Monarch butterfly (Danaus plexippus) breeding distribution and habitat preferences in Southeastern Ontario
Bibliographic record
Abstract
Habitat loss is considered a strong driver of the decline of the eastern migratory population of the North American monarch butterfly (Danaus plexippus). While research has focused on the loss of suitable habitats in agricultural areas in the American Midwest, little is known about monarch breeding habitat preferences at the northern limits of its summer range in Canada. I first conducted a literature review on monarch habitat preferences and population dynamics across its North American range and on the role of community science in the monitoring of spatial dynamics. Seventeen years of community science records (n=5461) reporting the presence of butterfly species in southeastern Ontario were then used to compare land covers and spatial attributes of butterfly records that included the monarch with records that did not. The models indicate that the probability of observing monarchs, compared to other butterflies in this region, decreases going northward and westward, away from water bodies, and with increasing deciduous or needleleaf forest cover. Clusters of monarch observations (hot spots) are found north of Lake Ontario. Compared with cold spots where the probability of observing the monarch is low, the hot spots tend to have more shrubland and less deciduous forest and urban land cover. A field comparison of the vegetation at a subset of hot and cold sites identifies potential nectaring species at these latitudes, and compares how milkweed abundance, plant richness, and the diversity of potential nectaring plants drive habitat preferences. It offers some of the first evidence that, in this region, milkweed abundance may not be a limiting factor for monarch breeding habitat selection. It also shows a greater ecological gradient in potential nectaring species assemblages in hot spots than in cold ones, ranging from grassland species in conserved lands in the developed regions near Lake Ontario, to forest edge species and shrubs within rights of way in forested regions to the north. While the importance of preserving monarch resources in agricultural landscapes has been acknowledged, the role of successional habitats in forested landscapes has been little considered. This research shows that preserving such spaces is an important feature of monarch conservation at the northern range edge. This study also demonstrates the value of community science data to delineate areas of conservation interest
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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".