Ecological correlates of stress for a habitat generalist in a biofuels landscape
Bibliographic record
Abstract
Understanding the success of habitat generalist species requires knowledge of how individuals respond to stressors that vary across habitats within landscapes. Habitat structure can affect stress by altering predation risk, conspecific densities, and densities of heterospecific competitors. Increased demand for biofuels will alter habitat structure for species in agroecosystems worldwide. We measured stress responses of deer mice (Peromyscus maniculatus (Wagner, 1845)), a widespread habitat generalist, in a biofuels landscape. We quantified fecal corticosterone concentrations for individuals in four biofuel crops: switchgrass (Panicum virgatum L.), miscanthus (Miscanthus × giganteus Greef & Deuter ex Hodkinson & Renvoize), mixed prairie, and corn (Zea mays L.). We also evaluated stress responses of deer mice to the annual harvesting of corn. Deer mice inhabiting switchgrass and mixed prairie had higher fecal corticosterone concentrations compared with mice in corn and miscanthus. Fecal corticosterone concentrations correlated positively with abundances of conspecifics and behaviorally dominant voles (prairie vole, Microtus ochrogaster (Wagner, 1842); meadow vole, Microtus pennsylvanicus (Ord, 1815)) across habitats. Stress levels of deer mice depended on how habitat structure modified the competitive environment. Deer mice did not exhibit increased fecal corticosterone concentrations in response to corn harvest, a rapid and extensive habitat disturbance common to agroecosystems. Our research is the first to investigate how landscape change due to biofuels expansion can affect stress levels of individuals.
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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) | 0.000 | 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) | 0.005 | 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 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".