Carrying Capacity of Wetland Habitats Used by Breeding Greater Snow Geese
Bibliographic record
Abstract
Because geese can damage their arctic breeding habitats through overgrazing, there is debate about limiting the rapid growth of the greater snow goose (Chen caerulescens atlantica) population and setting a population goal. To answer these questions, we assessed the nutritional carrying capacity of freshwater wetland habitats for breeding greater snow geese at the Bylot Island colony, Nunavut, Canada, Specifically, we (1) mapped the different types of wedands on the island; (2) estimated net aboveground primary production of these habitats; (3) compared total food availability with predicted total food requirements of the current population; and (4) validated our predictions of plant biomass consumed by comparing them to the intensity of goose grazing measured. Freshwater wetlands represented 173 ± 6 km 2 or 11% of the total area of the south plain of Bylot Island. Streams and wet polygons were the most important habitats in terms of availability of suitable forage plants for geese. The average net above-ground primary production ranged from 21.0 ± 4.6 along lakes to 46.0 ± 9.8 g/m 2 in polygon channels. We estimated the total food supply available for geese in wetlands at 2,625 ± 461 tons in 1997 but only 1,247 ± 473 tons in 1996, a year of low plant production. We predicted a summer food requirement for goslings at 8.1 ± 0.6 kg/bird, for breeding adults at 7.9 ± 2.3, and for nonbreeding adults at 4.7 ± 1.5, and we predicted the total summer food requirements of the goose population at 1,201 ± 160 tons. The predicted amount of biomass removed (32 ± 7%) agreed well with the actual amount of biomass removed measured in mid-August (39 ± 11%) in 1997, but not in 1996 (67 ± 27% vs 26 ± 17%, respectively), possibly because the goose population was lower that year due to poor breeding success. In 1997, the goose population was at 46 ± 10% of the theoretical short-term carrying capacity (341,000 geese) of the wetlands of Bylor Island. We recommend keeping the goose population below this theoretical carrying capacity.
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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 | 0.001 | 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) | 0.001 | 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 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".