Data and code from: Global change affects large herbivore forage biomass through gradual successional shifts and abrupt disturbances
Bibliographic record
Abstract
Forage availability is a key factor regulating large herbivore populations. Global changes in land use and climate may affect the spatiotemporal distribution of forage across the ranges of large herbivores, especially in mountain ecosystems. We test two synergistic hypotheses for how landscape and climate changes from 2001 to 2023 have affected forb and graminoid biomass at the peak of the growing season within and across ecoregions of the eastern slopes of the Rocky Mountains in Alberta, Canada. The successional change hypothesis posits that the encroachment of woody vegetation into previously herbaceous communities has reduced forage biomass. The disturbance hypothesis proposes that abrupt community shifts caused by fire and timber harvesting have increased forage biomass. We used remote sensing to quantify temporal changes in land cover and disturbances, NDVI greenness and phenology indices, and spring climate. We then used in-situ vegetation data to parameterize generalized linear and gradient boosted regression tree models of forb and graminoid biomass to predict annual peak forb and graminoid biomass. We found that herbaceous land cover declined while shrub and forest area increased, and the percent of annual biomass within herbaceous areas declined from woody encroachment. Disturbance effects varied, with rising forage biomass in conjunction with increased area of logged forests in the foothills ecoregion, while burned areas declined and had a reduced contribution to the percent of annual biomass. We found that spring became warmer across the study area and ended earlier in the alpine, suggesting the effects of long-term climatic shifts may be strongest at higher ecoregions. Disturbance frequency, succession, and climate together shaped forage biomass in space and time. Increased prescribed fire and other ecological restoration actions may be needed to ensure that shifts in forage biomass do not threaten large herbivore persistence in the face of global change.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.118 | 0.075 |
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".