Diet variability in Eurasian perch (Percafluviatilis) as a response to environmentalvariables along a latitudinal gradientKasparas Bublys

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Diet variability in Eurasian perch (Perca fluviatilis) as a response to environmental variables along a latitudinal gradient

Kasparas Bublys

Degree project inbiology, Master ofscience (2years), 2018 Examensarbete ibiologi 45 hp tillmasterexamen, 2018

Biology Education Centre and Department ofEcology and Genetics, Uppsala University Supervisor: Peter Eklöv

External opponent: Kristin Scharnweber

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difference in the prevalence of specialist individuals was found along the latitudinal gradient and water transparency levels. Habitat was the main factor that significantly affected niche width and level of specialization with both being significantly higher in the littoral habitat. Taken together my results suggest that climate change might indirectly affect niche patterns by altering fish densities through changes in productivity resulting in niche and specialization variation among habitats.

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4 Introduction

Generally, a particular species may only use part of the resources available to it. Measurements of resource use (niche width) along dimensions such as prey size provide us with insight into specialization of a particular species (Sale 1974). Niche width traditionally describes a range of resources a population exploits and is a ubiquitous feature of all species (Roughgarden 1972), with broad niches found in generalist species while narrow niches are common for specialist organisms. A populations’ niche width reflects the balance between the diversifying effects of intraspecific competition and constraints imposed by interspecific competition (Van Valen 1965;

Roughgarden 1972; Grant & Price 1981; Taper & Case 1985; Bolnick et al. 2010). Van Valen (1965) was first to propose that resource use among individuals of a population can vary

significantly. Roughgarden (1972, 1974) later provided a quantitative framework for discussing within-population niche variation and suggested that the total niche of a population can be expressed as a sum of two components: within- and between- individual variation in resources used. Most subsequent niche studies considered within-individual resource use variation as rare or otherwise unimportant and tended to treat all conspecifics of a population as ecologically equivalent (Bolnick et al. 2003). It was later shown that individual specialization is common amongst various taxa and that some generalist populations could in fact be composed of multiple specialists (Bolnick et al. 2003).

Variation of niche width with latitude has been hypothesized for several decades now with MacArthur (1972) proposing that population niche breadth decreases at lower latitudes. Species diversity is higher and species interactions are stronger at the tropics than at higher latitudes (Hillebrand 2004, Schemske et. al. 2009). Both of these factors should lead to increased interspecific competition resulting in a higher prevalence of narrow niche specialist species at

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lower latitudes. However, empirical studies evaluating the proposed latitudinal niche width gradient remain inconclusive (Vazquez & Stevens 2004) with approximately equal number of terrestrial studies supporting and refuting the latitudinal niche width gradient hypothesis (Papacostas & Freestone 2016). A recent study of brachyuran crabs revealed that the pattern of positively correlated niche width and latitude proposed by MacArthur was true only among temperate and not tropical species of the crabs (Papacostas & Freestone 2016). This latitude- niche breadth relationship might be further complicated by the fact that species previously thought to be generalists might in fact be heavily specialized at an individual level especially if the degree of within population specialization varies across the same gradient.

Climate warming is expected to have a profound effect on freshwater fish communities and their structure (Jeppesen et al. 2010, 2012). In fact, many freshwater species might have already shifted their geographic ranges, species interactions, and seasonal activities in response to ongoing climate change (IPCC, 2014). As a consequence, climate change can directly influence dietary niche width and specialization where researchers have shown that climatic conditions and not competition is the main predictor for dietary specialization of terrestrial lizards (Gainsbury &

Meiri, 2017). Fish being ectotherms are unable to physiologically thermoregulate and are directly affected by changes in water temperature (Jeppesen et al. 2010). Furthermore, temperature has been found to be an important predictor of body-size structure of European freshwater fish assemblages (Emmrich et al. 2014) and life-history traits of Eurasian perch (Perca fluviatilis) such as growth rates, life span, and reproductive investment all of which change along a latitudinal temperature gradient (Heibo et al. 2005).

Eutrophication effects are intensified by climate warming (Moss et al. 2011). Changes in water transparency can be a result of many processes such as sediment resuspension, brownification,

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and eutrophication (Bartels et al. 2012). No matter the source, reduced water transparency can affect aquatic organisms that depend on vision for foraging, intra-specific communication, or mating (Järvenpää & Lindström 2004, Heubel & Schlupp 2006, Ljunggren & Sandström 2007).

Bartels et al. (2012) showed that the diet composition of littoral perch could be influenced by water transparency with increased reliance on littoral resources in clear water conditions. A later study linked reduced transparency brought on by increased levels of dissolved organic carbon (DOC) with reduced habitat coupling via diet shift towards pelagic resources, more homogenized morphology and diet, as well as increased eye size, suggesting a morphological response of perch to lower visual conditions (Bartels et al. 2016).

Eurasian perch is considered a generalist species that is known to undergo two ontogenetic shifts during its lifetime (Persson 1988) and is the subject of my investigation. Perch juveniles feed on zooplankton, then shift to macroinvertebrates at intermediate sizes, and finally after reaching a certain size, become mainly piscivorous (Persson 1988, Hjelm et al. 2000, Svanbäck & Eklöv 2002). Over its lifetime Eurasian perch not only increases in trophic position, but may also change its diet width (Persson 1988, Quevedo et al. 2009, Svanbäck & Persson 2009, Svanbäck et al. 2015). Eurasian perch are also known to specialize in feeding on either pelagic or littoral

prey types with littoral perch diet consisting of more macroinvertebrates while the diet of pelagic fish contains more zooplankton (Svanbäck & Eklöv 2002, Svanbäck et al. 2008, Quevedo et al.

2009). The phenotype of Eurasian perch is known to vary in relation to the habitat use of an individual (Svanbäck & Eklöv 2002, 2003). Although this variation has a hereditary component it seems to be mostly related to the inherent phenotypic plasticity of the perch (Svanbäck &

Eklöv 2006).

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7 Aims

In this study I attempted to investigate how niche width and several other diet-based

characteristics might depend on latitude, climatic zone and water transparency. I did this by studying the diet composition of Eurasian perch (Perca fluviatilis) sampled from 10 lakes over a 12.65 degrees of latitude gradient in the temperate and boreal climatic zones. Multiple studies of perch diet ecology have already been conducted in great detail but most of these studies were rather geographically constrained. The main goal of this study was to investigate the potential impact of climate change on niche use of perch focusing on diet variation along a latitudinal gradient and at varied light climate. To achieve this I made several predictions: (1) population niche width will be significantly greater at higher latitudes, (2) individual specialization will be more prevalent in darker lakes and in lakes at lower latitudes, (3) population diet overlap

between habitats will be greater at lower latitudes and in clearer water conditions, (4) reliance on littoral resources will be greater in lakes with clearer water and at higher latitudes.

For prediction 1 I expected that northern perch populations might expand their niche following ecological release from reduced interspecific competition and potentially confirm MacArthur’s latitude-niche variation (Bolnick et al. 2010). Alternatively, in prediction 2 I expected that perch would experience reduced intraspecific competition by becoming more specialized in their diets (Bolnick et al. 2010). This would happen if interspecific competition is high or prey accessibility and foraging success are low as might be the case in southern lakes or lakes with poor light climate respectively. Predictions 3 and 4 are based on observed differences in habitat coupling and diet preferences at varying light climates (Bartels et al. 2012, 2016) and density dependent habitat preferences of Eurasian perch (Persson et al. 2000, Svanbäck, & Persson 2004, Svanbäck et al. 2008).

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Methods

Field sampling

Eight Swedish lakes were sampled between the 18^th of July and 21^st of August and 2 German lakes were sampled between the 17^th and 19^th of September, 2017. The sampling of Swedish lakes was carried out in collaboration with the Swedish University of Agricultural Sciences’

Department of Aquatic Resources (SLU Aqua). The lakes were selected from a pool of lakes that were to be sampled this year and were based on their latitude and transparency (as measured in previous surveys). I assigned the four northernmost Swedish lakes into a “boreal” climatic zone with all the remaining lakes into a temperate “warm temperature” climatic zone based on the updated Köppen-Geiger climate classification (Kottek et al. 2006; Rubel et al. 2017). Lakes with a Secchi depth lower than 3 meters were considered “turbid”, while the Secchi depth in “clear”

lakes was between 3 and 6 meters.

Table 1. Summary of sampled lakes

Lake Latitude Secchi

depth (m) Climatic zone Water transparency

N fish Pel.

N fish Litt.

Vuolgamjaure 65.66 4.5 Boreal Clear 0 30

Remmarsjön 63.86 2.6 Boreal Turbid 8 30

Källsjön 61.63 0.85 Boreal Turbid 0 30

Dagarn 59.89 5 Boreal Clear 15 30

Gyslättasjön 57.1 1.78 Warm temperature Turbid 30 30

Fiolen 57.09 3.86 Warm temperature Clear 30 30

Stora Skärsjön 56.67 3.76 Warm temperature Clear 29 28

Brunnsjön 56.59 1.13 Warm temperature Turbid 30 30

Großer Vätersee 53.01 4.15 Warm temperature Clear 27 29

Wuckersee 53.01 5.5 Warm temperature Clear 13 30

The Swedish lakes were fished overnight by SLU Aqua teams using standardized survey multi- mesh gill nets (type Norden: littoral nets 5-55 mm mesh, 30 x 1.5 m; pelagic nets 10-55 mm mesh 27.5 x 6 m) set just outside the macrophyte belt of the littoral zone and in the pelagic

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habitat of the lakes, up to a depth of 6 meters. After the nets were lifted 30 perch, if possible, were taken from each of the habitats and stomachs were removed and frozen for later analysis.

Fish catches in the pelagic zone in some of the lakes were few with two of the boreal lakes having no perch caught in the pelagic zone (Table 1). The German lakes were fished by a team from Leibeniz- Institute of Freshwater Ecology and Inland Fisheries and followed the same general procedure as the Swedish lakes. Overall, 480 perch individuals were caught.

Diet analysis

Diet assessment followed the outline described in Svanbäck and Eklöv (2003). In short, stomach content of every fish were analyzed under a dissecting microscope and all fish and invertebrates were identified to the lowest practical taxonomic level (family, genus or species). Up to 10 individuals of every taxa were measured. The length measurements were used to obtain biomass (dry weight) estimates based on available length-weight regressions (Eklöv and Svanbäck unpublished data). All prey items found in perch stomachs were also divided into eight common functional groups: littoral invertebrates, benthic cladocera, chironomids, pelagic cladocera, copepods, pelagic macro-invertebrates, terrestrial invertebrates, and fish. The resulting proportional biomass for each individual was used to calculate niche metrics in further diet analyses. Due to known differences in both diet and morphology, the pelagic and littoral subpopulations of perch were treated as separate in the analysis (Svanbäck & Eklöv 2002,

Svanbäck et al. 2008, Quevedo et al. 2009). A sum of littoral invertebrate and benthic cladoceran proportions was also recorded for littoral resource reliance comparisons. Of the 480 perch

stomachs analyzed, 140 (29.2%) were empty or with no identifiable prey items and were excluded from further analyses.

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10 Niche metrics

Total niche width (TNW) is made up of two components, the within-individual and between- individual components (WIC and BIC respectively). WIC is the average variance of the resources found within the diet of an individual and BIC is the variance in mean resource use between individuals (Roughgarden 1972, Bolnick et al. 2002). The relationship between these values can be expressed as TNW= WIC+BIC. To estimate diet width of the perch Levins (1968) trophic index B was used. The index is calculated as:

Here pj is the proportion of the diet of the jth diet category. This index was calculated for each individual and the average value for the subpopulation was treated as the within-individual component (WIC) while the equivalent proportional averages of diet categories calculated from that subpopulation was treated as total niche width (TNW, see Bolnick et al. 2002 for similar method). Finally, WIC/TNW ratios were calculated. This ratio varies between 0 and 1 and provides a measure of individual specialization in the population. When WIC/TNW is high (approaching 1), individual specialization is low as majority of the individuals are utilizing most of the population’s niche, with the opposite being true at lower values (Bolnick et al. 2002).

Additionally, proportional similarity index (PSi) was calculated for each individuals’ diet comparing it to the average diet of the subpopulation (Bolnick et al. 2002). It is calculated as follows:

.

Here pij is the proportion of resource j that is used by the population that is also used by the individual i and qj is the proportion of the jth resource category in the overall niche of the population. For individuals specializing in a single diet item j, PSi will take on the value of qj,

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while individuals that consume diet items in direct proportion to the population will have a PSi value of 1. The prevalence of individual specialization (IS) in a population is then measured as an average of PSi values of the individuals in that population (Bolnick et al. 2002). The same formula was used to calculate diet overlap between pelagic and littoral habitats in each lake based on average proportions of prey items between the two habitats.

Statistical analyses

The indices were calculated and summarized in Microsoft Excel 2013. Additionally, regression analyses for each habitat with latitude and TNW as independent and dependent variables respectively were performed in Excel using the data analysis add-in. Further statistical analyses were performed in PAST3 (Hammer et al. 2001) and PRIMER v 6.1.16 (Clarke & Gorley 2006) with the PERMANOVA add-on package was used to perform multivariate statistical analyses on diet data.

Initial exploratory data ordination was performed using non-metric multidimensional scaling (nMDS) plots in PAST3 using TNW, IS and WIC/TNW values of each habitat to construct the resemblance matrix.

A Shapiro-Wilk test of normality and a Levene’s test for homogeneity of variance

(homoscedasticity) were applied to IS, TNW and WIC/TNW values by climatic zone, and water transparency. All values satisfied conditions of normality and homoscedasticity with only TNW by climatic zone returning a borderline value for Levene’s test (p=0.0583). ANOVAs for the effect of climatic zones and water transparency on diet indices within habitat were performed.

Additionally, ANOVAs for significances between the two habitats were also performed. As before IS, TNW and WIC/TNW values were assessed with a Shapiro-Wilk’s test of normality

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and as a result TNW values were log-transformed to satisfy normality assumptions of ANOVA.

Levene’s test for homoscedasticity was satisfied in all cases.

Significance for individual level diet width (Levins B) between lakes, climatic zones and water transparency at each habitat were tested in PAST3 with Kruskal-Wallis test for equal medians, a non-parametric alternative to ANOVA. This was done after multiple unsuccessful attempts to transform the data to meet the assumptions for normality and in some cases homoscedasticity.

PERMANOVA analyses were performed on individual level diet data divided by habitat (littoral and pelagic). Lakes were nested within climatic zone and water transparency and all factors were considered as fixed. Diet data (% dry biomass by prey category) were arcsine-square root

transformed and resemblance matrices were based on Bray-Curtis similarity. Unrestricted

(n=9999) permutations with type III sums of squares were used to test for significance of models.

Results

Total niche width and latitude

Linear regression analysis showed no total niche width relationship with latitude in littoral (R²= 0.004, p>>0.05) or pelagic (R²=0.001, p>>0.05) habitats of the sampled lakes. Attempts to fit non-linear models available in PAST3 did not yield any results.

Diet niche and specialization

Non-parametric multi-dimensional scaling plots based on a resemblance matrix constructed from TNW, IS and WIC/TNW values of each lake and habitat (Figure 1) suggested that lakes were clustering by habitat and the other two factors were overlapping heavily. Based on this observation as well as general knowledge of differences between pelagic and littoral perch populations, all further analyses were carried out on per-habitat basis.

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Total niche width was significantly different between the pelagic and littoral habitats (ANOVA:

F1, 16=13.65, p=0.0019) with broader niche in the littoral zone (Figure 2a). Total niche width was not significantly different between climatic zones and water transparency levels in either of the habitats (Table 2).

Proportional within-individual component of total niche width (WIC/TNW) differed

significantly between pelagic and littoral habitats (ANOVA: F1, 16=16.88, p=0.00082) and was

Figure 1. nMDS plots of lakes highlighting a) climatic zone, b) water transparency, c) habitat . Resemblance matrix constructed from TNW, IS and WIC/TNW values.

Figure 2.Boxplots of a) total niche width (TNW), b) proportional within-individual component (WIC/TNW), c) individual specialization (IS) values between habitats. Whiskers are SE.

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higher in the pelagic, indicating a lower degree of specialization in the pelagic habitat across all sampled lakes (Figure 2b). No significant differences between climatic zones or water

transparency were discovered in either habitat (Table 2).

Finally, significant difference in individual specialization (IS) between habitats was confirmed (ANOVA: F1, 16=16.21, p=0.00097) with higher IS values in the pelagic (Figure 2c). Like WIC/TNW, higher IS values indicate reduced prevalence of specialization in the population.

Again, no significant differences in IS values were discovered between climatic zones and water transparency (Table 2).

Table 2 Summary of the ANOVA results for IS, TNW and WIC/TNW between climatic zones and water transparency in pelagic and littoral habitats.

Climatic zone Water transparency

Pelagic habitat F1, 6 p F1, 6 p

IS 2.422 0.1706 0.3072 0.5994

TNW 0.1584 0.7044 0.01305 0.9128

WIC/TNW 2.723 0.15 0.1133 0.7479

Climatic zone Water transparency

Littoral habitat F1, 8 p F1, 8 p

IS 0.02124 0.8877 0.4093 0.5402

TNW 0.007551 0.939 0.005608 0.9421

WIC/TNW 0.000462 0.9834 0.1469 0.7115

Individual level niche breadth (Levins B) in both habitats showed no significant difference between climatic zones and water transparency levels (Kruskal-Wallis test for equal medians:

p>>0.05).

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15 Diet

Diets of littoral perch differed significantly between all 3 factors (climatic zone, water

transparency and lakes), and suggested a significant interaction between climatic zone and water transparency (Table 3). Significance value for pelagic perch diets between climatic zone was borderline non-significant (PERMANOVA: Pseudo-F=2.3185, P= 0.0541). Pelagic perch diets proved to differ significantly between water transparency levels and lakes (Table 3).

Table 3 Summary of PERMANOVA results for perch diets. CZ- climatic zone, WT- water transparency, CZxWT- interaction between CZ and WT. Significant p values highlighted in green.

Factor Littoral Pelagic

Pseudo-F P(perm) Pseudo-F P(perm)

CZ 9.7625 0.0001 2.3185 0.0541

WT 4.9386 0.0006 5.5987 0.0004

CZxWT 4.5001 0.0016 4.0403 0.0052

Lakes(CZxWT) 6.6059 0.0001 23.637 0.0001

Littoral diets were significantly different between all boreal clear, boreal turbid and temperate turbid lakes with only non-significant differences in diet found in the temperate clear lakes between Fiolen - Wuckersee and Große Vatersee - Wuckersee (post hoc pair-wise

PERMANOVA). Pelagic diets between lakes in temperate clear and temperate turbid groups all differed significantly (post hoc pair-wise PERMANOVA: P<0.05). Due to the absence of fish from two of the boreal lakes no boreal groups for pair-wise analysis could be formed. For exact proportional diet composition see Appendix Figure 1 and Figure 2.

Diet overlap and littoral resource reliance

No significant difference in diet overlap was found between climatic zones (ANOVA: F1,

6=0.5788, p=0.4756) or water transparency levels (ANOVA: F1, 6= 2.863, p=0.14). Regression of diet overlap and latitude proved to be non-significant (R²=0.05, p>>0.05).The proportion of littoral resources in littoral fish diet was significantly higher in the boreal lakes (ANOVA: F1,

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8=10.32, p=0.012, figure 3a). No significant difference in littoral resource use was found between the water transparency levels (ANOVA: F1, 8=1.779, p=0.219, figure 3b).

Discussion

Habitat had a greater effect on both niche width and prevalence of individual specialization than latitude or water transparency further emphasizing foraging trade-offs between littoral and pelagic perch populations. As a whole, littoral perch had wider trophic niche and were more specialized (lower IS and WIC/TNW values) than pelagic individuals. Increased individual specialization (IS) could indicate reduced ability to switch between habitats, while higher proportional within-individual component (WIC/TNW) suggests increased range of available resources in littoral habitats (Marklund et al. 2018). Perch are also known to have more

specialized diets at high intraspecific densities (Svanbäck, & Persson 2004). In summary, littoral perch appear to feed on a wider array of prey than pelagic individuals, but are rather specialized in their diets probably as a result of increased intraspecific densities.

Figure 3. Proportion of littoral resources between a) climatic zones, b) water transparency levels

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Pelagic-littoral diet overlap was not significantly different across the climatic zones or water transparency levels, running counter to my prediction (3). However, even though the proportion of littoral resource use did not differ between levels of visual conditions, it was significantly higher in littoral perch from boreal lakes as predicted. Higher degree of littoral habitat use might be the result of lower overall densities in the northern lakes as perch are known to prefer littoral habitats at low densities (Persson et al. 2000, Svanbäck, & Persson 2004, Svanbäck et al. 2008) as well as higher proportion of pelagic prey items in the diets of littoral perch from temperate zone lakes (Appendix Figure 1).

Neither total niche width (TNW) of a population nor the individual level niche width (Levins B) were found to have any relationship with latitude over the sampled range, with no significant differences between the northern and southern lakes, leading me to reject my prediction (1). This climate or latitude dependent prediction was based on the MacArthur’s latitude-niche width variation theory with the expectation being that at lower latitudes an increase in interspecific competition might manifest itself resulting in a reduction of niche width. As an alternative hypothesis I predicted that individual specialization would be more prevalent in more turbid and temperate lakes leading to a tighter partitioning of the existing niche among individuals.

Similarly, lower benthic foraging efficiency due to reduced light conditions might result in increased intraspecific competition in the littoral, driving individual diet variation. I expected this because of observed foraging trade-offs between morphologically distinct perch, and the fact that these morphological divergences seem to be related with water transparency, being more

pronounced at good light conditions (Svanbäck & Eklöv 2002, 2003, Bartels et. al 2012).

However, measures of individual specialization (WIC/TNW, IS) showed no significant

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difference between climatic zones or water transparency levels in either of the habitats, again forcing me to reject my initial prediction (2).

The results show that significant interactions do not seem to be driven directly by either inter- or intraspecific competition, as initially expected, but instead by intraspecific density-dependent factors. Fish densities increase with lake productivity and cause a reduction in mean fish size due to density-dependent food limitations (Jeppensen et al. 2010). Lake productivity also generally increases towards lower latitudes and this is closely tied to temperature (Brylinsky & Mann 1973, Karlsson et al. 2005). This was also a clear pattern in our data showing lower perch densities overall in the northern lakes and a northwards decrease in pelagic perch. Reduced catches in the pelagic habitat of northern lakes that we experienced during sampling might also be related to this pattern. As climate change is expected to increase productivity of most currently unproductive lakes we can expect changes in perch life history and density to follow.

Eventually, increasing temperatures could lead to increased perch expansion into pelagic habitats in northern lakes.

Conclusion

Habitat and not climatic zone or water transparency was the main predictor of Eurasian perch niche width and degree of specialization. The results of this study seem to suggest that climate affects Eurasian perch niche and individual specialization through density dependent habitat preference resulting in the observed variation between habitats but not between climatic factors.

Although we can expect major changes to life-history traits such as growth rate and age at maturity as well as community compositions of northern perch populations due to climate change, changes in niche width and individual diet specialization are unlikely as long as their densities remain comparable to those of present-day southern perch communities.

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19 Acknowledgements

I would like to thank Peter Eklöv for his supervision and endless patience. I would also like to thank Matilda Andersson, as well as SLU Aqua and IGB-Berlin teams for all the help in the field.

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Figure 1. Proportional littoral perch diet composition based on dry weight biomass estimates.

Figure 2. Proportional pelagic perch diet composition based on dry weight biomass estimates.

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Diet variability in Eurasian perch (Percafluviatilis) as a response to environmentalvariables along a latitudinal gradientKasparas Bublys