Is a species distribution model output reliable to test niche limitation at the northern range limit of a Pacific coastal dune plant?
Bibliographic record
Abstract
Jacqueline Grubel* and Christopher G. Eckert (Faculty Supporter) It is widely thought that the size, shape and location of a species’ geographical distribution are a spatial expression of its realized niche, and this assumption is central to evolutionary biology, biogeography and conservation. Yet, the hypothesis that geographical range limits are niche limits is not well supported by experimental translocations of species beyond their range limits. Beyond range populations often exhibit fitness high enough for self-replacement. In contrast, environmental niche models based on bioclimatic data often suggest a decline in habitat suitability beyond range limits, thereby supporting niche limitation. However very few studies have evaluated whether species distribution models (SDMs) accurately predict the viability of populations in nature, and scant results to date are not supportive. Long-term transplant with the short-lived, Pacific costal dune endemic plant Camissoniopsis cheiranthifolia (Onagraceae) suggest that populations are viable beyond the northern range limit over multiple generations. We constructed an SDM based on a large range-wide database of species records plus standard bioclimatic variables and substrate type. We also included sea surface temperature, which greatly modifies the climate of dune habitat. Preliminary results suggest that our SDM reliably predicts the fitness of experimental populations. However, both approaches indicate that something other than niche limitation enforces the northern range limit of this species. Results from this well-studied dune plant suggest that range limitation via constraints on dispersal may play an important role in limiting northern range expansion.
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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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".