The dynamics of nitrogen movement in an Arctic salt marsh in response to goose herbivory: a parameterized model with alternate stable states
Bibliographic record
Abstract
Summary LPBN is a parameterized simulation model of flows of nitrogen (N) in an ecosystem of cyanobacteria, grass and grazers, based on the N dynamics of a grazed Puccinellia lawn in an intertidal marsh on Hudson Bay. This system shows two alternate stable states: (a) lawns that either support a foraging population of lesser snow geese, or are not grazed by geese; and (b) exposed saline sediments that support little or no vegetation. The model represents the flow of N from cyanobacterial fixation, the major N input into the system, to the geese that migrate in autumn; those that do not return represent the major N output from the system. We have modelled N fixation, the transformations of N in the soil, plant growth, lawn regeneration, and goose grazing and grubbing. The model simulates steady‐state flows of N similar to those observed in the field at zero and at moderate goose density, and it also simulates the transition to the state of zero plant biomass, a consequence of increased grubbing at high goose density. The simulated steady‐state flows are found to be more sensitive to changes in the parameters that describe N fixation and goose biology, than to similar changes in the parameters describing plant biology. Because the model shows the alternate stable states and the transition between them, with values for the state variables that are consistent with field data, we conclude that N dynamics are crucial in determining the stability of the real salt marsh‐goose system. The determining factor is the loss of the input of N from fixation when lawn area is reduced because the rate of goose grubbing exceeds that of plant re‐establishment.
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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 | 0.002 | 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".