Patterns of vegetation change and the recovery potential of degraded areas in a coastal marsh system of the Hudson Bay lowlands
Bibliographic record
Abstract
Summary In recent decades, foraging by increasing numbers of lesser snow geese has led to loss of vegetation and changes in soil conditions in marshes on the Hudson Bay coast. Changes in species composition were recorded in areas unprotected from goose foraging and in exclosures of varying age (5–15 years) erected in intact swards and on bare sediments where foraging had occurred at La Pérouse Bay, Manitoba. In the supratidal marsh, plants failed to establish naturally in either open or exclosed (15 years) plots in bare areas. In moist intertidal soils, vegetative fragments of the asexual speciesPuccinellia phryganodesreadily established and formed a mat in exclosures (5 years). Changes in species assemblages occurred over 11 years in exclosed and adjacent open plots in intertidal and supratidal marshes. Loss of vegetation cover and species richness, particularly dicotyledonous species, and the reversion of later successional plant assemblages to earlier successional assemblages occurred in open plots. In the absence of foraging, late successional graminoids and willow species replaced early successional graminoids. Late successional grasses of the upper intertidal marsh died when transplanted into degraded soils but still survived after one season in control plots, suggesting that an early successional template is needed for establishment. In the absence of goose foraging, natural re‐vegetation by clonal propagation can occur only where edaphic conditions are suitable. Within exclosures, vegetation changes resemble those in undamaged areas where goose foraging pressure is still moderate. We propose a state and transition model for vegetation change in the system based on succession patterns, alternative vegetation states and geomorphological events.
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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 | 0.001 |
| Scholarly communication | 0.001 | 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".