Nutrient limitation of plant growth and forage quality in Arctic coastal marshes
Bibliographic record
Abstract
Summary Foraging by geese has led to vegetation loss in salt marshes along the Hudson Bay coast and lesser snow geese are increasingly grazing inland freshwater marshes. We determined whether different nutrients limit the growth of forage plants in the two habitats, and whether these differences affect the nutritional quality of vegetation available to geese at La Pérouse Bay, Manitoba. Results from fertilization experiments indicate that primary productivity in the salt marsh is both nitrogen and phosphorus limited, whereas the freshwater marsh is phosphorus limited. Total amounts of calcium, magnesium and potassium in above‐ground biomass per unit area showed similar differences in limitation. Leaves of preferred forage species have higher nutrient concentrations (nitrogen, phosphorus, calcium, potassium, magnesium, sodium) and lower C : N and C : P ratios than alternative forage. The main forage species in the salt marsh ( Puccinellia phryganodes ) has higher nutrient content per unit mass, for nitrogen, magnesium, calcium and sodium, than the major freshwater marsh species( Carex aquatilis ). The difference in nutritional quality of forage between the marshes is likely to have had consequences for goose fitness, and may have contributed to the reported declines in gosling survivorship and size. At moderate grazing intensities, seasonal growth of salt‐marsh forage is maintained by addition of nitrogen and, to a lesser extent, phosphorus from high numbers of goose faeces to swards. In contrast, the low densities and low phosphorus content of goose faeces in the phosphorus‐limited freshwater marsh mean that plants are unlikely to recover rapidly from the effects of grazing. As a consequence, the freshwater marsh is likely to become increasingly less productive as foraging intensifies. Nutrient gradients in vegetation across an ecotone and changes in foraging behaviour have resulted in adverse effects on both the growth rates of individuals and the population structure of a herbivore.
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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".