A neutral‐metabolic theory of latitudinal biodiversity
Bibliographic record
Abstract
Abstract Aim Latitudinal gradients of species richness represent Earth's first‐order biodiversity pattern. Most species groups display a near‐monotonic decline in richness from the equator to the poles, yet there exists little mechanistic theory to derive such patterns from first principles. Here we integrate two key advances – neutral theory and the metabolic theory of ecology – to reconstruct global species richness gradients and test underlying causes. Location Simulated global meta‐community. Methods We constructed a spatially explicit global meta‐community with constant per capita rates of disturbance, speciation and dispersal. No gradient emerged in this neutral base model. Focusing on the oceans as a model system, we added a water temperature gradient of 0–30°C that independently affected rates of community turnover and speciation based on established metabolic scaling laws. We also added a gradient in habitat area that roughly parallels the observed decrease in ocean area from tropical to polar waters. Results Thermal effects on the community turnover rate caused a transient latitudinal gradient that ultimately disappeared. Thermal effects on speciation produced a dynamically stable but relatively weak gradient. Increasing habitat area towards the equator in combination with thermal effects on speciation rate produced a more realistic gradient that emerged from the combined effects of species–area and species–energy theory. Main conclusions This reasonably simple model provides a platform to explore support for processes underpinning large‐scale biodiversity gradients, and the ability of prominent ecological theories, independently or in combination, to capture them.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".