Long‐term persistence of experimental populations beyond a species' natural range
Bibliographic record
Abstract
Ecological experiments usually infer long-term processes from short-term data, and the analysis of geographic range limits is a good example. Species' geographic ranges may be limited by low fitness due to niche constraints, a hypothesis most directly tested by comparing the fitness of populations transplanted within and beyond the range. Such studies often fail to find beyond-range fitness declines strong enough to conclude that geographic range limits are solely imposed by niche limits. However, almost all studies only follow transplants for a single generation, which will underestimate the importance of niche limitation because critical but infrequent range-limiting events may be missed and methodological issues may artificially boost the fitness of beyond-range transplants. Here, we present the first multi-generation beyond-range transplant experiment that involves adequate replication and proper experimental controls. In 2005, experimental populations of the coastal dune plant Camissoniopsis cheiranthifolia were planted at four sites within and one site beyond the northern limit. Fitness of initial transplants was high beyond the limit, suggesting that the range was limited by dispersal and not niche constraints. To better address the niche-limitation hypothesis, we quantified density and fitness of descendant C. cheiranthifolia populations 12-14 yr (˜10 generations) after transplant. Average annual fruit production and density of reproductive individuals were as high beyond the range as at four comparable experimental populations and eight natural populations within the range, and the beyond-range population had more than tripled in size since it was planted. This provides unprecedented support for the conclusion that northern range limit of C. cheiranthifolia results from something other than niche limitation, likely involving constraints on local dispersal.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".