Atlantic surfclam larval transport, population connectivity, and physical drivers on the Middle Atlantic Bight and Georges Bank
Bibliographic record
Abstract
The Atlantic surfclam, Spisula solidissima, is one of the most commercially important species along the Northeast U.S. coast. Similar to many other benthic invertebrates, surfclam life history includes a dispersive larval stage. Larval dispersal plays a key role in determining connectivity among geographically distinct populations, and is further influenced by physical dynamics and larval behavior. In this graduate work, a coupled modeling system combining a physical circulation model of the Middle Atlantic Bight (MAB), Georges Bank (GBK) and the Gulf of Maine (GoM), and an individual-based surfclam larval model has been implemented to study surfclam larval transport pathways, inter-population connectivity patterns, as well as the associated physical mechanisms. Model results show a mean along-shore connectivity pattern from the northeast to the southwest among the surfclam populations. High-frequency (periods of 2~10 days) variation in larval along-shore drift is found to be due to along-shore surface wind stress variation, with the seasonal variation speculated to be driven mainly by changes in the across-shelf density gradient. Surfclam across-shelf larval movement is also highly correlated with the along-shore surface wind stress as mediated by coastal upwelling and downwelling episodes. This correlation is further dependent on larval vertical distribution with respect to the thermocline, which is a direct result of the mutual interaction of the physical environment and larval behavior. Water temperature is found to play a dominant role in larval settlement patterns. In the vertically integrated time-mean heat balance regulating water temperature on the MAB shelf, surface air-sea heat flux and horizontal heat advection are the two most important terms. Seasonal variation of water temperature is mainly controlled by the seasonally varying surface heat fluxes. Across-shore horizontal heat advection variations associated with different coastal across-shore circulation patterns contribute water temperature variations on shorter time scales from days to weeks. The long-term (e.g., decadal or longer) variation of water temperature is likely due to the variation of along-shore heat advection from the mean along-shore barotropic current acting on the mean along-shore temperature gradient, related to the large-scale coastal current system running from Labrador in the north to Cape Hatteras in the south.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".