Beta diversity and factors that drive land-snail patterns in Jiangxi Province, People’s Republic of China
Bibliographic record
Abstract
Jiangxi Province is a biodiversity hotspot in the People’s Republic of China and has abundant land-snail species (247). Beta diversity is a key concept for understanding the functioning of ecosystems, the conservation of biodiversity, and the management of ecosystems. Here, the pattern of beta diversity for land snails in Jiangxi Province was analyzed. The results showed that the spatial turnover component was the main contributor to beta diversity, indicating that additional conservation efforts must target an increase in the number of protected areas, which should be spread across each one of the areas, to maximize the protection of species diversity. The nestedness component of diversity was always low, but there was a marked difference between microsnails, in which zero values occurred in 41.3% of all cases, and macrosnails, in which zero values occurred in only 2.7% of cases. There was a difference in the pattern of beta diversity between the two. The principal coordinate analysis showed a clear pattern with four groups in Jiangxi Province. In addition, we found significant effects of precipitation and altitude on overall beta diversity. These results will provide important basic information for the conservation of biodiversity in land snails.
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 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".