Fading indirect effects in a warming arctic tundra
Bibliographic record
Abstract
Abstract Indirect interactions in food webs can strongly influence the net effect of global change on ecological communities yet they are rarely quantified and hence remain poorly understood. Using a 22-year time series, we investigated climate-induced and predator-mediated indirect effects on grazing intensity in the tundra food web of Bylot Island, which experienced a warming trend over the last two decades. We evaluated the relative effects of environmental parameters on the proportion of plant biomass grazed by geese in wetlands and examined the temporal changes in the strength of these cascading effects. Migrating geese are the dominant herbivores on Bylot Island and can consume up to 60% of the annual production of wetland graminoids. Spring North Atlantic Oscillation, mid-summer temperatures and summer abundance of lemmings (prey sharing predators with geese) best-explained annual variation in grazing intensity. Goose grazing impact increased in years with high temperatures and high lemming abundance. However, the strength of these indirect effects on plants changed over time. Grazing intensity was weakly explained by environmental factors in recent years, which were marked by a sharp increase in plant primary production and steady decrease in grazing pressure. Indirect effects do not seem to be reversing the direct positive effect of warming on wetland plants. We suggest that cascading effects on plants may lag considerably behind direct effects in vertebrate dominated arctic communities, especially where key herbivore populations are strongly affected by factors outside of the Arctic.
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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 | 0.001 |
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".