Rates, patterns, and drivers of tree reinvasion 15 years after large‐scale meadow‐restoration treatments
Bibliographic record
Abstract
Tree encroachment threatens the biodiversity and ecological functioning of grasslands worldwide. Reversing effects of encroachment requires not only removing trees, but limiting subsequent invasions, which can stall grassland reassembly. We quantified rates and patterns of conifer reinvasion of mountain grasslands (meadows) in western Oregon, 7 and 15 years after experimental tree removal with or without burning. We assessed frequency (percentage of 100 m 2 subplots) and density of reinvading trees in six 1‐ha plots as a function of burn treatment, abundance in the adjacent forest (a proxy for seed availability), and distance to or orientation of forest edges. After 15 years, frequency and density of colonists varied widely among plots (24–57% of subplots and 60–250 trees/ha, respectively), but burning had no effect on either measure. Abies grandis , which dominated adjacent forests, was the principal invader. Colonization by less‐common Pinus contorta and A. procera was correlated with species' density and basal area in adjacent forests, suggesting that establishment was seed limited. Annualized rates of invasion were similar between early and late sampling intervals (9–10/trees/ha). Establishment was generally greater along the forested edges of plots (0–10 m) than in the core (10–50 m). Prominence of shade‐tolerant A. grandis along northerly‐facing edges suggests strong microclimatic controls on establishment. In sum, tree removal, with or without prescribed fire, is successful in reversing effects of conifer encroachment. Despite abundant seed rain, reinvasion is slow and spatially restricted. Periodic hand removal of colonizing trees, while they are small, can be done efficiently and economically.
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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".