Permeability of coastal biogeographic barriers to marine larval dispersal on the east and west coasts of North America
Bibliographic record
Abstract
Abstract Aim We assess the role of contemporary oceanography and species traits in shaping observed patterns of biogeography over broad spatial scales. Location Our study domain covers the east and west coasts of North America, from 30° to 73° N on the east coast and 33° to 73° N on the west coast. Time period Hydrodynamic models use climatological fields from 1990 to 2015 on the east coast, and 1993 to 2018 on the west coast. Major taxa studied Model simulations represent larval dispersal for generalized benthic invertebrate species distributed in the subtidal zone from 10 to 100 m depth, with planktonic larval durations ranging from 21–60 days. Methods We conducted a literature review to identify major biogeographic barriers along the east and west coasts of North America, and then assessed the permeability of these barriers to larval dispersal using Lagrangian particle tracking. We ran a series of simulations in which we varied the suitable habitat distribution, planktonic larval duration, and spawning seasonality of simulated larvae (i.e., particles) to assess the effects of species traits on biogeography. Results Our results showed a strong alignment of observed biogeographic barriers with larval dispersal patterns, with high variation in barrier permeability depending on the traits of the species considered. The location of suitable habitat and the season during which particle release occurred were the biological traits that drove much of the variation in barrier permeability among simulations on both coasts. Main conclusions Our results indicate an important role of contemporary oceanographic and geographic features in determining the biogeography of species whose primary dispersal is during larval stages, suggesting that climate change is likely to alter patterns of species biogeography. Our results also demonstrate that species traits play a strong role in determining the location and strength of biogeographic barriers.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".