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A Fatty Acid Based Bayesian Approach for Inferring Diet in Aquatic Consumers.

Galloway AW, Brett MT, Holtgrieve GW, Ward EJ, Ballantyne AP, Burns CW, Kainz MJ, Müller-Navarra DC, Persson J, Ravet JL, Strandberg U, Taipale SJ, Alhgren G - PLoS ONE (2015)

Bottom Line: 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 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.

View Article: PubMed Central - PubMed

Affiliation: Oregon Institute of Marine Biology, University of Oregon, Charleston, Oregon, 97420, United States of America.

ABSTRACT
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.

No MeSH data available.


Non-metric multi-dimensional scaling (NMDS) plots of the FA profiles used (n = 26 FA; Euclidean distance).One outlier cryptophyte profile is removed from the NMDS plots for clarity, but this outlier was included in the FA-based analyses. A) Algal diets (filled symbols) and Daphnia fed those diets (open symbols) and associated resource polygons for each treatment group (stress = 0.09). B) The real Daphnia in the ‘consumer-resource library’ (no algal diets), with 100 ‘pseudo-Daphnia’ used in the analyses (see Methods; stress = 0.07).
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pone.0129723.g001: Non-metric multi-dimensional scaling (NMDS) plots of the FA profiles used (n = 26 FA; Euclidean distance).One outlier cryptophyte profile is removed from the NMDS plots for clarity, but this outlier was included in the FA-based analyses. A) Algal diets (filled symbols) and Daphnia fed those diets (open symbols) and associated resource polygons for each treatment group (stress = 0.09). B) The real Daphnia in the ‘consumer-resource library’ (no algal diets), with 100 ‘pseudo-Daphnia’ used in the analyses (see Methods; stress = 0.07).

Mentions: The phytoplankton and Daphnia data compiled for this study show different phytoplankton groups have very distinct FA composition and the FA profiles of Daphnia are strongly influenced by their diets (Fig 1, also see Supporting Information, S1 Table). Daphnia that consumed diatoms, green algae and cryptophytes had FA profiles that were strongly statistically associated with their diets (i.e., r2 = 0.87 ± 0.04), but weakly associated with conspecifics consuming alternative diets (i.e., r2 = 0.19 ± 0.18). The diatom diets used in our experiments were characterized by high proportions of the FAs 14:0, 16:2ω7, 16:3ω4, 20:5ω3, and especially 16:1ω7. Furthermore, Daphnia that consumed diatoms were characterized by high proportions of these same fatty acids. Green algae, and the Daphnia that consumed green algae, were characterized by high proportions of 16:2ω6, 16:3ω3, 16:4ω3, and especially 18:1ω9, 18:2ω6 and 18:3ω3. Both cryptophytes, and the Daphnia that consumed cryptophytes, were enriched with 18:3ω3, 18:4ω3 and 20:5ω3. Despite these similarities, Daphnia generally had more 20:4ω6 and 20:5ω3, and less 22:5ω6 and 22:6ω3 than their algal diets.


A Fatty Acid Based Bayesian Approach for Inferring Diet in Aquatic Consumers.

Galloway AW, Brett MT, Holtgrieve GW, Ward EJ, Ballantyne AP, Burns CW, Kainz MJ, Müller-Navarra DC, Persson J, Ravet JL, Strandberg U, Taipale SJ, Alhgren G - PLoS ONE (2015)

Non-metric multi-dimensional scaling (NMDS) plots of the FA profiles used (n = 26 FA; Euclidean distance).One outlier cryptophyte profile is removed from the NMDS plots for clarity, but this outlier was included in the FA-based analyses. A) Algal diets (filled symbols) and Daphnia fed those diets (open symbols) and associated resource polygons for each treatment group (stress = 0.09). B) The real Daphnia in the ‘consumer-resource library’ (no algal diets), with 100 ‘pseudo-Daphnia’ used in the analyses (see Methods; stress = 0.07).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4482665&req=5

pone.0129723.g001: Non-metric multi-dimensional scaling (NMDS) plots of the FA profiles used (n = 26 FA; Euclidean distance).One outlier cryptophyte profile is removed from the NMDS plots for clarity, but this outlier was included in the FA-based analyses. A) Algal diets (filled symbols) and Daphnia fed those diets (open symbols) and associated resource polygons for each treatment group (stress = 0.09). B) The real Daphnia in the ‘consumer-resource library’ (no algal diets), with 100 ‘pseudo-Daphnia’ used in the analyses (see Methods; stress = 0.07).
Mentions: The phytoplankton and Daphnia data compiled for this study show different phytoplankton groups have very distinct FA composition and the FA profiles of Daphnia are strongly influenced by their diets (Fig 1, also see Supporting Information, S1 Table). Daphnia that consumed diatoms, green algae and cryptophytes had FA profiles that were strongly statistically associated with their diets (i.e., r2 = 0.87 ± 0.04), but weakly associated with conspecifics consuming alternative diets (i.e., r2 = 0.19 ± 0.18). The diatom diets used in our experiments were characterized by high proportions of the FAs 14:0, 16:2ω7, 16:3ω4, 20:5ω3, and especially 16:1ω7. Furthermore, Daphnia that consumed diatoms were characterized by high proportions of these same fatty acids. Green algae, and the Daphnia that consumed green algae, were characterized by high proportions of 16:2ω6, 16:3ω3, 16:4ω3, and especially 18:1ω9, 18:2ω6 and 18:3ω3. Both cryptophytes, and the Daphnia that consumed cryptophytes, were enriched with 18:3ω3, 18:4ω3 and 20:5ω3. Despite these similarities, Daphnia generally had more 20:4ω6 and 20:5ω3, and less 22:5ω6 and 22:6ω3 than their algal diets.

Bottom Line: 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 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.

View Article: PubMed Central - PubMed

Affiliation: Oregon Institute of Marine Biology, University of Oregon, Charleston, Oregon, 97420, United States of America.

ABSTRACT
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.

No MeSH data available.