Riparian vegetation assemblages and associated landscape factors across an urbanizing metropolitan area
Bibliographic record
Abstract
While diverse, native riparian vegetation provides important functions, it remains unclear to what extent these assemblages can persist in urban areas, and under what conditions. We characterized forested riparian vegetation communities across an urbanizing metropolitan area and examined their relationships with surrounding land cover. We hypothesized that native and hydrophilic species assemblages would correlate with forest cover in the landscape. For each of 30 sites in the Portland—Vancouver metro area, we recorded vegetation at 1-cm intervals along 3 transects using the line-intercept method. Land cover was characterized at 2 scales: within 500 m of each site and across the entire watershed. Multivariate analyses were used to evaluate relationships between species composition and land cover patterns. A classification tree was created to determine landscape predictors of riparian community type. Results indicated a strong relationship between watershed land cover and vegetation diversity and structural complexity. Our hypothesis of native species association with landscape forest cover in urban riparian areas was supported, but we found no clear relationship between land cover and wetland indicator status. Our results suggest that high watershed forest cover (at least 15%) may enable the persistence of functionally diverse, native riparian vegetation communities in urban landscapes.
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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 | 0.002 |
| 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".