Rapid environmental degradation in a subarctic ecosystem influences resource use of a keystone avian herbivore
Bibliographic record
Abstract
1. Environmental degradation can change resource use strategies of animals and thereby affect survival and fitness. Arctic herbivores may be especially susceptible to the effects of such environmental change because their rapid growth rates demand high-quality forage, which may be limited as environmental conditions deteriorate. We studied the consequences of a trophic cascade, driven by Lesser Snow Goose (Chen caerulescens caerulescens) overgrazing on the south-west coast of Hudson Bay, Canada, which has caused tidal marsh (TM) degradation and the reduction in high-quality forage plants, on gosling growth and resource use. 2. We compared resource use and body size of goslings that inhabited tidal and freshwater marsh (FM) to determine how current foraging strategies influence growth and to test the hypothesis that during early growth goslings require and so consume high-quality TM plants, but that during later growth they may switch to foraging in lower-quality FM. 3. To investigate gosling resource use throughout growth, we measured once a week for 28 days the body size of goslings as well as stable isotope ratios (δ(34) S, δ(15) N and δ(13) C) in multiple tissues of goslings that were collected from both TM and nearby FM. We also measured the stable isotope ratios in forage plants sampled along transects and from gosling foreguts. We used an isotope-mixing model to determine the contribution of FM plants to gosling tissues. 4. Contrary to the proposed hypothesis, goslings inhabiting FM or TM primarily consumed FM plants during early growth. Furthermore, goslings that foraged extensively in FM had similar growth rates and grew to a similar size and body mass, as goslings that foraged in the degraded TM. However, goslings that currently inhabit freshwater or TM were significantly smaller than goslings that inhabited TM in the 1980s prior to habitat degradation. 5. Consequences of smaller overall body size include decreased survival and fecundity for arctic-nesting geese. The ability of phenotypically plastic responses to sustain persistence is limited by reaction norms and the extent of environmental change. Current research is assessing whether those limits have been reached in this system.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 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".