Taxonomic and phylogenetic diversity of vascular plants at Ma’anling volcano urban park in tropical Haikou, China: Reponses to soil properties
Bibliographic record
Abstract
Anthropogenic processes and socio-economic factors play important roles in shaping plant diversity in urban parks. To investigate how plant diversity of Ma' anling urban volcano park in Hainan Province, China respond to these factors, we carried out a field investigation on the taxonomic and phylogenetic diversity of vascular plants and soil properties in this area. We found 284 species of vascular plants belonging to 88 families and 241 genera, which included 194 native species, 23 invasive species, 31 naturalized species, 40 cultivars, and 4 rare / endangered plant species. Tree composition and richness significantly varied between different vegetation formations (plantation, secondary forest, and abandoned land). Plant species richness and community composition were significantly affected by elevation (El), soil water content (WC), total soil nitrogen (TN) and soil organic matter (SOM). There were significant diversity differences between plantations and abandoned lands, but not between the plantations and secondary forests. The flora in the study site was tropical in nature, characterized by pantropic distributions. Compared to adjacent areas, floristic composition in the study site was most similar to that of Guangdong, followed by that of Vietnam. Our study revealed the diversity patterns of volcanic plants and provided the basis for future planning of plant conservation, such as preserving plant species, maintaining plant habitats, and coordinating plant management in this region.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 source (direct Gemma or distilled Codex), 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".