Prior selection prevents the loss of an ecosystem cycle during acidification
Bibliographic record
Abstract
Abstract Ecosystem processes vary temporally due to variation in environmental variables, such as when diurnal variation in sunlight causes diurnal cycles in net primary production. This variability can be characterized by its frequency and amplitude, used to define “normal” functioning of an ecosystem. Relatively little research has addressed how normal modes of variability, such as diurnal cycles, are lost or recovered, following anthropogenic stress. We conducted an aquatic mesocosm experiment to test whether prior application of environmental stress, in the form of moderate acidification, affected the diurnal cycle of dissolved oxygen when exposed to severe acidification. High-frequency data from sensor loggers deployed in 12 mesocosms showed that severe acidification caused a temporary loss of diurnal variation in dissolved oxygen concentration. However, pre-exposure to an acidic environment resulted in the persistence of the diurnal cycle. We hypothesize that pre-exposure shifted the community to acid tolerant genotypes and/or species of algae and other photosynthetic organisms. Our findings suggest that the stability of ecosystem cycles is intrinsically liked to the stress tolerance of the species assemblage.
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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 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".