Long-term aspen dynamics, trophic cascades, and climate in northern Yellowstone National Park
Bibliographic record
Abstract
We report long-term patterns of quaking aspen (Populus tremuloides Michx.) recruitment for five ungulate exclosures in the northern ungulate winter range of Yellowstone National Park. Aspen recruitment was low (<3 aspen·ha−1·year−1) in the mid-1900s prior to exclosure construction due to herbivory by Rocky Mountain elk (Cervus elaphus Linnaeus, 1758) but increased more than 60-fold within 25 years after exclosure construction despite a drying climatic trend since 1940. Results support the hypothesis that long-term aspen decline in Yellowstone’s northern range during the latter half of the 20th century was caused by high levels of ungulate herbivory and not a drying climate. Gray wolves (Canis lupus Linnaeus, 1758) were reintroduced during 1995–1996. For the period 1995–2012, we summarized annual predator–prey ratios, ungulate biomass, and drought severity. The average density of young aspen increased from 4350 aspen·ha−1 in 1997–1998 to 8960 aspen·ha−1 in 2012; during the same time period, those >1 m in height increased over 30-fold (from 105 to 3194 aspen·ha−1). Increased heights of young aspen occurred primarily from 2007 to 2012, a period with relatively high predator–prey ratios, declining elk numbers, and decreasing browsing rates. Consistent with a re-established trophic cascade, aspen stands in Yellowstone’s northern range have increasingly begun to recover.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".