Deconvoluting Thermodynamics from Biology in the Aquatic Food Web Model
Bibliographic record
Abstract
Abstract Bioaccumulation of hydrophobic pollutants in an aquatic food web is governed by exposure concentrations in sediment and water phases and by complex trophic interactions among the various species. We demonstrate that biological interactions and exposure from the chemical environment can be deconvoluted for aquatic food webs to allow clearer assessments of the role of thermodynamic drivers from the sediment and surface water phases. We first demonstrate the feasibility of this deconvolution mathematically for hypothetical food webs with 3 and 4 interacting species and for more realistic real-world food webs with >10 species of aquatic organisms (i.e., the freshwater lake food web in Western Lake Erie [ON, Canada] and the marine food web in New Bedford Harbor [MA, USA]). Our results show both mathematically (for the simple food webs) and computationally (for the more complex food webs) that a deconvoluted food web model parameterized for site-specific conditions can predict the bioaccumulation of polychlorinated biphenyls in aquatic organisms same as existing complex food web models. The merit of this approach is that once the thermodynamic and biological contributions to food web bioaccumulation are computed for an ecosystem, the deconvoluted model provides a relatively simple approach for calculating concentrations of chemicals in organisms for a range of possible surface water and sedimentary concentrations. This approach is especially useful for calculating bioaccumulation of pollutants from freely dissolved concentrations measured using passive sampling devices or predicted by fate and transport models. The deconvoluted approach makes it possible to develop regulatory guidelines for a set of surface water and sediment (or porewater) concentration combinations for a water body that is able to achieve a risk-based target for fish concentration. Environ Toxicol Chem 2021;40:2145–2155. © 2021 SETAC. Abstract Thermodynamic influences of surface water and porewater separated mathematically from complex food web interactions. Csw and Cpw = dissolved concentrations of the hydrophobic organic contaminants in surface water and sediment porewater, respectively; fsw and fpw = fractional influence of surface water and porewater, respectively; BAFfish,A = bioaccumulation factor for Fish A.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".