Bluebills and bayou bivalves: Hurricane‐driven trophic cascades affect wintering abundance of Lesser Scaup in Louisiana
Bibliographic record
Abstract
Abstract The estuaries of coastal Louisiana overwinter a continentally significant proportion of Lesser Scaup ( Aythya affinis ; colloquially, “bluebills”), a migratory bird species of conservation concern since population declines began in the 1980s. Thirty‐eight years of aerial waterfowl surveys of Lake Pontchartrain—an oligohaline estuarine lagoon in southeast Louisiana—show that scaup abundance fluctuates between 0 and 1,194,907 birds, though the mechanisms driving this variation are unknown. Previous studies have shown that scaup feed primarily on mollusks, and so changes in the benthic prey community have the potential to strongly influence scaup dynamics on the Lake. Benthic communities are in turn shaped by both natural and anthropogenic disturbances (e.g., hurricanes and spillway openings), potentially creating a lagged bottom‐up trophic cascade that ultimately affects scaup abundance. Using 22 yr of paired benthic invertebrate and aerial waterfowl survey data, we found scaup populations increased with the abundance of medium‐sized Rangia clams ( Rangia cuneata ) and Dwarf Surf Clams ( Mulinia lateralis ). Those prey species declined in years when the Lake was hit by a hurricane, but medium‐sized Rangia rebounded strongly the year after, likely because storm‐surge salinity induces spawning. Using long‐term aerial survey data for scaup, we indeed found strong declines on the Lake in years when a hurricane made landfall, but scaup abundance increased the following year, presumably responding to large numbers of medium‐sized Rangia. Our three‐part analysis makes a strong case for a hurricane‐driven bottom‐up trophic cascade that affects scaup populations on Lake Pontchartrain. This study adds to a growing literature demonstrating not only that estuaries are tidally and seasonally dynamic, but that punctuated disturbance events can be important for maintaining ecosystem function.
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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) | 0.025 | 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".