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.