75 years of anthropogenic change and its impact on Canadian butterfly taxonomic and phylogenetic diversity
Bibliographic record
Abstract
Abstract Previous studies have documented very little net change in average quadrat-level species richness and phylogenetic diversity. However, although the average remains centered around 0, there is much variation around this mean and many outliers. The relative contribution of anthropogenic drivers (such as climate change or land use change) to these outliers remains unclear. Traits may dictate species responses to these changes, and if relatedness is correlated with trait similarity, then the impacts of anthropogenic change may be clustered on the phylogeny. We build the first regional phylogeny of all Canadian butterfly species in order to examine change in community phylogenetic structure in response to two main documented drivers of change -- climate change and land use change -- across 265 species, 75 years and 96 well-sampled quadrats. We find no evidence that, on average, communities are becoming more or less clustered than one would expect. However, there is much variation depending on the magnitude and type of anthropogenic change occurring within a quadrat. We find that climate change as well as agricultural development is reducing species richness within a quadrat, and these species that are lost tend to be scattered across the phylogeny. However, agricultural abandonment is having the opposite effect: we find increasing species richness in the years immediately following it and decreasing distance between species in quadrats with the highest rates of abandonment, such that the species that colonize these plots tend to be close relatives of those already present and thus contribute little novel phylogenetic diversity to an assemblage. Consistent with previous work, small changes in local species richness may conceal simultaneous change in other facets of biodiversity.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".