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Due to altered biogeochemical processes related to climate change, highly colored dissolved organic carbon (DOC) from terrestrial sources will lead to a water "brownification" in many freshwater systems of the Northern Hemisphere. This will create deteriorated visual conditions that have been found to affect habitat-specific morphological variations in Eurasian perch (Perca fluviatilis) in a previous study. So far, potential drivers and ultimate causes of these findings have not been identified. We conducted a field study to investigate the connection between morphological divergence and polyunsaturated fatty acid (PUFA) composition of perch from six lakes across a gradient of DOC concentration. We expected a decrease in the prevalence of PUFAs, which are important for perch growth and divergence with increasing DOC concentrations, due to the restructuring effects of DOC on aquatic food webs. In general, rate of morphological divergence in perch decreased with increasing DOC concentrations. Proportions of specific PUFAs (22:6n-3, 18:3n-3, 20:5n-3, and 20:4n-6) identified to primarily contribute to overall differences between perch caught in clear and brown-water lakes tended to be connected to overall decline of morphological divergence. However, no overall significant relationship was found, indicating no severe limitation of essential fatty acids for perch inhabiting brown water lakes. We further broaden our approach by conducting a laboratory experiment on foraging efficiency of perch. Therefore, we induced pelagic and littoral phenotypes by differences in habitat-structure and feeding mode and recorded attack rate in a feeding experiment. Generally, fish were less efficient in foraging on littoral prey (Ephemeroptera) when visual conditions were degraded by brown water color. We concluded that browning water may have a strong effect on the forager's ability to find particular food resources, resulting in the reduced development of evolutionary traits, such as habitat- specific morphological divergence., Competing Interests: The authors have declared that no competing interests exist.

We modified the stable isotope mixing model MixSIR to infer primary producer contributions to consumer diets based on their fatty acid composition. To parameterize the algorithm, we generated a 'consumer-resource library' of FA signatures of Daphnia fed different algal diets, using 34 feeding trials representing diverse phytoplankton lineages. This library corresponds to the resource or producer file in classic Bayesian mixing models such as MixSIR or SIAR. Because this library is based on the FA profiles of zooplankton consuming known diets, and not the FA profiles of algae directly, trophic modification of consumer lipids is directly accounted for. To test the model, we simulated hypothetical Daphnia comprised of 80% diatoms, 10% green algae, and 10% cryptophytes and compared the FA signatures of these known pseudo-mixtures to outputs generated by the mixing model. The algorithm inferred these simulated consumers were comprised of 82% (63-92%) [median (2.5th to 97.5th percentile credible interval)] diatoms, 11% (4-22%) green algae, and 6% (0-25%) cryptophytes. We used the same model with published phytoplankton stable isotope (SI) data for δ13C and δ15N to examine how a SI based approach resolved a similar scenario. With SI, the algorithm inferred that the simulated consumer assimilated 52% (4-91%) diatoms, 23% (1-78%) green algae, and 18% (1-73%) cyanobacteria. The accuracy and precision of SI based estimates was extremely sensitive to both resource and consumer uncertainty, as well as the trophic fractionation assumption. These results indicate that when using only two tracers with substantial uncertainty for the putative resources, as is often the case in this class of analyses, the underdetermined constraint in consumer-resource SI analyses may be intractable. The FA based approach alleviated the underdetermined constraint because many more FA biomarkers were utilized (n < 20), different primary producers (e.g., diatoms, green algae, and cryptophytes) have very characteristic FA compositions, and the FA profiles of many aquatic primary consumers are strongly influenced by their diets.