We examined run timing of 1SW Atlantic salmon originating from multiple, genetically distinct populations within a single large river system. To the best of our knowledge, this study represents the first detailed study of return migration behavior of Atlantic salmon applying GSI approach as a ‘tagging’ method. The results demonstrated significant and temporally stable differences in timing of arrival with 1SW salmon originating from tributary populations entering fresh water earlier than their counterparts from headwater and mainstem populations. There were also differences between sexes whereby females arrived earlier than males within tributary populations, whereas no such differences were found for 1SW salmon originating from headwater and mainstem populations. The observed differences in run timing among populations were related to population size and sea-age group structure of the spawning stock, but not to in-river migration distances.
In addition to the usability of archived tissue samples, a major advantage of the GSI approach is that large sample sizes can easily be obtained as unlike conventional tagging studies it is not dependent on the recapture rate of marked individuals. However, the GSI approach is not without impediments. While the genetic structure of the system and the used methodology are important in determining the individual identification success, an important, but difficult to assess and therefore often neglected potential source of error in mixed stock assignment studies is the adequacy of the baseline data. In the following, we will first discuss the issues related to genetic tagging method and the accuracy of GSI of Teno salmon. Thereafter, we proceed to discuss our findings in more detail and provide implications for management.
Methodological aspects: genetic stock identification
Power analyses of expected accuracy of GSI employing 32 microsatellite loci (mean 14.8 alleles per locus) within the Teno population complex (global FST = 0.07) indicated very high individual assignment success: near 100% for tributary salmon and over 90% success for the MS/HW salmon. The higher success in assigning tributary fish was expected as they are genetically more diverged (FST = 0.1) and less diverse (GD = 60–80%) compared to MS/HW fish (FST = 0.02). In general, the levels of assignment success were in concordance with expectations from a number of simulation studies indicating that a near 100% assignment success can be achieved by using ≥10 moderately variable microsatellite loci in a set of 10 populations with FST ≥ 0.1 (Cornuet et al. 1999; Manel et al. 2002) and in some cases very high assignment success (∼90%) can be achieved even with lower level of differentiation FST ≥ 0.02 and fewer loci (Hauser et al. 2006). However, the high level of GSI accuracy with e.g. oncor and CBayes methods is expected only in situations with the baseline data available from each potential source population (Anderson et al. 2008).
Indeed, our simple power analyses with a population sample missing from the baseline data suggested that performing GSI using e.g. oncor, nearly all individuals originating from populations not included in the baseline were incorrectly assigned to one of the four most diverse and less diverged MS/HW populations. This indicated that the relative contribution of these populations to the fisheries catch sample would be inflated by the relative contribution of populations not in the baseline. In our study, this was a conceivable source of error if not considered as there are at least three tributaries draining to the mainstem of Teno with considerable 1SW salmon stock that were not sampled for the baseline.
Although, the magnitude of error due to having individuals from nonsampled populations in the mixture sample cannot be systematically accounted for in any simulations of accuracy (Anderson et al. 2008), an approach where Structure analysis was performed using additional ‘dummy’ clusters, i.e. K + 4 clusters [where K was the number of populations (14) in the baseline data], was found a potential strategy to minimize the error resulting from incomplete baseline data. This was demonstrated in our test runs with Structure, where individuals of each tributary population were in turn treated as of unknown origin, and analysis performed with up to three additional clusters (K + 3): nearly all individuals from the ‘unknown’ populations were correctly identified and assigned to these dummy clusters indicating that individuals of unknown origin could potentially be filtered out by using ‘dummy’ clusters.
Performing Structure analyses with four ‘dummy’ clusters (K = 18) on our mixed stock fisheries catch samples, 224 individuals were excluded from the data as originating from nonsampled populations. The majority of these individuals were assigned to the MS/HW populations with oncor (92%) and with Structure (84%; K = 14) according to expectations from the simulations. In our final GSI solution, a further 176 individuals had ambiguous genotypes and were not assigned to any of the clusters. These individuals may have been inter-population hybrids, inbred or from other nonreferenced populations (Baudouin et al. 2004). At this point, we do not have the means to assess the true accuracy of the individual assignments, but based on our simulations and test runs we expect the deduced GSI solution to be appropriate. A more comprehensive baseline data from the more remote areas in the headwaters should enable us to assess the accuracy of our GSI solution and the ‘dummy’ cluster approach, in addition to performing a more exhaustive genetic structure assessment of these areas.
Nevertheless, the adopted ‘dummy’ cluster approach represents a potential alternative to exclusion methods, where the genotype of each individual is compared to a set of simulated individuals and excluded if its probability of appearing falls below a set threshold, e.g. as implemented in GeneClass (Cornuet et al. 1999). The adopted approach, however, is likely more efficient than the exclusion method, as CBayes and Structure have been shown to outperform GeneClass in assigning individuals to populations (Manel et al. 2002; Koljonen et al. 2005; but see Hauser et al. 2006). However, the performance of Structure and GeneClass in excluding individuals from populations of unknown origin should be thoroughly tested with a view to identifying also inter-population hybrids and inbred individuals (Baudouin et al. 2004).
One of the advantages of the GSI approach is that large sample sizes can be obtained with relatively little effort compared to conventional tagging studies. For example, during six consecutive years, Stewart et al. (2002) tagged more than 30 000 salmon of which they obtained <700 returns, yielding a ∼2% recapture rate. In this study within the Teno river system, the ‘recapture rate’ was ∼79%, nearly 40 times of what would have been expected from the conventional tagging studies. It must be noted, however, that in mark–recapture studies accuracy of individual assignment is without error assuming that individual was marked at natal site. An alternative tagging method, marking individuals on their way to natal sites using radio-tags, has been successfully applied on Pacific salmon (e.g. Keefer et al. 2004). In this approach, population of origin is identified by last observation or the actual breeding event of an individual, and the accuracy is related to the population straying rate. In the case of genetic tagging of Teno salmon, expanding the baseline data to cover all populations contributing to the mixed stock fishery are expected to increase both the accuracy and the ‘recapture rate’ of GSI analyses with relatively small genotyping effort.
Variation in run timing
This study demonstrated significant differences in run timing among 1SW Atlantic salmon originating from different populations within the Teno river system. The results also confirmed a remarkable level of temporal stability in migration pattern despite varying water flow regimes and fish abundance. Generally, the 1SW salmon from tributaries entered freshwater first, on average nearly 2 weeks earlier than their counterparts from headwater and upper mainstem populations. Interestingly, the 1SW salmon from the two populations closest to estuary, Teno mainstem lower and Maskejohka (T) arrived latest, but in general, timing of freshwater entry was not related to in-river migration distance. Instead, it was significantly and positively related to population size; 1SW salmon originating from small populations arrive first, and to sea-age structure of the spawning stock; the higher the proportion of larger MSW females in the population, the later the 1SW salmon arrive. These insights to the migration behavior of Atlantic salmon are interesting from the biological as well as from the management perspective.
Although the time gap between runs of tributary 1SW salmon and mainstem/headwater 1SW salmon appears small (2–3 weeks) compared to e.g. ‘fall’ and ‘spring’ runs in Pacific salmon (Keefer et al. 2004; Anderson and Beer 2009) or that reported by Stewart et al. (2002) for the Scottish Atlantic salmon, the observed difference may nonetheless play a significant role in optimal timing of arrival to a sub-arctic river (70°N). The functional argument for the adaptive significance of the trait is that salmon would not waste resources in feeding areas to change its behavior unless it was adaptive. As earlier studies have demonstrated the genetic basis of the timing of salmon arrival (Hansen and Jonsson 1991; Stewart et al. 2002), the first condition of Taylor’s (1991) three prerequisites for demonstrating local adaptation is fulfilled. But what is the mechanism of selection responsible for the maintenance of the trait and is differential expression of the trait associated with differential reproductive capability?
One potential mechanism of selection for the earlier run timing of tributary 1SW salmon compared to the MS/HW is the water level and the accessibility of the spawning site. Characteristic to tributaries, apart from Utsjoki, is the lack of lakes. Consequently, the breakage of ice in mid/late May is followed by a very short spring flood period after which the water discharge and level rapidly decreases. As a result, tributaries become shallow compared to the MS/HW and in some years the tributaries may even occasionally be inaccessible to salmon later in the season. Thus, in tributaries late arrival may strongly be selected against, while in the MS/HW run timing is not constrained by water level.
Contrary to the tributaries, postponing arrival may be a better strategy for 1SW salmon breeding in the MS/HW. Our result showing that the proportion of MSW females in the spawning stock was significantly and positively related to run timing of 1SW salmon (Fig. 4) suggests that sea-age structure of the spawning population may have played a significant role in shaping the migration behavior. In spawning areas with a low proportion of larger MSW females, i.e. majority of the tributaries, 1SW salmon can compete and gain control over the best spawning sites, making early arrival beneficial in terms of breeding success, while at sites with a higher proportion of MSW salmon, postponing arrival and remaining at the feeding areas to increase in size at maturity may be a better strategy for 1SW salmon.
Among tributary 1SW salmon, sex had a significant effect on the timing of river entry: females arrived significantly earlier than their male counterparts. Among MS/HW 1SW salmon, there was no significant difference in the timing of arrival between sexes although in Kárášjohka (HW) females appeared to arrive earlier than males. These results are in accordance with earlier studies reporting earlier accumulation of females in the total catch of 1SW salmon (Niemelä et al. 2006). However, our results highlight the importance of appropriate management units, since general trends, as e.g. 1SW females arriving earlier than males, may be driven by population rather than sex-specific differences in run timing. At least in the Teno, the earlier ascendance of tributary populations may drive the earlier accumulation of females in the total catch of the mainstem mixed stock fishery, as 1SW females are common in tributaries, but not in the MS/HW. But why do females leave feeding areas at sea earlier than males?
According to theory, the intensity of sexual selection drives the arrival timing of individuals on breeding grounds and e.g. in migratory birds, both male-biased adult sex ratios and high levels of sperm competition both produce protandry, i.e. males arriving first (Kokko et al. 2006). Similarly, the importance of territorial control may cause females to precede males in arriving to breeding grounds. In the Teno, tributaries are generally dominated by 1SW salmon, although 2SW females are not uncommon, while in the MS/HW there are up to seven and eight different sea-age groups (including previous spawners) for females and males, respectively (Niemelä et al. 2006). As females are known to choose the breeding location where they dig redds to lay eggs in, with males competing for access to females (Fleming 1996), territorial control is characteristic behavior of Atlantic salmon. Interestingly, the aggressive behavior of females for a territory does not begin until close to the start of breeding season, late September. This is supported by snorkeling observations and telemetry studies in tributaries of Teno suggesting that females and males rest, often side-by-side, in deeper pools of the tributaries (Orell and Erkinaro 2007; P. Orell, unpublished data). The distance from the resting or holding site may often be hundreds of meters from the actual spawning site. Why then, is there a difference in the run timing between sexes, when there is more than 2 months before the start of the spawning season? Telemetry studies have indicated that immediately following the ascendance to natal river, salmon show searching behavior by migrating up and down the river for several kilometers before coming to a holding phase (Økland et al. 2001). Females finding and evaluating possible spawning sites before the low water level and rise of temperature, which both limit swimming performance and influence the physiological response to exhaustive exercise (reviewed by Kieffer 2000), is a potential hypothesis to be tested for explaining this behavior.
An alternative explanation to variation in timing of return migration is that arrival to fresh water is simply associated with the use of different feeding grounds in the open sea. The use of different oceanic regions has been previously related to variation in run timing among sea-age classes (Shearer 1992), but Jutila et al. (2003) further showed that salmon of same sea-age, but with different backgrounds (wild versus hatchery) also utilized different areas in the Baltic Sea basin. They proposed that differences in the sea distribution of postsmolts may result from the availability of suitable prey in relation to the size of a smolt.
Finally, as the samples used in this study were collected by local fishermen from drift net, weir and gill net fisheries, and net fisheries in general are known to be size selective (Reddin 1986), it is important to consider how well such a sampling procedure represents the natural 1SW salmon run of Teno River. As the smallest net size allowed in the mainstem of Teno is 58 mm (knot to knot), it is possible that the smallest 1SW salmon may pass through a net without being caught. Given that tributary 1SW salmon are generally 20–25% smaller in size (mean weight 1.2 kg) than their mainstem counterparts (Länsman and Niemelä 2010), it is possible that their contribution to the total 1SW stock may be underestimated in our study. However, a simple size selective fishery could not generate the observed pattern of run-timing behavior. While we acknowledge the potential for nonrandom sampling, this is unlikely to change the conclusions of the study regarding run-timing differences and its relationship to the sea-age structure of the spawning populations. On the contrary, if a fraction of the smaller tributary fish escape the fishery early in the season, our main result, that the proportion of tributary fish is higher early in the season, would actually be conservative.
Implications for management
The discovery of clear differences in run timing of 1SW salmon originating from different populations within a river system has considerable implications for the estuary and in-river management of salmon. Operating net fisheries are often seen as size selective and their potential to introduce directional selection pressure on size at maturity or growth rate is attested (Conover and Munch 2002; Ernande et al. 2004; Swain et al. 2007) and now widely accepted. Much less appreciated and only very recently realized is the potentiality for fisheries induced directional selection and/or differential exploitation rates among populations owing to variation in migration behavior (Quinn et al. 2007; Hard et al. 2008; Anderson and Beer 2009). Salmon fisheries are often temporally regulated with high fishing effort at use during a short fishing season (Crozier et al. 2004; Siira et al. 2009), but in the light of this study, such a strategy is likely to result in heavily biased harvest of 1SW fish of particular populations and/or sex. For example, allowing the mixed stock fisheries in Teno to operate intensively the first month of the fishing season would result in a relative overexploitation of tributary salmon. From this perspective, harvest pressure should be distributed evenly across the whole migration window of 1SW salmon by controlling effort. This should minimize the potential evolutionary response (Quinn et al. 2007; Hutchings and Fraser 2008).
From the perspective of total effective size of the meta-population, considerable gain can be made through a harvest strategy adjusted prioritizing between different subpopulations varying in size and degree of isolation (Tufto and Hindar 2003). To increase the effective population size (Ne), the optimal harvesting strategy in terms of maximizing the total yield, is to harvest relatively less isolated and/or smallest populations because these contribute more to the total effective size with a relatively small reduction in the total yield (Tufto and Hindar 2003). In the light of this theory, allowing 1SW targeted fisheries in the mainstem to operate only from late June allowing salmon from tributary populations to escape fisheries would lead to an increase in the total Ne, i.e. conserving genetic variation, while minimizing the reduction in the harvesting yield.
Management of salmon fisheries on both sides of the Atlantic is in general, through procedures recommended by the North Atlantic Salmon Conservation Organization (NASCO; http://www.nasco.int), moving toward the use of management targets as a tool for evaluating stock status. First-generation spawning targets have recently been developed also for some parts of the Teno river system (Hindar et al. 2007). Although the present study provides important information on the return migration behavior of salmon from different populations, which in itself is useful to the managers, several factors need to be considered and investigated in order to reach specific spawning targets in the Teno. This study investigated only 1SW salmon in the Teno River, which comprise about 60% of the total number, but only 20% of the total weight of salmon catches. The MSW component of the salmon stock is thus more important in terms of catch yield. Differences in run timing of MSW salmon originating from different parts of Teno may also exist and unraveling the contribution of each population to MSW fisheries during the fishing season should be investigated. Furthermore, although radio-telemetry studies have suggested high exploitation rates for the Teno salmon fisheries in general (up to 60–70%; Erkinaro et al. 1999; Karppinen et al. 2004), practically nothing is known about the relative population-specific harvest rates. As the in-river salmon fisheries in Teno include commercial, presumably size selective methods such as weir (19% of total catch), gill net (10%) and drift net (12%), in addition to the recreational rod and line (58%) the selectivity of different fisheries for different populations should be also investigated in order to build a comprehensive and adaptive management strategy of Teno salmon. Similarly, there is an obvious need to study the exploitation of various returning populations of the Teno system in the coastal mixed stock salmon fishery in Norway.