Speciation and endemism under the model of island biogeography
Bibliographic record
Abstract
Speciation has been considered as a primary process contributing to species diversity, but its contribution to the diversity of local communities has not been fully appreciated. Based on the theory of classic island biogeography, we derived a model for the number of endemic species as a function of the processes of immigration, speciation, and extinction. The model shows that species endemism on an island is proportional to speciation rate but decreases with the sum of immigration and extinction rates (i.e., the species turnover rate). The model predicts that the contribution of immigration to species richness in local communities decreases with time, while the contribution of speciation to local richness increases with time. It further shows that only when the speciation rate is larger than half of the extinction rate can new species added from speciation eventually surpass those added from immigration. We conclude that, although the model leads to an apparent positive relationship between percentage endemism and species diversity on an island, this positive endemics-diversity relationship is not necessarily driven by speciation.
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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 | 0.000 | 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".