Role of avoidance behavior in the response of <i><scp>F</scp>olsomia candida</i> to above‐freezing cooling temperatures
Bibliographic record
Abstract
Abstract Although avoidance behavior is thought to be one of the major strategies for arthropods to cope with cold, there is a general lack of data supporting its use. This study tested the suggestion that Collembola migrate deeper into the soil to avoid cooling temperatures during the transition from summer to winter. We released mature hemi‐edaphic Folsomia candida Willem (Collembola: Isotomidae) in large (5 301 cm3) and small (306 cm3) soil microcosms exposed to ambient temperatures ranging between 5 and 20 °C. Springtails released in the large microcosms for periods of 2, 3, and 4 weeks dispersed throughout the soil column but remained more abundant in the upper third layer of the soil column whether exposed to weekly decreasing temperatures or a constant ambient temperature of 20 °C. Both small (juvenile) and large (mature) springtails exposed to cooling were more abundant in the upper third than in the middle or lower third of the soil columns after 2, 3, or 4 weeks. Groups of F. candida released in small microcosms provided with a positive soil temperature gradient displayed the same vertical distribution, with 90% of individuals clustered in the top 4.5 cm of the 15‐cm column whether exposed to air temperatures of 5, 10, 15, or 20 °C. Results from the two types of microcosms demonstrated that the vertical distribution of springtails remains strongly biased to the upper soil layer regardless of the temperature of their environment and whether the temperature in the soil column was uniform or graduated. This supports our prediction that hemi‐edaphic species such as F. candida do not relocate to warmer deeper soil layers, but tend to remain in the surface soil layer where they can acclimate to the cooling temperature.
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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".