Time since first naturalization is key to explaining non‐native plant invasions on islands
Bibliographic record
Abstract
Abstract Aim Investigating the extent of insular invasions by non‐native species (i.e., the number of islands they occupy) is central to island conservation. However, interrelationships among plant life history traits, naturalization histories, and island characteristics in determining island occupancy by non‐native plant species are poorly understood. We investigated whether island occupancy by different non‐native plant species declines in relation to their year of first naturalization and whether periods of first naturalization differ among growth forms, dispersal modes, and biogeographic origins. Then, we asked if non‐native plants that naturalized more recently occur more frequently on islands that are large, less isolated, and close to urban areas. We contrasted trends across growth forms, dispersal modes, and biogeographic origins. Location 264 offshore islands in northern Aotearoa New Zealand. Taxa Vascular plant species. Methods We combined field surveys and published data for 767 non‐native plant species on the islands. We categorized each species according to its growth form ( n = 3), dispersal mode ( n = 4) and biogeographic origin ( n = 5) and identified its year of first naturalization in Aotearoa New Zealand. We tested our hypotheses using ANCOVA and generalized linear models (GLMs). Results There were similar declines in island occupancy in relation to the year of first naturalization in Aotearoa New Zealand across all trait and biogeographic origin categories. First naturalization times of herbaceous species, those with unspecialized dispersal modes, and those originating from Eurasia and the Mediterranean basin were disproportionately earlier than other categories. Non‐native plants with more recent first naturalization occur more frequently on large islands close to urban areas, but not on less isolated ones. Relationships with island characteristics did not differ among trait and biogeographic origin categories. Main Conclusions Overall, time of first naturalization was more important than trait and biogeographic origin categories in explaining non‐native plant invasion patterns on islands. Since there were similar relationships between island occupancy and the year of first naturalization in Aotearoa New Zealand for all categories, management bodies should focus on non‐native plant species of trait and biogeographic origin categories that have naturalized recently (e.g., woody species from other regions within Oceania), and on large islands close to urban areas. Introduction and naturalization histories provide essential context for interpreting the role of plant traits and biogeographic origin in understanding plant invasions on islands.
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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 | 0.001 |
| 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".