Canadian Journal of Fisheries and Aquatic Sciences. Seasonal and Spatial Patterns of Growth of Rainbow Trout in the Colorado River in Grand Canyon, AZ

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1 Seasonal and Spatal Patterns of Growth of Ranbow Trout n the Colorado Rver n Grand Canyon, AZ Journal: Manuscrpt ID cjfas-15-2.r1 Manuscrpt Type: Artcle Date Submtted by the Author: 23-Jun-15 Complete Lst of Authors: Yard, Mcheal; Grand Canyon Montorng and Research Center, Korman, Josh; Ecometrc Research Inc. Walters, Carl; Unversty of Brtsh Columba, Fsheres Centre Kennedy, Ted; Grand Canyon Montorng and Research Center, ; USGS, Grand Canyon Montorng and Research Center Keyword: RIVERS < Envronment/Habtat, DAMS < Envronment/Habtat, FRESHWATER FISHERIES < General, GROWTH < General, POPULATION DYNAMICS < General

2 Page 1 of Seasonal and Spatal Patterns of Growth of Ranbow Trout n the Colorado Rver n Grand Canyon, AZ Mchael D. Yard 1, Josh Korman 2, Carl J. Walters 3, and Theodore A. Kennedy U.S. Geologcal Survey, Southwest Bologcal Scence Center, Grand Canyon Montorng and Research Center, 2255 N. Gemn Dr., Flagstaff, AZ 861, USA. myard@usgs.gov 2 Ecometrc Research Inc., 356 W 22 nd Ave., Vancouver, BC V6S 1J3, Canada. jkorman@ecometrc.com Fsheres Centre, Aquatc Ecosystems Research Laboratory, 22 Man Mall, Unversty of Brtsh Columba, Vancouver, BC V6T 1Z4, Canada. c.walters@fsheres.ubc.ca June 23,

3 Page 2 of Abstract Ranbow trout (Oncorhynchus mykss) have been purposely ntroduced n many regulated rvers, wth nadvertent consequences on natve fshes. We descrbe how trout growth rates and condton could be nfluencng trout populaton dynamcs n a 13-km secton of the Colorado Rver below Glen Canyon based on a large-scale mark-recapture program where ~8, ranbow trout were recaptured over a 3-year perod (12-14). There were strong temporal and spatal varatons n growth n both length and weght as predcted from von Bertalanffy and boenergetc models, respectvely. There was more evdence for seasonal varaton n the growth coeffcent and annual varaton n the asymptotc length. Boenergetc models showed more varablty for growth n weght across seasons and years than across reaches. These patterns were consstent wth strong seasonal varaton n nvertebrate drft and effects of turbdty on foragng effcency. Hghest growth rates and relatve condton occurred n downstream reaches wth lower trout denstes. Results ndcate that reducton n ranbow trout abundance n Glen Canyon wll lkely ncrease trout sze n the talwater fshery and may reduce downstream dspersal nto Grand Canyon. Keywords: Growth, Boenergetcs, Populaton Dynamcs, Rvers, Salmonds 33 2

4 Page 3 of Introducton Body sze and growth exert a strong nfluence on fsh populaton dynamcs (Xu et al. ), and growth rate s often used as a surrogate measure of ftness (Schluter 1995). Rapd growth leads to larger body sze and greater fecundty or earler sexual maturaton, whch can mprove ftness (Hutchngs and Jones 1998; Utrlla and Lobon-Cerva 1999). Slower growth wll ncrease the tme ndvduals are exposed to hgher predaton rates f predaton s greater for smaller fsh (Houde 1987; Rce et al. 1993), or ncrease rsk of starvaton durng perods of low food avalablty (Hurst 7; Lnnansaar and Cunjak ). Growth may be an mportant determnant of movement (Wysujack et al. 8; Olsson et al. 6; Jonsson and Jonsson 11). Theoretcally, anmals should dstrbute themselves such that growth and reproducton are maxmzed (Montgomery et al. 1991), but ndvduals must trade-off the benefts of movng to envronments wth more food or reduced competton wth the dsadvantages assocated wth movement, whch mght nclude ncreased predaton durng movement or ncreased starvaton rsk f more proftable locatons are not found (Hansen and Closs 9). Growth s conventonally measured as a change n length and weght over tme. Fsh may dstrbute more energy to growth n length or weght dependng on the crcumstances. Followng perods of starvaton, growth n body mass may be greater than growth n length, and durng perods of starvaton, reductons n body mass wll not be accompaned by reductons n length. These types of growth redstrbutons are often nadequately captured n feld studes whch typcally estmate growth on an annual tmescale. Growth n length can be estmated n the feld based on observed growth ncrements from taggng studes (Francs et al. 1988) but changes n length frequency dstrbutons over tme also provdes nformaton on growth. Studes of change n body mass are often based on boenergetc models (Hansen et al. 1993) whch nclude parameters only estmable from laboratory studes (Bartell et al. 1986; Ellott et al. 1995). Rarely are both growth-n-length and growth-n-weght approaches used n the same analyss. A more ntegrated approach conducted on a shorter seasonal tme scale s requred to better understand effects of the envronment on the growth of fsh. Ranbow trout (Oncorhynchus mykss) were ntroduced below Glen Canyon Dam begnnng n 1964 shortly after dam closure. The populaton thrved n the Glen Canyon talwater, located n the frst 25 km downstream of the dam, owng to perennally clear and cool water condtons resultng from mpoundment. Szes for the largest ranbow trout captured n the 3

5 Page 4 of blue-rbbon trout fshery that developed n the talwater ranged from 5-6 cm n the 197s and 198s, but have declned to a current maxmum sze of about 35 cm (Korman et al. 12; McKnney et al. 1999). Ths declne may have been caused by a reducton n the avalablty of large food tems n the drft (Gammarus lacustrus), hgher trout denstes caused by ncreased recrutment due to a reducton n hourly fluctuatons n flow from the dam begnnng n the early 199s, or both. Some ranbow trout that recrut n the Glen Canyon talwater dsperse downstream nto Marble Canyon where water clarty s reduced and trout denstes are lower (Korman et al., ths ssue). Dspersal of ranbow trout from Glen Canyon can have negatve effects on natve fsh, lke the endangered humpback chub (Gla cypha, Coggns et al. 11), that resde near the confluence of the Lttle Colorado Rver (LCR, see Fg. 1 of Korman et al., ths ssue). Abotc and botc factors whch nfluence the growth rates of trout and the ftness of the populatons n Glen and Marble Canyons may nfluence the extent of downstream dspersal of trout and ther abundance near the LCR. In ths study, we descrbe seasonal and spatal varaton n growth rates of ranbow trout n the Colorado Rver downstream of Glen Canyon Dam, and use ths nformaton to better understand factors that could be nfluencng ther populaton dynamcs. We ft von Bertalanffy and Walters and Essngton () boenergetcs models to length- and weght-ncrements determned from taggng, respectvely. We qualtatvely evaluate the effects food avalablty, turbdty, and trout densty on seasonal and spatal patterns n growth. We compare shfts n length dstrbutons over tme wth predctons based on the von Bertalanffy model to provde nsght on temporal- and sze-dependent varaton n mortalty, movement, and recrutment. Our study of growth of ranbow trout below Glen Canyon Dam s unque because t s based on a large-scale mark-recapture program, where over 8, ranbow trout were recaptured over a 13- km study area durng a 3-year perod Methods Study Area The study area extends from Glen Canyon Dam (rver klometer [rkm] ) to the confluence of the Lttle Colorado Rver (rkm 13, see Fg. 1 of Korman et al., ths ssue). We sampled fve reaches n ths area: I) rkm ; II) rkm ); III) rkm ; IVa) rkm ; and IVb) rkm Reach I s assumed to represent condtons 4

6 Page 5 of characterstc of Glen Canyon, whch extends from the dam to the confluence wth the Para Rver (rkm 27.), and s wde, shallow, and low-gradent. Marble Canyon s km long and extends from the Para Rver to the LCR confluence. Reaches II, III, and IVa are assumed to represent condtons n upper, mddle, and lower Marble canyon, respectvely. Samplng reaches n ths secton are steeper and more confned than n Glen Canyon. Large nputs of fne sedment from the Para Rver, whch generally occur durng the summer monsoon season, result n shortterm ncreases n turbdty as well as a channel bed wth hgher proportons of fnes than n Glen Canyon. Reach IVb s ntended to represent condtons n the LCR nflow reach, whch s affected by cumulatve sedment nputs from both the Para and the LCR and s therefore more frequently turbd. Reaches IVa and IVb are part of the most sgnfcant rearng area for juvenle Humpback chub n the manstem Colorado Rver below Glen Canyon Dam (Gloss and Coggns 5; Yackulc et al. 14). Samplng Nghttme boat electrofshng was used to sample ranbow trout. Downstream samplng trps were conducted four tmes per year n Aprl, July, September, and January from Aprl 12 through September 14 (11 trps). Two nghts of samplng were conducted n each of the frst four reaches, wth eght nghts spent n reach IVb to support an exstng mark-recapture study of juvenle humpback chub (Yackulc et al. 14). Reaches I-III were each 6 km long, wth the upper 4 km sampled on nght 1 and the lower 4 km sampled on nght 2 (see Fg. 2 of Korman et al., ths ssue). Thus, upper and lower 2 km sectons were sampled once per trp, whle the central 2 km sectons were sampled twce (2 passes). Reaches IVa and IVb were shorter n length at 2. and 2.25 km long, respectvely, and were sampled n ther entrety each nght for two consecutve nghts. Electrofshng effort on the frst two passes for all reaches was completed at a pace of approxmately 3 seconds per meter of shorelne. The addtonal samplng n IVb conssted of slow-paced electrofshng (4.3 seconds per meter) to maxmze catch of small humpback chub, and requred two nghts of effort to cover the reach. Nnety hoop nets were also deployed along the shorelne n ths reach and checked daly for 8 consecutve days. Incremental growth was based on measurements of fsh recaptured across one or more trps (hereafter referred to as across-trp recaptures). All fve study reaches were dvded nto 25-m long stes along the shorelne on each bank (Fg. 2). Rver-left and rver-rght stes were sampled by separate crews 5

7 Page 6 of consstng of an electrofshng boatman and netter. Captured fsh were kept n aerated 4-L buckets and transported by a tender boat to a central processng locaton. Incomng fsh were kept aerated and flushed wth water to mantan adequate water qualty. Groups of -15 fsh were anesthetzed wth clove ol. Ranbow trout 75 mm captured n the central 2 km secton of each reach (reaches I-III, all of reaches IVa and IVb) were tagged wth passve ntegrated transponders (PIT) usng standardzed methods (Persons et al. 12). Fork length and weght were recorded to the nearest mm and gram for fsh 15 mm, and.1 g for smaller fsh. Followng processng, fsh were held n aerated buckets for 3 mnutes pror to release. Unhealthy tagged fsh were euthanzed after the holdng perod; otherwse remanng fsh were released at the center of the orgnal 25-m ste of capture. Total tme from capture to release typcally ranged from 1-2 h. Holdng experments were conducted on each trp to estmate PIT tag sheddng and mortalty rates due to capture and processng. These same experments also provded nformaton on measurement error. A random sample of 25-4 ranbow trout processed on the frst nght samplng from each of four stes wthn each reach were held n separate 1-L contaners usng a PVC frame anchored to shore and suspended at water surface. Contaners were perforated wth small holes to allow water to crculate. After 24 hours, fsh were removed from enclosures, anesthetzed, re-measured, re-weghed, and re-scanned. The number of fsh that ded or shed ther tags was recorded and lve fsh were returned to ther orgnal capture ste. In addton to the Downstream trps conducted four tmes per year n fve reaches, we also conducted one to two day Glen Canyon trps each year between October and December to provde a better representaton of the populaton supportng the talwater fshery. We marked and recaptured trout over the entre 25-km length of Glen Canyon followng the same samplng protocols descrbed above. Over the study perod (11-14), we conducted 16 samplng trps n total whch ncluded 11 Downstream trps and fve Glen Canyon trps. We quantfed spatal and temporal varaton n nvertebrate drft based on methods descrbed by Kennedy et al. (14). Drft samples were collected by boat at center of channel for 5 mnutes usng a fne mesh net (.25-mm mesh, crcular net wth a 51cm da. openng, 1:5 rato of openng dameter to length). A set of 6 samples were collected at md-day and 7 samples were collected durng the evenng crepuscular perod (startng 1 h before and endng 1 h after sunset) on two consecutve nghts. Half of the samples were collected near the surface ( cm below 6

8 Page 7 of water surface) and half were collected near the bottom (1 m above channel bottom). Samples were preserved n the feld usng 95% ethanol. We computed average drft concentraton (# m -3 ) per reach from all samples. We present results for only the three taxa commonly consumed by ranbow trout n Grand Canyon (Cross et al. 11, 13; Kennedy et al. 14) whch are chronomds (mdges), Smulum artcum (a blackfly), and Gammarus lacustrs (an amphpod). Length-Based Growth Modellng We estmated von Bertalanffy growth parameters based on changes n fork length between release and recapture events for PIT-tagged ranbow trout usng the maxmum lkelhood approach developed by Francs (1988). Length at recapture was predcted from, (1) ˆ ' K T L = L + ( L L ) (1 e ) 169 where ' ˆ L s the predcted fork length of fsh on recapture, L s the measured length at release, L s the estmated average length at the termnal age (asymptotc length), K s the estmated growth coeffcent, and T s the tme at large between release and recapture expressed n unts of years. Equaton 1 predcts a lnear decrease n growth rate wth ncreasng sze-at-release ( L ) and can predct negatve growth when L > L. Negatve growth n length s unlkely and nconsstent wth the boenergetcs model we use to predct growth n weght. We therefore constraned predcted growth n length ( ) to be usng, (2a) C = L L 1+ e 1, and 177 (2b) Lˆ ' = Lˆ C + (1 C ) L 178 C approaches as L becomes ncreasngly larger than L, and C s 1 when L < L. Ths 179 results n Lˆ = L n the former case and no change to predctons from eqn. 1 n the latter case The logstc functon (eqn. 2a) for the adjustment to predcted length (eqn. 2b) results n a smooth change n predctons whch does not nterfere wth the nonlnear search. A range of models were estmated to quantfy temporal and spatal varaton n growth. The most complex model we evaluated (the global model) estmated L and K separately for each trp 7

9 Page 8 of nterval (t) and reach (r, denoted by model name L K tr tr ). Under the smplest (null) model, a sngle set of parameters was appled to all trp ntervals and reaches (e.g., L ). Models of K ntermedate complexty used the same parameter values across reaches but allowed them to vary across trp ntervals (e.g., L t K ), or used the same parameter values across trp-ntervals but t 188 allowed them to vary among reaches (e.g., L r K r ), or used other combnatons (e.g., L ). We also explored models that allowed parameters to vary across years ( y = 12, r K tr 13, 14) or seasons ( s = Jan-Apr, Apr-Jul, Jul-Sep, Sep-Jan for wnter, sprng, summer, and fall seasons, respectvely). The most complex temporal model estmated separate parameters for each of the ntervals between the 11 downstream trps for all fve reaches, as well as parameters for the nterval between the frst Glen Canyon trp (November 11) and the frst downstream trp (Aprl 12) n reach I (53 parameters). Releases and recaptures of fsh from Glen Canyon trps n 12 and 13 were grouped nto the nearest downstream trp (fsh from October Glen Canyon trps grouped nto September downstream trps, fsh from December Glen Canyon trp grouped nto January downstream trps) to assgn the approprate temporal parameter values, but the tme-at-large used to predct growth n length and weght for these fsh was based on the actual nterval between release and recapture. Approxmately 5% of trout were recaptured on two or more trps after the ntal release trp. To use ths nformaton n the estmaton of models wth temporal varaton n parameters, the predcted fnal length at recapture was based on applyng equaton 1 teratvely through all trps ntervals between the release and recapture events. For example, f a fsh was released on trp 1 and recaptured on trp 3, the predcted length on trp 2 would be based on the release sze on trp 1 and parameters for trp nterval 1, and ths predcton would be used as to predct length on trp 3 based on parameters from trp nterval 2. L n equaton 1 Parameters were estmated by mnmzng the followng negatve log lkelhood (NLL) functon usng the AD model bulder software (Fourner et al. 11), 9 2 ( L Lˆ ) (3) NLL = log( σ p + σ m ) + log( 2π ) ( σ + σ ) p m 8

10 Page 9 of where σ p s the standard devaton n the predcted length at recapture for fsh due to ndvdual varaton n growth, σ m s the standard devaton n predcted length due to measurement error, and L s the observed sze on recapture. σ m s treated as a constant and calculated based on dfferences n length measurements for fsh that were recaptured wthn 24 h from release or held as part of 24 h tag mortalty and sheddng experments. We assume multplcatve error for ndvdual varaton n growth and therefore compute σ p from, (4) σ p = L ˆ CVL where CV L s the estmated coeffcent of varaton n length among ndvduals gven an expected length predcted by equaton 1. As for the von Bertalanffy parameters ( L and K), CV L was held constant across all reaches and trp ntervals (null model, CV L ), allowed to vary across these strata (global model, CV Ltr ), or was allowed to vary by reach (CV Lr ), trp nterval (CV Lt ), or annual or seasonal tme perods. We used the Akake Informaton Crtera (AIC; Burnham and Anderson 2) to compare alternate models to test for temporal and spatal dfferences n growth. We also evaluated a model where growth was assumed to be ndependent of sze-at-release. In ths case, the same lkelhood was used, but the predcton of length-at-recapture only depended on a sngle mean growth rate parameter, rather than L and K. Ths model was compared to the null von Bertalanffy model to provde a formal test for the effects of fsh sze on growth. Models wthn -2 AIC unts of the most parsmonous model (the one wth the lowest AIC) were consdered to have strong support; models wthn 2-7 unts were consdered to have moderate support, and models that had AIC values > 7 unts relatve to the best model were consdered to have weak support (Burnham and Anderson 2). Weght-Based Growth Modellng We used the Walters and Essngton () boenergetcs model (WE), d n (5) Wˆ = W + ( H W m W ) T 9

11 Page of to predct weght at recapture ( Wˆ ) as a functon of weght-at-release ( W ). The terms nsde the parentheses predct the growth rate per year based on the dfference n metabolc gans and losses. The net food consumpton rate, H, s a tme-dependent product of temperature-dependent maxmum feedng rate, the proporton of maxmum raton acheved, the assmlaton effcency, and 1-SDA, where SDA represents specfc dynamc acton and actve metabolc costs proportonal to food ntake rate. The product of m and W n represents the standard metabolc rate. The exponents d and n represent the effect of body weght on the maxmum food consumpton and standard metabolc rates, respectvely. We dd not estmate n but nstead fxed t at a value of 1, as the exponent terms can be dffcult to estmate from feld data drectly (Walters and Essngton ; van Poorten and Walters ). Equaton 5 s an approxmate regresson model to predct weght but can lead to potentally based estmates of boenergetcs parameters when T s large. When n=1, there s nstead an analytcal soluton for Wˆ gven W for all possble tmes at large ( T ) based on exact ntegraton of eqn. 5. The analytcal soluton n regresson format s gven by, 25 d d H d m d T d (6) Wˆ (1 ) 1 = W + ( W e ) (1 ) m For fttng, the whole rght hand sde of eqn. 6 s rased to the power functon of 1 to predct Wˆ as a 1 d W and the boenergetcs parameters H, m, and d. We used the same lkelhood form (eqn. 3) and error assumptons (eqn. 4) as for the length analyss wth CV W replacng CV L to account for ndvdual varaton n growth n weght. We mplemented the model n the same teratve way to be able to nclude observatons from fsh whch were recaptured more than one trp after release. As for the growth n length analyss, we used AIC to compare models wth dfferent temporal and spatal stratfcaton n the estmaton of H, m, and CV W. We also compared the WE model to one where growth n weght was ndependent of weght-at-release, and to a von Bertalanffy model whch assumes a lnear relatonshp between growth n weght and weght-at-release. A maxmum of temporal strata per reach were estmated as no trout were weghed on the November 11 trp. Parameters for the Apr12-Jul12 nterval could not be estmated n reach II as no fsh were weghed on the Aprl 12 trp n ths reach.

12 Page 11 of Seasonal and spatal varaton n growth was summarzed by predctng growth n weght and length for a -mm fsh. Length-weght relatonshps were used to convert the mm fork length to weght whch was then used n the boenergetcs model as W to predct growth n weght. Length-weght regressons were computed for each trp and reach based on all avalable length-weght data for ranbow trout by least squares usng the standard lnear transformaton (log(w)=a+b log(l)). We used relatve condton factor to descrbe and compare the energetc state of the trout populaton across reaches and trps (Neff and Cargnell 4). Relatve condton factor was computed as the rato of observed weght to predcted weght for each fsh, and then averaged for each reach and trp. Predcted weght was calculated based on the observed fork length and a sngle weght-length regresson whose parameters were estmated from observatons from all reaches and trps. Relatve condton values < 1 ndcate that a fsh s lghter and n an energetcally weaker state than expected gven ts observed length. To compare how well we could predct change n relatve condton factor based on growth n length and weght models, we compared the observed relatve condton factor by trp and reach based only on tagged fsh that were recaptured, wth estmated relatve condton from length and weght growth models. Length-at-Age, Mean Age, and Brth Year Length-at-age curves were generated for each reach by assumng that a trout.5 yrs. from hatch s 92 mm, and then teratvely computng length for subsequent ages (on a quarterly tmestep) usng the von Bertalanffy L and K estmates for each trp nterval n 13. The fxed sze at.5 yrs. was computed from the best-ft lnear relatonshp between fork length and daly age as determned by counts of daly rngs on otolths extracted from 4 age- ranbow trout captured n Glen Canyon n 11 (Luke Avery [USGS] unpublshed data). Age-frequency dstrbutons were calculated from length-frequency dstrbutons usng the length-at-age curves. Length-frequency dstrbutons for each trp and reach were computed based on -mm length bns (7-4 mm) usng all avalable length measurements from each reach and trp, excludng any wthn-trp recaptures. The probablty of beng age.5-6 yrs. for each sze class n the length-frequency was then computed by assumng that age for each sze class s normallydstrbuted wth a mean and varance determned from the length-at-age curve. Fnally, the relatve frequency for each age was calculated as the sum product of the number of fsh n each 11

13 Page 12 of sze class and the probablty of beng each age. The approach s the nverse of the standard procedure used n stock synthess models to dstrbute fsh of a gven age nto multple sze classes (e.g., Fourner et al. 1998; Taylor et al. 5; Korman et al. 12). Age frequency dstrbutons were converted to brth year frequency dstrbutons by subtractng age from the date the length frequency sample was taken.the average age of ranbow trout for each reach and trp was computed as a frequency-weghted mean of the age frequency dstrbuton. Length-Frequency Analyss Changes n length-frequency dstrbutons over tme are potentally drven by szedependent varaton n growth, mortalty, mgraton, and recrutment, as well as by szedependent varaton n capture probablty. We predcted length-frequency dstrbutons for each reach and trp by advancng the observed length-frequency dstrbtuton from the prevous trp usng von Bertalanffy growth parameters. Dscrepances between predcted and observed length- frequences were used to gan nsght on sze-dependent varaton n recrutment, dspersal, and mortalty. Length-frequences were predcted by dstrbutng fsh n each sze class on trp t to multple sze classes on trp t+1 based on the predcted mean growth and varaton n growth over the trp nterval usng the followng procedure: ) Observed length-frequency dstrbutons were calculated for each reach and trp by -mm sze class for trout rangng from 7-4 mm (LF, where s the ndex for each sze class); 2) Assumng error n predcted length s normally-dstrbuted at any length (eqn. 4), the transton probablty for a fsh growng from one sze class to another between trps can be calculated as, 317 (7a) θ, j = σ j w x+ ( x l j ) σ 2π w x 2 e j 2 dx where, θ s the transton probablty from sze class on trp t to sze class j on trp t+1, x s the mdpont for sze class j on trp t+1, w s the wdth of a sze class ( mm), l j s the predcted mean length on trp t+1 for a fsh wth a length equal to the mdpont of sze class on trp t, and σ j s the standard devaton n the predcted mean length. The latter two values 12

14 Page 13 of were computed usng von Bertalanffy growth parameters for each nterval and the nterval length between trps t and t+1 (eqn s 1 and 4); and 3) The predcted probablty of beng n sze class j on trp t+1 (plf j ) was computed by weghtng the observed length-frequency for each sze class on trp t by the probablty of movng from that sze class to sze class j on trp t+1 usng, (7b) plf j = LF θ j LF θ, j, j Korman et al. (ths ssue) hypotheszed that the large number of -175 mm trout observed n reaches II and III on the frst downstream trp (Aprl 12), orgnated from a very large annual cohort produced n Glen Canyon the prevous summer. If ths hypothess s correct, the sze-dstrbuton for trout 175 mm n Glen Canyon on the November 11 trp, advanced by growth over the November 11 to Aprl 12 perod n reaches II and III, should predct the sze dstrbuton n that reach on the Aprl 12 trp. However, as there was no samplng n reaches below Glen Canyon pror to the Aprl 12 trp, an estmate of growth over the November 11 to Aprl 12 perod for reach II and III was not avalable. We therefore used growth parameters for the trp nterval mmedately followng the Aprl 12 trp (Apr12-Jul12) to predct the advancement of the length-frequency dstrbuton between the November 11 and Aprl 12 trps n reaches II and III. Ths requred an adjustment of the growth nterval to apply growth parameters to, snce the growth rate between Aprl and July would not be representatve of the growth rate over the entre November 11 to Aprl 12 perod. We estmated ths earlysprng growth nterval by nonlnear search. The ft of the predcted length-frequency dstrbton for the Aprl 12 trp for any estmate of ths nterval was determned by assumng that observed length-frequences are a multnomally-dstrbuted random varable that depend on the predcted proporton of fsh n each sze class. The kernal of the multnomal log-lkelhood (LL) was computed as, 348 (7c) LL = LF j log( plfj) j 13

15 Page 14 of We used the optm functon n R (R Development Core Team ) to fnd the early-sprng nterval whch maxmzed ths log lkelhood. Ths procedure was also used to estmate the earlysprng growth nterval requred to best predct the observed length frequency on the Aprl 12 trp n reach I, gven growth parameters from the Aprl-July 12 nterval n that reach. The statstcal estmate of the length frequency dstrbuton n Aprl 12 trp n reach I was then compared to the calculated dstrbuton based on the actual growth parameters for the November 11 to Aprl 12 perod and the known total duraton of that nterval. Ths provded a partal valdaton of the early-sprng growth nterval estmaton approach, and also facltated comparons of the tmng of growth n early-sprng n reaches I, II, and III Results Sample Sze and Measurement Error Over 16 trps we captured more than 19, ranbow trout, and PIT-tagged 7,66 ndvduals, from whch trout growth n length and weght was determned for 7,951 and 7,4 across trps recaptures, respectvely (Table 1). Approxmately 5% of recaptures were fsh that were recaptured one trp after the release trp. Ths component of the recaptures provded better nformaton to evaluate seasonal varaton n growth than fsh recaptured two or more trps after release. However, we were stll able to use the large sample of fsh from the latter group n growth estmaton owng to our teratve mplementaton of the Francs (1988) tag-based von Bertalanffy model. Across all trps and reaches, fork length and weght of 6,355 and 5,563 ndvdual trout were measured twce wthn 24 h, respectvely. The standard devaton n dfferences (σ m ) n fork length and weght between the frst and second measurements was 2.7 mm and 5.3 g, respectvely. Trends n Growth There was strong support for the von Bertalanffy model whch predcts reduced growth wth ncreasng fsh sze (Fg. 1 and Fg. S1) relatve to the mean growth model whch assumes sze-ndependent growth (Table 2, frst 2 rows). There was strongest support for the global model that allowed growth parameters to vary by both trp nterval and reach (global model n Table 2, model L tr -K tr -CV tr ) compared to models where parameters vared by only trp nterval (t), reach (r), or were constant across both these strata (null). There was more evdence for 14

16 Page 15 of varaton n parameters across trp ntervals than across reaches, ndcatng that year and seasonal effects were greater than spatal effects (rows 3 and 4 n Table 2). Of models where only one parameter could vary by both trp and reach, there was stongest support for the model where the growth coeffcent (K) vared among these strata (group 1 n Table 2). There was more evdence for varaton n L across years than seasons, whle the opposte was true for K and CV L (group 2 n Table 2). L was lower n 14 than other years n all reaches, and declned from 356 to 254 mm between 12 and 14 n reach I (Fg. S1). Hghest values of K occurred durng the sprng (Apr-Jul) and were lowest durng fall (Sep-Jan) and wnter (Jan-Apr) n reach I, and fall and summer (Jul-Sep) n reaches downstream of the Para Rver (II-IVb). Models wth reach- and trp nterval- or seasonal-varaton n asymptotc length estmated L s that were unrealstcally small or large and often at the bounds used n the estmaton procedure, and estmates of L were strongly negatvely correlated wth estmates of K n these cases. Ths occurred because there was very lttle nformaton to estmate L durng perods when both both small and large fsh were not growng (e.g., Fg. 1, reach III September 13-January 14). Model L yr -K tr -CV tr had the lowest AIC score (3 rd ) of all models that generated relable estmates of L, and was therefore used n latter analyses that requred predctons of growth n length. Model L yr -K tr -CV tr, and many other versons of the von Bertalanffy model, appeared to overestmate growth durng the Aprl-July nterval n some reaches and years, especally for trout released at smaller szes (sold lnes n Fg. s 1 and S1). Ths occurred n part because of the constrant that growth n length cannot be negatve (eqn. s 2a and 2b), whch results n slghtly lower estmates of L and hgher estmates of K. Ths effect s most pronounced durng the sprng nterval when growth s hghest. The appearance of postve bas n sprng growth also occurs because predctons are based on the ft to all data ponts, but only growth ncrements from tagged fsh recovered one trp after the release trp (.e., from adjacent trps) can be plotted. The contrbuton from non-adjacent observatons s substantve (approxmately 5% of the sample, see Table 1) and s partcularly mportant when sample sze from adjacent trps s small (e.g., reach I, Aprl-July nterval). Fttng the model to only adjacent-trp growth ncrement data (dashed lnes n Fg. S1) results n slghtly lower growth durng the sprng nterval, whch ndcates that trout released n Aprl and recaptured n July grow less per unt tme over the sprng nterval than fsh released n Aprl but recaptured on trps after July. We speculate that 15

17 Page 16 of ths dfference could be caused by faster growng fsh usng habtat further from shore durng hgh growth perods (Aprl-July), whch would make them less vulnerable to capture at that tme. The WE boenergetc model (Walters and Essngton ) ft the growth n weght data well, and often had a notceable parabolc shape, especally durng perods of hgh growth (Fg. s 2 and S2, Aprl-July 13). There was strong support for the WE model relatve to a model where we assumed growth n weght was ndependent of weght-at-release (Table 3, null vs. mean only). The WE model also had more support than the von Bertalanffy model (null-vonb) whch assumes a lnear relatonshp between growth n weght and weght-at-release. There were no problems wth obtanng relable estmates for H, m, and CV w for the global model (Fg. S2). However, the power parameter for the maxmum food consumpton rate (d n eqn. 5) was strongly confounded wth estmates of H and m for all cases where we allowed t to vary by trp nterval or season. The unstratfed estmate of d was relably determned (.69 wth a standard devaton of.21). Lke the growth-n-length analyss, the global model that allowed boenergetc parameters (except d) to vary by both trp nterval and reach had the lowest AIC score of any of the models that were evaluated, and there was more support for models that allowed boenergetc parameters to vary by trp nterval than by reach. Of models where only one parameter could vary by both trp and reach, there was stongest support for the model where the H coeffcent (food consumpton) vared among these strata (group 1 n Table 3). There was more evdence for seasonal- than nterannual-varaton n boenergetc parameters (group 2 n Table 3). Net food consumpton was always hghest durng the sprng nterval, and was lowest durng fall and wnter n reach I, and summer and fall n reaches below the confluence of the Para Rver (II-IVb, Fg. S2). Owng to varaton n parameters of the von Bertalanffy length and boenergetc models, there were strong annual-, seasonal- and reach-specfc dfferences n growth n length and weght (Fg. 3). Wthn reaches, growth n length and especally weght was always hghest durng the sprng nterval (Apr-Jul). Growth n sprng declned progressvely over the three years of study n all reaches except IVb. Growth n length and weght n fall (Sep-Jan) was very low n all reaches. There was also lmted growth n length durng the wnter nterval (Jan-Apr) n all reaches. However, there was growth n weght over the wnter nterval n reaches downstream of the Para Rver confluence (II-IVb). In the summer (Jul-Sep), trout grew n length and weght n 16

18 Page 17 of reach I, whle n reaches downstream of the Para Rver, there was no growth n length or weght, and fsh lost weght n the reach below the LCR (IVb). A strong seasonal pattern n relatve condton was seen n all reaches and was drven by seasonal changes n growth n length and weght (Fg. 4). Condton was usually at a mnmum durng January trps and ncreased rapdly n the sprng to attan a peak by the July trps. Declne n condton from July to September trps was relatvely small n reach I compared to the other reaches nfluenced by hgh levels of turbdty at that tme (see Fg S1c of Korman et al., ths ssue). Wthn seasons, condton factor generally declned over the perod of study. For example, n reach I, condton was 1.14, 1.6, and.95 n July 12, 13, and 14, respectvely. And unlke other years, there was no ncrease n condton between Aprl and July trps n 14 n reach I, and a much more lmted ncrease n other reaches. Closer examnaton of the data n reach I ndcates that the largest fsh experenced the bggest declnes n condton on the most recent samplng trps (Fg. S3). Predctons of seasonal changes n relatve condton factor from the growth n length and weght models for recaptured trout were very consstent wth observed changes (Fg. 4). The predcted trends matched the trend based on the large sample (all fsh that were measured and weghed) except for reach-trp strata when the sample sze for recaptures was low. Seasonal and spatal trends n nvertebrate drft concentraton (Fg. 5) lkely drove some of the patterns n trout growth and condton (Fg. s 3, 4, and S3). Glen Canyon had lower drft concentratons for all taxa compared to other reaches whch may be the result of much greater trout densty (see Fg. 6 of Korman et al., ths ssue), and could explan lower trout growth rates n ths reach (Fg. s 3 and 5). Chronomds and to some extent Gammarus concentratons were hghest n Aprl and July as were trout growth rates and ncreases n condton. Smuld denstes n reaches downstream of the Para Rver (II-IVb) were substantvely hgher than n reach I n January, whch may explan the much hgher growth n weght (and recovery n condton) between January and Aprl trps n downstream reaches. In all reaches, the average condton over Aprl and July trps n 14 was lower than n prevous years (Table 4). Concdent wth ths, there was a sudden ncrease n the number of trout that were recaptured n reaches other than the one they were released from on the last two trps (July 14 and September 14). About 5% of the total number of across-reach recaptures occurred on these last two of 11 (reaches II-IVb) or 16 (reach I) trps. Ths recent ncrease n 17

19 Page 18 of both downstream and upstream long dstance movement may be related to the system-wde decrease n condton durng sprng and summer of 14. Length-at-Age and Trends n Mean Age and Brth Year Length-at-age curves based on von Bertalanffy parameter estmates for 13 showed a strong wthn-year seasonal pattern due to the large varaton n growth coeffcents among trp ntervals (Fg. 6). Younger fsh attaned a larger sze more quckly n reaches II-IVb owng to hgher growth n wnter and sprng, whch more than compensated for reduced growth n these downstream reaches over summer when turbdty was hgh. Asymptotc length ranged from mm across all reaches. Mean age of ranbow trout ncreased over the duraton of the study n reaches I and II (Table 5). For example, n reach I, mean age on the Aprl 12 trp was 1.2 yrs. and ncreased to 3.4 yrs. by the September 14 trp. Ths occurred because a very large annual cohort was produced n 11 and there was lmted recrutment n later years, so the mean age of the populaton ncreased as the domnant 11 cohort aged. The average age of ranbow trout also ncreased wth dstance from Glen Canyon Dam n the frst year of the study. Ths occurred because of the domnance of the 11 cohort n reaches I and II, and because reaches further downstream were populated wth larger and older fsh. The average brth year, whch dentfes the year the domnant cohort was produced n, was 11 n reach I and 9 n reach IVb n the frst year of the study. If the majorty of the populaton near the LCR orgnated from Lees Ferry as movement data suggest (Korman et al., ths ssue), the pattern n mean age and brth year ndcate that the average tme to move from Glen Canyon to the LCR s approxmately two years. Length-Frequency Analyss Length-frequency dstrbutons predcted from nterval-specfc growth rates were very smlar to observed dstrbutons n reaches II-IVb (Fg. S4), but there were substantal dscrepances n reach I (Fg. 7). The smlarty n observed and predcted dstrbutons n II-IVb ndcates that growth parameters estmated by tag recaptures accurately represent growth for the larger unmarked populaton, and that there are lmted effects of sze on mortalty, dspersal, and capture probablty n these reaches. Some of the dfferences between observed and predcted length-frequency dstrbutons n reach I were drven by a combnaton of sze-dependent 18

20 Page 19 of recrutment and seasonal heterogenety n capture probablty for smaller sze classes. Lengthfrequences for trout < mm were underpredcted on September trps n all three years, especally n 12 when recrutment of small fsh was hghest. Ths dscrepancy s an artfact resultng from the lower sze lmt for taggng. Gven growth rates between July and September n reach I (Fg. s 1 and S1), the majorty of fsh n the 7- mm sze class n September orgnated from fsh < 7 mm n July. However, as fsh < 75 mm were not tagged and therefore not ncluded n the calculatons, the model cannot grow these sze classes nto the 7- mm sze classes by September, and therefore underpredcts ther abundance. The large mode of fsh < mm on the September 12 trp was not observed on the January 13 trp but then reappeared on the Aprl 13 trp (Fg. 7). As a result, the model over- and then under-predcted the frequency n these sze ranges on January and Aprl 13 trps, respectvely. Ths dscrepancy was lkely caused by a temporary reducton n capture probablty of small fsh to electrofshng on the January 13 trp. Effects of sze-dependent losses due to mortalty or dspersal were also apparent n the length frequency analyss for reach I. Across all reaches and trps, the bggest dscrepancy between observed and predcted length-frequency dstrbutons was the large over-predcton of fsh between mm on the September 12 and 13 trps n reach I (Fg. 7). Ths sze class would grow about -15 mm between the September and January trps (Fg. s 1 and S1), and the model accurately predcts the relatve frequency of 14-5 mm fsh n January n both years. Ths ndcates that the mssng mm sze class on the September trps dd not reappear on later trps. The loss of ths sze class between July and September thus appears to be permanent and must therefore be drven by hgher rates of mortalty or dspersal over ths trp nterval. Advancement of the observed length frequency from Glen Canyon on the November 11 trp n reaches II and III ndcated that the large number of -175 mm trout observed n these reaches on the frst downstream trp (Aprl 12) lkely orgnated from the very large annual cohort produced n Glen Canyon the prevous year. In reach I, the length frequency dstrbuton on the Aprl 12 trp was accurately predcted based on the observed length dstrbuton on the November 11 trp and the best-ft growth parameters for the Nov11-Apr12 nterval (Fg. 8). The alternate approach, where the length frequency from the November 11 trp was advanced to the Aprl 12 trp based on the growth parameters for the Apr12-Jul12 19

21 Page of nterval n reach I, and an estmate of the early-sprng nterval (14 days), also accurately predcted the Aprl 12 trp length dstrbuton. The length frequency dstrbuton n reaches II and III on the Aprl 12 trp could only be computed by the latter method. The estmated earlysprng growth nterval for reaches II and III based on growth parameters for the Apr12-Jul12 nterval was 44 and 42 days, respectvely, approxmately one-month longer than n reach I. These ntervals underestmated the frequences for the smallest and largest sze classes on the Aprl 12 trp n reaches II and III because the values used to model ndvdual varaton n growth were too low (CV L =.4 for both reaches). Predcton usng the estmated ndvdual varaton n growth for the Nov11-Apr12 nterval n reach I (CV L =.11) led to early-sprng ntervals of 56 and 53 days for reaches II and III, respectvely, and provded a better ft to the observed length frequences from the Aprl 12 trp Dscusson The large number of drect observatons of growth obtaned n ths study provdes a unque opportunty to evaluate alternate boenergetc and growth-n-length models usng feld data. There was more support for the WE boenergetcs model, whch assumes a parabolc relatonshp between growth n weght and length at release (Parker and Larkn 1959), compared to the von Bertalanffy model that assumes the growth relatonshp s lnear and negatve. Food consumpton and metabolc loss parameters n the WE model showed more varaton across seasons and years than across reaches (wth the excepton of reach I), and there was more evdence for greater temporal varaton n food consumpton than metabolc loss. It s not surprsng that metabolc loss dd not have as strong of an effect on growth n a regulated rver system where seasonal varaton n water temperature s lmted. The von Bertalanffy growth-n-length model also showed stronger temporal rather than spatal varaton n growth whch was lkely caused by a seasonal varaton n food avalablty, prey detecton as determned by turbdty, and energy expendture (Metcalfe 1986; Hansen et al. 13). In wnter (Jan-Apr) there was no growth n Glen Canyon (reach I), but there was modest growth n length and substantal growth n weght n reaches II-IVb where food avalablty at ths tme was hgher. In later months, trout growth was hghest n sprng (Apr-Jul) n all reaches, when water s generally clear even n the most downstream reaches where trout denstes were lower. Trout grew n summer (Jul-Sep) n reach I where water clarty s hgh throughout the year (Vochck and Toppng ). In contrast, trout

22 Page 21 of n the downstream reaches (II-IVb) dd not grow n length over the summer and lost weght when turbdty was hgh due to nputs from the Para and Lttle Colorado Rvers (Fg. S1, Korman et al., ths ssue), whch lkely reduced foragng effcency (Sweka and Hartman 1). Growth n fall (Sep-Jan) was poor n all reaches when food avalablty was low. Although ranbow trout n the Colorado Rver are broadly dstrbuted throughout Glen, Marble, and Grand Canyons, trout denstes found among the study reaches declne wth ncreasng dstance from Glen Canyon Dam (Korman et al., ths ssue). Structural features and bed forms of the channel, the frequency and magntude of suspended sedment loads (Ted Mels [USGS] unpublshed data), and food avalablty are all spatally varable (Cross et al. 13). So t s somewhat strkng that the growth models ndcated that seasonal and nterannual dfferences n growth were much greater than spatal dfferences. We were also surprsed that trout growth n Glen Canyon was generally lower than n downstream reaches because the former reach has some of the hghest prmary and secondary producton rates n the system (Cross et al. 13; Hall et al. 15). It s lkely that very hgh trout denstes n Glen Canyon have a top-down effect whch reduces drft denstes resultng n reduced growth. Results from ths study suggest that, wth respect to trout growth, there are two rver sectons that functon partally ndependent of each other. Growth n the upper secton (reach I) may largely be controlled by strong densty dependent top-down effects, whle growth n the downstream secton (contanng the four remanng reaches) s more lkely regulated by densty ndependent factors such as turbdty. As observed n other rver systems (Jenkns et al. 1999; Olsson and Greenberg 4; Olsson et al. 6), t s lkely that trout dsperse from Glen Canyon when juvenle denstes are hgh and growth rates are low, nto downstream reaches where juvenle and adult fsh denstes are low and growth rates are seasonally greater. Thus, the two major sectons are lnked through ths dspersal process. The combned growth and length-frequency analyss provded useful nsghts about the populaton dynamcs of ranbow trout. There was very good correspondence between observed and predcted dstrbutons n reaches II-IVb, ndcatng that effects of fsh sze on capture probablty, mortalty, and dspersal were relatvely lmted n Marble Canyon and near the LCR. The length-frequency analyss also showed that the observed dstrbutons for trout -175 mm n reaches II and III on the Aprl 12 trp were accurately predcted usng the length-frequency from reach I and growth rate estmates n reach II and III. In conjuncton wth other nformaton 21

23 Page 22 of on movement (Korman et al., ths ssue), ths result strengthened the nference that the large number of trout < 175 mm n upper and mddle Marble Canyon observed at the start of the study were lkely produced n Glen Canyon n the prevous year. On the other hand, there were substantve over predctons of mm trout n reach I on two September trps (12-13), whch lkely ndcated greater mortalty or dspersal-related losses for ths sze class over the summer. In anadromous populatons of ranbow trout (steelhead), smolts typcally range from 14- mm n length (Ward and Slaney 1998; Jonsson and Jonsson 11). It s possble that the potental dspersal-related losses of ths sze class seen n the length frequency analyss could be the result of a smolt-lke behavour. Our fndngs have a number of mportant mplcatons for management of ranbow trout below Glen Canyon Dam. Hgher growth and condton of trout n reaches wth lower trout denstes suggests that reducng trout abundance n Glen Canyon could ncrease the sze of trout n the talwater fshery (Jenkns et al. 1999). Long-dstance movement data from ths study (Korman et al., ths ssue) suggests that dspersal of ranbow trout ncreases followng perods of hgh recrutment (11) and also when condton factor s low, whch has been observed n other systems (Hlderbrand and Kershner 4; Wysujack 8; Skjellevk 12). Thus, reducng trout recrutment n Glen Canyon va flow manpulatons (Fausch et al. 1; Arndt et al. 2) and through targeted harvestng should reduce dspersal through a reducton n both the proporton and total abundance of fsh that dsperse. The recent declne n relatve condton of larger trout n Glen Canyon was lkely caused by reduced producton and avalablty of nvertebrate prey tems, coupled wth ncreased metabolc demand due to hgh trout bomass and elevated water temperatures (Fg. S1, Korman et al., ths ssue). Although, trout denstes are probably regulatng avalablty of drft, t s uncertan whether the recent system-wde declne n trout growth and condton can be attrbuted to an overall top-down effect on benthc prey densty (Feltmate and Wllams 1988, 1991) or due to changes n the benthos caused by other bologcal and envronmental factors (Cross et al. 11, 13). A smlar trend of hgh trout abundance followed by low growth and condton was seen n Glen Canyon between and 6, and hgh denstes at the start of ths frst cycle were lkely caused by hgh flows between 1996 and 1998 (Korman et al. 12). Reducng large recrutment events of trout va flow manpulatons followng hgh flow perods could potentally reduce the extent of these boom-and-bust cycles (Lobon-Cerva 9). Hgh flow events ntended to buld 22

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