High variability in spawning migration of sea trout,Salmo trutta, in two northern Swedish rivers

J . O S T E R G R E N

Department of Wildlife, Fish, & Environmental Studies SLU (Swedish University of Agricultural Sciences), Umea, Sweden &Evolution & Ecology Program, International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria

H . L U N D Q V I S T & J . N I L S S O N

Department of Wildlife, Fish, & Environmental Studies SLU (Swedish University of Agricultural Sciences), Umea, Sweden

Abstract Telemetry was used to examine spawning migration of sea trout, Salmo trutta L. (n = 126), in tworivers in northern Sweden. The spawning areas defined by radio-tagged fish differed between the river systems. Inthe River Vindelalven, sea trout spawned in the main stem and 80% of tagged individuals returned to areas wherehatchery-reared juveniles had been previously stocked. In the River Pitealven, 74% of tagged sea trout ascendedtributaries for spawning. Tagged fish were categorised into three groups of migratory pattern. CART (classificationand regression tree) analysis indicated that distance from tagging location to spawning site (Sdist) explained themigratory patterns. Large Sdist separated fish with stepwise upstream migration from those with up- and down-stream migrations and one-directional direct migration. Fish tagged early in the season migrated the longestdistance to spawning areas. Stocking locations and sex explained the large search behaviour up- and downstreamin the rivers. The findings are important for the sustainable management of sea trout in the Gulf of Bothnia.

KEYWORDS : hatchery, homing, human impact, radio-tagging, salmonid, water temperature.

Introduction

Sea trout, Salmo trutta L., often ascend small-sizedstreams to spawn (e.g. Elliott 1994; Bagliniere &Maisse 1999), where intermediate flow regimes, gravelsize and habitat complexity match the habitat prefer-ence of the species (Armstrong et al. 2003). Individualsreturn to their natal spawning area, a well-knownstrategy in salmonid populations (Stuart 1957; Klemet-sen et al. 2003) termed homing. The successful migra-tion from the sea to the spawning areas is thus of greatimportance for reproductive success. Knowledge aboutthis phase in the life history is crucial to understandpopulation trends and potential human impacts onpopulation change by, for example dams, flow regu-lations, freshwater habitat degradation and overex-ploitation (Thorstad et al. 2008). Despite upstreammigration of Atlantic salmon, Salmo salar L., receivingconsiderable attention (see review by Thorstad et al.2008), less interest has been paid to the migratory

behaviour of sea trout, which has a similar life history.Information on the spawning migration of sea trout isgenerally lacking (Milner et al. 2006), and only a fewstudies describe the migratory patterns in a free flowingriver, i.e. without man-made obstacles such as damsand hydropower facilities (Finstad et al. 2005). Finstadet al. (2005) indicated that the spawning migration ofsea trout occurred in three phases – an upstreammigration, search and a holding phase – similar tomigratory patterns in Atlantic salmon (Økland et al.2001). Other studies focused on the migration behav-iour of brown trout as they encounter man-madebarriers for migration (e.g. Ovidio & Philippart 2002Calles & Greenberg 2005). The effect of environmentalfactors on salmonid migration seems to vary with thesize of the river, geomorphology and geographicallocation (Trepanier et al. 1996; Thorstad et al. 2008).

Sea trout populations in streams and rivers enteringthe Gulf of Bothnia, northern Baltic Sea, are in poorstatus according to ICES (2006), because of likely

Correspondence: Johan Ostergren, Department of Wildlife, Fish, and Environmental studies, SLU (Swedish University of Agricultural

Sciences), SE-901 83 Umea, Sweden (e-mail: johan.ostergren@vfm.slu.se)

Fisheries Management and Ecology, 2011, 18, 72–82

doi: 10.1111/j.1365-2400.2010.00774.x � 2010 Blackwell Publishing Ltd.72

Fisheries Managementand Ecology

negative effects of habitat degradation, log floatingdams, hydropower dams and over-fishing at sea(Nilsson et al. 2005; Jutila et al. 2006). Many rivershave been stocked with hatchery-reared fish as amitigation strategy during the last 50 years (Jonsson2001; Lundqvist et al. 2006). The consequences ofdams and compensatory stockings in this area, e.g. onpopulation dynamics and genetic introgression in seatrout, have rarely been investigated (but see Nilssonet al. 2008). To design a sustainable managementprogramme for the sea trout in this area, knowledgeof spawning areas and migratory behaviour is needed.This study aims to fill this gap, investigating andcomparing the spawning migration of sea trout in twoof the largest river systems entering the Gulf ofBothnia, the rivers Pitealven and Umealven, the latterwith its large tributary the River Vindelalven. Thegoals of this study were (1) to examine and comparespawning migration and spawning site selection ofradio-tagged sea trout in the rivers Vindelalven andPitealven; and (2) to discuss observed patterns inrelation to the impact of dams and stocking ofhatchery-reared trout.

Material and methods

Study areas

The River Vindelalven, the largest tributary of theRiver Umealven, and the River Pitealven originatefrom the Scandinavian mountains, �450 km from thecoast, and enter the Gulf of Bothnia at around 63–65�N 20–21�E (Fig. 1). Both rivers have a hydropowercomplex including dam with fish ladder in the lowerreaches: in the R. Umealven, �32 km (Stornorrfors;Fig. 2) and in the R. Pitealven (Sikfors; Fig. 3),�40 km from the coast, respectively. Historically, therivers were impacted by log floating (Nilsson et al.2005), and many side-channels and tributaries wereblocked. In particular, the R.Vindelalven was blockedby more than 150 small dams (Tornlund 2002), but themajority have now been removed. Fish migration intothe R. Vindelalven was hindered by a hydropower damat Umealven between 1925 and 1935 (Monten 1988),and few sea trout had the possibility to enter the riverfor spawning during this 10-year period. As mitigation,large-scale stockings (�1 million one-year-old individ-uals) of hatchery-reared sea trout have been conductedin the R. Vindelalven. Of these, 90% were released inthe main stem and 10% in tributaries. Forty-fivepercent (n = 436 000) of stocked juveniles werereleased in the area at the Renforsen (data fromVattenfall AB, Sweden). The broodstock consisted of a

mix of wild and hatchery-reared sea trout, includingsea trout from other rivers. (Lundqvist et al. 2006). Inthe R. Pitealven, �27 000 one-year-old hatchery seatrout were released annually until 1999 (data fromNational Board of Fisheries, Sweden). Because esti-mated survival rate from one-year-old parr to adultfish is <1% (Degerman et al. 2001), stocking in theR. Pitealven probably had limited influence on the seatrout population.

River Vindelälven

Bothn

ianBay

Sorsele

Umeå

Vindeln

River Piteälven

Piteå

Vidsel

Tagging location

Tagging location

14 16 18 20 22

64

65

66

0 50 100

km

River Vindelälven

Gulf o

f Both

nia

Sorsele

Umeå

Vindeln

River Piteälven

Piteå

Vidsel

Tagging location

Tagging location

River Umeälven

River Vindelälven

Bothn

ianBay

Sorsele

Umeå

Vindeln

River Piteälven

Piteå

Vidsel

Tagging location

Tagging location

14 16 18 20 22

64

65

66

0 50 100km

River Vindelälven

Gulf o

f Both

nia

Sorsele

Umeå

Vindeln

River Piteälven

Piteå

Vidsel

Tagging location

Tagging location

River Umeälven

Figure 1. Map of the study area with tagging locations marked at the

two fish ladders. Longitude and latitude is marked on the outside of the

figure.

Ammarnäs

VindelälvenLaisälven

Renforsen

Umeälven

0 60 km30

Norrfors,tagging location

Umeå

Figure 2. Location of radio-tagged sea trout at time for spawning in

September and October in the River Vindelalven in 2002 (grey circles)

2003 (white circles) and 2004 (black circles). See text for further details.

SPAWNING MIGRATION OF SEA TROUT 73

� 2010 Blackwell Publishing Ltd.

All fish passing the ladder in the R. Umealeven werenetted, counted, measured (total length, cm) andweighed (g). Species, sex and origin (wild or hatchery)are noted. Hatchery-reared salmon and sea trout canbe distinguished by the presence (wild) or absence(hatchery) of the adipose fin which was removed fromthe majority of hatchery fish after 1971. However,because hatchery fish with intact adipose fin were alsooccasionally released, this characterisation is not100%. The fish ladder in the R. Umealven is openfor fish migration during the period 20 May to 30September, and the number of annually returning wildadult sea trout migrants averaged 50 (SD ± 34)between 1974 and 2004. In the R. Pitealven, the ladderis open from 20 May to 15 October, and a digital fishcounter (VAKI Camcounter) records number andspecies of passing fish. Mean annual number was 98(SD ± 50) individuals between 1992 and 2004. Theseare low stock sizes when the relatively large catchmentareas of suitable spawning and rearing habitatsthroughout the watersheds, 12 625 km2 for theR. Vindelalven and 10 800 km2 for the R. Pitealven,are taken into consideration (ICES 2006; Ostergren2006). Two major rapids influence upstream migrationof fish in the R. Pitealven; the rapid Fallforsen, whichhas a fish ladder, and the impassable rapid, Storforsen,located 70 and 90 km from the coast, respectively. Thelargest tributary of the R. Pitealven, the R. Varjisan,enters downstream of the Storforsen.

Radio-tagging and tracking

A total of 126 sea trout (approximately 11% of theentire spawning run in the studied rivers during thestudy) were externally radio-tagged (ATS-F2120 activ-ity transmitters with mortality signal, i.e. fixed fre-quency of 60 ppm after 16 h of no tag movement, massof 15 g in air and battery life of ca 400 days) at thebeginning of their spawning migration between Juneand September 2002–2004. Fish were netted from theexit of the fish ladders at the spillway dams, tagged,weighed (0.1 kg), measured (total body length, BL cm),sexed and a fin clip taken for genetic analysis. Geneticanalyses indicated that all tagged fish belonged to thenative river populations and thus were not strayersfrom other rivers (Ostergren 2006). As a consequenceof difficulties getting wild fish, 10 hatchery-rearedindividuals (absence of adipose fin) were tagged in2002. Only fish in good condition were tagged, and theratio of radio transmitter weight to fish biomass neverexceeded 2%, below general recommendations toensure radio tags were unlikely to cause negativeeffects on study fish. The tag was attached to the fishbelow the dorsal fin with two plastic covered 0.5-mmsteel wires inserted horizontally through the upper partof the musculature and fixed on the back with plasticplates. During the tagging procedure – duration�3 min – fish were kept in a water-filled tube withthe head in darkness. The fish did not show anyexternal sign of discomfort during the procedure. Thewater in the tube was taken directly from the river,thus water temperature was equivalent to the naturalenvironment. The handling and tagging methods werespecifically approved by the Swedish Animal WelfareAgency (nr: A65-01). The tagging procedure differedbetween the rivers because of the different design of thefish ladders (described in detail by Rivinoja 2005) inthe two rivers. In the R. Vindelalven, no anaestheticwas used in line with earlier studies (e.g. Thorstad et al.2000; Finstad et al. 2005) to avoid the extra handlingtime and stress of keeping large, wild fish in tanks.Thus, the fish were released back to their naturalenvironment immediately after tagging. In theR. Pitealven, the tagged individuals were released�1.4 km upstream of the fish ladder to avoid fallbacks,and as a consequence, the fish were anaesthetised (withMS222) during the tagging procedure. After tagging,and during transportation, the fish were held in 1-m3

tanks with oxygenated water for �1 h of recovery. Ofthe 126 tagged sea trout, 90 (58 females) individuals(average BL 67 cm; min–max: 52–86 cm) were radio-tagged in the R. Vindelalven and 36 (28 females) (BL,62; 50–90 cm) individuals in the R. Pitealven (Table 1).

Sikån

VarjisånStorforsenHundforsen

Piteälven

Sikfors, tagginglocation

0 30 km

Piteå

Fällforsen

Figure 3. Location of radio-tagged sea trout at time for spawning in

September and October in the River Pitealven in 2002 (grey circles) 2003

(white circles) and 2004 (black circles). See text for further details.

J. OSTERGREN ET AL.74

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Manual tracking (ATS-R2100 receivers) was carriedout mainly from a car and by foot, but also from anairplane and a boat. Additional archival receivers(ATS-D5040 and LOTEK SRX_400) connected tosingle antennas (four or six element Yagi) continuouslydetecting and logging data from individual fish wereplaced at the power station areas to examine behaviourof radio-tagged fish at the power stations, i.e. registerfallbacks. All receivers were calibrated for maximumprecision in transmitter registrations to be able tospecify the exact migration route of individual fish.Fish were located by manual tracking on average onceper week during June to September with an accuracyof ±100 m (car and airplane tracking) and once every2–3 days during spawning time from late September tothe end of October with an accuracy of ±50 m in themain stems and ±10 m in the tributaries (tracking byfoot and boat). From November and throughout thewinter, tracking was less frequent (twice per month).Positions were logged with a GPS (Garmin 12XL anda Palm Pilot).

Water flows and temperatures

Both the rivers Vindelalven and Pitealven have meanannual flows of about 180 m3 s)1 (data from VattenfallAB and Skelleftea Kraft AB, Sweden). Usually, thesemountain rivers have a bimodal spring flood regimewith an earlier forest-derived flood from the lowercatchment and a latter mountain-derived flood. Winterflows are typically low, about 40–80 m3 s)1, followedby a distinct increase during the spring flood events.Peak flows of �1000 m3 s)1 and 600 m3 s)1 wererecorded in mid-July 2004 in the rivers Vindelalvenand Pitealven, respectively. Water temperature in therivers, measured with archival temperature units(Onset-TidBit) at the tagging sites, normally variedbetween 1 and 24 �C, with temperatures steadilydecreasing from above 20 �C in August to below5 �C in late September, and lower than 1 �C from

November to April. Manual measurements showedthat water temperatures generally were 1–2 �C lower intributaries at higher altitude and decreased morerapidly during autumn.

Data analyses

Data from 55 (R. Vindelalven) and 31 (R. Pitealven)tagged individuals were used in the analyses ofspawning site selection. These were defined as fish thatwere alive (no mortality signal from tag) at the time ofspawning, which was known from the ripeness of thesea trout broodstock in the hatchery at Norrfors (R.Umealven) and the water temperature, because spawn-ing normally takes place at temperatures below 5 �C(Ake Forssen, Norrfors hatchery, personal communi-cation). In addition, this was correlated against visualobservations by local fishermen on trout spawning intributaries. The radio-tagged individuals were trackedall year around for the years 2002–2005, which helpedto define the spawning time window based on migra-tion behaviour. Typically, tagged fish moved rapidlydownstream within the time window for spawning,which indicated completed spawning, and then over-wintered in the main stems of the rivers (Ostergren &Rivinoja 2008). In the R. Vindelalven, the peakspawning period took place in the first 2 weeks inOctober and in the R. Pitealven about 1 week earlier.Spawning sites were defined as the positions of radio-tagged fish at spawning time. Loss of data in the R.Vindelalven occurred mainly in the vicinity of thetagging site (Table 2).

In the analyses of migratory patterns, individualslacking tracking data points for a period of 2 monthsor more were excluded; data from 51 (R. Vindelalven)and 28 (R. Pitealven) individuals were used. Aparameter, search reach Sr, was used as to describeup- and downstream movements during spawningmigration and was defined as the distance fromthe uppermost position before the first downstream

Table 1. Number (n), proportion of total spawning run, mean total body length BL (cm), mean weight (kg) and sex ratio on radio-tagged

individuals per year in the rivers Vindelalven and Pitealven

Year

Radio-tagged

(n)

Tagged of spawning

run (%)

Mean length,

BL (cm)

Mean

weight (kg)

Males

(n)

Females

(n)

Sex unidentified

(n)

Vindelalven 2002 29 23 68 3.7 8 20 1

2003 31 21 66 3.1 8 23 0

2004 30 9 66 3.1 15 15 0

Pitealven 2002 5 3 74 4.5 1 3 1

2003 14 7 61 3.0 2 12 0

2004 17 9 60 2.0 4 13 0

Total 126 11 65 3.2 38 86 2

SPAWNING MIGRATION OF SEA TROUT 75

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migration turn (>500 m), and the lowest positionbefore spawning, i.e. the river reach used for up- anddownstream movement prior to spawning. Threegroups of migratory patterns were identified anddefined as: (a) considerable up- and downstreammigrations, i.e. Sr that exceeded 3.5 km; (b) a stepwisemigratory pattern with several holding or restingpositions; and (c) a direct continuous upstreammigration, i.e. no holding or resting positions exceptat spawning areas.

Tree models (CART: classification and regressiontrees, Crawley 2007) analyses were performed toinvestigate explanatory variables to the observedmigratory patterns. Classification trees are non-para-metric tests that split data sets into new subgroups andminimise misclassification. Classification trees werechosen over logistic regression analysis because of itsability to handle mixed data types, to model bothlinear and non-linear relationships, to handle dichot-omous variables well, and to capture non-additivebehaviour without having to specify a priori the formof interactions (Olden & Jackson 2002). For theclassification tree, data from both rivers were pooled,and groups of migratory pattern Mpat was chosen asresponse variable, as a nominal (N) parameter con-sisting of the observed groups of migratory pattern a, band c. Predictor variables included in the model were:river R (nominal = N, Vindelalven/Pitealven), tagyear Tyear (N, 2002/2003/2004), tag day nr Tday

(continuous = C), body length BL (C, cm), sex G (N,male/female), distance from tagging site to spawningsite Sdist (C, km), spawning in a tributary Strib (N, yes/no) and migrating to a stocking location Lstock (N, yes/no). It was not possible to include origin in theanalyses because hatchery-reared individuals withintact adipose fin had been stocked. Two regressiontree analyses were performed using Sdist and Sr ascontinuous response variables. Data from both riverswere pooled, and all parameters as described abovewere included as explanatory variables in these models,except Mpat.

Statistical analyses were conducted using R (http://www.r-project.org). For statistical tests with normallydistributed data, Welch two-sample t-test was used, andfor non-parametric values, Wilcoxon’s signed-rank testwas used. Linear regression (LR) and Pearson’s prod-uct-moment correlation (PC) were used to examinerelationships between Sdist, BL and Tday; the r2 valuespresented are adjusted R-squared values given by R.The CART analyses were performed using default valuesfor tree models in R (http://www.r-project.org, Crawley2007), and results fromprune.tree (model, best = 4) areshown. Temperature effects on downstream migrationwere analysed using a Mann–Whitney two-tailed testand logistic regression with the probability of migratingupstream as the response variable.

Results

Spawning sites

River Vindelalven: The main spawning area defined byradio-tagged fish was located at the rapid Renforsen,58.3–60.4 km upstream of the tagging location. Theproportion of tagged individuals aggregating in thisarea was high; 46, 50 and 60% in the years 2002, 2003and 2004, respectively (Fig. 2). The average Sdist was72.9 km (min–max: 19.6–312 km, median 59.3 km)over the 3 years, with no difference between years(Wilcoxon rank: 2002 and 2003; W = 147, P = 0.905,2002 and 2004; W = 113, P = 0.543, 2003 and 2004;W = 161.5, P = 0.144). The longest migrating indi-vidual entered a tributary, the River Laisalven (Fig. 2).Of all tagged fish, 80% (n = 44) were located in areaswhere juvenile sea trout had previously been stocked.A significant negative correlation was found betweenSdist and Tday (PC, d.f. = 53, t = )3.26, P = 0.0019;LR, d.f. = 1 and 53, F = 10.63, r2 = 0.15,P = 0.0019; Fig. 4). There was also a significantcorrelation between BL and Sdist (PC, d.f. = 53,t = )3.05, P = 0.0036; LR, d.f. = 1 and 53,F = 9.30, r2 = 0.13, P = 0.0036; Fig. 4) and no

Table 2. Number and fate of radio-tagged individuals in the rivers Vindelalven and Pitealven

Year

Radio-tagged

(n)

Reliable

data (n)

Fallbacks

(n)

Tag loss or

mortality (n)

Fishing

(n)

Tag failure

(n)

Other

fate (n)

Vindelalven 2002 29 13 13 3 0 0 0

2003 31 22 2 4 2 0 1

2004 30 20 4 4 0 2 0

Pitealven 2002 5 4 0 1 0 0 0

2003 14 11 1 1 1 0 0

2004 17 16 0 1 0 0 0

Total 126 86 20 14 3 2 1

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correlation between BL and Tday (PC, d.f. = 53,t = 0.472, P = 0.639; LR, d.f. = 1 and 53,F = 0.222, r2 = )0.015, P = 0.639). Tday differedbetween the years (Welch t-test, 2002 and 2003:d.f. = 33, t = )5.45, P < 0.001; 2002 and 2004:d.f. = 30, t = )2.77, P = 0.0096; 2003 and 2004:d.f. = 37, t = )3.16, P = 0.0031), and females weresignificantly smaller than males (Welch t-test:d.f. = 56, t = )3.13, P = 0.0028).River Pitealven: In the R. Pitealven, many of the

radio-tagged individuals ascended tributaries forspawning, 75, 36 and 94% in 2002, 2003 and 2004,respectively. Most fish entered the tributary R. Var-jisan (n = 13) and a secondary tributary to the R.Varjisan, the R. Sikan (n = 7) (Fig. 3). Three addi-tional tributaries entering the R. Pitealven downstreamof the R. Varjisan were used for spawning and eightindividuals spawned in the main stem. The averageSdist was 81 km (3.3–141.3 km, median 87.4 km) overthe 3 years, with no difference between years (Welcht-test, 2002 and 2003; d.f. = 11, t = 1.21, P = 0.252,2002 and 2004; d.f. = 5, t = 0.258, P = 0.807, 2003and 2004; d.f. = 14, t = )1.21, P = 0.246). Theindividual with the largest Sdist was found in thetributary R. Sikan. A negative correlation was foundbetween Sdist and Tday in the R. Pitealven (PC,d.f. = 29, t = )4.54, P < 0.001; LR, d.f. = 1 and29, F = 20.69, r2 = 0.40, P < 0.001; Fig. 4). Therewas no correlation between BL and Sdist (PC,d.f. = 29, t = 0.321, P = 0.750; LR, d.f. = 1 and29, F = 0.103, r2 )0.031, P = 0.750; Fig. 4) orbetween BL and Tday (PC, d.f. = 29, t = 0.330,

P = 0.744; LR, d.f. = 1 and 29, F = 0.109,r2 = )0.031, P = 0.744).

Migratory pattern

River Vindelalven: In the R. Vindelalven, up- anddownstream migrations (pattern a; Fig. 5), was ob-served in 47% (n = 26) of sea trout. On average, theirsearch reach was 37 km (max–min: 3.6–75.5 km).Among fish displaying this pattern, 50% (n = 13)lacked a holding phase of their position at spawningtime. The stepwise migration, pattern b (Fig. 5), wasfound in 20% (n = 11) and included one or severalholding or resting positions, although 55% (n = 6)lacked a holding phase at their spawning site prior tospawning. Finally, 14 fish (25%) exhibited a rapid,steady upstream migratory phase and stopped neartheir spawning location, followed by an inactiveholding phase until spawning, pattern c (Fig. 5).

There was a significant difference in Sdist between thegroups of migratory patterns (Wilcoxon rank, a and b;W = 35, P = 0.023, a and c; W = 208, P = 0.478, band c; W = 242, P = 0.001). Pattern b fish displayedthe longest Sdist with a mean distance of 119 kmcompared with 52 km in fish with up- and downstreampattern a and 62 km for those showing a continuousupstream migration pattern c.

River Pitealven: In the R. Pitealven, 26% (n = 8) ofthe individuals exhibited pattern a searching a reach ofon average 18 km (3.5–55.0 km). Pattern b wasexpressed by 52% (n = 16), of which 56% (n = 9)lacked a holding phase at their position at the

0

50

100

150

150 170 190 210 230 250 270

0

50

100

150

200

250

300

350

45 55 65 75 85

BL (cm)

(a)

(b)

(c)

(d)

S dis

t (km

)S d

ist (

km)

Tday

Figure 4. Relationships between distance to spawning area from tagging location Sdist and day nr at tagging Tday in the R. Vindelalven (a) and the R.

Pitealven (b). Relationships between Sdist and fish size BL in the R. Vindelalven (c) and the R. Pitealven (d). Lines show linear regression.

SPAWNING MIGRATION OF SEA TROUT 77

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spawning time. Finally, 13% (n = 4) showed migra-tory pattern c with a holding phase at the spawningposition. Fish from the R. Pitealven exhibiting astepwise pattern b also displayed the longest spawningmigration, but the differences were non-significant(Welch t-test, a and b; d.f. = 3.77, t = )1.62, P =0.184, a and c; d.f. = 4, t = )0.108, P = 0.919, b andc; d.f. = 14, t = 0, P = 1) with an average distanceof 92 km compared with 59 km for fish with pattern a,and 54 km for those with pattern c.

A total of 11 individuals rested or were delayed onaverage 25 days (7–50 days) at the Fallforsen rapid,42 km upstream of the tagging location. There was nodifference experienced in environmental conditions(water flow and water temperature) between theindividuals that were delayed compared with thosethat were not (n = 14).

CART analyses

The classification tree analysis with migratory patterns(a, b and c) as the categorical response variable

generated a model with five terminal nodes (foursplits), and the three variables Sdist, Strib and Tday werethe only explanatory variables in the model (Fig. 6).The residual mean deviance was 1.46 (108.3/74),and the misclassification error rate was 0.317 (25/79).The first split was at Sdist of 92 km, separating patternb at higher values (Fig. 6). The second split Strib alsoseparated pattern b as fish spawning in tributaries.Patterns a and c were separated at the next two splits,by Sdist and Tday (Fig. 6 for details). In summary, thismodel classified 78% of pattern b fish by a distance tospawning site larger than 92 km and fish spawning intributaries. The model also showed that sea trout(n = 19, 24%) migrating shorter than 57 km andspawning in the main stems displayed pattern a or conly (Fig. 6).

The regression tree analysis with distance to spawn-ing site Sdist as a continuous response variable gener-ated a model with five terminal nodes (four splits) andthe variables Tday, R, Sr and BL were used in the model(Fig. 7). Fish tagged earlier than 12 July (Tday = 194)migrated longer distances than fish tagged later thanthis date, and this group of fish was split into rivers (R)

163 183 203 223 243 263 283

0

40

80

120

160

0

40

80

120

160

0

40

80

120

160

(c)

(b)

(a)

Tday

S dis

t (km

)S d

ist (

km)

S dis

t (km

)

Figure 5. Examples of typical migratory patterns of radio-tagged sea

trout. Trout exhibiting (a) several up- and downstream movements, (b)

stepwise migration pattern and (c) rapid migration directly to spawning

area. Sdist is distance to spawning area from tagging location and Tday is

day nr at tagging.

|

MigratoryPattern Mpat

n = 79Sdist < 92 km

Bn = 16

(A)(C)

n = 2n = 0

n = 61 Strib

YesB

n = 5n = 0n = 4

Non = 52

Sdist < 57 km

Cn = 17n = 10n = 6

n = 33 Tday < 233.5

An = 4

n = 0n = 1

Cn = 12

n = 2n = 0

(A)(C)

(A)(B)

(B)(C)

(A)(B)

Figure 6. CART classification tree with migratory pattern a, b and c as

categorical response variable. Oval represents the root of the tree.

Number of individuals and explanatory variable at the first classifica-

tion split with a threshold value are given. A split of continuous vari-

able < X means that fish with larger values than X is classified to the

rectangle to the right, and a fish with smaller value of X to the left in the

figure. Classification criterion with categorical variables (e.g. yes/no) is

given in the following rectangles. Rectangles represent decision points

(dotted outline) and terminal nodes (solid outline). In the terminal

nodes, the classification category with number of individuals (bold text)

and misclassified individuals and their true class (normal text) are given.

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as R. Vindelalven fish migrated the longest distance(Fig. 7). For fish tagged later than 12 July, individualsdisplaying a search reach (Sr) larger than 3.4 kmmigrated the shortest distance. This model also showedthat of fish tagged later than 12 July with Sr < 3.4 km,BL explained Sdist (Fig. 7 for details). The regressiontree analysis with search reach (Sr) as a continuousresponse variable generated a model with four terminalnodes (three splits), with the variables Lstock, G andTday were the explanatory variables in the model(Fig. 7). The first split separated fish migrating to areaspreviously used in stocking programmes, as fish with alarge Sr. In this group, males had a larger Sr thanfemales, and within the male group early tagged fish(Tday < 30 July) had a larger Sr (Fig. 7 for details).

Fallbacks and loss of data

Loss of data was mainly the result of fallbacks, tag lossor unknown mortality (Table 2). Fallbacks weredefined as individuals that actively or passively moveddownstream following tagging and entered the turbineintake at the power station (n = 17) or the dam spillway (n = 3). Tag loss or unknown mortality upstreamof the tagging location (n = 14) was mainly detectedat rapids. In total, 22 individuals tagged at the fishladder in the Umealven were registered �2.4 kmdownstream of the tagging location close to the water

intake at the Stornorrfors power station. These fish,together with three individuals that were registereddownstream of the spillway dam, were tagged at asignificantly higher water temperature (mean 19 �C,SD ± 2.4 �C) than radio-tagged individuals (n = 60)that continued upstream through the Vindelalven(mean 17 �C, SD ± 2.4 �C) (Mann–Whitney two-tailed; Z = )4,03; P < 0.001). A water temperatureof 20 �C was critical, causing downstream displace-ment (logistic regression; B = )0.47 SE = 0.14; Con-stant = 9.29; SE = 2.56; P < 0.001). The majority ofthe downstream displaced fish (n = 19) were detecteddead or disappeared presumably entering the turbineintake at the power station. During the tagging period,water flow in the power station varied between 200 and600 m3 s)1. No correlation was apparent betweenlikelihood of downstream migration and water flow.

Discussion

Brown trout is well known for its highly plastic lifehistory, and the species can be found in a widediversity of aquatic habitats (Elliott 1994; Klemetsenet al. 2003). This study demonstrated the variablebiology of the anadromous morph of brown trout (seatrout), in terms of high variability in individualmigratory pattern and selection of spawning habitat.The huge individual variation observed in this study

|Distance Sdist

n = 86Tday < 193.5

n = 33River R

n = 53 Sr < 3.4 km

Piteälvenn = 26

~88 km

Vindelälvenn = 7

~171 km

n = 25~48 km

n = 28BL < 63

n = 6~98 km

n = 22~57 km

(a)

|

Searchreach Srn = 79Lstock

Non = 35~5 km

Yesn = 44 Sex G

Femalen = 23

~13 km

Malen = 21

Tday < 211.5

n = 8~51 km

n = 13~18 km

(b)

Figure 7. CART regression trees with distance to spawning area from tagging location Sdist (a) and search reach Sr (b) as continuous response

variable. Oval represents the root with number of individuals and explanatory variable at the first split and a threshold value. A split of continuous

variable < X means that fish with larger values than X is classified to the rectangle to the right, and a fish with smaller value of X to the left in the

figure. Decision criterion (e.g. Pitealven/Vindelalven) with categorical variables is given in the following rectangles. Rectangles represent decision

points (dotted outline) and terminal nodes (solid outline). In the terminal nodes, number of individuals in the node and their average Sdist (a) or Sr (b)

are given.

SPAWNING MIGRATION OF SEA TROUT 79

� 2010 Blackwell Publishing Ltd.

made analyses difficult. An approach, therefore, sep-arated the tagged individuals into three groups ofexhibited migratory pattern and investigated explana-tory variables to these differences in migration behav-iour. The classification tree analysis indicated thatdistance to spawning site from tagging location was themain explanation of migratory patterns. Spawninglocation (tributary or main stem) and also day oftagging explained the patterns further. Thus, sex, fishsize, year, stocking location and river did not explainthe groups of migratory pattern. Fish migrating longdistances, and those fish spawning in tributaries,displayed a stepwise migratory pattern. There areseveral possible explanations for this migration behav-iour. (1) Long distance migrating fish might simplyneed several resting positions on their way to thespawning grounds, also observed by Økland et al.(2001) in Atlantic salmon in the River Tana, Norway.(2) Sea trout spawning in tributaries hold downstreamof a tributary waiting for suitable environmentalconditions (water flows and/or water temperatures)before ascending to spawn (Evans 1994). In Scottishrivers, Atlantic salmon enter the main rivers through-out the year (Shearer 1990), but ascend the tributariesjust before spawning time, during increased riverdischarge event (Webb & Hawkins 1989). Also, enter-ing a tributary might increase risk of predationmortality, because the fish are more exposed inshallower waters. (3) Stepwise migration may indicatethat certain parts of rivers, i.e. rapids, can act as partialmigration barriers slowing down migration speeds(Arnekleiv & Kraabøl 1996; Ovidio & Philippart 2002;Rivinoja 2005). In the present study, a rather longdelay, or resting behaviour, of up to 50 days wasobserved at a relatively short and steep rapid in the R.Pitealven. No correlations with water flow and tem-perature and passage success was found, although high(and low) flows and temperatures can hinder upstreammigrating trout passing obstacles (Trepanier et al.1996; Arnekleiv & Rønning 2004).

The CART analysis also indicated that considerableup- and downstream migrations were shown by fishspawning closer to the tagging location. With a shortdistance to their spawning site, fish could be spendingtime on searching for mates or searching for asuitable spawning habitat or also searching for theirnatal area.

Regression tree analyses indicated that the distanceto spawning area was mainly explained by the day oftagging, where early tagged individuals had the longestmigration distance. This was supported by the linearregression analyses, because negative relationshipsbetween distance of migration and tagging day were

apparent in both rivers. Also, this is in accordance withother studies on sea trout in the R. Vindelalven(Andersson 1988), and Atlantic salmon in the R. Tana(Økland et al. 2001) where a negative relationshipsbetween migration distance and tagging day have beenobserved. In the CART analysis, river and search reachexplained the distance further.

The third CART analysis, with search reach as theresponse variable, showed that stocking location, sexand tag day might explain this migration behaviour.Fish migrating to a location used in stocking pro-grammes exhibited a larger search reach than fishmigrating to an area not used for stocking. Also, maleshad a larger search reach than females, and, finally,earlier tagged males had a larger search reach thanlater tagged males. A possible explanation to thesearch behaviour may thus be that some tagged fishwere of hatchery origin and therefore had a compro-mised homing ability. Hatchery-reared salmon seem tohave less pronounced homing than wild fish (Quinn2004 and references therein). Jokikokko (2002)reported that radio-tagged, hatchery-reared salmonreleased as smolts in the R. Simojoki, Gulf of Bothnia,showed a more erratic spawning migration patternthan wild salmon when they returned as adults. In thisstudy, males migrated further up- and downstreamthan females. This contrasts with observations byFinstad et al. (2005) who found no such sex-relateddifferences. It is well known that salmonid males aremore active during the spawning event, e.g. searchingand competing for mates, than females (e.g. Webb &Hawkins 1989). Hence, males could be expected tomove more up- and downstream.

When comparing the two rivers studied, there weredifferences between location of spawning areas selectedby tagged sea trout, with tributaries being used in theR. Pitealven but not in the R. Vindelalven. When fishmigrations into the R. Vindelalven were limited by thehydropower dam constructions in the R. Umealvenbetween 1925 and 1935 (Andersson 1988), few seatrout had the possibility to spawn. In addition, manyof the tributaries with suitable trout habitat have beencut off by dams and were channelised during the logfloating era (1870–1980) (Nilsson et al. 2005). Takentogether, these activities have likely had a hugenegative effect on the sea migrating trout populationin the R. Vindelalven. The main aggregation of radio-tagged sea trout at spawning time in the R. Vindelal-ven was around the principle release location for alarge number of stocked, hatchery-reared sea troutfrom 1936 to 1999. Although speculative, it is plausiblethat the stockings have influenced the sea trout’s choiceof spawning area in R. Vindelalven, because 80% of

J. OSTERGREN ET AL.80

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radio-tagged fish migrated to spawn in areas histori-cally used for stocking.Downstream migrations were also correlated with

water temperature immediately after tagging in the R.Vindelalven. Fish tagged at above 20 �C moved, ordrifted, downstream. This could be a consequence oftagging and handling at a temperature already stressfulto the fish. Downstream migration after radio-taggingwas noted by others (Gerlier & Roche 1998), and inthis study, this behaviour resulted in individualsentering the turbine intake, or spillway dam, causingincreased mortality.In conclusion, radio-tagged sea trout in the rivers

Vindelalven and Pitealven exhibited varying migratorypatterns, possibly explained by the distance to spawn-ing sites and the choice to spawn in a tributary. Humanactivities, such as damming and stocking of hatcheryfish, may have influenced the sea trout’s migrationbehaviour and spawning site selection. This studyillustrated that sea trout spawning long distances fromthe sea, and in tributaries in R. Pitealven, enter theriver early in the season. This is important to considerin the management of the sea trout to avoid overex-ploitation of subpopulations. The information onspawning areas, and delays at rapids reported is alsoimportant for sustainable management, as some areasmay be protected against habitat degradation andfishing.

Acknowledgments

We thank B. Wiklund, P. Rivinoja, A. Oberg, J.Isaksson, P. Lidstrom, C. Pouchard, M. Lindback, H.-A. Carlsson, S.-E. Blom, T. Enmark, D. Holmqvist, T.Stenlund, S. Westberg, Vindelalvens fiskerad, Piteal-vens Ekonomiska forening, Vattenfall AB staff inNorrfors, Vattenfall Service Nord AB, Hotell Storfor-sen, Sikfors Camping, Umea Flygklubb, Eislab, B.Efraimsson, Gunda med familj for help. Paul Kempand three anonymous people are thanked for valuablecomments on an earlier version of the manuscript. Theproject was financed by the Ministry of SustainableDevelopment (LIP), EU-fundings Mal 1 and a coop-eration between the following communities: Arjeplog,Arvidsjaur, Lycksele, Pitea, Sorsele, Vannas, Vindeln,Alvsbyn and also the County administration in Norr-and Vasterbotten and the National Fisheries Board.Further funding to J. Ostergren was received from:Goran Gustafsson stiftelse for natur och miljo iLappland, Kempestiftelsen, Stiftelsen Carl-Fredrikvon Horns fond och Knut och Alice Wallenbergsstiftelse. The handling and tagging procedure was

approved by the Swedish Animal Welfare Agency nr:A65-01.

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