The Trials and Tribulations of Grassland Restoration on Government Island
Bibliographic record
Abstract
Government Island is a roughly 3.25 square mile island located in the Columbia River northeast of the Portland Airport. Since 2021 Mosaic Ecology has worked with the Port of Portland to rehabilitate a 50-acre restored grassland site that sits just east of the I-205 bridge. The restoration area is a test field for creating future mitigation areas to offset development impacts on nesting bird habitats in nearby areas. Prescribed fire, the most easily recognized grassland management technique, is unavailable due to the constraints of a major freeway and airport. When Mosaic began managing the site invasive vegetation was beginning to overrun the area, including velvet grass (Holcus lanatus), Canada thistle (Cirsium arvense), and Himalayan blackberry (Rubus armeniacus). Coupled with the increase in invasive vegetation, a lack of disturbance has led to an overall reduction of species diversity, homogenization of vegetative size classes, and dense grass cover, all of which reduce the habitat quality for nesting grassland birds. Through a variety of management activities, including herbicide application and mowing, Mosaic staff has worked to “reset” a 25-acre portion of the restoration area, with the intent to reestablish a more resilient grassland community. This presentation will discuss the many logistical hurdles of large-scale restoration on an island, designing plant communities with invasive species management in mind, and the importance of including human initiated disturbance activities in the persistence of diverse grassland systems in the built environment.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".