Research Article
Research Article
Stable isotope values and trophic analysis of invasive three-spined stickleback in Upper Lake Constance points to significant piscivory
expand article infoSarah Maria Gugele§|, Jan Baer, Christina Spießl, Elizabeth Yohannes§#, Steve Blumenshine¤, Barnaby J. Roberts§, Mario R. Mota-Ferreira, Alexander Brinker§
‡ Fisheries Research Station Baden-Württemberg, Langenargen, Germany
§ University of Constance, Konstanz, Germany
| State Government of Vorarlberg, Division Agriculture and Rural Area, Department Fisheries and Water Ecology, Hard, Austria
¶ Technical University of Munich, Freising, Germany
# Max-Planck Institute of Animal Behavior, Radolfzell, Germany
¤ CSU-WATER, Fresno, United States of America
Open Access


The three-spined stickleback Gasterosteus aculeatus was introduced into Lake Constance in the 1940s and occupied a limited range until late 2012. Since then the species has expanded from a solely littoral habitat in Upper Lake Constance, but now makes seasonal migrations into the pelagic zone. This behavioral change has been accompanied by a drastic increase in stickleback abundance. In order to integrate information about feeding of sticklebacks in Upper Lake Constance over two consecutive years, stomach content analysis was combined with seasonal stable isotope analysis on two types of tissue (muscle and liver). Isotope values were also obtained for zooplankton, whitefish larvae and eggs. We calculated the contribution of potential food sources for sticklebacks’ diet using a Bayesian mixing model (SIMMR). Furthermore, we determined stickleback trophic position, and δ15N and δ13C values were compared with those of other fish species of Lake Constance. The results of the Bayesian model as well as the stomach content analysis showed clear evidence of stickleback predation on fish eggs and larvae. Stickleback δ15N values were elevated during winter and comparable to those of piscivorous pike, while δ15N values of zooplankton were reduced, and those of whitefish larvae were similar to those of sticklebacks after accounting trophic fractionation of N isotopes. Trophic position calculations further identified sticklebacks as piscivorous, while the δ13C values of the liver and stomach content analysis suggests that a benthic-pelagic species pair may exist in Lake Constance. These findings support the hypotheses that sticklebacks in Lake Constance can display piscivorous feeding behaviour on sympatric fish species, most likely whitefish larvae and eggs.


Carbon littoral source, Gasterosteus aculeatus, larvae predation, niche overlap, trophic position, whitefish


Aquatic invasive species (AIS) are of concern worldwide due to their devastating impacts on ecosystems and economies (Havel et al. 2015; Treanor et al. 2017). Furthermore, the number of AIS in freshwater ecosystems will increase in the future because AIS are still translocating outside of their native ranges and in many cases AIS have not fully occupied their potential ranges (Strayer 2010a). Additionally, the introduction of AIS drives changes in the structure and functioning of existing ecosystems and complicates their management (Strayer 2010b). Therefore, knowing the trophic niches and consumption impacts of AIS is crucial to addressing the implications for food webs and ecosystems (Bodey et al. 2011). This is especially true in Lake Constance, one of the largest lakes in Central Europe, where the three-spined stickleback (Gasterosteus aculeatus L., 1758), hereafter referred to as stickleback, was introduced accidentally in the mid-1940s (Roch et al. 2018), because it is known that sticklebacks could have detrimental effects on native fish community if hyperabundant stickleback population established (Bergström et al. 2015; Byström et al. 2015). For over half a century the species existed almost exclusively in small swarms near the shore but, since the end of 2012, has expanded from littoral habitats into the pelagic zone of Upper Lake Constance (ULC) and undergone a drastic increase in abundance (Eckmann and Engesser 2019; Gugele et al. 2020). Only two years later, in September 2014, stickleback shoals represented 96% of all pelagic fish and 28% of the total pelagic fish biomass (Eckmann and Engesser 2019), a globally unique situation for a large and deep oligotrophic lake. After 2014, average stickleback abundances plateaued to between 1280 and 7990 individuals/ha in the pelagic zone of Lake Constance (Eckmann and Engesser 2019), with a peak abundance of 19100 individuals/ha recorded in September 2017 (Gugele et al. 2020). Recent stomach content analysis of sticklebacks has identified zooplankton (Daphnia spp.) as their main prey (Ogorelec et al. 2022). Since the native pelagic whitefish (Coregonus wartmanni Bloch, 1784) also mainly feed on zooplankton (Eckmann and Rösch 1998; Ogorelec et al. 2022), high stickleback abundances may have deleterious impacts on native whitefish via interspecific competition. By 2015 the yield of native whitefish, the main target species of the local fishery (Baer et al. 2017), had declined drastically from around 300–600 mt (metric tons) before stickleback invasion to less than 150 mt (Roch et al. 2018). At the same time, the average weight of whitefish (age classes 3–5) captured in the pelagic zone has undergone a 17%–51% decline (arithmetic mean: 33%) (Rösch et al. 2018). Besides, integrated bioenergetics and growth modelling revealed increasing competition with sticklebacks as a chief factor in reduced growth of whitefish in the lake (DeWeber et al. 2022).

There is also evidence that sticklebacks in Lake Constance may impact whitefish as predators of whitefish larvae and eggs (Roch et al. 2018; Rösch et al. 2018; Ros et al. 2019; Gugele et al. 2020; Baer et al. 2021). Whitefish spawn in November and December (Eckmann 1991) and whitefish larvae with a total length below 4 cm, which resembles the gape limitation of sticklebacks (cf. Roch et al. 2018) can be found in Lake Constance from February until the end of May (Eckmann 1989). Additionally, stickleback aggregations were documented in habitats where the newly hatched whitefish larvae were found from March to April, both in the pelagic zone and near the shoreline (Gugele et al. 2020). However, it should be kept in mind that pelagic whitefish spawn near the water surface in the open waters of the lake (Eckmann 1991) and their eggs sink relatively quickly to depths as great as 250 m (Eckmann and Rösch 1998), leaving a short time window to predate on them. Nevertheless, sticklebacks are able to locate whitefish eggs even during complete darkness (Baer et al. 2021) but only forage in depths down to around 30 m (Eckmann and Engesser 2019; Gugele et al. 2020), so any consumption of whitefish eggs must take place before they sink and become unattainable.

Furthermore, the distribution of the whitefish larvae is normally patchy (Ransom et al. 2022) and evidence of predation of whitefish larvae by sticklebacks may be only coincidentally available for single sticklebacks. These factors mean the role of sticklebacks in Lake Constance food web, including their impact on native lake whitefish, is not entirely simple, and predation of whitefish eggs and larvae may be a rare behaviour, posing only a minor threat to naturally hatched or stocked whitefish larvae. However, each year 100–200 million larvae between 18–25 mm in size are stocked in the littoral and pelagic zone across the whole lake (Baer et al. 2023). Consequently, it is hypothesized that the stocked larvae may act as an easily available, nutrient and energy rich food source in the oligotrophic water that might facilitate the stickleback invasion’s development, permitting the species to fully exploit the pelagic habitat while simultaneously reducing recruitment of whitefish (Roch et al. 2018).

Therefore, to get more insight into the feeding ecology of sticklebacks in ULC, we performed monthly stable isotope analysis of stickleback muscle and liver tissue over a two-year period. In addition to providing information on the diet of an organism over time, stable isotope analysis can illuminate feeding habitats, quantify complex interactions, and be used to track elements, energy, or mass through food webs and ecosystems (Post 2002; Janjua and Gerdeaux 2011). Stable isotope ratios of carbon and nitrogen have been applied extensively in food web studies over the past 30 years (Janjua and Gerdeaux 2011) and have proved useful in assessing the impacts of invasive species on trophic structures (Vander Zanden and Rasmussen 1999; Bodey et al. 2011). In the present study, stable isotope analysis was carried out on stickleback and their potential prey in the pelagic zone (zooplankton, whitefish eggs and larvae) alongside classic stomach content analysis and stable isotope mixing models to address the following four research questions: 1) Do the δ15N values and trophic position of sticklebacks reflect the seasonal feeding of whitefish larvae and eggs or that of other food sources, such as zooplankton? 2) Where do invasive sticklebacks sit relative to other fish species in the trophic structure of Lake Constance? 3) How does the trophic position of sticklebacks in Lake Constance compare to that of conspecifics in similar ecosystems? 4) Are there any differences in isotopic signature between sticklebacks caught in littoral and pelagic habitats? The answers to these questions have implications beyond Lake Constance because similar tendencies, i.e. increased predation by introduced sticklebacks on native fish species, are also being observed elsewhere (Ljunggren et al. 2010; Bergström et al. 2015; Byström et al. 2015).

Materials and methods

Ethics statement

Approval of the present study by a review board institution or ethics committee was not necessary because all fish were caught under permits issued by the local fisheries administration (Regierungspräsidium Tübingen), by qualified (license-holding) personnel subject to regular checks by the local fisheries administration (Regierungspräsidium Tübingen). All fish were caught according to the German Animal Protection Law (Tierschutzgesetz § 4) and the ordinance on slaughter and killing of animals (Tierschutzschlachtverordnung § 13).

Sampling of sticklebacks

Lake Constance is part of the Rhine drainage basin and is bordered by Austria, Germany and Switzerland (47°38'N, 9°22'E). The total surface area of 536 km2 is divided between the large (472 km2), deep (>250 m) Upper Lake (ULC) and the smaller (63 km2), shallower Lower Lake (LLC). Due to missing data and lack of knowledge about the stickleback situation in LLC and different type of lake (warm, mesotrophic), this basin was excluded in the present study. Thus, the current study only focusses on warm monomictic, large oligotrophic pre-alpine basin of ULC. The fish community of ULC comprises a minimum of 30 species (Eckmann and Rösch 1998) of which about 10 are targeted by professional fishermen (Rösch 2014). Of these, whitefish (Coregonus spp.) are the most economically important, and fisheries management is based on routine monitoring of this important group ( An overview of the fisheries situation is given by Baer et al. (2017).

Stickleback sampling of ULC was conducted monthly, from March 2017 until November 2018, using littoral and pelagic gillnets with mesh sizes of 10–12 mm. All nets had a height of 3 m, while length varied with mesh size: 30 m for nets with 10 mm mesh and 15 m for the 12-mm mesh net. All pelagic nets were deployed to drift freely behind the nets used in the monthly monitoring of whitefish (mesh sizes 36–44 mm), at depths of 3–15 m according to the areas of greatest stickleback abundance recorded during hydroacoustic surveys (Gugele et al. 2020). Benthic nets were set at depths from 6 to 20 m. All nets were set overnight, with a soak time of about 15 h. The overall catch in the pelagic gillnets (number per unit effort, NPUE, as n/m2 per net) was low from January to September (NPUE 0.03–0.25) and peaked between November and December (NPUE 1.1–7.7), the spawning season of whitefish (Baer et al. 2022b). Catches in the benthic gillnets were highest during the stickleback spawning season between May and July (NPUE 11.8–59.0) and a second peak was again observed during November and December (NPUE 6.0–79.0; Baer et al. 2022b).

10 to 34 samples of stickleback white muscle and liver tissue were taken from each monthly catch. Catches of fewer than 10 individuals (recorded in August and September each year, plus April 2017, July 2017 and October 2018) were excluded from analysis. C and N stable isotope analysis was run on 275 sticklebacks. Of these, 193 were caught in the littoral zone and 82 in the pelagic zone. All fish were euthanised with an overdose of clove oil (1 mL L−1) and a gill cut. They were measured post-mortem (total length (TL) to the nearest mm), weighed to the nearest 0.01 mg and sex was recorded. Some sticklebacks were infested with the pseudophyllidean cestode Schistocephalus solidus, and because it is known that the health status of a fish can have direct effects on the stable isotope values (Karlson et al. 2018), a combined parasite-to-host biomass ratio (parasite index, PI) was calculated as an indirect measure of the severity of infestation (Baer et al. 2022b). All parasites were counted per host, blotted, and weighed to the nearest 0.01 mg and PI was determined using the formula

PI = P/H (1)

where P is the total weight of the parasites and H is the mass of the host without the parasite.

Due to internal procedures, gastrointestinal tracts (stomach and intestine) were analysed from a subsample of 109 sticklebacks; 69 caught in the pelagic zone and 40 caught in the littoral zone (TL 68 mm ± 6 mm standard deviation SD). Samples were taken during all four seasons (autumn 2017, winter 2017, spring 2018, and summer 2018), and for each season and each habitat, the gut contents of at least 10 individuals were analysed with the exception of some sampling dates (20 during winter and summer in both pelagic and littoral zone, and 19 during spring in the pelagic zone). Food items were identified and counted in a zooplankton counting chamber and categorised into five groups, namely copepods (nauplii, copepodites and copepods of Cyclopoida, Calanoida and Harpacticoida); Bosmina (all members of the genus Bosmina); other herbivorous/detritivorous cladocerans (Daphnia spp., Diaphanosoma brachyurum and Chydoridae); predatory cladocerans (Bythotrephes longimanus and Leptodora kindtii); fish (eggs and larvae) and other (Chironomidae, Annelida, Bivalvia, Collembola, Ceratopogonidae, Ephemeroptera, adult Heteroptera, Hydrachnidia, adult Mysidae, Nematoda, Ostracoda, Plecoptera, Simuliidae and Trichoptera). Diet quantification of sticklebacks followed the use of the numerical method and diet was calculated as a percentage of the total number of prey items eaten per stickleback (Amundsen and Sánchez-Hernández 2019). Furthermore, we calculated for each season and habitat the mean number (± standard deviation SD) of consumed food items per category.

Stable isotope analysis of sticklebacks, the diet of sticklebacks and other fish species

Although stable isotope analyses on fish C and N are generally performed using muscle tissue alone, the more rapid turnover of liver tissue means isotope signatures there reflect more recent feeding (Boecklen et al. 2011). Repeated at suitable intervals, in this case monthly, these tissue-based differences in signal lag can help resolve the timing of hard-to-predict peaks in seasonal prey availability, such as that of whitefish eggs and larvae.

Tissue samples from sticklebacks caught in 2017–18 were prepared for analysis by drying them in an oven at around 60 °C for 48 hr and grinding them into a fine powder. Lipid extraction was performed on the samples because some studies have shown that in tissues with C:N ratios greater than 3.5, such treatment reduces bias in δ13C values (Skinner et al. 2016). Therefore, lipid extraction of samples was conducted by adding 200 µL of 2:1 Chloroform:Methanol mixture to the powdered tissue. Afterwards, samples were vortexed and centrifuged for two minutes at 4000 rpm. The excess sample was discarded, and centrifugation was repeated 2–4 times until the sample colour changed from yellow to colourless. Samples were then washed in 200 µL Milli-Q water, followed by further vortexing and centrifugation for 2 min (4000 rpm). Again, the excess sample was discarded, and washing was repeated multiple times during the lipid extraction. Next, samples were dried in a fume hood for 48 hr, then ground again to a fine powder and weighed (ca. 0.7 mg) to the nearest 0.001 mg in tin capsules, using a microbalance (Chyo Balance Corporation, Kyoto, Japan).

To measure isotopic ratios samples were combusted in a vario MICRO cube elemental analyser (Elementar Analysensysteme GmbH, Hanau, Germany). The emerging gases were separated via gas chromatography and passed into a Micromass Isoprime isotope mass spectrometer (Isoprime Ltd., Cheadle Hulme, UK) for determination of the 13C/12C and 15N/14N ratios (R). Measurements are reported in δ-notation (δ13C, δ15N) in parts per thousand deviations (‰), where δ = 1000 × (Rsample/Rstandard – 1) relative to the Pee Dee Belemnite (PDB) for carbon and atmospheric N2 for nitrogen. Two sulphanilamide (Isoprime internal standards) and two casein samples were used as laboratory standards for every 10 unknowns in the sequence. Replicate assays of internal laboratory standards indicated measurement errors (SD) of ± 0.05% and 0.15% for δ13C and δ15N, respectively.

To compare the isotopic values of sticklebacks with those of other species of fish in ULC, 128 additional sampled of muscle tissue were analysed from bleak (Alburnus alburnus L., 1758; n = 18; mean TL 60 mm ± 6 mm SD) roach (Rutilus rutilus L., 1758; n = 34; mean TL 263 mm ± 71 mm SD); rudd (Scardinius erythrophthalmus L., 1758; n = 12; mean TL 217 mm ± 40 mm SD); tench (Tinca tinca L., 1758; n = 19; mean TL 226 mm ± 147 mm SD); pelagic whitefish (n = 21; mean TL 308 mm ± 55 mm SD); burbot (Lota lota L., 1758); n = 19; mean TL 374 mm ± 38 mm SD); and pike (Esox lucius L., 1758; n = 5; mean TL 289 mm ± 44 mm SD). All were sampled with gill nets during August and September 2020. All fish were euthanised with an overdose of clove oil (1 mL L−1) and a gill cut. Using data from stomach content analyses carried out in prior studies, all fish species were divided into different feeding guilds: whitefish were categorised as zooplanktivorous; burbot as partly piscivorous (Hansen et al. 2022); pike as piscivorous; roach, bleak, and tench as benthivorous/insectivorous; and rudd as herbivorous (Baer et al. 2022a). Due to the stomach content analysis from this study, sticklebacks were categorised as omnivorous. Samples of white muscle were excised and frozen (-20 °C) until further processing.

For calculating the trophic position of sticklebacks, pike and burbot, faucet snails (Bithynia tentaculata, n = 10) were collected in August 2020 from the littoral habitat and used for the estimation of the littoral baseline (=δ15Nlit. base). Quagga mussels (Dreissena rostriformis bugensis, n = 200) were collected from free-standing piles in the pelagic zone 0.5–2 m depth in the upper mixed layer of Lake Constance and used for the estimation of the pelagic baseline (=δ15Npel. base).

To gain more insight into the isotopic signatures of potential stickleback prey during winter and spring, five samples of zooplankton (wet weight (g): mean = 2.34, SD = 2.53) were netted with 300 μm mesh in the epilimnion of ULC, first in October and December 2021, then in February, March, and early May 2022. An abundance of pollen in the lake epilimnion during April 2022 prevented an uncontaminated sample being taken during that month. In addition, in December 2021, 36 females of C. wartmanni (pelagic whitefish) and 42 C. macrophthalmus (benthic whitefish) were caught during spawning at their spawning grounds in ULC as part of routine sampling conducted by the Fisheries Research Station of Baden-Württemberg. To get the isotopic signature of whitefish eggs and larvae, a small sample of eggs was taken from each individual and larvae hatched from the eggs of pelagic whitefish (kept at a hatchery facility in Langenargen, Baden-Württemberg) were also sampled. After hatching, larvae were held in rearing vats until the yolk sac was partly absorbed and larvae had begun to exhibit normal swimming behaviour. From these non-fed, free-swimming larvae, four subsamples of multiple individuals (n: mean = 172, SD = 100) were taken and euthanised with an overdose of carbonated water. Clove oil was avoided in this instance as it may have biased isotopic readings, and unlike larger fish, the delicate larvae cannot be easily washed without damage. To remove potential biases due to the length of time between the main stickleback sampling (2017–2018) and the sampling of the zooplankton, whitefish eggs and larvae (2021–2022) (Fig. 1), a further 50 sticklebacks were caught for additional stable isotope analysis in January, February and April 2022 (25 each in the pelagic and littoral zone, in total 150) using gill nets.

Figure 1.

Timeline of sampling in the present study.

Samples of sticklebacks caught in 2022 and other fish were prepared for stable isotope analysis via freeze drying at -50 °C under pressurisation (<1 mbar), and ground to homogenous powder using a mixer mill. Whitefish egg samples were dried at 60 °C in a drying oven, before being stored in a glass desiccator filled with silica desiccator beads; the desiccator was stored in a cool, dark environment. Samples of plankton and pelagic whitefish larvae were dried overnight in a drying oven (60 °C), then stored in freezers at -20 °C. Each individual dried sample of plankton, whitefish larvae and whitefish eggs were then separately homogenised using a BeadRupture Homogenizer (Omni International, Kennesaw, Georgia, United States) by dispensing the sample into a plastic microtube, with a number of sterilised metal beads (<0.5 mL), and processing the sample into a fine, homogenous powder. The times and speeds used in the homogenisation process were adapted according to the individual condition of the samples. After homogenisation, samples were stored in freezers at -20 °C. Sample powder (0.3–0.4 mg) was weighed into tin capsules and combusted in an isotope ratio mass spectrometer (Delta plus, Finnigan MAT, Mas-Com GmbH, Bremen, Germany), interfaced (viaConFlo II, Finnigan MAT, MasCom GmbH, Bremen, Germany) with an elemental analyser (EA 1108, CarloErba, Thermo Fisher SCIENTIFIC, Milan, Italy). Because the mean C:N values (±SD) of all fish samples were below 3.5, lipid extraction of fish muscle tissue was not conducted (Matthews et al. 2010; Skinner et al. 2016). Measurements are reported in δ -notation (δ13C, δ15N) in parts per thousand deviations (‰), where δ = 1000 × (Rsample/Rstandard – 1) relative to the Pee Dee Belemnite (PDB) standard for carbon and atmospheric N2 for nitrogen. Finely ground animal horn (keratin) was used as a laboratory standard for every 10 unknowns in sequence. Replicate assays of internal laboratory standards indicated measurement errors (SD) of ± 0.05% and 0.15% for δ13C and δ15N, respectively.

Trophic position of sticklebacks

The trophic position of sticklebacks was calculated according to the protocol established by Post (2002) for a two-source food web:

Tophic position = λBase + (δ15Nstickleback– [δ15Nlit. base* α + δ15Npel. base * (1 – α)])/Δn (2)

α=δ13Cstickleback-δ13Cpel.baseδ13Clit.base-δ13Cpel.base (3)

where λBase denotes the trophic position of the consumer (λBase = 2) used for the estimation of the littoral (=δ15Nlit. base) and pelagic (=δ15Npel. base) baseline. The isotope values of faucet snails and quagga mussels were used for δ15Npel. base and δ13Cpel. base. As filter feeders, quagga mussels are an ideal integrator species for representing the consumer base of the pelagic food web, and are favoured over bulk seston or plankton samples, which may include non-consumer material and undifferentiated detritus and thus bias stable isotope ratio signatures. The isotopic ratios of quagga mussels and faucet snails were assessed using the same method applied for plankton, whitefish eggs and larvae (see above). δ13Cstickleback is the measured δ13C value of sticklebacks muscle. δ15Nstickleback is the measured δ15N value of sticklebacks muscle, Δn is the enrichment in δ15N per trophic level (Δn = 3.4 (Minagawa and Wada 1984; Vander Zanden and Rasmussen 1999; Post 2002; Reimchen et al. 2008)) and α denotes the proportion of sticklebacks carbon derived ultimately from littoral sources. A Δn value of 3.4 is commonly used for sticklebacks (Post 2002; Matthews et al. 2010), but in the light of recent reviews suggesting a lower level of δ15N enrichment for carnivorous fish (Vanderklift and Ponsard 2003; Boecklen et al. 2011; Blanke et al. 2017; Kambikambi et al. 2019), a further analysis as included using Δn = 2.0 as a value for the trophic enrichment of δ15N in sticklebacks.

To compare the trophic position of sticklebacks with piscivorous fish species, the trophic position for pike and burbot was then calculated for each pike and burbot using the formula: Trophic position = [(piscivorous fish δ15N – δ15Nlit. base)/ Δn] + λBase (Nyqvist et al. 2018).

Statistical analysis

To test the effects of covariates on the δ15N or δ13C of muscle or liver tissue and the trophic position of sticklebacks, the following general linear model (GLM) (Sachs 1997) was used:

Yijklmno = μ + αi + βj + (αβ)ij + γk + δl + εm + ζn + ηo + θijklmno (4)

where Yijklmno is δ15N or δ13C in muscle or liver tissue or the trophic position of sticklebacks; µ is the overall mean, αi denotes month, βj is total length, (αβ)ij is the interaction between month and total length, γk represents year and was added to the model as a random factor, δl is habitat (pelagic or littoral zone), εm is sex (male or female), ζn denotes the infection state (yes/no), ηo is parasite index and θijklmno is the random residual error. Model requirements, i.e. residuals not violating linearity, normality or non-independence were checked by inspecting residuals (predicted vs. expected plots) and multicollinearity by inspection correlation of independent variables. Single outliers with extreme values were excluded from the dataset (selection criteria: more than eight times standard deviation). Student’s t-test was used for post hoc comparisons between habitat and sex after testing for homoscedasticity (Levene test) and by building contrasts (Sokal and Rohlf 2003). The GLM for trophic position of sticklebacks was also run with Δn set at 2.0.

Differences in mean δ15N and δ13C values among Lake Constance fish species were examined using Tukey-Kramer HSD-tests.

The contribution rate of potential food sources for sticklebacks’ diet was estimated using the Bayesian mixing model in the SIMMR package (Parnell and Inger 2019), which was based on the SIAR package (Parnell et al. 2010), and implemented in the R 4.04 software (R Core Team 2020). We run separated mixing models for isotopic signatures of the liver samples of sticklebacks collected in winter (December to March) and in the summer (June and July). We choose to use only liver values because isotope values of the liver react faster than those of the muscles (time lag of only one month, Perga and Gerdeaux 2006). We include as potential food sources the isotopic values for whitefish larvae and eggs of both whitefish species, plankton, burbot, pike, and chironomids from both pelagic and littoral habitats. Whitefish eggs and larvae are only available for stickleback during winter (Roch et al. 2018; Baer et al. 2021); as such, they were not included in the model for summer samples. Furthermore, we used the isotopic values from burbot and pike as a proxy for the food source “fish”, because eggs and larvae of pike are known to be a food source for sticklebacks (Bergström et al. 2015) and the larvae of burbot are small and are available for sticklebacks the whole year round (Probst and Eckmann 2009). The δ15N and δ13C values of chironomids from both habitats were taken from previous samplings in Upper Lake Constance, made in 2015–2017, representing mean yearly values (kindly provided by M. Sabel and D. Straile). As correction factors, we used the widely accepted trophic enrichment factors (TEFs) (Cui et al. 2021) to estimate the direct contribution of food sources to detritivores (chironomids) and planktivores (whitefish) and omnivores (stickleback), and the indirect contribution of food sources to sticklebacks caught in the pelagic and littoral zone during winter and summer. In order to simplify the model and to enhance interpretability, we performed a-posteriori combination of some of the food sources that fell on similar regions of the isospace plot (Suppl. material 1: fig. S1). We combined the isotopic values of both species of whitefish eggs and larvae to category “Whitefish eggs” and “Whitefish larvae”, the chironomids from both habitats to “Chironomids”, and the burbot and pike to new category “Fish”. Furthermore, to get more insight into the importance of the prey category “Fish”, we also ran the model without this category. SIMMR relies on a Markov Chain Monte Carlo to find possible solutions and disregards those not probabilistically consistent with the data. The iterations run were 104, the burn-in was 103, the posterior was thinned by 10, and the number of chains fit was 4.

Furthermore, data from all examined fish species were pooled according to feeding guild in order to calculate a standard ellipse area corrected for small samples (SEAc). The SEAc represents the core isotopic niche of each guild after factoring in maximum likelihoods. It comprises around 40% of data and resembles a two-dimensional measurement of standard deviation (Jackson et al. 2011). The small sample size-corrected standard ellipse area (SEAc) represents the core isotopic niche area of the individuals sampled. The isotopic niche overlap of omnivorous sticklebacks with the remaining feeding guilds was subsequently calculated as a proportion of the sum of non-overlapping areas of the SEAcs. All analyses were performed using the SIBER package (Stable Isotope Bayesian Ellipses in R, v. 2.15; (Jackson et al. 2011)) in R (v. 4.04, (R Core Team 2020)).

To compare the trophic position of sticklebacks in Lake Constance to that of conspecifics in similar ecosystems (to see if the position in ULC is common), the trophic positions of sticklebacks from Lake Constance (here: mean value of all sticklebacks, independent of habitat) were compared to lake populations from North America (Matthews et al. 2010) and Norway (Østbye et al. 2016) using a z-test on arithmetic means and standard deviation with post hoc Bonferroni correction. We used for this comparison all lakes cited by Matthews et al. (2010) and only lake populations from Norway with a clear assignment to the isotopic values of sticklebacks (Einletvatn and Farstadtvatn lake). The same trophic position calculation (according to Post 2002) and the same trophic enrichment factor (Δn = 3.4) used in this study also applied to analyses of these lake systems.

Unless further specified, all statistics were performed in JMP Pro 15.1 (64 bit, SAS Institute).


Stable isotope values of sticklebacks (main sampling)

For sticklebacks sampled between 2017 and 2018 (mean TL 66 mm ± 5 mm (± SD)), the mean δ15N value was 14.9 ± 1.2‰ (± SD) for muscle and 14.6 ± 2.2‰ (± SD) for liver tissue. The lowest δ15N values for stickleback muscle tissue were recorded in summer (June-July), with mean values between 14.1‰–14.3‰ (Fig. 2). During autumn and winter (October-February) intermediate values of 14.5‰–15.2‰ were measured, and the highest values of between 15.3‰–15.7‰ occurred during spring in March and April (Fig. 2). Similar trends were observed for δ15N in stickleback liver tissue, with lowest mean values occurring during the summer months (12.3‰–12.4‰), intermediate values from October to December (14.6‰–15.7‰) and highest values in March and April (16.1‰–16.6‰) (Fig. 2). δ15N in the liver showed more monthly variation than muscle tissues in both littoral and pelagic habitats (F-tests on within-group variations; 3.88185,180 and 3.2582.70 respectively, both P ≤ 0.001). Month had a significant influence, with the effect strength greatest in muscle tissue δ15N (GLM, r2 = 0.23, n = 252, P < 0.0001, Table 1). No other parameters had a significant effect (Table 1). The GLM for δ15N values of liver tissue (r2 = 0.60, n = 266) showed a similar result for month and year effects (P < 0.0001 and P < 0.01, respectively). The interaction between TL and month also significantly affected liver δ15N, while no other parameters showed any significant effect (Table 1).

Table 1.

The significance and effect strength of study parameters on the δ15N and δ13C values of muscle and liver tissue of sticklebacks from Lake Constance.

muscle liver
parameter effect strength (± standard error) effect strength (± standard error)
month 0.96xxx (± 0.005) 0.986xxx (± 0.01)
habitat 0.001 (± 0.001) 0.007 (± 0.001)
total length 0.247 (± 0.01) 0.059 (± 0.005)
sex [m/f] 0.004 (± 0.001) 0.006 (± 0.001)
infested [yes/no] 0.023 (± 0.001) 0.001 (± 0.002)
parasite index 0.001 (± 0.001) 0.004 (± 0.001)
TL*month n.a. n.a.
muscle liver
parameter effect strength (± standard error) effect strength (± standard error)
month 0.513xxx (± 0.01) 0.776xxx (± 0.009)
habitat 0.011 (± 0.001) 0.062x (± 0.005)
total length 0.187 (± 0.01) 0.099 (± 0.006)
sex [m/f] 0.127xxx (± 0.004) 0.146xxx (± 0.007)
infested [yes/no] 0.0069 (± 0.003) 0.006 (± 0.005)
parasite index 0.26 (± 0.007) 0.022 (± 0.003)
TL*month n.a. n.a.
Figure 2.

Fitted spline intervals of δ15N and δ13C in the muscle and liver of sticklebacks sampled in 2017–2018. Solid lines are the mean values, and shaded areas represent upper and lower 95% confidence intervals during the course of the year in Lake Constance.

Mean δ13C values averaged -30.5 ± 0.8‰ (± SD) for stickleback muscle tissue and -31.2 ± 1.5‰ (± SD) for liver tissue. Muscle δ13C was lowest during July (-29.5‰) and fluctuated slightly between -30.1‰–-31.0‰ (Fig. 2) during all other sampling months. Stickleback liver δ13C values were highest during July (-28.5‰) and lowest during March (-32.2‰) and varied across other sampling months between -31.0‰–-32.0‰ (Fig. 2). The model testing effects on δ13C muscle values (GLM, r2 = 0.27, n = 251, P < 0.0001) revealed that only month and sex had a significant influence (P < 0.0001). Post hoc comparison found that female fish had significantly lower muscle δ13C values than males (Student-t, P < 0.05), but the effect strength of sex was 5× smaller than for month (Table 1). All other parameters had either no impact or exhibited only weak effects (Table 1). Month and sex had a significant influence (P < 0.0001) on liver δ13C (GLM, r2 = 0.46, n = 255, P < 0.0001), and as with muscle δ13C, females exhibited lower values than males (Student-t, P < 0.05). In contrast to the δ13C level in muscle tissue, however, habitat had a significant effect (P < 0.05) on liver δ13C, with significantly lower values in sticklebacks from the pelagic zone compared to littoral specimens (Student-t, P < 0.05). Overall, the effects of sex and habitat on the whole model were low (Table 1). There were no significant differences in the isotopic signature of sticklebacks caught in the pelagic and littoral habitat, except for the liver δ13C values.

Stable isotope values of zooplankton, whitefish and sticklebacks (additional sampling)

The δ15N value of zooplankton increased from October (10.6‰) until December (13.4‰), showed the highest peak in February (14.4‰) and decreased until April to a value of 7.9‰ (Fig. 3). Eggs of pelagic whitefish showed a mean δ15N value of 13.9 ± 0.5‰ (± SD) and did not differ significantly from those of benthic whitefish, which had a mean δ15N value of 14.1 ± 1.1‰ (± SD) (t-test, P > 0.05). The combined mean δ15N value for eggs of both species was 14.0 ± 0.8‰ (± SD), significantly higher than that of zooplankton sampled in the same months (Fig. 3). The mean δ15N value of sampled whitefish larvae, 15.3 ± 0.2‰ (± SD), was also higher than that for zooplankton sampled in the same months (Fig. 3). Sticklebacks sampled in 2021–2022 exhibited a mean δ15N value of 15.4 ± 0.5‰ (± SD) and a mean δ13C value of -31.0 ± 0.6‰ (± SD) and were close to results from winter 2017–2018. No differences were observed in mean δ15N and δ13C values between month and habitats (Tukey-Kramer-HSD, P > 0.0.5). The δ15N values of sticklebacks showed no difference from those of whitefish larvae but were notably higher than those for zooplankton (Fig. 3). In March and April, when the zooplankton showed decreasing δ15N values, the δ15N values of sticklebacks continued on the same level as the month before (Fig. 3).

Figure 3.

Arithmetic mean δ15N values with standard deviation of zooplankton, whitefish eggs and larvae and sticklebacks from the pelagic and littoral zone of Upper Lake Constance sampled in winter 2021–2022.

The δ13C values of sampled zooplankton showed no clear temporal trend (-32.9‰ in October, -34.2‰ in December, -34.0‰ in February, -35.9‰ in March, and -34.8‰ in April). The mean δ13C value of pelagic whitefish eggs was -33.7 ± 0.4‰ (± SD), significantly different to that of benthic whitefish eggs at -33.1 ± 0.6‰ (± SD) (t-test, P < 0.05). The mean δ13C value of whitefish larvae was -33.2 ± 0.5‰ (± SD).

Stomach content analysis

Nearly all analysed sticklebacks had food in their digestive tracts. Only one individual sampled in the pelagic zone during spring had an empty stomach. The numerically dominant food source for sticklebacks during spring and winter, independent of sampled habitat, were copepods (Table 2). Interestingly, in 4 out of 10 sticklebacks (40%) sampled during spring in the littoral zone, fish eggs of unknown taxa were recorded, and in winter, the stomachs of two out of 20 (10%) pelagic sticklebacks contained fragments of fish eggs and partially digested fish larvae. Differences between the stomach contents of sticklebacks sampled in the pelagic or littoral zone became more obvious during other seasons. In summer, pelagic sticklebacks consumed mostly Daphnia (Table 2) while littoral sticklebacks fed mostly (73%) on benthic macroinvertebrates, mainly chironomids (here: other, Table 2). One stickleback caught in the littoral zone during summer had consumed 14 fish eggs of unknown taxa, amounting to 38% of all food items present in that individual’s digestive tract. In autumn, copepods remained the most common prey category (81%) consumed by pelagic sticklebacks, whilst Bosmina (74%) were the most frequent prey category in littoral. Autumn was the only season when no fish (larvae or eggs) were found in either pelagic or littoral stickleback digestive tracts (Table 2).

Table 2.

Diet composition of sticklebacks (prey types expressed as a percentage of the total number of prey items eaten: during spring, summer, autumn and winter, and as the mean number of consumed individuals per stickleback ± SD) sampled in pelagic and littoral zone of Upper Lake Constance. h/d cladocera = other herbivorous/detritivorous cladocera.

diet habitat spring summer autumn winter
copepods pelagic 85.95% 12.12% 81.44% 56.06%
371 ± 254 124 ± 215 596 ± 304 172 ± 76
littoral 58.18% 12.49% 15.50% 68.98%
124 ± 215 7 ± 7 28 ± 36 122 ± 158
Bosmina pelagic 2.41% 5.63% 6.82% 0.13%
10 ± 7 7 ± 8 50 ± 36 1 ± 1
littoral 0.67% 6.54% 73.83% 1.13%
1 ± 2 2 ± 3 111 ± 74 1 ± 1
h/d cladocera pelagic 10.66% 78.83% 11.47% 43.69%
46 ± 29 96 ± 108 84 ± 71 134 ± 61
littoral 0.96% 4.16% 2.41% 13.55%
1 ± 3 2 ± 1 2 ± 2 17 ± 23
predatory cladocera pelagic 0.05% 3.00% 0.27% 0.06%
1 ± 1 4 ± 5 4 ± 4 1 ± 0.6
littoral 0.00% 0.36% 0.04% 0.11%
0 1 ± 0 1 ± 0 1 ± 0
fish (eggs, larvae) pelagic 0.00% 0.00% 0.00% 0.03%
0 0 0 1 ± 0
littoral 2.34% 3.78% 0.00% 0.00%
1 ± 1 1 ± 4 0 0
other pelagic 0.93% 0.41% 0.00% 0.02%
5 ± 5 1 ± 1 0 1 ± 0
littoral 37.84% 72.67% 8.22% 16.22%
13 ± 8 35 ± 29 4 ± 11 7 ± 5

Bayesian mixing model

The results of the SIMMR mixing model suggested a clear seasonal distinction in the contribution of food sources to sticklebacks (Fig. 4). During winter, whitefish larvae and whitefish eggs contributed a mean proportion of 30–40% (the highest contribution) to the diet, while zooplankton and chironomids are of lesser importance (mean values between 10–15%), independent of sampling habitat (littoral or pelagic zone) (Fig. 4). During summer, the importance of chironomids and zooplankton increased to proportions of 25–30% (chironomids) and 35–40% (zooplankton). During summer, neither whitefish eggs nor whitefish larvae are available. However, other protein-rich sources, i.e. fish larvae from later spawning species, increased in importance during that time to provide a mean value of 30% (pelagic zone) and 40% (littoral zone), compared to winter, when fish (non-whitefish) contribute a proportion of around 15% to the diet of sticklebacks (Fig. 4). When we excluded the category “Fish” from the model, the importance of chironomids and plankton increased during summer to proportions of 30–35% for chironomids and 65–70% for zooplankton (Suppl. material 1: fig. S2), however, during winter, the importance of whitefish eggs and larvae was (with a mean contribution of 30–45% to the diet) similar to the outcome of the model which included the category “Fish” (Suppl. material 1: fig. S2). The detailed summary of both Bayesian mixing models (SIMMR) outputs and matrix plots of source contribution proportions are given in the supplements (Suppl. material 1: tables S1–S4).

Figure 4.

Posterior distribution of dietary proportion estimates of different food sources from sticklebacks from the pelagic and littoral zone of ULC during summer and winter, according to Bayesian modelling, expressed as Box-and-Whisker plots with median values and interquartile range (IQR), and minimum and maximum if it doesn’t extend the IQR value beyond 1.5. Data outside this range are plotted individually.

Stable isotope values of other fish species from Lake Constance

For the other fishes species examined from Lake Constance, mean δ15N values for muscle tissue varied by up to 4.0‰, with a minimum of 9.6 ± 1.1‰ for herbivorous rudd and a maximum of 13.6 ± 0.1‰ for piscivorous pike with whitefish, bleak, roach, burbot, and tench exhibiting intermediate values (Fig. 5). At the time of sampling (summer), mean stickleback muscle δ15N (14.3 ± 1.2‰) did not differ from that of exclusively piscivorous pike (Tukey-Kramer-HSD, P > 0.05) and was significantly higher than that of all other fish species (Tukey-Kramer-HSD, P < 0.0.5). The δ15N values of quagga mussels and faucet snails were 5.6 ± 0.1‰ and 6.9 ± 0.2‰ respectively (Fig. 5).

Figure 5.

δ15N versus δ13C bi-plot showing the mean isotope values of aquatic consumers in Lake Constance during summer (August and September). Horizontal and vertical bars represent ± SD of total pooled data. The standard ellipse areas (SEAc) represent the core isotopic niche for each trophic guild (comprising ~ 40% of the data; (Jackson et al. 2011)).

The mean muscle δ13C of all analysed fish species, except sticklebacks, ranged from -29.6 ± 1.4‰ for whitefish to -21.4 ± 1.9‰ for rudd, while mean values for bleak, roach, tench, pike and burbot ranged between -28.4‰ and -25.1‰ (Fig. 5). At the time of sampling, in summer, the mean muscle δ13C of sticklebacks (-30.5 ± 1.0‰) was significantly lower than that of all other fish species (Tukey-Kramer-HSD, P < 0.0.5). The δ13C values of quagga mussels and faucet snails were -30.1 ± 0.3‰ and -24.3 ± 0.9‰ respectively (Fig. 5).

Fig. 5 shows the core isotopic niche of each feeding guild. SEAc values range from 2.43 (zooplanktivorous) to 6.56 (benthivorous). The niche overlap between omnivorous sticklebacks and other feeding guilds was limited to a 9% overlap with zooplanktivorous whitefish.

Trophic position of sticklebacks

The statistical model testing effects on the stickleback trophic position (GLM, r2 = 0.29, n = 249, P < 0.0001) identified a significant influence of month (P < 0.0001), which comprised > 64% of total effect strength revealed the model (Table 3). When using a Δn value of 3.4, the mean trophic position of sticklebacks in Lake Constance was 4.7 ± 0.6 (± SD). The reduced Δn value of 2.0 yielded stickleback trophic positions of 6.7 ± 1.0 (± SD). This is unrealistic given the food web and feeding guilds of Lake Constance. Consequently, further analyses of trophic position are based solely on results from the Δn = 3.4 iterations of the model. The lowest trophic positions for sticklebacks were calculated for the summer months of June and July (4.4–4.6) and the highest for the spring months of March and April (4.9–5.0). No other tested parameters had a significant effect on trophic position (Table 3).

Table 3.

The significance and effect strength of different parameters on the trophic position of sticklebacks in Lake Constance.

parameter effect strength
month 0.969xxx (± 0.005)
habitat 0.001 (± 0.001)
total length 0.235 (± 0.01)
sex [m/f] 0.001 (± 0.001)
infested [yes/no] 0.012 (± 0.001)
parasite index 0.011 (± 0.0011)
TL*month n.a.

The trophic position for piscivorous pike in ULC was 4.2 ± 0.2 (± SD) and for partly piscivorous burbot 4.2 ± 0.4 (± SD).

A seasonal trend in stickleback trophic position was apparent, with lowest values during the stickleback spawning season (summer months), and increasing in the spawning season of whitefish during autumn and winter (Fig. 6).

Figure 6.

Fitted spline intervals of the trophic position of sticklebacks in Upper Lake Constance. Solid lines are the mean values, and shaded areas represent upper and lower 95% confidence intervals during the course of the year.

Trophic position of sticklebacks in other lakes and in comparison to Lake Constance

Sticklebacks from Lake Constance have a significantly higher trophic position than investigated populations in North America and Norway (z-test, P < 0.001) (Fig. 7). The proportion of littoral carbon in the diet of sticklebacks (α) from Lake Constance (mean = 0.06, standard error = 0.01) is comparable with that observed in populations with a “limnetic-like” phenotype from Norway and North America (α ≤ 0.4; Fig. 7) but far from that documented for benthic populations (α ≥ 0.6; Fig. 7).

Figure 7.

Comparison of trophic position and littoral carbon in the diet of three-spined sticklebacks. Values for sticklebacks from Lake Constance in black (mean value of all analysed sticklebacks, independent of habitat), from North America in blue and Norway in red; error bars indicating standard deviation. The eight North American stickleback populations (Matthews et al. 2010) (PRL = Priest Lake, KL = Kennedy Lake, PAL = Paxton Lake, CL = Cranby Lake, DL = Dugout Lake) and the two from Norway (Østbye et al. 2016) (EP = Einletvatn pond, FL = Farstadtvatn lake) are subdivided into limnetic (n = 4), benthic (n = 4) and intermediate (n = 1) ecophenotypes.


A key insight from the present study is the seasonal trend in δ15N from stickleback muscle and liver, with the highest values occurring during winter and spring. These values assist us to answer research question 1 (Do the δ15N values and trophic position of sticklebacks reflect the seasonal feeding of whitefish larvae and eggs or that of other food sources, such as zooplankton?). It could be hypothesised that the seasonal trend is linked to elevated δ15N values of the main food resource during winter (here copepods and cladocera), as observed in Lake Geneva where whitefish consume mainly zooplankton during the winter months (Perga and Gerdeaux 2005, 2006). There, the seasonal nature of zooplankton δ15N was echoed in the tissues of whitefish after a lag of one month in the case of liver tissue, and four to five months later in the case of muscle tissue. Sticklebacks from Lake Constance also consume large quantities of zooplankton (Ogorelec et al. 2022). However, it appears that stickleback δ15N values are only partly dictated by the isotopic signature of zooplankton. On the one hand, we can see a winter increase and decrease in the δ15N values of stickleback liver (as in Lake Geneva) and observe a switch from the summer diet of Daphnia and macrozoobenthos to copepods during winter. Much the same diet shift and increases in δ15N were observed in a study from North America (McIntyre et al. 2006). On the other hand, δ15N values in stickleback tissue from ULC increase up to 16.6‰ and are distinctly higher than those observed in local zooplankton (7.9‰–14.4‰). Moreover, values in stickleback muscle (which typically respond more slowly to dietary change) decreased only slightly after winter, and never fell below 14.1‰ throughout the year. In contrast, the δ15N value of zooplankton decreased to below 8‰ in April. Therefore, seasonal changes in zooplankton feeding from Daphnia to copepods alone cannot be responsible for the distinctly elevated δ15N values observed in ULC sticklebacks during winter or the moderately high values (well above those recorded in other fish species) observed during the rest of the year. Were that the case, we would expect to observe much lower δ15N values year-round and a much stronger decrease after winter. Additionally, during summer, the mean δ15N value of stickleback muscle (14.3 ± 1.2‰) was significantly higher than that of adult whitefish (13.2 ± 0.5‰), indicating differences in feeding ecology. Our stomach content analyses partially support the stable isotope results, as in winter the stomachs of 20% of pelagic sticklebacks contained fragments of fish eggs and partially digested fish larvae, while in spring 40% of littoral sticklebacks sampled contained fish eggs of unknown taxa. Judging by the season and pigmentation, the eggs and the larvae most likely belong to whitefish. Furthermore, stable isotope analysis of whitefish eggs and larvae revealed much higher δ15N levels than were identified in zooplankton. Thus, it is highly likely that the δ15N increase in the liver of sticklebacks during winter and spring and the high δ15N values in the muscle during spring are at least partly due to piscivory. Moreover, the outcome of our stable isotope mixing models estimates that whitefish larvae and whitefish eggs were the dominant prey items of sticklebacks during winter. This outcome suggests that we severely underestimate the predation rate during winter using the stomach content analysis alone. We guess that two factors are responsible for this outcome: first, the stormy winds during and after the spawning seasons, which hampered a normal sampling and second, the extremely patchy distribution of whitefish larvae (Ransom et al. 2022) and therefore clutched appearance of larvae in the diet of sticklebacks, which is further supported by mass feeding (Roch et al. 2018). It could be hypothesised that during food scarcity in winter, when the density of zooplankton and benthic macroinvertebrates is much lower compared to summer (Ogorelec et al. 2022), whitefish eggs and larvae are an exceptionally valuable additional diet component for sticklebacks due to their easy availability and undisputed caloric value (Ros et al. 2019; Baer et al. 2021). Furthermore, the Bayesian model calculated for summer a proportion of 30% (pelagic zone) and 40% (littoral zone) of fish in the diet of sticklebacks. As for winter, this outcome starkly contrasts with our stomach content analysis. We found only one female stickleback, caught in August, which had eaten 14 fish eggs. However, even if cannibalistic behaviour is well known for sticklebacks (FitzGerald and van Havre 1987; Mehlis et al. 2010), those eggs were highly likely not from sticklebacks, because sticklebacks in ULC spawn much earlier, between April and June (Gugele et al. 2020). Different cyprinids, like bleak Alburnus alburnus and the white bream Blicca bjoerkna, are multiple spawners and some spawn until the end of July (Rinchard and Kestement 2003). Thus, it seems likely that sticklebacks from ULC consume, if the opportunity arises, eggs from other fish species, i.e. cyprinids, as has been observed in other water systems before (Dukowska and Grzybkowska 2014). Furthermore, nearly all fish from ULC spawn in the littoral zone, not in pelagic waters. Therefore, the difference in fish consumption from sticklebacks caught during summer in both habitats most probably reflects the availability of fish eggs and larvae in both habitats. All in all, the results from the stable isotope mixing models pointed to a significant piscivorous behaviour of sticklebacks in ULC. It is well known from other parts of the world that sticklebacks can consume high amounts of fish seasonally: in the Baltic Sea sticklebacks were observed to migrate purposely to the spring spawning grounds of perch and pike, where they fed on eggs and larvae of those species. This leads to significant stock reductions of the latter two species (Ljunggren et al. 2010; Bergström et al. 2015; Byström et al. 2015). In ULC, similar patterns were observed (sticklebacks migrated to the spawning grounds of whitefish, Gugele et al. 2020).

The answers to research questions 2 (Where do invasive sticklebacks sit relative to other fish species in the trophic structure of Lake Constance?) and 3 (How does the trophic position of sticklebacks in Lake Constance compare to that of conspecifics in similar ecosystems?) are somewhat contradictory. Generally, Lake Constance sticklebacks occupied an extraordinarily high trophic position (mean = 4.7), even using a conservative estimate of trophic enrichment (Δn = 3.4). Other studies, using the same calculation and the same values for trophic enrichment and trophic position of the consumer (λBase = 2), yielded markedly lower scores: The mean trophic positions calculated for sticklebacks in lakes of North America and Norway ranged from 2.9 to 3.7 (Matthews et al. 2010; Østbye et al. 2016), and in Japan, the species occupies a mean trophic position of 2.8 (Ravinet et al. 2014), however, in those lakes no piscivorous behaviour of sticklebacks was observed. In large oligotrophic lakes, trophic positions higher than 4 are normally occupied by at least partly piscivorous fish like arctic charr (Salvelinus alpinus L., 1758) or perch (Perca fluviatilis L., 1758) (Eloranta et al. 2015). In ULC, pike and burbot showed trophic positions of around 4.2, and their mean δ15N values are highly comparable to sticklebacks. However, this does not mean that they were all at the same trophic level because it is proven that the intra- and interindividual variation in the isotopic composition depends not only on the diet, but also on the amount of isotopic variations among the food sources (Matthews and Mazumder 2005). We found large seasonal variations in the isotopic signatures of zooplankton in ULC as other authors did (Perga and Gerdeaux 2006; Janjua and Gerdeaux 2011). In those cases, modelling the trophic position of fish species is hardly reliable because many sources of δ15N variation are, therefore, unrelated to trophic variation (Matthews and Mazumder 2005; Janjua and Gerdeaux 2011). Another explanation for the high trophic position of sticklebacks in ULC sticklebacks could be the δ15N or δ13C values (here: baseline values) of other consumers represented here by faucet snail and quagga mussel. It is known that interannual variation in the δ15N or δ13C values of snails and mussels can occur (Westrelin et al. 2023). We sampled snails and mussels two years after we sampled the sticklebacks which may have biased our outcomes. Furthermore, it is known that the δ15N or δ13C values for dreissenids in Lake Constance (zebra mussel Dreissena polymorpha Pallas, 1771), are depth, water temperature and season dependent (Yohannes et al. 2014). However, even if we use this seasonal variation to consider potential innerannual variation and to adjust the δ15N or δ13C values for the season (late summer) to a range of -30.5‰ to -34.5‰ for δ13C and 6‰ to 9‰ for δ15N (cf. Yohannes et al. 2014) for the baseline values, stickleback trophic position always exceeds 4. In other lakes, for example, the western basin of Lake Erie in the US, δ13C values of around -22‰ were reported for quagga mussels (Guzzo et al. 2011). Those values would lead, even in Lake Constance, to a different α-value, and a trophic position of around 3.5 and are, thus, very comparable to other lakes in North America (Matthews et al. 2010). However, the western basin of Lake Erie is much warmer than Lake Constance and mesotrophic (Guzzo et al. 2011), and it is generally known that δ15N values in warmer ecosystems are generally lower while δ13C values tend to be elevated in cooler systems (Yohannes et al. 2014). These factors must be considered when looking to trophic position results for sticklebacks from other parts of the world, even if they are acquired using the same equation (Post 2002) and the same method. Ecosystems operating under different temperature regimes may not be strictly comparable. However, comparisons between this study and those from Canadian and Norwegian lakes with similar cooler temperature regimes are valid, and by these benchmarks, the trophic position of stickleback in Lake Constance is remarkably high. Further investigations are needed to disentangle the effects of temperature on stable isotope turnover rates and diet-tissue discrimination patterns.

The diet and stable isotope mixing model evidence of regular or at least occasional piscivory by Lake Constance sticklebacks are corroborated by comparison of the mean δ15N muscle values of sticklebacks with those of fish species from a range of foraging guilds. Sticklebacks possessed significantly higher muscle δ15N values (up to 5‰) than the zooplanktivorous and/or benthivorous and herbivorous fish in our analysis, including whitefish, bleak, roach, tench, and rudd. Other studies have shown δ15N differences between years for various fish species, but the values of the fish species from one foraging guild tend to be more or less stable from year to year (Janjua and Gerdeaux 2011). Furthermore, mean stickleback δ15N muscle values in Lake Constance are much the same as those of pike here and in other lakes (Juanes et al. 2002; Craig 2008). This indicates that a considerable portion of stickleback diet is derived from protein-rich prey (Gu et al. 1996; Frisch et al. 2014), such as fish eggs or larvae. Recent studies of sticklebacks in Lake Constance in which stomach content analysis identified zooplankton as the only prey (Bretzel et al. 2021; Ogorelec et al. 2022), should be scrutinised in the light of these findings, as indigestible arthropod body parts will remain longer in alimentary tract than protein-rich prey items (Preston et al. 2017). And the extremely patchy distribution of whitefish larvae (Ransom et al. 2022) makes regular feeding highly doubtful. Not only the present study but also other studies dealing with invasive fish species have shown that stable isotope analysis, together with the modelling of contribution rate of potential food sources to consumers, can provide a more effective assessment of an invader’s feeding behaviour and potential environmental impacts than classical stomach content analysis alone (Brush et al. 2012).

The answer to research question 4 (Are there any differences in isotopic signature between sticklebacks caught in littoral and pelagic habitats?), if only the δ13C values recorded in stickleback muscle tissue are considered, is relatively clear: the answer is no. The low values (-30.5 ± 0.8‰) point to pelagic feeding of the species (France 1995). The apparently low proportion (<10%) of littoral carbon (α) assimilated from the diet of ULC sticklebacks strongly suggests that the population comprises predominantly pelagic feeders. In benthic-feeding individuals of this species, the proportion of littoral carbon is normally around 60% or higher (Matthews et al. 2010; Østbye et al. 2016). However, it is somewhat surprising that littoral habitat has so little influence on stickleback muscle δ13C values, as stomach content analysis suggests that during summer and autumn, littoral and pelagic sticklebacks consume distinctly different diets: significantly, dietary overlap was only observed in winter and spring (Table 3). Muscle tissue is typically favoured in stable isotope analysis to characterise longer-term feeding patterns and to differentiate consumers into ecotypes or guilds (Matthews et al. 2010; Østbye et al. 2016), while the rapid turnover of liver tissue means it incorporates and processes diet components faster than muscle tissue and is thus more sensitive to short-term feeding changes (Perga and Gerdeaux 2006). These trends are borne out in the current study, where a seasonal habitat shift appears to significantly affect δ13C liver levels but not muscle tissue δ13C levels. It may be that the duration of littoral feeding is too short to register in muscle or that a potentially reduced feeding rate during the littoral phase (during/after spawning in summer and autumn) is compensated by an increased feeding rate during the pelagic phase (winter and spring), or that an interplay of these effects occurs. Thus, further studies of stable isotope signatures of the liver will be needed to ascertain which of these three possibilities is the case and also to further test the recent theory that a benthic-pelagic species pair (one littoral, one pelagic, cf. Dahms et al. 2022) exist in Lake Constance. The latter question may require the deployment of specific markers, such as fatty acids (Hou et al. 2020; Rubenson et al. 2020) or sophisticated genetic analysis (Marques et al. 2016). Further laboratory studies are also required to attain more detailed and species-specific information regarding the effects of different diets (zooplankton, fish eggs, fish larvae, etc.), the impact of starvation, spawning, and parental care on the isotopic expression in stickleback muscle and liver tissue. The hypothesis that stocking with recently hatched whitefish larvae (as has been the practice in ULC for over a century) facilitates stickleback population growth and spread (Roch et al. 2018) also requires further investigation in order to ascertain whether stocking is a factor prompting the stickleback invasion of the pelagic zone in ULC.

Results of this study pertinent to the original research questions include confirmation from stomach content analysis that sticklebacks feed on whitefish larvae and eggs as well as fish of unknown taxa: corroborated by δ15N values, the outcome of stable isotopes mixing models, and trophic profiling. Stable isotope analysis revealed significantly elevated δ15N values comparable to those of pike and consistent with piscivory, and δ13C profiles identified stickleback as mostly pelagic feeders. Furthermore, it appears that while the trophic position of sticklebacks is independent of their littoral and pelagic foraging habitats, differences in the isotopic signature of littoral and pelagic captures were visible in the liver, offering support for the idea that stickleback has a key role coupling the littoral and pelagic food webs of Lake Constance. However, actual data (not shown) of stomach contents of piscivorous fish, such as pike, catfish, char or trout (Salmo trutta), revealed that sticklebacks were only eaten occasionally by other fish and stickleback predation seems instead to be mostly from fish-eating birds, which would render this avenue a dead end for the aquatic ecosystem. However, a similar assessment was hypothesized for the dreissenid mussels in the Great Lakes, where the lakewide degree of mussel predation by fish was believed to be limited, but when round goby (Neogobius melanostomus) and lake whitefish (Coregonus clupeaformis) began to feed intensively on quagga mussels they contributed significantly to Great Lakes’ food webs (Madenjian et al. 2010). Whether the predatory fish of Lake Constance will adapt to the stickleback resource, especially in the pelagic zone, is an open question for the future.


The study results support the hypothesis that Lake Constance sticklebacks feed occasionally but rather intensively on the eggs and larvae of whitefish and some other fish species. This finding is in line with findings from the Baltic Sea, which highlight the negative impacts of stickleback predation on other fish species (Ljunggren et al. 2010; Bergström et al. 2015; Byström et al. 2015). The data in this study sheds important light on the puzzle of the Lake Constance stickleback invasion, in particular the question of how they have become such an important component of the food web of this large ecosystem. Our results suggest that sticklebacks in ULC are predators of whitefish larvae and eggs with significant negative consequences for their recruitment, and that this behaviour should be considered in the future management of the lake.


Special thanks to Prof. J. Geist, Prof. K. Auerswald and Dr. R. Schäufele from the Technical University of Munich for the opportunity to conduct stable isotope analyses of snails, mussels and parts of the fish samples and for advice on technical issues and scientific support. We thank Karl-Otto Rothaupt for the support of stable isotope measurement of sticklebacks, D. Straile and M. Sabel for the isotopic data for chironomids, and the fishermen Gugele, Revermann, and Meichle for fish sampling. We thank A. Ros and S. Roch from the Fisheries Research Station for help in calculating the isotopic niche overlap. Thanks to Amy-Jane Beer for improving the manuscript.

Sarah Maria Gugele was funded by the “Fischereiabgabe Baden-Württemberg” and supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)—298726046/GRK2272 and by the grant “SeeWandel: Life in Lake Constance – the past, present and future” within the framework of the Interreg V programme “Alpenrhein-Bodensee-Hochrhein (Germany/Austria/Switzerland/Liechtenstein)” the funds of which are provided by the European Regional Development Fund as well as the Swiss Confederation and cantons. Barnaby J. Roberts was funded by the University of Konstanz and by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – 298726046/GRK2272. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.


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Supplementary material

Supplementary material 1 

Supplementary information

Sarah Maria Gugele, Jan Baer, Christina Spießl, Elizabeth Yohannes, Steve Blumenshine, Barnaby J. Roberts, Mario R. Mota-Ferreira, Alexander Brinker

Data type: docx

Explanation note: table S1. Quantiles of the posterior distribution of the Bayesian mixing model parameter estimation. table S2. Correlation of the posterior distribution of the Bayesian mixing model parameter estimation. figure S1. Isospace plot representing the isotopic signatures of the stickleback liver samples caught in summer (June and July) and in winter (December to March). table S3. Quantiles of the posterior distribution of the Bayesian mixing model parameter estimation for models without the fish sources. table S4. Correlation of the posterior distribution of the Bayesian mixing model parameter estimation for models without the fish sources. figure S2. Posterior distribution of dietary proportion estimates of different food sources from sticklebacks from the pelagic and littoral zone of ULC during summer and winter, according to Bayesian modelling without fish sources, expressed as Box-and-Whisker plots with median values and interquartile range (IQR).

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