Temperature dependent competitive interactions between ( alpinus) and brown ( trutta)

David Jonsson

Student Degree Thesis in Ecology 30 ECTS Master’s Level Report passed: 9 June 2009 Supervisor: Pär Byström Summary

The outcome of competitive interactions between species is strongly related to species specific foraging capacities and metabolic demands. In aquatic organism like fish the outcome of competitive interactions therefore depend on temperature since 1) vital rates like metabolism, digestion and foraging rates are strongly dependent on temperature, and 2) different species have different temperature optima for these rates. In this study, I examine if variation in temperature change the outcome of competitive interactions between Arctic char and . Growth and survival over a 35 days period of young Arctic char and brown trout were studied at two different temperatures scenarios (cold and warm, average 14.3 and 16.9 °C respectively) in a large scale pond experiment. Growth of both species decreased with increasing temperature, which was suggested to depend mainly on increasing metabolic cost at higher temperatures. Growth of Arctic char was strongly negatively affected by brown trout density at high temperatures whereas brown trout growth was not affected by density of Arctic char in either temperature treatment. Densities of insect larvae decreased over the experiment whereas densities of mollusks were constant and diet analysis at the end of the experiment suggested that brown trout were able to feed on a relatively abundant mollusk resource which was not used by Arctic char. The results from this study strongly suggests that temperature can affect competitive interactions between species and that competitive interactions between brown trout and Arctic char shifts more in favour to brown trout with increasing temperature. In the light of expected increasing lake water temperatures due to climate change a shift is predicted in many mountain lake ecosystems dominated by Arctic char to ecosystems instead dominated by brown trout.

Introduction

Competition between individuals through similar use of limited resources has profound effects on individual growth rates, survival and fecundity and thus affects overall population and community dynamics (Connell 1983, Schoener 1983, Begon et al. 1996, Marchad & Boisclair 1997). The strength and outcome of competitive interactions both between individuals of the same species and between species are determined basically by two functions: the capacity to reduce shared resources and the ability to have positive growth at low resource densities (Persson 1985, Werner 1994). The capacity to reduce resource densities mainly depends on the individual’s capacity to digest food while the capacity to have positive growth at low recourse densities depend on the search efficiency and metabolic demands of the consumer. In poikilothermic organisms like fish physiological processes including digestion, metabolic demands as well as search efficiency strongly depend on temperature (Beaupre et al. 1993, Angilletta et al. 2002, Larsson 2002, Byström et al. 2006). In fish, different species are adapted to specific temperature regimes and consequently differ in temperature optima for e.g. maximum growth capacity, digestion capacity and foraging capacity (Persson 1986, Bergman 1988, Larsson 2004, Byström et al. 2006). As a consequence, competitive advantages of one species over another may decrease or even be reversed as a result of changes in water temperatures (Persson 1986, Taniguchi et al. 1998, Hasegawa et al. 2007). In general salmonid fish species are adapted to a life in cold water systems and therefore salmonids may be displaced from warmer systems through ecological interactions with species which are more adapted to warmer climates (Taniguchi et al. 1998, Byström et al. 2007). Examples of such salmonids are Arctic char (Salvelinus alpinus) and brown trout (Salmon trutta). Both Arctic char and brown trout are found in both allopathic or sympatric populations in high latitude lake systems (Klemetsen et al. 2003b). Of these two species, Arctic char has been suggested to be the most cold water adapted species in the Northern hemisphere and Arctic char is found at higher altitudes and latitudes than brown trout (Klemetsen et al. 2003b). This is certainly an effect of the capacity of Arctic char to feed and grow both at very low temperatures and poor light conditions (Ali et al. 1984, Brännäs & Wiklund 1992, Klemetsen et al. 2003a, Byström et al. 2006). Optimal temperature for growth is 16 °C for Arctic char and 16-17 °C for brown trout while the preferred temperature for Arctic char and brown trout is 11.8°C and 16.0°C respectively (Ojanguren et al. 2001, Larsson 2002). This suggests that Arctic char is more adapted to a colder climate than brown trout and vice versa. Thus, interactions strength between Arctic char and brown trout are likely to depend on temperature and Arctic char is likely more favored in water systems with lower temperatures and with increasing water temperatures these interactions may change and shift to an advantage for brown trout.

2 The aim with this study was to reveal if temperature had an effect on the outcome of competition between Arctic char and brown trout. Based on the two species preferred temperatures, Arctic char should be favored over brown trout in lower water temperatures and vice versa. In order to examine that hypothesis, two large scale ponds were used. The water temperature in one pond was adjusted to resemble summer conditions in a subarctic mountain lake and in the second pond a scenario reflecting a climate change with conditions of 2.5 °C warmer water temperature was applied. This temperature increase caused condition in the warmer pond to closely resemble preferred temperatures for brown trout.

Methods

Pond experiment The experiment was carried out in two closely situated ponds (32 m x 10.8 m), located in Umeå (63º48'36"N, 20º14'37"E), Sweden. The two ponds were each divided into eight enclosures (4 m x 10.8 m, mean depth 0.9 m), separated with plastic sheets. Each enclosure had an inflow of water while each pond only had one outlet. The separating walls between each enclosure had an opening (covered with plastic net with a mesh size of 3 mm) to direct water to the outlet situated at one end of the ponds. In order to create a temperature difference between the two ponds, the inflow of water (approx. temperature 10° C) to the ponds was set to 0.031 l/s respectively 0.19 l/s. From now on the respectively pond is referred to as the warm- respectively the cold treatment. The average temperature over the experimental period in the warm treatment was 14.3°C (± 0.5° C) and in the cold treatment 16.9°C (± 0.5° C) (Fig. 1).

Figure 1. Temperature in the two ponds (±1 SD) over time. The average temperature in the warm pond was 16.9°C (dotted line) and in the cold pond 14.3°C (dashed line).

Concentrations of Tot-P and Tot-N in incoming water were; < 1 µg/l and 31 µg/l, respectively. As a consequence of the higher water flow together with the low nutrient concentrations in incoming water, Tot-P and Tot-N were higher at the end of the experiment in the warm treatment than in the cold treatment (mean ± 1SD, warm treatment; Tot-P 8.6 ± 1.6 µg/l, Tot-N 108.1 µg/l ± 22.1 µg/l, cold treatment; Tot-P 5.9 ± 1.3 µg/l, Tot-N 73.7 ± 10.0 µg/l). The experimental setup was designed to reveal temperature effects on intra- and interspecific competitive interactions between Arctic char and brown trout. In addition to the created temperature difference between the ponds, the variation in nutrient concentrations caused the ponds to simulate two different environments, one similar to a warm lake with higher nutrient concentration (warm treatment) and the other similar to a cold lake with lower nutrient concentrations (cold treatment). In each pond a design with four treatments were used: two single species treatments with either 70 individuals of Arctic char or brown trout, a low density mixed treatment with 35 Arctic char and 35 brown trout and a high density mixed treatment with 70 Arctic char and 70 brown trout. Treatments were replicated twice for each temperature treatment.

3 Fish Both Arctic char and Brown trout (from now on referred to as char and trout) were hatched and reared in a commercial fish farm. In early summer the fish were transported to Umeå and held separately in large holding tanks for three days and feed with a mixture of live zooplankton and frozen chironomids before the pond experiment started. On the day of introduction (14 June), the fish were sorted to homogenize size distributions and sample of 100 individuals of each species were taken for initial size measurements. Initial size (mean ± 1 SD) of char; length, 45.5 ± 2.4 mm, weight 0.8 ± 0.32 g, initial size of trout; 49.3 ± 3.7 mm, 1.19 ± 0.13 g). Treatments were randomly assigned to enclosures and fish were gently introduced into the enclosures after being stepwise acclimatized to enclosure water temperatures. At the end of the experiment (19 July), all fish in the enclosures were sampled with a seine net and deep frozen until later examination of length, weight and stomach content in laboratory. Each enclosure was sampled until two subsequent hauls gave zero captures. In one pond, due to a hole in the net between two enclosures, escapes of 18 trout from a single species treatment were found in a single species treatment of char. However, there was no difference in growth between trout from that enclosure and the ones that escaped or between the two replicates of single species treatment of char. (T-test: trout; t27 = -0.273, p = 0.787, Char; t90 = -1.286, p = 0.202). Therefore, the escaped trout were included in statistical analyses of survival and included in the replicate from which they had escaped but these 18 trout were then excluded from all other analyses. In laboratory, all individuals were length measured to nearest mm and weighted after blotted dry to nearest 0.01 g. Stomachs were removed from 15 individuals of each species from all replicates. Stomach content (individuals with empty stomachs were disregarded) were then analyzed for 10 individuals of each species and treatment and the stomach content were classified to family or and length measured to thereafter obtain dry biomass using length-weight relationship (Persson et al. 1996 for macroinvertebrates and Dumont et al. 1975, Bottrell et al. 1976 for zooplankton). Stomach content were then group in four categories; terrestrial insects, aquatic arthropods (including Chironomidae, Coleoptera, Ephemeroptera and Trichoptera larvae and Acellus), mollusks (Bivalvia and Gyraulus) and zooplankton (Alonella, Bosmina, Daphnia, Scrabolerbris, calanoida and cyclopodia). The diet group aquatic arthropods were dominated by chironomids (mean ± 1 SD, char 91 % ± 24 % and trout 77 % ± 23 %).

Resources Macroinvertebrates were sampled with a core sampler (diameter, 0,079 m2) at the start (13 June), middle (6 July) and end (18 July) of the experiment. The upper four centimeters of sediment were collected and four samples were taken in each enclosure and then merge into one pooled sample. Pooled samples were then conserved in 95 % ethanol. The samples were sorted and counted and the macroinvertebrates were indentified to family or Genus and the length of 20 individuals of each group or all individuals if fewer were measured. Lengths were then transformed to dry weight biomass using length-weight relationship (Persson et al. 1996). Macroinvertebrates were then grouped into two categories, aquatic arthropods (Chironomidae, Coleoptera, Ephemeroptera, Trichoptera and Asellus) and mollusks (Bivalvia and Gyraulus). Zooplankton was sampled in each enclosure with a 100 µm mesh net that was drawn horizontally four meters at depth of 0.1 m at the start (13 June), middle (6 July) and end (18 July) of the experiment. Each sample was conserved with Lugol’s solution. Zooplankton were counted and indentified to family or genus and the length of 15 individuals of each category or all individuals if fewer were present were measured. Lengths were then transformed to biomass using length-weight relationship (Dunmount et al. 1975, Bottrell et al. 1976). Zooplanktons were then grouped in two categories cladocera (Alonella, Daphnia, Bosmina and Scrabolerbris) and copepods (calanoida and cyclopodia).

Statistical analyses

For all statistical analyses SPSS 15.0 were used. Response variables were analyzed by univariate ANOVA’s, repeated measures ANOVA and t - test. Data were transformed to meet the distribution and homogeneity assumptions (Levene’s test) of univariate ANOVAs and sphericity assumptions of repeated measures ANOVA. Survival was arcsine square root transformed and all other response variables were ln-transformed when appropriate.

4 Results

Survival Survival was higher for both char and trout in the warm treatment and there was a strong tendency that overall survival of char was higher than for trout (Two-way ANOVA: Species F1,20 = 4.14, p = 0.055; Temperature F1,20

= 35.0, p < 0.001; Species x Temperature F1,20 = 0.001, p = 0.97). Separate analyses for char and trout of treatment and temperature effects showed no effects of treatment on survival or any interactions between treatment and temperature (Two-way ANOVA: Char; Treatment F2,6 =

2.350, p = 0.176; Temperature F1,6 = 15.0, p = 0.008; Treatment x Temperature F2,6 = 1.24, p = 0.36, Trout;

Treatment F2,6 = 0.65, p = 0.56; Temperature F1,6 = 30.6, p < 0.001; Treatment x Temperature F2,6 = 0.51, p = 0.62) (Fig. 2).

Figure 2. Average survival (+1 SD) of char and trout between density- and temperature treatments.

Growth Overall growth rate of trout was higher than for char and growth rate were higher for both char and trout in the cold treatment (two-way ANOVA, Species F1,20 = 19.9, p < 0.001; Temperature F1,20 = 27.2, p < 0.001; Species x

Temperature F1,20 = 0.20, p = 0.66) (Fig. 3). Separate analysis of growth responses for respectively species showed that the growth rate of char differed between density treatments (Fig. 3 & table 1). The growth rate of char was negatively affected by the presence of trout and especially so in the warm treatment (Fig. 3). In contrast, growth of trout was not affected by the presence of char (Fig. 3 & table 1) but it was evident in the cold treatment that growth rate of trout was higher in the low density mix treatment than when alone or at high mix treatment (One-way ANOVA: Treatment F2,3 = 47.0, p = 0.005) (Fig. 3).

Figure 3. Average growth (+1 SD) of char and trout between density- and temperature treatments.

5 Table 1. Two-way ANOVA (F-values) on the effect of density- and temperature treatments on growth rate of char and trout. Numbers in bold indicates significant test at the level of P > 0.05. Significance level: * = 0.01 < P < 0.05; ** = 0.001 < P <0.01; *** = P < 0.001.

Source of variation df F Arctic char Treatment 2,6 10.261* Temp 1,6 23.033** Treatment x Temp 2,6 3.275

Brown trout Treatment 2,6 3.181 Temp 1,6 57.144*** Treatment x Temp 2,6 0.321

Diet

Overall there were differences in diets between char and trout (Multivariate (Wilks’Λ) test: Species, F4,17 = 29.9, p < 0.000; Temperature, F4,17 = 3.48, p = 0.030; Species x Temperature, F4,17 = 12.6, p = 0.000) (Fig. 4). Char had higher proportion of zooplankton in their diet while trout feed more on terrestrial insects and mollusks (Fig. 4 & table 2). Terrestrial insects were found in a higher proportion in the diets of fish in the warm temperature treatment while zooplankton was found in a higher proportion in the diets of consumers in the cold temperature treatment. Terrestrial insects was found in a higher proportion in diets of char in the warm treatment whereas trout feed more on mollusks in the warm treatment and more aquatic arthropods in the cold treatment (Fig. 4 & Table 2). In addition, within the diet category mollusks there were a major difference between the species as char feed exclusively on Bivalvia (100% ± 0%, mean ± 1 SD) with a size of 0.63 mm ± 0.15 mm (mean ± 1 SD) whereas trout diets in that category were dominated by Gyralus (81.2% ± 25%, mean ± 1 SD) with a size of 1.06 mm ± 0.34 mm (mean ± 1 SD).

Figure 4. Diets in proportions of char and trout between density- and temperature treatments.

6 Table 2. Two-way ANOVA (F-values) of the effect of species and temperature treatments on diets of consumers and Two-way ANOVA’s (F-values) of the effects of density- and temperature treatments on the diets of char and trout respectively. Numbers in bold indicates significant test at the level of P > 0.05. Significance level: * = 0.01 < P < 0.05; ** = 0.001 < P <0.01; *** = P < 0.001.

Source of Aquatic variation df Terrestrial arthropods Mollusks Zooplankton Species diet

Species 1,20 51.448*** 1.307 19.419*** 77.262*** Temp 1,20 9.329** 0.336 1.212 7.687* Species x Temp 1,20 13.489** 8.876** 10.542** 1.186

Arctic char diet Treatment 2,6 1.074 0.713 1.387 1.588 Temp 1,6 32.042** 2.133 2.748 4.003 Treatment x Temp 2,6 0.081 0.121 1.902 0.171

Brown trout diet Treatment 2,6 1.711 0.851 0.270 0.624 Temp 1,6 0.197 8.969* 7.330* 5.168 Treatment x Temp 2,6 2.577 2.982 0.398 0.762

Resources Biomass of the mollusks differed between treatments and was higher in the low density mix treatments (Fig. 5 & table 3). Overall, biomass of mollusks was higher in the warm treatment and in the cold treatment the high density mix treatment had a lower biomass of mollusks than in the warm treatment. There were no temperature or treatment effects on the remaining resource categories, but the group aquatic arthropods decreased over time, especially so in the warm treatment (Fig. 5 & table 3).

Figure 5. Macroinvertebrates and zooplanktons average biomasses (±1 SD) over time in the different density- and temperature treatments.

7 Table 3. Reapeted mesure ANOVA (F-values) of the effects of density treatments, temperature treatments and time on the m croinvetebrate and zooplankton groups. Numbers in bold indicates significant test at the level of P > 0.05. Significance level: * = 0.01 < P < 0.05; ** = 0.001 < P <0.01; *** = P < 0.001.

Source of variation Univ. Insect df larvae Molluscs Cladocerans Copepods Treatment 3,8 1.628 18.750** 0.217 1.619 Temp 1,8 2.528 46.171*** 1.500 1.434 Treatment x Temp 3,8 0.266 6.872* 1.482 0.129 Time 2,16 4.434* 1.199 1.842 0.711 Time x Treatment 6,16 0.582 0.649 0.920 0.574 Time x Temp 2,16 0.477 0.525 0.774 2.482 Time x Treatment x Temp 6,16 0.299 0.635 0.364 1.164

Discussion

Overall, both char and trout had higher growth rates in the cold treatment than in the warm treatment. The if any, lower resource levels in the cold treatment together with higher inorganic nutrient availability in the warm treatment suggest that the higher growth rates in the cold treatment was not a result of higher resource availability or productivity in the cold pond. Survival was higher in the warm treatment which might be advanced as an explanation for the observed growth differences between the temperature treatments. However density-dependent effects as an explanation for this growth difference goes against the fact that growth rates in the cold treatment was higher even in high density mixed treatment than corresponding growth in the low density mix treatment in the warm treatment (species specific comparisons). Thus, this strongly suggests that the observed mortality differences cannot explain the differences in growth responses between temperature treatments. Instead based on above, I suggest that higher metabolic costs for the fish, as an effect of the higher temperature, can explain the overall differences in growth between the warm- and cold treatment. Correspondingly, based on Elliott (1976) and Lyytikäinen & Jobling (1998) the metabolic costs are approximate 40-60% higher for char and trout in the warm treatment compared to the cold treatment. Increased metabolic costs as an effect of higher temperature must be compensated by a higher intake rate to render similar growth rates. However, as recent developed size and temperature scaling relationships suggests that, at limited resources the increase in temperature leads to lower growth rates as the metabolic costs increases more than the search capacity with temperature (Byström et al. 2006). Thus, if resource densities or production are not increasing an increase in temperature should lead to lower growth rates in char and trout. When alone without trout (allopatric treatments) in the warm treatment char had similar growth rates as trout, while in the presence of trout (sympatric treatments) char growth was reduced and lower than for trout. Corresponding decrease in char growth was much less pronounced in the cold treatment. This strongly suggests that competitive interactions between char and trout are temperature dependent and that trout is favored when temperature increases. Studies have showed that char is forced into pelagic areas in lakes with trout (Svärdsson & Nilsson 1985, Alanärä et al. 1994). The ponds, in this study have a mean depth of 0.9 m and thereby resemble a nearshore benthic habitat. According to Jansen et al. (2001) char is more efficient than trout when feeding on zooplankton whereas the opposite is the case when they are feeding on macroinvertebrates. These differences may explain the pronounced higher growth of trout compared to char in the warm treatment, when there was a higher total abundance of macroinvertebrates and an overall low abundance of zooplankton in the ponds. With increasing metabolic cost for both species and the need of higher food intake to cover the metabolic cost then gives trout advantage when search efficiency is not increasing to the same extent as metabolic costs (Byström et al. 2006). The fact that char had similar growth rates as trout in allopatric warm treatment may then be explained by the higher densities of zooplankton in that treatment (cladocerans, figure 5) and thus strengthen above theory. Furthermore, char diet consisted more of terrestrial insects in the warm treatment, which may indicate that higher metabolic demands forced char to feed on less preferred resources to compensate for the higher metabolic cost. There are also no reasons to suspect that terrestrial insect density should differ between the two ponds due to their closeness – also indicated by similar proportion of terrestrial insects in diets of trout in the two ponds. The resource category aquatic arthropods decreased over time, especially so in the warm treatment, indicating that resources were limited which likely affected char more as they are less efficient in feeding in macroinvertebrates than trout (Jansen et al. 2001). Mollusk densities were higher in warm treatment and trout

8 based on diet data appeared to be able to utilize this relatively abundant prey category to larger extent than char. This ability to feed on mollusks will give trout an additional advantage over char when energy demands increase and more preferred prey like insects larvae thus decreases in abundance. Moreover trout has been suggested to be a stronger interference competitor than char (Kalleberg 1958, McHugh and Budy 2005). Temperature has also been shown to affect the strength of interference interaction as higher temperatures increase effects of interference (McMahon et al. 2007). Thus, in benthic nearshore habitats like the environment in the experimental ponds, trout may have an additional advantage by restricting feeding opportunities or feeding areas for char which negatively may affect char growth even further especially at higher temperatures. The results in my study considering species specific growth responses to competitive interactions corresponded qualitatively to what could be predicted based on each species preferred temperature range (Ojanguren et al. 2001, Larsson 2002). In the studied temperature interval, representing normal to high August summer temperatures in alpine lakes, trout had a strong negative effect on char growth at higher temperatures. The reverse was not observed in the cold treatment in the studied temperature interval and trout growth seemed mainly depend on temperature and not by the presence of char. At much lower temperatures one might expect the reverse pattern as char is found in lakes with higher altitude and are able to feed and grow at extremely low temperatures (Brännäs & Wiklund 1992, Klemetsen et al. 2003a, b, Byström et al. 2006). This also suggest that competitive interactions between the two species could be season depend and char may have an advantage during the winter season. One important aspect for temperature dependency in competitive interactions is the temperature dependency in species foraging abilities. Persson (1986) showed in a study that perch is favored over roach at lower water temperatures and the foraging advantage shift to favor roach at higher water temperatures. Temperature related patterns considering competitive interactions have been observed in other field studies. Brown trout is suggested to replace white-spotted char (Salvelinus leucomaenis) at localities with higher water temperatures (Takami et al. 2002). Furthermore, the same patterns are also present in other species pairs. McMahon et al. (2007) found that (Salvelinus fontinalis) had strong negative effect on the growth of the more cold water adapted (Salvelinus confluentus) at higher water temperatures. On the other hand, brown trout and Brook trout were found to be superior competitors over Creek chub (Semotilus atromaculatus) in temperatures under 20 °C and a reverse was the case for temperatures over 26 °C (Taniguchi et al. 1998). In general, studies have shown that temperature is an important factor in explaining large scale regional species distribution patterns (Fausch 1989, Tonn 1990, Holbrook, Schmitt & Stephens 1997, Taniguchi and Nakano 2000), whereas at the local scale competitive and predatory interactions determines species composition in the ecosystem (Persson et al. 1986, Byström 2007, McMahon et al. 2007). With increasing temperatures non-native species are expected to invade into new areas (Tonn 1990, Chu, Mandrak & Minns 2005). Invasion of new species can then change the species compositions in specific ecosystems by predation (e.g. Byström 2007). My study, like a few other have also showed that temperature affect competitive interactions and thus temperature can change species composition or shift in dominance relationships between species (Persson 1986, Taniguchi et al. 1998, Hasegawa et al. 2007, McMahon et al. 2007). In conclusion, temperature had large impact of the outcome of competitive interactions between the Arctic char and brown trout. With an increase in water temperature due to a global warming, species which are adapted to higher water temperatures certainly will invade new areas. Increased temperature may favor the invasive species and consequently replacement or shifts in dominance patterns of species are likely to occur. Based on results from this study together with the documented high migratory ability of brown trout (Klemetsen et al. 2007b) a warmer climate will likely also allow invasions of brown trout into systems previously only suitable for and only inhabited by Arctic char. Hence, as an effect of increasing water temperatures a shift in dominance relationships is expected in mountain lake ecosystems from lakes dominated by Arctic char to systems more dominated by brown trout.

Acknowledgments

Thanks to Pär Byström for helping out with data analyses and this manuscript.

9 References

Alanärä, A., Eriksson, L-O & Brännas, E. 1994. Röding (Salvelinus alpines). Laxfiskarnas biologi, ompendium nr 9, pp. 34-39. (red. Alanärä, A) Swedish University of agriculture Sciences (Sw). Ali, M. A., Klyne, M. A. and Einarsson, G.1984. Ecophysiological adaptations of the retina in the Arctic charr. – In: Johnon, L. and Burns, B. L. (eds), Biology of the Arctic charr. Univ. of Manitoba Press, pp. 251–261. Angilletta Jr, M. J., Niewiarowski, P. H. & Navas, C. A. 2002. The evolution of thermal physiology in ectotherms. Journal of Thermal Biology 27: 249-268. Beaupre, S. J., Dunham, A. E. & Overall, K. L. 1993. The effects of consumption rate and temperature on apparent digestibility coefficient, urate production, metabolizable energy coefficient and passage time incanyon lizards (Sceloporus merriami) from two populations. Functional Ecology 7: 273-280. Begon, M., Harper, J.L. and Townsend, C.R. 1996. Interactions. Ecology: 211-482. Third editions Blackwell Sciences Ltd, London, England Bottrell, H. H., Duncan, A., Gliwich, Z., Grygieruk, M.; Herzig E. A., Hillbrich-Ilkowska, A., Kurasawa, H., Larsson P. and Weglenska, T. 1976. A reviem of some problems in zooplankton production studies. Norw. J. Zool. 24: 419-465 Bergman, E. 1988. Temperature-dependent differences in foraging ability of two precids, Perca fluviatilis and Gymnocephalus cernuus. Environmental biology of fishes. Vol. 19 No. 1, pp. 45-53. Brännäs, E., Wiklund, B. S. 1992. Low temperature growth potential of Arctic char and . Nordic Journal of Freshwater Research. 67, 77-81. Byström, P., Andersson, J., Kiessling, A., and Eriksson, L.O. 2006. Size and temperature dependent foraging capacities and metabolism: consequences for winter starvation mortality in fish. Oikos. 2006, 115, 43-52 Byström, P., Karlsson, J., Nilsson, P., Ask, J. & Olofsson, F. 2007. Substitution of top predators: Effects of pike invasion in a subarctic lake. Freshwater biology. 2007, 52, 1271-1280 Chu C., Mandrak N.E. & Minns C.K. (2005) Potential impacts of climate change on the distributions of several common and rare freshwater fishes in Canada. Diversity and Distributions, 11, 299–310. Connell., J. H. 1983. On the Prevalence and Relative Importance of Interspecific Competition: Evidence from Field Experiments. Am. Nut. 1983, Vol. 122, pp. 661 Dunmont, H. J., Van de Velde, I. and Dunmont, S. 1975. The dry weight estimate of biomass in a selection of cladocera, copepod and rotifer from the plankton, periphyton and bentos of continental waters. Oecologia 19: 75-97 Elliott, J.M. 1976. The Energetics of Feeding, Metabolism and Growth of brown trout (Salmo trutta L.) in Relation to Body Weight, Water Temperature and Ration Size. The Journal of Ecology, Vol. 45, No. 3, pp. 923-948. Fausch, K. D. 1989. Do gradient and temperature affect distributions of and interactions between brook char (Salvelinus fontinalis) and other resident salminids in streams? Pages 303-322 in H Kwanabe, F. Yamazaki and D. L. G. Noakes, editors. Biology of charrs and masu salmon. Physiology amd Ecology Japan, Kyoto. Hasegawa, K. & Maekawa, K. 2007. Different longitudinal distribution patterns of native white-spotted charr and non-native brown trout in Monbetsu stream, , northern Japan. Ecology of Freshwater Fish. 2008, 17: 189–192 Holbrook, S.J., Schmitt R.J. & Stephens J.S. (1997) Changesin an assemblage of temperate reef fishes associated with a climate shift. Ecological Applications, 7, 1299–1310. Jansen, P.A., Slettvold, H., Finstad, A.G. & Langeland, A. 2002. Nich segregation between Arctic char (Salvelinus alpinus) and brown trout (Salmo trutta): an experimental study of mechanisms. Can. J. Fish. Aquat. Sci. 59: 6-11. Kalleberg, H. 1958. Observations in a stream tank of territoriality and competition in juvenile salmon and trout (S. salar L. and S. trutta L.). Rep Inst. Freshw. Res. Drottninghilm, 39: 55-98. Klemetsen, A., Knudsen, R., Staldvik, F. J., Amundsen, P.-A. 2003a. Habitat, diet and food assimilation of Arctic char under the winter ice in two subarctic lakes. vol. 62, I5, 1082-1098 Klemetsen, A., Amundsen, P-A., Dempson, JB., Jonsson, B., Jonsson, N., O’Connell, M.F., Mortensen, E. 2003b. Atlantic salmon Salmo salar L.,brown trout Salmo trutta L. and Arctic charr Salvelinus alpinus (L.): a review of aspects of their life histories. Ecology of Freshwater Fish. 2003, 12. 1–59.

10 Lyytikäinen, T. & Jobling, M. 1999. Effects of thermal regime on energy and nitrogen budgets of an early juvenile Arctic charr, Salvelinus alpinus, from Lake Inari. Environmental Biology of Fishes, Vol. 54, No. 2, pp. 219-227. Larsson, S. 2002. Thermal performance of Arctic char: Intraspecific variation and competitive ability. Ph.D. thesis, Swedish university of agricultural sciences, Sweden Larsson, S. 2004. Thermal preference of Arctic char, Salvelinus alpinus, and brown trout, Salmon trutta – implications for their niche segregation. Enviromental Biology of Fishes. 2005, 73: 89-96. Marchad, F. & Boisclair, D. 1997. Influence of gish density on the energy allovation of juvenile brook trout (Salvelinus fontinalis). Can. J. Fish. Aquat. 1998, Sci. 55: 796-805 McHugh, P., Budy, P. 2005. An experimental evaluation of competitive and thermal effects on brown trout (Salmon trutta) and Bonneville ( clarki Utah) performance aling an altitudinal gradient. Canadian Journal of Fisheries and Aquatic sciences. 62: 2784-2795. McMahon, T. E., Zale A. V., Barrows F. T., Selong J. H., Danehy R. J. 2007. Temperature and competition between Bull trout and Brook trout: A test of the elevation refuge hypothesis. Trans. Of American Fisheries society. 136: 1313-1326. Ojanguren, A.F., Reyes-Gavilán F.G., Braña, F. 2001. Thermal sensitivity of growth, food intake and activity of juvenile brown trout. J. Thermal biol. 26: 165-170Persson, L. 1985. Asymmetrical Competition: Are Larger Competitively Superior? Am. Nat. Vol. 126, pp. 261 Persson, L. 1985. Asymmetrical Competition: Are Larger Animals Competitively Superior? Am. Nat. Vol. 126, pp. 261 Persson, L. 1986. Temperature –induced shift in foraging ability in two fish species, Roach (Rutilus rutilus) and Perch (Perca fluviatilis): Impact for coexistence between poikilotherms. Journal of animal ecology. 55, 829-839 Persson, L., Andersson, J., Whalström, E. and Eklöv, P. 1996. Size-specific interactions in lake systems: Predator gap limitation and prey growth rate and mortality. Ecology 77: 900-911. Schoener, T. W. 1983. Field experiments on interspecific competition. Am. Nat. 122:240-285. Svärdsson, G. and Nilsson, N-A. 1985. Fiskebiologi. Report. Institute of freshwater research. Drottningholm. (Sw) Taniguchi, Y., Rahel, F.J., Novinger, D.C. and Gerow, K.G. 1998. Temperature mediation of competitive interactions among three fish species that replace each other along longitudinal stream gradients. Can. J. Fish. Aquat. Sci. 55: 1894–1901 Taniguchi, Y. and Nakano, S. 2000. Condition-specific competition: implications for the altitudinal distribution of stream fishes. Ecology 81: 2027-2039. Takami, T., Yoshihara, T., Miyakoshi, Y., Kuwabara, R. 2002. Replacement of white-spotted charr Salvelinus leucomaenis by brown trout Salmo trutta in a branch of the Chitose River, Hokkaido. Vol. 68 Issue. 1 Pages: 24-28. Tonn W.M. (1990) Climate change and fish communities – a conceptual framework. Transactions of the American Fisheries Society, 119, 337–352. Werner, E.E. 1994. Ontogenetic scaling of competitive relations: Size-dependent effects and responses in two anuran larvae. Ecology. 75(1), pp.197-213a.

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