Do fluctuating water levels alter nest survivorship in reservoir shrubs?
Bibliographic record
Abstract
Reservoirs often have highly fluctuating water levels. The perimeters of these impoundments, which alternate between being exposed or inundated by water (drawdown zone), are used by nesting birds, but at the risk of nest submergence when water levels rise. For species that nest above the ground in shrubs, foraging and predation may also be affected by flooded habitat. Our objective was to clarify the net impact that habitat flooding has on nest survivorship at Arrow Lakes Reservoir, British Columbia, Canada. This reservoir typically shows a pattern of water management where water is stored during the spring snowmelt (increasing water levels) and released later in the year. Yellow Warblers (Setophaga petechia; n = 272 nests) and Willow Flycatchers (Empidonax traillii; n = 81 nests) nested in similar parts of the drawdown zone, but differences in their nesting behaviors, particularly timing of nesting, caused the flycatchers to experience more nest submergence. Flycatchers also nested on a floating island of bog habitat, offering them some protection from nest submergence. We found little evidence that drawdown zone shrubs functioned as ecological traps. In flooded conditions, 28% of warbler nests failed due to submergence. Warbler nest daily survival rate (DSR) declined with advancing ordinal date, and we concluded that their DSR was not influenced by habitat flooding. For flycatchers, 50% of nest failures were caused by submergence under flooded conditions, but DSR did not differ between flooded (0.960 ± 0.009) and unflooded conditions (0.958 ± 0.012). We speculate that these counterintuitive results may be explained by a reduction in predation levels during flooded conditions, which may compensate for nest submergence. Finally, we found that nest DSR was enhanced in the floating island habitat (0.986 ± 0.005), indicating that floating habitat islands can be highly productive and may hold potential as a management tool for enhancing productivity of reservoir drawdown zones.
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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 | 0.001 | 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) | 0.004 | 0.007 |
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; both teacher heads agree on what is shown here.
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".