Factors influencing vascular plant diversity on 22 islands off the coast of eastern North America
Bibliographic record
Abstract
Abstract Aim The influence of physiographic and historical factors on species richness of native and non‐native vascular plants on 22 coastal islands was examined. Location Islands off the coast of north‐eastern USA and south‐eastern Canada between 41° and 45° N latitude were studied. Island size ranges from 3 to 26,668 ha. All islands were deglaciated between 15,000 and 11,000 yr bp ; all but the four New Brunswick islands were attached to the mainland until rising sea level isolated them between 14,000 and 3800 yr bp . Methods Island species richness was determined from floras compiled or revised since 1969. Simple and multiple regression and rank correlation analysis were employed to assess the relative influence of independent variables on species richness. Potential predictors included island area, latitude, elevation, distance from the mainland, distance from the nearest larger island, number of soil types, years since isolation, years since deglaciation, and human population density. Results Native vascular plant species richness for the 22 islands in this study is influenced most strongly by island area, latitude, and distance from the nearest larger island; richness increases with island area, but decreases with latitude and distance from the nearest larger island as hypothesized. That a similar model employing distance from the mainland does not meet the critical value of P confirms the importance of the stepping‐stone effect. Habitat diversity as measured by number of soil types is also an important predictor of native plant species richness, but at least half of its influence can be attributed to island area, with which it is correlated. Two historical factors, years since deglaciation and years since isolation, also appear to be highly correlated with native species richness, but their influence cannot be separated from that of latitude for the present sample size. Non‐native vascular plant species richness is influenced primarily by island area and present‐day human population density, although human population density may be a surrogate for the cumulative effect of several centuries of anthropogenic impacts related to agriculture, hunting, fishing, whaling, tourism, and residential development. Very high densities of ground‐nesting pelagic birds may account for the high percentage of non‐native species on several small northern islands. Main conclusions Many of the principles of island biogeography that have been applied to oceanic islands apply equally to the 22 islands in this study. Native vascular plant species richness for these islands is strongly influenced by physiographic factors. Influence of two historical factors, years since deglaciation and years since isolation, cannot be assessed with the present sample size. Non‐native vascular plant species richness is influenced by island area as well as by human population density; human population density may be a surrogate for other anthropogenic impacts.
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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) | 0.000 | 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 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".