Didemnum vexillum: invasion potential via harvesting and processing of the Pacific oyster (Crassostrea gigas) in British Columbia, Canada
Bibliographic record
Abstract
Experimental studies evaluating the effects of food availability on the movement of free-ranging animals generally involve food supplementation rather than suppression.Both approaches can yield similar insights, but we were interested in the potential for using food suppression for the management and control of invasive predators, in particular, the brown treesnake (Boiga irregularis) on Guam.However, understanding a species' response to food resources is critical before employing such a strategy.We studied the movements of 24 radio-tagged B. irregularis initially caught within four 4-ha unfenced plots in rodent-abundant (control) and rodent-suppressed (treatment) grassland habitats over a 40-day period.Because monitoring duration differed among snakes, we also analyzed short-term (16-day) activity areas.Over the 16 days, snakes associated with rodent-suppressed plots had 86% larger activity areas (ha), 94% greater dispersal distances (m), and 43% greater movement rates (m/h) than snakes associated with control plots.Boiga irregularis moved extensively, but these movements were not always reflected in the size of the snake's total activity area.Movement rates did not differ between sexes, but snakes in above-average body condition moved greater distances per hour than those in below-average condition irrespective of treatment.Our study indicates that a relatively small prey suppression effort can cause almost immediate and significant changes in B. irregularis movement.On Guam, prey suppression might enhance control efforts by either increasing trap capture success or discouraging snakes from entering areas of conservation or management concern.However, the outcome of using prey suppression as a control tool in areas threatened with the accidental introduction of the brown treesnake is more difficult to predict and might have negative consequences such as elevated dispersal rates.
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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 | 0.001 |
| 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".