Habitat Restoration in a Changing World: Determining the Indirect Effects of Warming on Monarch Butterflies (Danaus plexippus) as Mediated by Changes in Nectar Quality
Bibliographic record
Abstract
Loss of natural habitats is one of the most critical threats to biodiversity. Habitat restoration is a key strategy to re-establish degraded ecosystems and support the persistence and colonization of pollinators and insects. Pollinator-focused restoration includes introducing floral resources to landscapes to increase native insect pollinator abundance. However, climate change is a major, intensifying threat globally, and insects are among the most affected groups experiencing population declines across the biosphere. Habitat restoration projects and decisions must consider climate change to ensure the effective functioning and resilience of restored habitats, but anticipating the effects of climate change on insects is difficult. Both direct and indirect effects of warming temperatures are expected to impact insect populations, but the indirect effects remain poorly studied. It is unclear how nectar plants will respond to warming temperatures and how these responses may impact insects. Since floral seed mixes are a key component of habitat restoration, exploring how different floral species will respond to warming temperatures, and how those responses may impact pollinators, is essential. The endangered Eastern migratory population of monarch butterflies (Danaus plexippus) is at risk due to climate change. Monarchs rely on nectar from late-season flowering plants in their breeding range in Canada to fuel their migration south to Mexico. Thus, warming-induced declines in the nectar quality of these plants may have critical conservation repercussions. Here, I used a field warming experiment at the monarch's northern range limit in Ontario, Canada, to examine i) the vegetative, floral, and nectar responses of 3 highly visited flowering species to warming, ii) the variation of those responses across the 3 species, and iii) the subsequent impacts of these responses on the body composition of adult monarchs. I found that the warming treatment lowered nectar quality and availability of late-season flowering plants. These warming-induced plant and nectar responses led to a decrease in the fat mass of monarchs who fed on the nectar of warmed plants. These body composition measurements are important metrics for monarch migration and overwintering survival. All three late-season flowering plant species experienced declines in nectar quality; it is unclear if a pattern of adaptive capacity exists in these plants. Therefore, habitat restoration projects should make planting decisions that are context-specific for the needs of the pollinators and plant communities in a specific area.
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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 | 0.001 |
| 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) | 0.000 | 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".