Ecological and evolutionary consequences of experimental and natural warming in the high Arctic tundra
Bibliographic record
Abstract
Recent increases in global temperatures are having substantial and often unpredictable consequences for the earth’s biota. Species’ responses to environmental change depend on 1) the ability of individuals to adjust in situ through phenotypic plasticity, 2) the rate at which evolutionary adaptation can occur, and 3) the ability of individuals to colonize newly suitable habitat through migration or propagule dispersal. Temperatures in the Arctic are increasing faster than anywhere else, yet our understanding of the consequences of climate change in the Arctic lags behind that of temperate ecosystems. In this thesis, I ask whether plant phenology has advanced in response to 21 years of experimental and ambient warming at Alexandra Fiord, Ellesmere Island, Canada. While experimental warming led to earlier flowering in three out of four species, flowering dates in the control plots were unchanged or delayed despite more than 1 °C of ambient warming over the 21-year period, likely due to concurrent delays in snowmelt. This suggests that the effects of altered snowmelt patterns can counter the effects of warmer temperatures, even generating phenological responses opposite to those predicted by warming alone. I then use reciprocal transplant experiments to test for evidence of evolutionary adaptation in two plant species to differing environmental conditions between two spatially proximate habitat types and in response to 18 years of experimental warming treatments. Results were consistent both with substantial phenotypic plasticity in response to site-to-site and year-to-year variability, and with evolutionary adaptation to site and treatment conditions. Differences across natural habitats were stronger than those across experimental treatments. This indicates that plastic and genetic responses to climate change are likely to play an important role in structuring future Arctic plant communities. Finally, I test the hypothesis that warming will confer a fitness advantage to “pre-adapted” southern immigrants relative to native populations. Despite experimental conditions 3-5 °C warmer than the historical average, local populations leafed-out earlier and attained greater maximum size than foreign populations in two of three species, suggesting that the success of southern immigrants may be limited by a lack of adaptation to novel non-climatic environmental conditions even when temperatures are suitable.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.001 |
| 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".