A lattice-automaton bioturbation simulator with coupled physics, chemistry, and biology in marine sediments (eLABS v0.2)
Why this work is in the frame
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Bibliographic record
Abstract
Abstract. Seawater–sediment interaction is a crucial factor in carbon and nutrient cycling on a wide range of spatial and temporal scales. This interaction is mediated not just through geochemistry but also via biology. Infauna vigorously mix sediment particles, enhance porewater–seawater exchange, and consequently, facilitate chemical reactions. In turn, the ecology and activity of benthic fauna are impacted by their environment, amplifying the sensitivity of seawater–sediment interaction to environmental change. However, numerical representation of the bioturbation of sediment has often been treated simply as an enhanced diffusion of solutes and solids. Whilst reasonably successful in representing the mixing of bulk and predominantly oxic marine sediments, the diffusional approach to bioturbation is limited by a lack of environmental sensitivity. To better capture the mechanics and effects of sediment bioturbation, we extend a published bioturbation model (Lattice-Automaton Bioturbation Simulator; LABS) by adopting a novel method to simulate realistic infaunal behavior that drives sediment mixing. In this new model (extended LABS – eLABS), simulated benthic organism action is combined with a deterministic calculation of water flow and oxygen and organic matter concentration fields to better reflect the physicochemical evolution of sediment in response to bioturbation. The predicted burrow geometry and mixing intensity thus attain a dependence on physicochemical sedimentary conditions. This interplay between biology, chemistry, and physics is important to mechanistically explain empirical observations of bioturbation and to account for the impact of environmental changes. As an illustrative example, we show how higher organic rain can drive more intense sediment mixing by “luring” benthic organisms deeper into sediments, while lower ambient dissolved oxygen restricts the oxic habitat depth and hence tends to reduce bulk mixing rates. Our model, with its oxygen and food availability controls, is a new tool to interpret the trace fossil record, e.g., burrows, as well as to explore biological engineering of past marine environments.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it