Spatiotemporal Variation in Cicada Diversity and Distribution, and Tree Use by Exuviating Nymphs, in East Asian Tropical Reef-Karst Forests and Forestry Plantations
Bibliographic record
Abstract
Abstract Spatiotemporal variation in the species composition, relative abundance, and plant use by cicada nymphs were studied among continuous and fragmented forests and human-modified forestry plantations upon an uplifted reef-karst substrate in tropical East Asia. Nymphal emergence was concentrated in the rainy season but tended to begin earlier, end later, or both, on plantations. Species abundances fluctuated over time and among the types of forests, with greater variation in plantations and fragmented forests. Seven cicada species were present, but the overall similarity in species composition was low among the forest types. Higher mean numbers of species and mean abundances occurred on plantations than in fragmented and continuous forests, but the species heterogeneity was higher in continuous forests and lowest on plantations. Exuviae were found at various heights that were correlated positively with the abundance of exuviae and negatively with the diameter at breast height of trees, whereas coefficients of variation in the height distribution among trees were not correlated with the abundance of exuviae. The plant-use breadth was widest in the cicadas Chremistica ochracea (Walker) and narrowest in Cryptotympana takasagona. Kato, Phtypleura takasagona Matsumura, and Euterpnosia koshunensis Kato, with the other species intermediate, corresponding with their relative abundance. Among-species overlap was generally higher in the continuous forests but declined in forest fragments and plantations. Our results indicated that fragmenting tropical primary forests and creating plantations may generate higher richness and abundance of annual cicadas, but risk the loss of rare or endemic species that show a greater preference for tree species of the primary forests.
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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) | 0.001 | 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".