Species’ traits modulate rapid changes in flight time in high-Arctic muscid flies under climate change
Bibliographic record
Abstract
Insects are experiencing notable phenological shifts owing to climate change, with substantial interspecific variability. However, our understanding is limited by a shortage of long-term studies, beyond Lepidoptera. This study presents a hierarchical modelling framework to analyse the phenological distribution of 11 muscid fly species across three vegetation types over 18 years (1996-2014) in Zackenberg, Northeast Greenland. We examined species-specific changes in phenology and assessed ecological traits for explaining interspecific variation. Additionally, we investigated the associations between phenological shifts and timing of snowmelt and temperature. We found consistent trends of earlier flight activity and interspecific variation in responses, with smaller species shifting their end-of-the-season activity at faster rates than larger species. Flight activity was strongly associated with the timing of snowmelt, while warming was linked to an earlier end-of-the-season activity. Late-active species exhibited more pronounced shifts in response to climate variations than early-active species. This study highlights that the species-specific climate sensitivity of high-Arctic muscid flies potentially has demographic effects if temporal overlap among interacting species changes. We advocate for prioritizing species-specific insect population studies, ideally analysed within the context of interacting species, to understand better and address disparities in responses to climate change.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".