Amphibian terrestrial habitat selection and movement patterns vary with annual life-history period
Bibliographic record
Abstract
Identification of essential habitat is a fundamental component of amphibian conservation; however, species with complex life histories frequently move among habitats. To better understand dynamic habitat use, we evaluated Wood Frog (Lithobates sylvaticus (LeConte, 1825)) habitat selection and movement patterns during the spring migration and foraging periods and described the spatiotemporal variability of habitats used during all annual life-history periods. We radio-tracked 71 frogs in Maine during 2011–2013 and evaluated spring migration, foraging activity center (FAC), and within-FAC habitat selection. Telemetered frogs spent the greatest percentage of each field season in hibernacula (≥54.4%), followed by FACs (≥25.5%), migration habitat (≥16.9%), and breeding sites (≥4.5%). FACs ranged 49 – 1 335 m2 (568.0 ± 493.4 m2) and annual home ranges spanned 1 413 – 32 165 m2 (11 780.6 ± 12 506.1 m2). During spring migration, Wood Frogs exhibited different movement patterns (e.g., turn angles), selected different habitat features, and selected habitat features less consistently than while occupying FACs, indicating that the migration and foraging periods are ecologically distinct. Habitat-use studies that do not discriminate among annual life-history periods may obscure true ecological relationships and fail to identify essential habitat necessary for sustaining amphibian populations.
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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 | 0.000 |
| 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".