Mammal extinctions and the increasing isolation of humans on the tree of life
Bibliographic record
Abstract
Abstract A sixth great mass extinction is ongoing due to the direct and indirect effects of human pressures. However, not all lineages are affected equally. From an anthropocentric perspective, it is often purported that humans hold a unique place on Earth. Here, we show that our current impacts on the natural world risk realizing that expectation. We simulated species loss on the mammalian phylogenetic tree, informed by species current extinction risks. We explored how Homo sapiens could become isolated in the tree if species currently threatened with extinction disappeared. We analyzed correlates of mammal extinctions risks that may drive this isolation pattern. We show that, within mammals, and more particularly within primates, extinction risks increase with the number of known threat types, and decrease with geographic range size. Extinctions increase with species body mass, trophic level, and the median longitudinal extent of each species range in mammals but not within primates. The risks of extinction are frequently high among H. sapiens close relatives. Pruning threatened primates, including apes (Hominidae, Hylobatidae), from the tree of life will lead to our species being among those with the fewest close relatives. If no action is taken, we will thus not only lose crucial biodiversity for the preservation of Earth ecosystems, but also a key living reference to what makes us human.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".