The seasonal dynamics of a High Arctic plant–visitor network: temporal observations and responses to delayed snow melt
Bibliographic record
Abstract
Plant–visitor food webs provide important insights into species interactions, and more information about their seasonal dynamics is vital to understanding the resilience of species to external pressures. Studies of Arctic networks can also improve our understanding of species responses to the pressures of climate change. This study provides the first description of a plant – insect visitor network in Svalbard, a High Arctic archipelago already experiencing the consequences of climate change. A subset of the network was collected from experimental plots where the snow melt date was delayed with snow fences. The deep snow plots delayed flowering and we expected this to disrupt plant–visitor interactions compared with ambient snow conditions. However, the composition of flowers and insect visitors were similar between regimes, and the network tracked patterns of overall flowering phenology. Nevertheless, the deep snow significantly reduced the average overlap between flower availability and insect activity, reducing the probability of an interaction. We suggest that at a landscape scale, Arctic pollinators will benefit from patchy changes to snow melt that maintain heterogeneity in the timing of flowering but changes that increase homogeneity in snowmelt across the landscape may negatively impact some species.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".