Productivity begets less phylogenetic diversity but higher uniqueness than expected
Bibliographic record
Abstract
Abstract Aim The positive effect of primary productivity on animal species richness is one of the most conspicuous ecological features on Earth. However, less is known about the relationship between ecosystems primary productivity and the evolutionary history of biota. Here, we analyse how global primary productivity relates to the phylogenetic structure of vertebrate assemblages, and to the distribution of the most distinct lineages and recently diversified clades. Location Global. Taxon Amphibians, birds and mammals. Methods We calculated relative phylogenetic diversity (i.e. phylogenetic diversity corrected for species richness), standardized effect size of the richness of top 25% evolutionary distinct species and of top 25% species‐level lineage diversification rates. We related these three metrics to mean net primary productivity (NPP) at the global scale, and for each zoogeographic region. We also tested the influence of the spatial scaling of species pool on the overall analyses (global, hemispheric and zoogeographic regions‐based species pools). Results Phylogenetic diversity (corrected for species richness) of the three taxa decreases with NPP (in contrast with species richness) and varies considerably in space. High productivity sites harbour more closely related species than low productivity sites consistently across zoogeographic zones. However, the phylogenetically most distinct species are also found in high productivity sites, while the top most rapidly diversifying lineages are found in the least productive sites. Modifying the spatial extent of the species pool did not affect the results much. Conclusions Benign conditions in high productivity sites (a) result in denser niche packing and thus allow for the coexistence of many closely‐related species and (b) protect the persistence of evolutionary distinct species. Low productivity sites may harbour fewer, more distinct and temporarily more variable niches that allow maintenance of unique lineages for longer periods of time.
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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".