Species richness of both native and invasive aquatic plants influenced by environmental conditions and human activity
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Invasive plants alter community structure, threatening ecosystem function and biodiversity, but little information is available on whether invasive species richness responds to environmental conditions in the same way that richness of native plants does. We surveyed submerged and floating-leaved plants in 99 Connecticut (northeast USA) lakes and ponds, collecting quantitative data on abundance and frequency. We used multiple linear and logistic regression to determine which environmental conditions were correlated with species richness of invasive and native plants. Independent variables included lake area, maximum depth, pH, alkalinity, conductivity, phosphorus concentration, productivity, and dominance (the proportional abundance of the most abundant and frequently found species), plus two estimates of human activity. Species richness of both native and invasive richness was correlated with alkalinity and human activity. Native richness also increased with water clarity, lake area, and productivity; invasive species richness also rose with pH. We found no evidence that richness of one group affected richness of the other. We also investigated patterns of dominance and found that native plants were as likely to become dominant as invasive species. Dominance occurred overwhelmingly in shallow lakes with high productivity.
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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) | 0.000 | 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 it