Species associations of congeneric species in a tropical seasonal rain forest of China
Bibliographic record
Abstract
Abstract: In tropical plant communities with diverse species, many congeners are found to coexist. Do environment or biotic interactions structure the coexistence of congeners in tropical forest communities? In this paper, we aimed to disentangle the effect of environment (first-order effects) and species interactions (second-order effects) on the spatial distributions of tree species. We used a classification scheme and torus-translation to test the first-order interaction of 48 species from 17 genera in a fully mapped 20-ha dipterocarp tropical seasonal rain-forest plot in Xishuangbanna, south-west China. Then we used heterogeneous Poisson null models to reveal significant uni- and bivariate second-order interactions. The results demonstrated that (1) 34 of the 48 studied species showed a significant relation with at least one topographic variable. This confirmed that topographical heterogeneity is important for distribution of these congeners. Spatial segregation (36.6%) and partial overlap (34.8%) were the most common bivariate association types in Xishuangbanna plot, which indicated first-order effects (environment) were strong. (2) For small-scale associations, 51% saplings (1 to ≤ 5 cm) (68.8% for large trees with dbh > 5 cm) of the species showed non-significant associations. For large-scale associations, 61.6% saplings (81.2% for large trees) of the species showed non-significant associations. Lack of significant species interactions provides evidence for the unified neutral theory. In conclusion, both environment and biotic interactions structure congeneric species' coexistence in tropical seasonal rain forest in this region.
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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 | 0.001 |
| 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 | 0.001 |
| 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 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".