Socio-Ecological Effects on the Patterns of Non-native Plant Distributions on Hainan Island
Bibliographic record
Abstract
Non-native plants spread to recipient areas via natural or human-mediated modes of dispersal, and, if the non-native species are invasive, introduction potentially causes impacts on native plants and local ecosystems as well as economic losses. Therefore, we studied the diversity and distributional patterns of non-native plant species diversity in the tropical island province of Hainan, China and its relationships with environmental and socioeconomic factors by generating a checklist of species and subsequently performing an analysis of phylogenetic diversity. To generate the checklist, we began with the available, relevant literature representing 19 administrative units of Hainan and determined the casual, naturalized, or invasive status of each species by conducting field surveys within 14 administrative units. We found that non-native plants of Hainan comprise 77 casual species, 42 naturalized species, and 63 invasive species. Moreover, we found that non-native plant species had diverse origins from North and South America, Africa, and Asia and that the most common species across administrative areas belong to the plant families Asteraceae and Fabaceae. Moreover, the numbers of non-native species distributed in the areas of Hainan bording the coast arer greater than those within interior areas of the province. Among the coastal areas, Haikou has the highest species richness and, simultaneously, the highest values for significantly, positively correlated predictor variables, population and GDP (R 2 = 0.60, P < 0.01; R 2 = 0.64, P < 0.01, respectively). In contrast, the landlocked administrative units of Tunchang and Ding’an have the smallest number of non-native species, while their populations are less than a quarter of that of Haikou and their GDP less than one tenth. Among natural environmental variables, we determined that the number of non-native species had the strongest correlation with the minimum temperature in the coldest month, which predicts a smaller number of non-native species. Additionally, non-native species are primarily distributed in urban and rural built-up areas and agricultural areas; areas that are dominated by human activities. Overall, our study provides a working checklist of the non-native plants of Hainan as well as a theoretical framework and reference for the control of invasive plants of the province.
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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 | 0.001 | 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".