Discussion:
Metabolic rate can be viewed as the most fundamental biological rate, explaining the pace at which organisms take up, transform, and expend energy (Brown et al. 2004). Thus, we also predict that the individual metabolic rate would profoundly shape TDF. To the best of our knowledge, this framework has only been applied to the study of TDF in small mammals (i.e. mice and rats: MacAvoy et al. 2006, MacAvoy et al. 2012), or birds (Ogden et al. 2004). However, in temperate ectothermic teleosts, where mass-specific metabolic rate is comparably slower, this process was assumed to be negligible. This view needs a revision, as our results show a clear and gradual relationship between TDF of muscle tissue (i.e. Δ13C and Δ15N ) and metabolic rate on the individual level. Thus, our results highlight that individual metabolic rate could be one of the factors explaining variable TDF within a single species. However, we could not detect any association between metabolic rate and TDF in liver tissue. Differences in metabolic rates and therefore TDF were especially pronounced between small and large perch. Thus, in accordance with Herzka (2005), our results highlight the need for establishing different TDF for specific ontogenetic stages to allow more precise interpretation of isotopic data.
Trueman et al. (2005) reported differences in individual growth rates of Atlantic salmon (Salmo salar ) to be associated with variable TDF. The authors suggested that this pattern could be explained by intraspecific differences in metabolism, but direct measurements of metabolic rates were not included. In many studies of TDF in ecothermic species, isotopic change has been attributed to growth rather than metabolism (Hesslein et al. 1993, Bosley et al. 2002), but see (Herzka et al. 2001, Tarboush et al. 2006, Sun et al. 2012). Unfortunately, we are not able to separate the isotopic change into contributions of growth and metabolic rate sensu Fry and Arnold (1982) as we did not track the precise individual weight increase. We approached this issue by including the final weight as a covariate in our models. Here, the strongest differences in TDF could be detected comparing juvenile to adult perch. Along with the highest SMR, juveniles also had the strongest approximate weight increase (Table 1). When measuring individual metabolic rate immediately before assessing their TDF we found fine scale differences that correlated strongly with Δ13C and Δ15N of muscles indicating that changes in metabolic rates could translate into variations in TDF (Kleiber 1932, 1947, Boecklen et al. 2011).
Results of posthoc comparisons of SMR between perch with an initial weight of 20-30 g caught in different habitats (pelagic and littoral) were not significant, but when analyzed separately, a significant difference appears with pelagic having a higher SMR (t-test: t7.633 = -2.406; P= 0.044), similar to previous results (Andersson et al. unpublished data). Generally, it is known that such intra-specific differences in metabolic rates within adult individuals exist in many species, including fish (Biro and Stamps 2010). However, less is known about differences between individuals living in different habitats. In many Swedish lakes including Erken, which is the origin of the perch used in this study, littoral and pelagic perch of the intermediate class size differ in their individual specialization for respective food items, which is even translated into adaptations of their morphology. While pelagic perch predominately ingest pelagic zooplankton and have a more streamlined body form, littoral perch include benthic macroinvertebrates in their diet to a higher degree and are characterized by a deeper body (Svanbäck and Persson 2004, Marklund et al. 2019). Potentially, habitat-specific differences in activity levels could be related to the differences found in SMR (Myles-Gonzalez et al. 2015, Watz et al. 2015). Pelagic perch need to be endurance swimmers in order to catch the smaller fast-moving prey, while littoral perch forage on larger prey items of lower mobility (Svanbäck and Eklöv 2004). Future research is needed to resolve the underlying causes for the differences found in SMR between littoral and pelagic perch. Interestingly, average Δ13C in muscle tissue of 20 – 30 g pelagic perch was lower compared to littoral perch of the same weight class (Table 1), but this difference was not significant. Thus, our data suggest a trend that the inverse relationship (i.e. elevated SMR leads to lower Δ13C), holds true not only between juveniles and adults, but also between the habitat-specific individuals of the same weight class.
While the effect of SMR was strong for Δ13C and Δ15N in in muscle tissue, we did not observe any relationship between SMR and TDF of liver tissue, indicating that individual metabolic rate has a stronger effect of tissue types with slower isotopic turnover. Generally, liver had lower TDF (Δ13C: 1.1 ‰ ± 0.4; Δ15N: 1.1 ‰ ± 0.5) compared to TDF of muscle tissues (Δ13C: 3.7 ‰ ± 0.5; Δ15N: 1.3 ‰ ± 0.6), showing relatively little change in the isotope values between consumer and prey. Our results are in line with the findings of other studies on tissue-specific difference in TDF in fish (Buchheister and Latour 2010, Matley et al. 2016), and the observed pattern might be due to different biochemical composition of the tissue types, e.g. the abundances of specific amino acids (Pinnegar and Polunin 1999).
Our values of Δ15N in muscle tissue are relatively low compared to the highly cited average value of 3.4 ‰ (Post 2002). However, variation in Δ15N between taxa is large, which is primarily attributed to different nitrogen assimilation and excretion modes (Gaye-Siessegger et al. 2003, Vanderklift and Ponsard 2003). Thus, fractionation is typically low when the C:N ratio of the diet is also low, as it was for our chironomid diet (4.7± 0.2) (Vanderklift and Ponsard 2003). For example, McCutchan et al. (2003) reported Δ15N of 1.4 ± 0.21 in consumers raised on a invertebrate diet, whereas consumers raised on a high-protein diet showed a Δ15N of 3.3 ± 0.26. Protein is the principal source of energy for perch, which are ammoniotelic organisms, and thus characterized by a relatively high N use efficiency that is linked to lower Δ15N (Trueman et al. 2005). Furthermore, a previous study of perch stoichiometry reported that C:N of perch varied with size, indicating that stoichiometric demands vary over ontogeny (Vrede et al. 2011). This could potentially affect assimilation and excretion rates and could have contributed to the variation of TDF between size classes as we have observed in this experiment, but further experiments are needed to include this factor.
In contrast, our derived values of Δ13C for muscle tissue were rather high compared to the typically assumed value of 0.3 ‰ (Post 2002) or 0.4 ‰ (McCutchan et al. 2003), though previous studies have reported similarly high values (e.g.Pinnegar and Polunin 1999, Barnes et al. 2007, Busst and Britton 2016). Vollaire et al. (2007) reported Δ13C of 4.02 ± 0.13 ‰ for juvenile perch feeding on artificial diet. A potential reason for variation in Δ13C could be a process termed “isotopic routing”, where resource constituents, such as proteins, lipids and carbohydrates are allocated to different tissue types (Schwarcz 1991). Altogether, we thus agree with Wolf et al. (2009) and acknowledge that further studies are urgently needed to understand variation of Δ13C in fish.
Variation in Δ15N, specifically in liver tissue was higher compared to that of Δ13C. We assume that this variability can be attributed to the fact that the δ15N of the diet was rather high (14.0 ‰ ± 3.7). Commercially raised chironomids are maintained in large flumes and cannibalism might occur which would result in higher δ15N of individual organisms. Another aspect that could potentially influence the variation in Δ15N, but also in Δ13C is the individual food intake, which was shown to influence TDF (Bosley et al. 2002, Barnes et al. 2007). In our study, perch shoals were fed at high feeding rates (approximately 15% of the individual wet weight–day), and left-over food was removed. However, this does not imply that all fish individuals fed until satiation. Strong hierarchies exist in perch shoals (Magnhagen 2012) and were observed in some of our tanks. Dominance behavior of single individuals might have prevented subordinates the access to food. This artefact of the experimental design adds to the previously mentioned confounding aspects and highlight again the complexity and difficulty involved in experimentally assessing general and widely applicable TDF.
In conclusion, our data emphasize the role of metabolic rate in shaping specific TDF (i.e. Δ13C and Δ15N of muscle tissue). Especially, our results highlight the substantial differences between individuals of different ontogenetic stages within a species.