateach dam we weighted the mean of the daily averagewith weights equal to the passage index for that day.To index the entire Lower Columbia River, we thenaveraged the index for each factor across the threedams.
As a measure of warmer/drier versus cooler/wettergeneral climatic conditions in the Pacific Northwest,we used the Pacific Northwest Index (PNI) developedby Ebbesmeyer and Strickland (1995), and retrievedfrom the DART website. This index was developed toevaluate how changes in ocean conditions off the
Washington coast, and possibly freshwater runoff,potentially affected oysters in Willapa Bay. They rec-ognized that complex interactions of coastal and oce-anic winds driving upwelling and coastal circulationpatterns, along with general oceanic circulation pat-terns, influenced coastal seawater temperatures, pre-cipitation patterns, and food sources that potentiallyaffected the oyster condition index. Further, theydetermined they could index changes in this complexinteraction off the Washington coast by measuring ter-restrial conditions in the State of Washington. Coolerwater temperatures off the Washington coast, andweather patterns that channeled greater volumes ofmoisture to the coast led to lower terrestrial air andwater temperatures, and higher snow pack. Con-versely, oceanic conditions that led to warmer oceantemperatures and weather patterns bringing less mois-ture led to higher terrestrial air and water temperaturesand lower snow pack. Variations in these patterns alsoaffect the biomass and species composition of oceanzooplankton (Peterson and Schwing, 2003). Thus, thePNI has the value of indexing not only a complex ofcoastal ocean conditions and weather patterns on ageographical scale smaller than the larger scale indicessuch as ENSO or PDO, but also environmental condi-tions that result from changing ocean conditions.
The PNI is derived from terrestrial measurementsbased on temperature, precipitation, and snowpack.Thus, we used the PNI in the year prior to the juvenilemigration (PNI.my-1) to provide a broad index of ter-restrial conditions during the period of fry/parr rearingthat might not get captured in the temperature, pre-cipitation, and flow measurements. It also possibly cap-tures changes in temperatures leading to differences inmigration timing or annual differences in river flowthroughout the basin during the year of the smoltmigration. We used PNI in the juvenile migration year(PNI.my) as an index of non-specific ocean conditionsoff the Washington coast that smolts experiencedwhen entering the ocean.
We also evaluated five other indices, in various rep-resentations, that others have used to relate climate/ocean conditions to variability in Pacific salmon popu-lations. We used the monthly North Pacific Index(NPI) (Trenberth and Hurrell, 1994) from the Cli-mate Analysis Section, NCAR, Boulder, U.S.A.(http://www.cgd.ucar.edu/cas/jhurrell/npindex.html).The NPI is a measure of the average atmospheric pres-sure at sea level over the North Pacific. We used theaverage of monthly NPI values from the winter(November through March) before sockeye smoltmigration. Changes in pressure lead to broad changesin wind patterns and temperatures. We used spring
transition date (‘CBR Mean Method’) (spr.tran) fromthe DART website. Based on indices of the intensityof large-scale, wind-induced coastal upwelling, theCBR Mean method is intended to determine the dateon which conditions switch from downwelling toupwelling. Earlier spring transition should result inmore productive waters at the time when sockeyesmolts first enter the ocean. We also developed directindices for actual upwelling, retrieving data from awebsite maintained by NOAA’s Pacific Fisheries Envi-ronmental Laboratory (http://www.pfeg.noaa.gov/products/PFEL).
We used average April ocean-upwelling at 45°Nand 125°W (upw.apr) because Scheuerell and Wil-liams (2005) found that it had a strong influence onColumbia River Chinook salmon SAR, and becauseupwelling intensity is associated with differing zoo-plankton composition (Keister et al., 2011). We chosethe April upwelling index because upwelling affectsprimary productivity, which is then sometimes fol-lowed by zooplankton increases (El-Sabaawi et al.,2012). Since Columbia River sockeye smolts enter theocean from about mid-May to mid-June, lagged zoo-plankton blooms following April upwelling mightinfluence sockeye smolt survival. On the other hand,Liu and Peterson (2010) did not find a correlationbetween Neocalanus sp. abundance off the Oregoncoast and coastal upwelling, so we also used upwellingdata for June (upw.jun) to represent the period whenColumbia River sockeye smolts enter the ocean andbegin to migrate north.
For the final variables we used representations ofthe Pacific Decadal Oscillation (PDO) because cyclesof the PDO have been found to relate to cycles in sal-mon production cycles (Mantua et al., 1997; Hareet al., 1999) and the North Pacific Gyre Oscillation(NPGO) because the NPGO correlates well withsalinity, nutrients, and chlorophyll in the North East-ern Pacific Ocean (Di Lorenzo et al., 2008) and thesehelp drive primary productivity in the North PacificOcean. We used monthly PDO values from the web-site maintained by the Joint Institute for the Study ofthe Atmosphere and Ocean (http://jisao.washington.edu/pdo/PDO.latest). We evaluated several differentperiods of PDO indices, including the year prior tomigration (annual average) (PDO.my-1), as it mayinfluence the ocean conditions that fish experiencedon arrival; April–July (PDO.apr-jul) of the migrationyear, to correspond to the period encompassing thejuvenile migration and to compare the NPGO(below); and November of the migration year throughApril of following year (PDO.1stwtr), as the first win-ter may affect year-class survival (Scheuerell and
Williams, 2005). For the NPGO indices we retrieveddata from the website maintained by E. Di Lorenzo(http://www.o3d.org/npgo/). Similar to the PDO vari-ables, we developed indices for the year prior to migra-tion (NPGO.my-1), April to July of the juvenilemigration year (NPGO.apr-jul), and during the firstwinter at sea (November of migration year throughApril of the following year (NPGO.1stwtr).
Model selection
We used information-theoretic methods for multi-model inference (Burnham and Anderson, 2002) toinvestigate the relative support provided by the datafor a suite of regression models between the responsevariable (log-SAR) and subsets of the normalizedexplanatory variables. Altogether we considered 19candidate explanatory variables, as described above, ina data set that included 26 observations. Out of con-cern for potential over-fitting of the data, we restrictedcandidate models to those including at most threeexplanatory variables (plus an intercept parameter),and with no non-linear terms or interactions. With 19candidate variables, there were 1159 possible models.All models were ranked according to Akaike’s infor-mation criterion with small sample correction (AICc),and sorted in decreasing order of AICc-weight. Weconstructed a 95% confidence set of models, whichconsists of the smallest possible set of models whoseAICc-weight sums to 0.95. We also computed AICc
-weights for each variable which measure the overallstrength of evidence for each predictor on a scale from0 to 1.
RESULTS
Demographics
Adult returns from the juvenile migrations in 2008and 2010 were two to three times greater than anyothers in the last 26 yr (Table 3); however, they wereproducts of two different processes. The return from2008 resulted from a high SAR, whereas the returnfrom 2010 resulted from a juvenile migration nearlydouble the size of other migrations over the yearsevaluated. While the number of smolts within migra-tion years varied (Table 4), the annual survival ofsmolts in the hydropower system from Rock IslandDam to McNary Dam had a positively increasingtrend (slope = 0.02 increase per year, r = 0.78,P < 0.01) over 1997–2010 (Fig. 3). There was a sta-tistically significant, although moderate, correlationbetween numbers of smolts in the juvenile migrationat McNary Dam and subsequent Columbia Riveradult return (r = 0.64, P < 0.01; both variables
log-transformed; Fig. 4). Smolt survival estimatesdownstream from McNary Dam were very impreciseand NOAA Fisheries estimated survival only for lim-ited years and only between McNary and BonnevilleDams (Faulkner et al., 2011) (Fig. 5).
Smolt-to-adult return rate (SAR)
The estimated annual SAR of the Columbia Riversockeye salmon population for migration years 1985through 2010 ranged widely, from 0.2% for 1993 to23.5% for 2008 (Table 4). The highest estimated SARcorresponded with the large Columbia River adultreturn in 2010 (Fig. 2). The highest Columbia Riveradult return occurred in 2012, mainly from the 2010juvenile migration, but the SAR from the 2010 migra-tion was less than one-third of the 2008 migration.The large adult return in 2012 came from a juvenilemigration with nearly double the number of smolts ofany other migration, whereas the large return in 2010came from a migration with smolt numbers slightlylower than average.
Comparison of Columbia River, Fraser River, and BarkleySound SARs
Columbia River sockeye salmon SARs had virtuallyno correlation with Fraser River (based on Chilko sys-tem stocks) sockeye salmon SARs (r = �0.13,P > 0.50), whereas they were moderately correlatedwith Barkley Sound sockeye salmon SARs (r = 0.66,P < 0.01; Fig. 6).
Model selection
The 95% confidence set included only 21 of the 1159candidate models, and April upwelling was in everyone of them (Table 5). The migration-year PNI was inthe 11 highest-weight models and 18 of the top 19.April upwelling had a variable weight of 0.996, andthe PNI in the migration year was close behind at0.927 (Table 6). The next highest variable wasPNI.my-1, with a variable weight of 0.499. All othervariable weights were very low. The ratio betweenAICc-weights for two models is called the ‘evidence
Table 3. Estimated age-class percentage of returning adults, with the estimated total adult return from each juvenile migrationyear, 1985–2010.
ratio’. The evidence ratio between the first two modelswas almost exactly equal to 10.0, which is consideredquite strong evidence for the best model (Burnhamand Anderson, 2002). Thus, the best model, whichincludes the three variables April upwelling, PNI inthe migration year, and PNI.my-1, was far better sup-ported by the data than any of the other models. Thebest model explained 82.1% of the variability in log-(SAR).
Because the covariates were all normalized, the rel-ative effect of variation was well summarized by themodel-averaged coefficients (and relative magnitudeof the estimated coefficients was roughly equal to therelative variable weight). Model-averaged coefficientsindicated that the sockeye SAR correlated positivelywith April upwelling and negatively with PNI: Aprilupwelling with the highest positive intensity led tohigher SARs. Ocean conditions and weather patterns
leading to warmer and drier terrestrial conditions(higher values of the PNI) in the migration year wereassociated with lower SARs and conditions leading tocooler and wetter conditions were associated withhigher SARs.
DISCUSSION
Since the construction of Bonneville Dam in 1938,the two largest adult sockeye salmon returns to theColumbia River have occurred in recent years, yet thesmolt-to-adult return rates for those 2 yr were substan-tially different. The large adult return from the 2008outmigration (adults returning primarily in 2010)occurred because of high survival from juvenile to
Figure 3. Estimated annual survival of juvenile sockeye sal-mon migrating from Rock Island to McNary Dam, 1997–2010 (2003 not available).
Figure 4. Estimated annual sockeye salmon smolt abun-dance at McNary Dam and estimated subsequent adultreturn to the Columbia River (Bonneville Dam count plusharvest below Bonneville Dam), 1985–2010 for smolts and1986–2012 for adults. (Linear regression line curves whenplotted on a log scale.)
Table 4. Estimated smolt-to-adult return rate (SAR) forsmolts migrating from McNary Dam as juveniles and return-ing to the Columbia River as adults (Bonneville Damcount + estimated lower river harvest), 1985–2010.
adult, whereas the high adult return in 2012 occurredbecause of a huge number of juveniles; survival fromjuvenile to adult was only one-third of the 2008 out-migration. The SAR of the composite Columbia Riverbasin sockeye salmon population has fluctuated widelysince 1985.
At first glance, SARs from the 2008 and 2009 juve-nile migrations may seem surprisingly high comparedwith the long-term time series. However, the range ofour estimates for Columbia River basin sockeye sal-mon falls within the range of SARs for other southernpopulations of North Pacific Ocean sockeye salmon,for example those in southern British Columbia, Can-ada, and Lake Washington in Washington State(Koenings et al., 1993). On the other hand, the trendof SAR in the Columbia River from 1985 through2005 was relatively flat as compared with the generaldownward trend in productivity estimates of sockeye
salmon stocks from the Fraser River (based on theChilko stock) and other coastal rivers (McKinnellet al., 2011; Peterman and Dorner, 2011), but Colum-bia River SAR varied similarly to sockeye SARs forBarkley Sound (Fig. 6). Peterman et al. (1998) foundthat environmental processes that affect variation insockeye survival operate on regional scales, rather thanon a larger ocean-basin scale, and that there was littleevidence of strong co-variation in marine survivalrates among stocks from different regions. Juvenilesfrom Barkley Sound and the Fraser and Columbia Riv-ers migrate to the Gulf of Alaska and grow there toadult size, suggesting that differences in SARs betweenthe stocks result from factors affecting juvenile migra-tions in areas of the ocean where they do not migratein common. Related to low return of adults from the2007 juvenile migration from the Fraser River, McKin-nell et al. (2011) speculated that Fraser River smoltsdied from warm water conditions in the area of QueenCharlotte Sound/Strait. Juveniles from the 2007migrations from the Columbia River and BarkleySound did not have low returns; they migrated fartheroffshore and therefore avoided the poor conditionsfaced by the inshore migrating Fraser River stocks.Our results support the hypothesis that adult returns tothe Fraser River from the 2007 outmigration weredecreased as a result of the migration route of juvenilesbefore entering the Gulf of Alaska.
In the river reach between McNary and BonnevilleDams available estimates of smolt survival are veryimprecise and we have no smolt survival estimatesfrom Bonneville Dam to the mouth of the ColumbiaRiver, thus impairing our ability to completely sepa-rate freshwater from seawater factors influencing SARsin recent years. However, for migration years 2008 and2010, freshwater survival estimates over the riverreach between McNary and Bonneville Dams wereessentially the same. This suggests that unless therewere considerable differences in survival during thefreshwater migration between Bonneville Dam andthe ocean, differences in ocean conditions had thegreatest influence on the threefold difference in SARsbetween the 2 yr. Although mortality to smolts infreshwater downstream of Bonneville Dam likelyoccurs, we know of no data nor can we hypothesize areasonable mechanism that would lead toward widelyvarying inter-annual changes in mortality. Thus, weconcluded that ocean conditions probably caused thelarge difference in SARs.
With exception of PNI in the year before themigration year (PNI.my-1), all our candidate variablesthat related to specific freshwater conditions had lowweights compared with the April upwelling and PNI
Figure 5. Estimated annual survival of juvenile sockeye sal-mon migrating from McNary Dam to Bonneville Dam foravailable years of data 1999–2010.
Figure 6. Estimated smolt-to-adult return rates for sockeyesalmon juveniles migrating from the Columbia River (1985–2010), the Fraser River (Chilko Lake system 1985–2009),and Barkley Sound on the west coast of Vancouver Island(Sprout and Grand Central Lakes 1985–2008).
in the migration year and they had similar weights tothe remaining candidate variables related to oceanconditions. This suggests that specific freshwater con-ditions within the migration year had little influenceon subsequent SARs. Potentially, overall warmer orcooler climate (as indexed broadly by PNI.my-1) hadsome influence on fish prior to migration or across a
broad composite of freshwater conditions within amigration year. On the other hand, analysis of theresiduals of the regression models – not reported here –suggested that there might be some mild autocorrela-tion present in the time series, and that the support forPNI.my-1 might simply reflect that this ‘lag-1’ versionof the important predictor variable PNI.my is pickingup a bit of the autocorrelation signal. Overall, adjust-ing for the mild autocorrelation had almost no effecton the importance of the April upwelling and PNI.myvariables.
As noted above, smolt survival between RockIsland and McNary Dams had an increasing trendthrough time, which might be expected to increasenumbers of smolts arriving at McNary Dam. Whilenumbers of smolts were not correlated with subsequentSARs, the number of smolts was moderately correlatedwith adult returns. Thus, improvement in survivalfrom smolt rearing areas, particularly between RockIsland and McNary dams, appears to have benefitedsockeye stocks.
Upwelling off the northern Oregon/Washingtoncoast increases chlorophyll concentrations, which inturn increases zooplankton and fish density (Hickeyand Banas, 2008). Stronger upwelling in April mayincrease nutrients sufficiently near the coast to boostphytoplankton blooms. Increased blooms may in turnlead to increased zooplankton communities and
Table 5. Models in 95% confidence set fitted to ColumbiaRiver sockeye salmon SARs from the 1985–2010 outmigra-tions. K includes the number of predictor variables in themodel, the intercept, and the variance.
Table 6. Variable weights and model-averaged coefficientsfor models fitted to Columbia River sockeye salmon SARsfor juvenile migration years 1985–2010.
VariableOcean orfreshwater
Variableweight Estimate (SE)
upw.apr O 0.996 0.559 (0.116)PNI.my O 0.927 �0.387 (0.131)PNI.my-1 F 0.499 �0.132 (0.149)lowCR.fl F 0.059 0.016 (0.034)NPGO.ap-jl O 0.055 0.011 (0.023)spr.tran O 0.046 �0.008 (0.018)med.date F 0.045 0.007 (0.015)NPGO.1stwtr O 0.041 0.008 (0.017)PDO.ap-jl O 0.038 �0.008 (0.016)NPGO.my-1 O 0.035 0.005 (0.012)trib.fl F 0.035 �0.005 (0.011)PDO.my-1 O 0.032 �0.004 (0.009)trib.prec F 0.031 �0.004 (0.009)PDO.1stwtr O 0.021 �0.002 (0.006)NPI.my O 0.021 0.002 (0.006)lowCR.sp F 0.019 0.002 (0.006)lowCR.tp F 0.019 �0.001 (0.004)upw.jun O 0.014 0.0004 (0.002)trib.temp F 0.013 0.00005 (0.002)
provide a larger prey base for sockeye smolts enteringthe ocean from the Columbia River in late May/earlyJune. The variability in the strength of the Aprilupwelling had a high association with sockeye SARs.In contrast, the June upwelling did not associate withSARs apparently because at the time of the smoltmigration, upwelling did not have an immediate posi-tive effect on the zooplankton community. The Aprilupwelling index was in all the best-supported models;there is clearly more evidence for its association withsockeye SARs than any of the other variables.
The PNI was developed to understand dynamics ofoysters in Willapa Bay (Ebbesmeyer and Strickland,1995). Thus, while the index is based on terrestrialmeasurements, the complex of ocean conditions andwind patterns off the Washington coast led to the ter-restrial conditions used in the index. Lower terrestrialtemperatures, greater precipitation, and greater snow-pack are the result of colder ocean waters and atmo-spheric conditions over ocean waters, whereas theopposite occurs under warmer ocean conditions andatmospheric conditions that lead to less precipitation.We think the high degree of support in the data forthe April upwelling and PNI effect on SAR is relatedmostly to the regional conditions in the northern Cali-fornia Current System off the Washington coast andthe southern portion of Vancouver Island, BritishColumbia, experienced by Columbia River sockeyesmolts when they first enter the ocean. We think thedifference in SARs between the Fraser River Chilkostock and Columbia River sockeye supports this con-clusion. Because of the complexity of ocean conditionsrepresented by the PNI, we cannot identify which con-ditions make the most difference. Certainly, PNI.myprovided information independent of the other oceanindices – the greatest R2 with any ocean index wasonly 19.5% (with NPI.my); the correlation with Aprilupwelling was weaker (R2 = 11%). Other than Aprilupwelling, none of the other individual ocean indiceswe considered had high weights in our models. Whileother researchers have found that West coast salmonpopulations generally have higher productivity undercooler ocean conditions, as indicated by a negativePDO (Hare and Mantua, 2000; Mantua and Hare,2002; Zabel et al., 2006), April upwelling and thePNI.my provided a stronger signal for Columbia Riversockeye salmon. This may relate to the scale of mostocean indices. The PDO encompasses a much largeroceanographic area than do upwelling and PNI.Cooler conditions represented by the PNI also corre-late with changes in zooplankton species compositionoff the Oregon coast (Peterson and Schwing, 2003;McClatchie et al., 2009; Keister et al., 2011). The
increased abundance in recent years of the northerncopepods Calanus marshallae, Pseudocalanus mimus, andAcartia longiremis (http://www.nwfsc.noaa.gov/research/divisions/fed/oeip/a-ecinhome.cfm) may haveimproved the food base for sockeye salmon juveniles(Landingham et al., 1998). Our results suggest thatocean conditions encountered by Columbia Riversockeye smolts immediately upon entering the oceanhave a large effect on subsequent survival. Unfortu-nately, we have no direct evidence for this. As detailedbelow, NOAA Fisheries has conducted ocean researchfor a number of years. As part of these studies, theyhave intensively sampled the Columbia River plumesince 1999. However, sockeye juveniles have onlybeen caught sporadically, and there was no correlationbetween the catch per unit of effort and either thesmolt population at McNary Dam or SAR. Because oflow and sporadic sockeye catches, NOAA Fisherieshas not taken many stomach samples of catches ofthese fish. Thus, there is a paucity of information onsockeye in their early ocean phase off coastalWashington.
In addition to following copepod productivity,NOAA has evaluated a number of other data setsrelating marine survival of Chinook and coho salmonto different indices. In 2005, all indicators were con-sidered poor for salmon survival, but in 2006 someindicators began to transition to more favorable condi-tions. In general, however, the 2006 ocean systemindicators appeared to provide moderate conditions, atbest, for salmon survival. Thus, the large number ofadult sockeye salmon returning to Bonneville Dam in2008 was not expected.
The lack of concordance in early ocean survivalvariability of sockeye salmon with Chinook and cohosalmon may relate partially to differences in migrationtiming. Sockeye salmon smolts migrate past Bonne-ville Dam, on average, about 2 weeks later than juve-niles of the other spring-migrating species andpotentially experience slightly changed physical con-ditions on entering the ocean. We note, however, thatmedian timing of sockeye smolts past Bonneville Damin 2008 and 2010 was nearly the same, whereas theSAR varied greatly. While Scheuerell et al. (2009)found that differences in migration timing of Chinooksalmon smolts passing Bonneville Dam were related todifferences in subsequent adult return rates, the pas-sage distribution of sockeye smolts at the dam wasmuch more compressed than that of Chinook salmon.This likely limited our ability to detect effects of smolttiming on subsequent adult returns.
We think it more likely that differences betweenColumbia River sockeye return rates and those for
Chinook and coho relate to differences in food sourcesutilized by the difference stocks. Sockeye salmon uti-lize ocean food resources differently, generally feedinglower in the trophic system (Brodeur and Pearcy,1990; Higgs et al., 1995; Landingham et al., 1998;Johnson and Schindler, 2009). Possibly, sockeye cantake immediate advantage of changes from poorer tobetter ocean conditions with favorable changes inupwelling conditions, whereas other species must waitfor the effects of changes to work up the food chain.
While our modeling found that factors downstreamfrom Bonneville Dam were associated most with therecent high SAR of Columbia River sockeye, this doesnot rule out the possibility that freshwater conditionsimproved the number of smolts and overall rates ofjuvenile survival and, thus, the magnitude of adultreturns. Certainly, we found improved freshwater sur-vival in smolts upstream of McNary Dam over timeand this should have led to a general increase in thenumber of smolts arriving at McNary Dam. Althoughwe found no correlation between smolt numbers andSARs, increased numbers of smolts have a positiverelationship with adult returns. We think that recentefforts by First Nations people and DFO in BritishColumbia to provide better migratory conditions foradults and smolts entering and leaving the Osoyoosand Skaha lakes have improved conditions for fish sur-vival (Hyatt and Stockwell, 2010) and that theseactions likely helped to increase adult returns.
If large annual changes in survival occurred in thefreshwater portion of the smolt migration downstreamof Bonneville Dam, and these changes were not cap-tured in our indices of lower Columbia River watertemperature, flow discharge, or the percentage of spillat dams, then it would lessen our ability to attributeocean factors to changes in SAR. We have no obviousway to address this issue. As noted above, however,the returns from the 2008 and 2010 smolt migrationswere much larger than other years, and the SAR in2008 was triple that of 2010. Thus, although our analy-ses were correlative, our results suggest that conditionsin the northern California Current System that sock-eye salmon juveniles first encounter on entering theocean have a large influence on future adult returns tothe Columbia River.
ACKNOWLEDGEMENTS
We thank Marc Trudel and an anonymous reviewerfor detailed comments on two versions of this manu-script. Responding to their concerns led to a muchimproved final product. We also thank numerous fieldbiologists and technicians from the smolt monitoring
program who sampled and marked smolts, and fieldbiologists and technicians from the CRITFC who sam-pled and took scales from returning adults. Jeff Fryerread all of the scales. Without their efforts, we wouldnot have had the data needed to conduct our analyses.
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