Microbial and animal nutrient limitation change the distribution of nitrogen within coupled green and brown food chains
Bibliographic record
Abstract
Numerous biotic mechanisms can control ecosystem nutrient cycling, but their full incorporation into ecological models or experimental designs can result in inordinate complexity. Including organismal nutrient limitation in models of highly dimensional systems (i.e., those with many nutrient pools/species) presents a critical challenge. We evaluate the importance of explicitly considering microbial and animal nutrient limitation to predict ecosystem nitrogen cycling across plant-based and detritus-based food chains. We investigate how eight factorial scenarios of microbial, herbivore, and microbi-detritivore (i.e., omnivores consuming microbes and detritus) nitrogen or carbon limitation alter the stocks and flows of nitrogen in an ecosystem model. We used a combination of partial derivatives of model equilibrium solutions and numerical simulations using randomly drawn parameter sets to explore the impact of each nutrient limitation scenario on nutrient stocks and flows. We show that switching microbes, herbivores, or microbi-detritivores from nitrogen to carbon limitation consistently altered the ecosystem response to changes in inorganic nitrogen supply, plant C:N ratio, and microbial C:N ratio. Organism nutrient limitation changed ecosystem nitrogen flows by altering the feedbacks between the abiotic and biotic pools. For example, microbi-detritivore nutrient limitation determined whether the microbial response to changes in inorganic nitrogen supply and C:N ratios was dependent on the size of detrital carbon or detrital nitrogen pool. Such correlated responses among biotic and abiotic pools set up a network of predictable changes in ecosystem properties sensitive to organism nutrient limitation. Scenarios with microbial limitation were generally sufficient to capture the suite of ecosystem responses to increasing inorganic nitrogen supply, while scenarios with animal limitation added new behavior whenever C:N ratios changed. We make the case for explicitly considering both microbial and animal nutrient limitation when predicting the flow and distribution of nitrogen across green and brown food chains.
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How this classification was reachedexpand
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) | 0.000 | 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 teacher head, 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".