Spatial scaling in northern landscapes : habitat selection by small mammals
Bibliographic record
Abstract
I examined a series of simple and repeated northern landscapes in the Hudson Bay \nLowland of Ontario to document regional and local patterns of population abundance \nof red-backed voles {Clethrionomys gapperi). I tested whether a spatially-explicit \necological process, density-dependent habitat selection, could account for population \nregulation of voles across a range of spatial scales. Over a large regional scale, \nmultiple regression analysis indicated that population density of voles was primarily \npredicted by location of sampling and measures of microhabitat. Regional abundance \npatterns, therefore, appear to be independent of nonadditive landscape effects and \nprobably result from large-scale biogeographic influences or differences in average \nhabitat quality between sites. At a local scale, my analysis identified density-dependent \nhabitat selection as a universal process structuring abundance patterns, \nregardless of regional differences in population density. Habitat selection, at the \ndispersal and perhaps microhabitat scales, thereby provides a feasible mechanism \nlinking landscape structure directly to population regulation.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.004 |
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".