Rapid riparian ecosystem decline in Rocky Mountain National Park
Bibliographic record
Abstract
Understanding the drivers of ecosystem collapse is critical for resource management, particularly for protected areas mandated to preserve biodiversity. In Rocky Mountain National Park, Colorado, tall willows (Salix spp.) dominated riparian vegetation, and a beaver-willow state was the natural ecosystem type in the Colorado River headwaters. However, willows comprise a portion of elk diets and are a preferred food for recently introduced moose, and the vegetation structure has changed dramatically since the early 2000s. To assess ecosystem changes, we analyzed time-series data on willow height from 1997 to 2021 inside and outside 3 exclosures built to exclude ungulates, area of tall willows in 1999 and 2019, area of open water from 1953 to 2019, vegetation composition in 1998 and 2021, groundwater depth from 1996 to 2021, surface water flow from 1953 to 2023, and climate from 1950 to 2023. Tall willow coverage and open water area declined by >90% from 1999 to 2019. Willow height outside the ungulate exclosures declined by more than 75% since the 1990s; yet, within exclosures that were formerly browsed, willow height increased by up to 500%. Tall willow communities have largely been replaced by grasslands. Browsing by elk and moose likely played a pivotal role in triggering a collapse of the beaver-willow state and the formation of an alternative moose-elk-grassland state that appears stable and may be difficult to reverse without direct human action. Restoration efforts will depend on a reduction in herbivory and reconnection of the river with its floodplain.
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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) | 0.001 | 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".