Range size, taxon age and hotspots of neoendemism in the California flora
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Aim Sustaining biological diversity requires the protection of the ecological, evolutionary and landscape‐level processes that generate it. Here, we identify areas of high neoendemism in a global diversity hotspot, the California flora, using range size data and molecular‐based estimates of taxon age. Location California, USA. Methods We compiled distribution and range size data for all plant taxa endemic to California and internal transcribed spacer (ITS)‐based age estimates for 337 putative neoendemics (15% of the endemic flora). This information was combined to identify areas in the state with high proportions of young and restricted‐range taxa. We overlaid the distribution of neoendemic hotspots on maps of currently protected lands and also explored correlations between our diversity measures and climate. Results The central coast of California, the Sierra Nevada and the San Bernardino Range contained endemics with the most restricted distributions on average, while areas in the Desert and Great Basin provinces found within the state were composed of the youngest neoendemics on average. Diversity measures that took age and range size into account shifted the estimate of highest endemic diversity in the state towards the Desert and Great Basin regions relative to simple counts of endemic species richness. Our diversity measures were poorly correlated with climate and topographic heterogeneity. Main conclusions Substantial portions of California with high levels of plant neoendemism fall outside of protected lands, indicating that additional action will be needed to preserve the geographic areas apparently associated with high rates of plant diversification. The neoendemic flora of the deserts appears particularly young in our analyses, which may reflect the relatively recent origin of desert environments within the state.
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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 | 0.001 | 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 it