Identifying the paths leading to variation in geographical range size in western North American monkeyflowers
Bibliographic record
Abstract
Abstract Aim Closely related species can vary tremendously in size of geographical range, yet the causes of such variation are poorly understood. Prominent hypotheses about range size emphasize effects of niche properties and habitat connectivity via the amount and occupancy of suitable habitat, respectively. Previous studies have examined single hypotheses in isolation; however, we assessed the relative importance of these effects along with their potential interactions, using monkeyflower species (genus Mimulus ) as a study system. Location Western North America. Methods We used primary occurrence data and climatic layers to estimate climatic niche breadth and position (relative to average regional climate), connectivity of climatically suitable habitat, and geographical range size of 72 monkeyflower species. Using path analysis, we then assessed the relative importance of climatic niche properties and connectivity of climatically suitable habitat in explaining variation in the amount and occupancy of climatically suitable habitat, respectively, and in turn, variation in geographical range size. Results We documented strong support for the hypothesized effects of climatic niche breadth, but not niche position and connectivity of climatically suitable habitat. Amount of climatically suitable habitat explained more variation in range size than occupancy of climatically suitable habitat, with amount and occupancy of suitable habitat together explaining c. 83% of the variation in range size. Main conclusions To our knowledge, this is the first study to show that climatic niche breadth, via its effects on the amount of climatically suitable habitat, is a strong predictor of geographical range size, thereby improving our understanding of the mechanisms driving species rarity.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".