Does climate change and plant phenology research neglect the Arctic tundra?
Bibliographic record
Abstract
Abstract Phenology, the annual timing of naturally recurring events in animals and plants, is exhibiting significant changes in response to climate change. Drastic shifts in the timing of plant activity have been observed in high‐latitude environments in particular, which are exposed to the greatest amount of warming. Taking into consideration the importance of plant growth and seasonal availability for the whole ecosystem, we would hope that ample research is conducted on the impacts of climate change on plant phenology in the Arctic tundra. We provide a geographic and temporal overview of research relating to impacts of climate change on plant phenology and investigate whether the Arctic tundra is receiving the research attention that appears warranted due to the rapid warming and large expected changes in this biome. We conducted a literature search for articles using the Institute for Scientific Information Web of Science and evaluated focus on biomes, and temporal trends for 2000–2015. We found that the tundra was one of the least researched biomes, when compared to all other biomes. Proportional to the land surface the tundra covers, significantly less research in North America has been devoted to this biome than expected, while profusion of research in Europe was as expected. Additionally, we found that in the past sixteen years, despite the increase in the number of articles published relating to climate change and plant phenology, the proportion of the research devoted to the tundra decreased over time. Our findings also indicate that more work is being done on plant phenology and climate change in lower latitudes. We suggest that the results of this analysis are due to three non‐insurmountable obstacles (access, expense, and complexity) and provide practical suggestions for increased investment in climate change and plant phenology research in the otherwise neglected Arctic tundra.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.037 | 0.003 |
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; both teacher heads agree on what is shown here.
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".