Soil moisture associations with burrow occupancy and reproductive success of Leach’s Storm-Petrels
Bibliographic record
Abstract
Parent birds are under selection to choose nest sites that protect themselves and their nestlings from threats. Burrow-nesting can provide protection from predators and buffer against inclement weather. Soil characteristics within and around burrows may determine suitability of sites for burrow-nesting, and parents may choose sites based on factors such as soil compaction, composition, and moisture. Leach’s Storm-Petrels (<em>Hydrobates leucorhous</em>) nest in burrows on islands that likely reduce predation and provide thermoregulatory and humidity benefits. We tested for associations between volumetric water content (hereafter, soil moisture) and nest site selection, burrow occupancy, and nest success. Soil moisture readings were taken from inactive and active burrow entrances and comparison points on Bon Portage Island, Nova Scotia, Canada. Soil moisture was significantly higher at comparison points than at burrows in each year; however, there was no difference in soil moisture at inactive versus active burrows or between burrows that were deemed to have or not to have produced a fledgling. Lower moisture content may allow for easier excavation; however, Leach’s Storm-Petrels often use the same burrow for many years, and soil moisture almost certainly changes over time, so measurements taken during our study may not be representative of conditions when sites were initially chosen. Nonetheless, burrowing will allow freer exchange of water vapor than burrow-free soil so that burrows are expected to have lower moisture than soil within the same microclimate. With climate change increasing the frequency of inclement weather, soil moisture data and use of weather stations may be useful for predicting which petrel burrows will be more susceptible to loss by flooding, thereby informing threat assessments during conservation planning.
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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) | 0.000 | 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".