Extinction risk of North American seed plants elevated by climate and land‐use change
Bibliographic record
Abstract
Summary Climate and land‐use change are expected to substantially alter future plant species distributions leading to higher extinction rates. However, little is known about how plant species ranges, richness and phylogenetic diversity of continents will be affected by these dynamics. We address this gap here by examining the patterns of species' distributions and phylogenetic relationships for 7465 seed plant taxa in North America. An ensemble of species distribution models was used to estimate the potential suitable habitat of species under different sets of climate, land‐use and dispersal constraint scenarios. We then evaluated the vulnerability and extinction risk of individual species to changes in climate and land use, and examined whether rare, endangered and evolutionarily distinct species were disproportionally threatened by climate and land‐use change. We show that ~2000 species may lose >80% of their suitable habitats under the A1b emission scenario for the 2080s, while ~100 species may experience >80% range expansions (a 20 : 1 ratio of loss to gain). When considering >50% range retraction and expansion, the ratio of loss to gain was 13 : 1. A greater loss of species diversity is expected at low latitudes, while larger gains are expected at high latitudes. Evolutionarily distinct species are predicted to have significantly higher extinction risks than extant species. This suggests a disproportionate future loss of phylogenetic diversity for the North American flora. Synthesis and applications. Our study provides continental‐scale evidence of plant species extinction risk caused by future climate and land‐use change, and highlights the importance of integrating phylogenetic measures into conservation risk assessments. This work provides insight into the status, trends and threats for a large share of North America's plant species by identifying risks and prioritizing conservation in a rapidly changing world.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".