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- Supporting Information
It is well established that antagonistic genotype by environment interactions for fitness can create adaptive spatial variation, where different genotypes are favored under different environmental conditions (Merila and Crnokrak 2001; Kawecki and Ebert 2004; Leinonen et al. 2008, 2013). Since the potential of populations to adapt to specific conditions carries strong implications for nature conservation and our understanding of evolutionary patterns, the quantification of local adaptation has become an important task in biological research.
Local adaptation may, however, be inferred in several ways, one of the most widely used being reciprocal translocation studies, where different populations are reared in a reciprocal manner in their locations of origin (Hereford 2009). Antagonistic patterns in the performance of different populations across environments and, especially, populations performing best in their native environment are inferred to reflect local adaptation (Kawecki and Ebert 2004; Hereford 2009). Although an efficient method for studying local adaptation, translocation studies suffer from two logistic shortcomings. First, it is often difficult to rear organisms originating from multiple populations under natural “common garden” conditions. This is especially the case in freely moving organisms. Second, since the objective is to examine antagonistic patterns of fitness of different genotypes across environments, it is crucial to have a correct measure of fitness. As fitness is a composite trait, its correct estimation is not a simple task (Shaw et al. 2008). Indeed, traits closely linked to fitness, such as survival or reproductive success, are likely to be involved in trade-offs with other fitness-related traits (De Jong and Van Noordwijk 1992; Reznick et al. 2000). Consequently, the inference of local adaptation is highly dependent on how fitness is estimated.
The above complications have led to the development of alternative ways to examine presence of local adaptation based on comparing observed genetic divergence in traits of interest to a scenario of neutral divergence. One such a methodology is QST–FST comparison (Spitze 1993), where neutral genetic divergence as estimated from neutral molecular markers (FST) is compared to the divergence in a quantitative trait (QST). QST is estimated as follows:
where σ2AB is the additive genetic variance component explained by population differences, whereas σ2AW is the within-population genetic variation of the trait. If QST << FST, stabilizing selection is inferred, if QST >> FST divergent selection is inferred, and if QST and FST are of the same magnitude, the trait under study is assumed to have evolved in a neutral manner.
In order to obtain reliable estimates of genetic variances for populations, it is crucial that the traits are recorded under common conditions, that is, when the populations compared are exposed to the same environment, since environmental effects may inflate variation in trait divergence (Pujol et al. 2008; Alho et al. 2010, 2011). In a similar vein, the estimation of genetic variances often requires controlled environmental conditions (Weigensberg and Roff 1996). Consequently, the vast majority of the studies using QST–FST comparisons to infer local adaptations have been conducted in laboratory conditions (Leinonen et al. 2008; Pujol et al. 2008). If the intention of the study is to infer local adaptation as it would appear under natural conditions, these preconditions make the strong assumption that there are no population × environment interactions in the focal trait. Although the inference for local adaptation via QST can be influenced by variation in experimental conditions (e.g., Richter-Boix et al. 2010; Hangartner et al. 2012), few studies have examined the presence of local adaptation using both translocation experiments and QST–FST comparisons, where the assumption of no population × environment interactions can be tested. Such interactions are also important from an evolutionary perspective, as the speed at which an evolutionary response may precede is likely to be dependent on the amount of plasticity of the trait (Price et al. 2003). In cases where the genetic effects are overridden by plastic responses to different environments, plasticity may impede an evolutionary response (e.g., Price et al. 2003; West-Eberhard 2003), suggesting that plasticity may play a key role at early stages of divergence. However, the relative amount of variation in fitness traits explained by environmental versus genetic effects under natural conditions has remained an unexplored topic in evolutionary biology.
This question is especially relevant in managed systems like salmonid fish populations, where individuals from foreign populations have frequently been introduced into native populations. If genotypes of different origin are highly plastic, we may expect that there is only weak or no selection against nonadapted (foreign) genotypes. On the other hand, if phenotypic variation is mainly genetic, we may expect that natural selection is acting directly on genetic variance and that nonadapted genotypes will be selected against. Sea-run brown trout (Salmo trutta) is commonly managed by sea-ranching, where breeding fish are caught from the wild, the offspring are reared in a hatchery and subsequently released into the wild at the smolt stage, when juvenile salmonids migrate to the sea (e.g., Petersson et al. 1996). The hatchery conditions differ strongly from the species' natural habitats, and adaptive divergence, where hatchery populations of the brown trout have higher growth rates than wild populations has been demonstrated (e.g., Rogell et al. 2012). In addition, genetic selection gradients for larger body size were very steep for wild trout populations reared in hatchery environments, indicating that body size is strongly genetically correlated with a causal trait upon which hatchery selection is acting (Rogell et al., unpubl. ms.). This is not surprising, since growth rate and body size frequently vary across environmental clines. Body size is often closely associated with fitness, and a large body size generally incurs higher reproductive capacity and competitive ability (Arendt 1997; Dmitriew 2011). However, the fact that many populations express submaximal growth rates is generally explained by costs of high growth in terms of a higher sensitivity to predators and environmental stress (Arendt 1997; Dmitriew 2011). For example, adaptive divergence in intrinsic growth rates in amphibians has been found across gradients of latitudinal climatic variation (Palo et al. 2004) and environmental stress (Rogell et al. 2009; Hangartner et al. 2012). Thus, the fast-growing hatchery populations are likely to be more competitively dominant/aggressive, but they are also likely to exhibit a more risk-taking behavior, which makes them more exposed to predation in the wild (Biro et al. 2004; Sundström et al. 2004).
Here, we examine the consistency of local adaptation across a range of environmental conditions, as well as the amount of phenotypic variance explained by population and environment, in a large-scale experiment conducted during two successive years. In a previous study, we reared several sea-run brown trout populations over the first growth season under controlled hatchery conditions and in a semi-natural experimental stream, respectively, to assess within- and among population variation, and to estimate QST for body size and survival (Rogell et al. 2012). Microsatellite markers were used to estimate neutral genetic differentiation (FST) between the study populations and to determine population and family origin of the experimental fish (Rogell et al. 2012). In a parallel study reported in this article, all parental crosses from all populations were stocked into natural streams devoid of trout, located close to the native streams of the focal populations. This allowed us to compare trait values of different populations in a semi-reciprocal manner.
The objectives of this study were (i) to investigate if adaptive patterns of brown trout life-history traits are consistent across stream environments and (ii) to assess the importance of population origin and rearing environment on growth and survival. Since our previous results showed that reaction norms in trout body size and survival across hatchery and experimental stream conditions were parallel (Rogell et al. 2012), we expected population × rearing environment interactions on size to be rather small, which would indicate that adaptive patterns of brown trout life-history traits are consistent across stream environments. Predictions for survival differ, however, since a trade-off between growth rate and survival can be assumed. As captive hatchery conditions lack predators, we expected the hatchery populations to have a stronger competitive ability in the experimental stream free from predatory fish. On the other hand, as fish predators are present in the natural streams, we expected hatchery trout to be more adversely affected by predation than their wild conspecifics in those environments. As we have no prior expectations, due to lack of previous studies, of how much variation in life-history traits that are explained by adaptive divergence versus plastic processes we assessed the importance of population origin and rearing environments on body size. We note that a stronger genetic than plastic component would allow a more efficient selection against nonnative genotypes.
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- Material and methods
- Conflict of Interest
- Supporting Information
We found that the evolutionary background of local brown trout populations explained a larger proportion of the phenotypic variation in an important life-history trait (body size) than plastic environmentally induced effects across natural rearing habitats. The small effect sizes of the population × environment interactions together with significant QST values further suggest that the adaptive divergence in body size remains constant across a range of local stream environments. Given that the speed of an evolutionary response may be hampered by abundant plastic variation in the trait, our results also suggest that the selection on the phenotypic variance is likely to induce fast evolutionary responses (Price et al. 2003).
Theory predicts that populations can adapt locally when there are antagonistic patterns in fitness across different environmental conditions (Kawecki and Ebert 2004). Although we could not detect any significant differences in survival, our fitness component, QST for body size was significantly higher than FST in all environments, and environment explained a smaller proportion of the phenotypic variation than population origin. Since QST represents a test for local adaptation, the very weak interactions between population and rearing environment provide indirect evidence for antagonistic fitness patters for populations reared in different environments. As previously shown, these patterns are likely to be due to selection for higher growth rates in the hatchery-reared populations (Rogell et al. 2012; Rogell et al. unpubl. ms.). The overall higher growth rates in the hatchery populations can be due to increased competition and lack of predation mortality in the captive environment (e.g., Petersson et al. 1996). Higher growth rates are often associated with behaviors such as increased risk taking and may thus carry cost in terms of increased predation in natural habitats (Biro et al. 2004; Sundström et al. 2004). Previous studies have found that animals often decrease their foraging activity in environments with predators, which may translate into reduced growth rate (Lima 1998; Tollrian and Harvell 1999).
However, our results suggest that the fast growth rates of hatchery populations are likely to be expressed in environments both with and without fish predation. Since these genotypes will be fast growing across all environmental conditions, the divergence by hatchery rearing may carry costs in natural environments. Hatchery fish have been shown to have lower fitness under natural conditions compared to wild fish. For example, Araki et al. (2007, 2009) showed that hybrids between hatchery and wild steel head trout suffered a ~40% reduction in fitness compared to wild fish under natural conditions. Such fitness losses are likely to reflect adaptive genetic changes associated with hatchery rearing (Araki et al. 2007; Araki et al. 2009; Rogell et al. 2012), but are these fitness losses likely to be constant across natural environments? We here show that the adaptive patterns of body size induced by hatchery rearing are similar across several natural habitats. Our results thus indicate that the phenotypic variation is to a large extent determined by genetic rather than environmental factors, and that hatchery adaptations may be efficiently selected against in the natural environments.
The methodology to infer selection based on QST–FST comparisons suffers from several methodological complications. Studies on the precision of QST estimates have shown that the variance of QST estimates is high and that there is a tendency for a downward bias, particularly when the number of populations is low (<20) and true QST is high (O'Hara and Merilä 2005). As this would suggest that our QST estimates are conservative, we do not find this a major drawback. Considering the low number of populations and streams in this study, Bayesian models have the advantage that model uncertainty is correctly summarized, and thus that correct confidence intervals for the parameter estimates can be constructed (Berger 1985). An additional source of error is the putative presence of maternal effects in the estimated among- and (broad sense) within-population variance components. Although we cannot exclude the potential confounding role of maternal effects, the rather similar results across the 2 years suggest that maternal effects were of minor importance in this study. Finally, we cannot exclude the possibility that our results are affected by competitive interactions as the hatchery fish are likely to be stronger competitors compared to the wild fish.
While our attempts to estimate survival in the natural streams were hampered by the generally low recapture rate in these streams, survival was considerably higher in the experimental stream (Rogell et al. 2012). The higher survival observed in the experimental stream could be due to the high productivity of this stream in combination with a lower predation pressure. Also, trout released in the experimental stream could have been less inclined to leave the stream because of the trap situated in the downstream part, whereas trout released in the natural streams (devoid of trout) could disperse and utilize larger areas of the streams (Elliot 1994; Rodriguez 2002), which in combination with predation may have resulted in lower recapture rates. However, previous studies have found that juvenile trout that are out-competed at their original areas suffer high mortality rates (Elliot 1986), and we thus argue that recapture rate may still be a relevant proxy for natural survival in the natural environments. As increased predation mortality is expected to be one of the main costs of high growth rates, we expected the fast-growing populations hatchery populations (from Dalälven and Åvaån) to express lower survival in the natural streams. No such pattern could be detected, and we were not able to make any inferences on population differences in survival due to the low recapture rates that gives very low statistical power.
Previous studies on genetic and phenotypic variation in salmonid fishes have found adaptive among-population variation in growth (e.g., Lahti et al. 2001; Fraser et al. 2011; Rogell et al. 2012), as well as plastic variation in relation to environmental factors like temperature and the amount of resources (Brett 1979; Klemetsen et al. 2003). Our results show that growth across different stream environments was quite similar, suggesting – perhaps surprisingly – a comparably low importance of local conditions affecting growth. The low plasticity found within the populations suggests that environmental variation is unlikely to buffer against natural selection, and that removal of maladapted genotypes may be fast under certain conditions.
On the other hand, it has been shown that adaptive divergence within species may affect ecological interactions and thus community structure (Bassar et al. 2010, 2012). It is thus not unlikely that the ecological niche may differ between hatchery and wild trout, and our results suggest that such differences may remain constant over a range of environmental conditions. Indeed, both conservation and fisheries biology harbor a great interest on organisms' potential to adapt to varying environmental conditions. For example, harvest, or its collateral effects, may change a species' evolutionary dynamics in a mode antagonistic to natural selection (e.g., Olsen et al. 2004), possibly resulting in decreased fitness of the harvested species and changes in community structure. Our results suggest that hatchery selection may have a stronger effect on key life-history parameters than environmental conditions, emphasizing the possibility that hatchery selection may also affect ecological interactions in stream environments following release or escape of domesticated populations.
To summarize, we have found that reaction norms for body size during the first growth season were rather parallel across several natural streams, and that population origin explained a larger part of the variation in growth than plastic effects induced by different environmental conditions. This, in turn, indicates that the relative performance is similar across a range of natural environments, and that higher growth rates induced by adaptation to hatchery conditions may be persistent across natural environments. According to life-history theory, a higher growth rate should occur at costs of other fitness components. In the present case, plasticity did not swamp the genetic differences, suggesting that fitness costs mediated by selection may be very strong. Such costs are likely to affect fitness of hatchery-reared fish in the wild. However, due to very low survival rates, we could not properly evaluate the effect of rearing environment on survival in the natural streams. Finally, it should be stressed that population differences (or a lack of them) seen during early life stages does not necessarily correlate well with lifetime success in survival and reproduction (cf. McGinnity et al. 2003), and further studies linking juvenile performance and adult fitness are thus needed.