Tree phylogenetic diversity supports nature’s contributions to people, but is at risk from human population growth
Bibliographic record
Abstract
ABSTRACT There is growing evidence for a link between biodiversity and ecosystem function, and for a correlation between human population and the species diversity of plants and animals in a region. Here, we suggest these relationships might not be independent. Using a comprehensive phylogeny of southern African trees and structural equation modelling, we show that human population density correlates with tree phylogenetic diversity and show that this relationship is stronger than the correlation with species richness alone. Further, we demonstrate that areas high in phylogenetic diversity support a greater diversity of ecosystem goods and services, indicating that the evolutionary processes responsible for generating variation among living organisms are also key to the provisioning of nature’s contributions to people. Our results raise the intriguing possibility that the history of human settlement in southern Africa may have been shaped, in part, by the evolutionary history of its tree flora. However, the correlation between human population and tree diversity generates a conflict between people and nature. Our study suggests that future human population growth may threaten the contributions to people provided by intact and phylogenetically diverse ecosystems.
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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 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".