Precipitation Drives the Abundance and Distribution of <i>Arctia virginalis</i> : A 40-Year Study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract To understand processes that govern the abundance and distribution of species, ecologists typically collect either long time series without surveying potential drivers or perform short-term experiments that may not scale up. We characterized the annual population dynamics of Arctia virginalis for 40 years and conducted experiments to examine the relative roles of abiotic conditions, host plants, predation, parasitoids, and viral infection. Rather than finding a single limiting factor, these factors were all important at some times or places. Annual densities varied by a thousand times and showed evidence of a regime shift around 2002, coincident with changing precipitation patterns. Wet sites and wet years supported higher densities, and precipitation interacted with most of the factors considered. Population control was context dependent, but water availability was generally the relevant context. Precipitation seems to be important for other Lepidoptera in western North America. Studies that include experimental tests of population drivers are required to manage insect populations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.000 | 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 it