Genetic Characterization of Periphyton Communities Associated with Selenium Bioconcentration and Trophic Transfer in a Simple Food Chain
Bibliographic record
Abstract
A major source of uncertainty in predicting selenium (Se) distribution in aquatic food webs lies in the enrichment factor (EF), the ratio of Se bioconcentration in primary producers and microorganisms relative to the concentration of Se in the surrounding water. It has been well demonstrated that EFs can vary dramatically among individual algal taxa, but data are lacking regarding the influence of periphyton community composition on EFs for a given geochemical form of Se. Therefore, the goals of this study were first to assess whether different periphyton communities could be established in aquaria with the same starting inoculum using different light and nutrient regimes, and second, to determine if the periphyton assemblage composition influences the uptake of waterborne Se (as selenite) and subsequent Se transfer to a model macroinvertebrate primary consumer. Periphyton biofilms were grown in aquaria containing filtered pond water (from Saskatoon, SK) spiked with approximately 20 μg Se/L (mean measured concentration 21.0 ± 1.2 μg Se/L), added as selenite. Five different light and nutrient regimes were applied to the aquaria (three replicates per treatment) to influence biofilm community development. After 6 weeks of biofilm maturation, 40 to 80 immature cultured snails (Stagnicola elodes) were added to each aquarium. The bacterial and algal members of the periphyton community were characterized by targeted metagenomic analyses before and after addition of snails to ensure the snails themselves did not significantly alter the biofilm community. Samples were collected for Se analysis of water, periphyton, and whole-body snail. The nutrient and light treatments resulted in substantially different compositions of the periphytic biofilms, with each being relatively consistent across replicates and throughout the study. Although the aqueous concentration of dissolved Se administered to treatments was constant, uptake by the different periphytic biofilms differed significantly. Both the low-light (61.8 ± 12.1 μg Se/g d.w.) and high-light (30.5 ± 4.7 μg Se/g d.w.) biofilms, which were found to have high proportions of cyanobacteria, contained statistically higher concentrations of Se relative to the other treatments. Furthermore, the concentration of Se in bulk periphyton was predictive of Se bioaccumulation in grazing snails but as an inverse relationship, opposite to expectations. The trophic transfer factor was inversely correlated with periphyton enrichment factor (r = -0.841). A number of different bacterial and algal taxa were correlated (either positively or negatively) with Se accumulation in periphyton biofilm and snails. Recent advancements in genetic methods make it possible to conduct detailed characterization of periphyton assemblages and begin to understand the influence that periphyton composition has on Se biodynamics in aquatic systems.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".