Eastern monarch larval performance may not be affected by shifts in phenological synchrony with milkweed
Bibliographic record
Abstract
Abstract Interacting species are experiencing disruptions in the relative timing of their key life‐history events due to climate change. These shifts can sometimes be detrimental to the fitness of the consumer in trophic interactions but not always. The potential consequences of phenological asynchrony for the monarch butterfly (Danaus plexippus) and its host plant (Asclepiasspp.) have not been well‐studied. Given that plants generally undergo seasonal declines in quality, if climate change delays the timing of the larval stage relative to the availability of younger milkweed plants, monarch performance could be negatively affected. Here, we explore the potential consequences for the eastern monarch population due to probable asynchrony with milkweed. We used field surveys around Ottawa, Canada, to determine monarch oviposition preference on common milkweed (Asclepias syriaca) plants and the seasonal availability of these plants. To determine the potential fitness consequences when females oviposit on nonpreferred plants, we conducted a field experiment to assess the effect of milkweed size on monarch larval performance (e.g., development time and final size). Preferred oviposition plants (earlier stages of development and better condition) were consistently available in large proportion over the summer season. We also found that declines in leaf quality (more latex and thicker leaves) with plant size did not translate into decreases in larval performance. Our results suggest that even if asynchrony of the monarch–milkweed interaction occurs due to climate change, the larval stage of the eastern monarch may not face negative consequences. Future studies should determine how the relative timing of the interaction will change in the region.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".