Spatial dynamics of animal‐mediated nutrients in temperate waters
Bibliographic record
Abstract
Abstract Consumer‐mediated nutrient dynamics (CND), through which animals' metabolic waste products fertilize primary producers, drive variability in nutrient availability in tropical waters. This variability influences primary productivity and community functioning. Yet, examinations of CND as a driver of nutrient variability in temperate marine ecosystems are limited. Therefore, we assessed the existence and drivers of variation in CND in temperate waters at meso, small, and fine spatial scales. We quantified the occurrence of 48 fish and 92 macroinvertebrate taxa and measured in situ ammonium at 27 northeast Pacific rocky reefs for 3 yr and 16 kelp forests of varying density for 1 yr. Ammonium concentrations ranged from 0.01 to 2.5 μ M across rocky reefs separated by tens of kilometers. The relationship between animal abundance and ammonium among sites was mediated by water flow, where flood tides seemed to “wash away” the effect of nutrient regeneration by animals, although enrichment was possible on ebb tides. Ammonium concentration was significantly greater within than outside of kelp forests, a difference that increased with kelp biomass, tidal exchange, and, to a lesser degree, animal biomass. Caging experiments revealed that fine‐scale (~ 2 m) ammonium variability and nutrient enrichment were only possible under low‐flow conditions. Our results suggest that CND drives nutrient variability at scales ranging from two meters to over 20 km, acting on a finer scale than allochthonous nitrogen sources such as upwelling. Therefore, CND are implicated as a previously overlooked driver of spatial variation in primary productivity in temperate marine 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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 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".