Advancing EDGE Zones: spatial priorities for the conservation of tetrapod evolutionary history
Bibliographic record
Abstract
Abstract The biodiversity crisis is set to prune the Tree of Life in a way that threatens billions of years of evolutionary history. To secure this evolutionary heritage along with the benefits it provides to humanity, there is a need to understand where in space the greatest losses are predicted to occur. We therefore present threatened evolutionary history mapped for all tetrapod groups, globally and within Biodiversity Hotspots, and identify priority regions of Evolutionarily Distinct and Globally Endangered (EDGE) species at both a grid cell and national level. We find that threatened evolutionary history peaks in Cameroon, whilst EDGE species richness peaks in Madagascar. We refined and advanced the 2013 EDGE Zone concept for spatially prioritising phylogenetic diversity using a novel complementarity procedure with uncertainty incorporated for 33,628 tetrapod species. This involved using extinction risk, phylogenetic, and spatial data to iteratively select areas with the highest accumulated threatened evolutionary history driven by unique species compositions. We identify 25 priority EDGE Zones, which are insufficiently protected and disproportionately exposed to high levels of human pressure. Together, the 25 EDGE Zones occupy 0.723% of the world’s surface but harbour one-third of the world’s threatened evolutionary history, half of which is endemic to these grid cells. They also contain part of the distribution of 918 EDGE tetrapod species, representing near one-third of all EDGE species, with 480 being endemic. Our tetrapod EDGE Zones highlight areas of immediate concern for researchers, practitioners, policymakers, and communicators looking to safeguard the Tree of Life.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".