THE INFLUENCE OF SWIMMING ON THE VERTICAL AND HORIZONTAL DISTRIBUTION OF MARINE INVERTEBRATE LARVAE
Bibliographic record
Abstract
Abstract:<br>This thesis aims to increase our understanding of mechanisms that influence larval dispersal in marine benthic invertebrates, particularly in the absence of strong oceanographic features (e.g. estuarine plumes, upwelling events, or markedly different water masses). Laboratory experiments identified behavioural mechanisms that regulate the vertical distribution of larvae in response to thermal stratification, and field studies in St. George’s Bay, Nova Scotia (NS), Canada, examined the relationship between larval abundance and physical variables (temperature, salinity, fluorescence, etc) and identified mechanisms that regulate larval distributions in situ. In the laboratory, I demonstrated that thermal stratification affects the vertical distribution of larvae by acting as a barrier to migration, or through temperature-dependent vertical swimming velocities. I also developed a random walk based model which highlighted that the key to successfully simulating larval response to temperature was 1) determining the temperature-dependent distribution of vertical swimming velocities and 2) the temporal autocorrelation in these velocities. In the field, the most striking pattern was that the larval distributions for species with similar swimming abilities were significantly correlated to one another at all scales (0.5 to 40 km). This suggests a common mechanism, related to larval swimming ability, which greatly influences the horizontal larval distribution. I found that the spatial scale of variability in larval distributions (~ 3 km) matches that in both the environmental variables and of coherent structures in current velocities (i.e. the tidal excursion). Results from an aggregation-diffusion model suggest that horizontal larval swimming could not be responsible for the observed level of aggregation in the larval horizontal distributions. I suggest that these horizontal patterns are the result of 1) an aggregative process (i.e. larvae swimming against a vertical current and maintaining their vertical position) and 2) a diffusive process which scales the aggregations to the scale of the coherent structures in current velocity (i.e. tidal excursion). In conclusion, this thesis increases our understanding of larval behaviour and its effects on larval dispersal. The results will be particularly useful to those who are interested in mechanisms regulate population connectivity, particularly those using bio-physical models to model dispersal trajectories.
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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 | 0.001 |
| 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) | 0.007 | 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".