Population dynamics of the northern short-tailed shrew, <i>Blarina brevicauda</i>: insights from a 25-year study
Bibliographic record
Abstract
The population demography of the northern short-tailed shrew, Blarina brevicauda (Say, 1823), was studied for 25 years in bluegrass, alfalfa, and tallgrass habitats in east-central Illinois. The population in bluegrass had higher over-winter population density, began increasing earlier in the year, peaked earlier in the year, had higher mean monthly densities and amplitudes of fluctuation, and remained higher for longer than did populations in alfalfa and tallgrass. Survival rates were greater in bluegrass and tallgrass than in alfalfa. The species displayed annual population fluctuations with little variation in amplitude among years in all three habitats. Seasonal reproduction appeared to be responsible for the annual fluctuations. Survival did not vary in relation to season, but was positively correlated with annual peak densities, whereas reproduction was not. There was no correlation between population densities of voles during April–August and annual peak densities of B. brevicauda. We conclude that annual fluctuations in B. brevicauda populations are driven by seasonal reproduction, while variation in mortality, most likely from predation, may explain differences in the amplitudes of annual peaks.
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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 | 0.000 |
| 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) | 0.001 | 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".