Climate adaptation is not enough: warming does not facilitate success of southern tundra plant populations in the high Arctic
Bibliographic record
Abstract
Rapidly rising temperatures are expected to cause latitudinal and elevational range shifts as species track their optimal climate north and upward. However, a lack of adaptation to environmental conditions other than climate - for example photoperiod, biotic interactions, or edaphic conditions - might limit the success of immigrants in a new location despite hospitable climatic conditions. Here, we present one of the first direct experimental tests of the hypothesis that warmer temperatures at northern latitudes will confer a fitness advantage to southern immigrants relative to native populations. As rates of warming in the Arctic are more than double the global average, understanding the impacts of warming in Arctic ecosystems is especially urgent. We established experimentally warmed and nonwarmed common garden plots at Alexandra Fiord, Ellesmere Island in the Canadian High Arctic with seeds of two forb species (Oxyria digyna and Papaver radicatum) originating from three to five populations at different latitudes across the Arctic. We found that plants from the local populations generally had higher survival and obtained a greater maximum size than foreign individuals, regardless of warming treatment. Phenological traits varied with latitude of the source population, such that southern populations demonstrated substantially delayed leaf-out and senescence relative to northern populations. Our results suggest that environmental conditions other than temperature may influence the ability of foreign populations and species to establish at more northerly latitudes as the climate warms, potentially leading to lags in northward range shifts for some species.
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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 | 0.000 |
| 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".