Scales of Mytilus spp. population dynamics: importance of adult displacement and aggregation
Bibliographic record
Abstract
The control of mussel population dynamics by larval supply and by more local processes affecting post-recruitment survival and growth has received considerable attention.However, immigration and emigration of adults and their contribution to colonization dynamics remain largely unknown.We manipulated the location and density of marked mussels in experimental transplants in the St. Lawrence Estuary (Québec).Our results reveal that colonization by Mytilus spp. is influenced by (1) passive adult movement through wave disturbance and immigration, (2) spatial aggregation and (3) topographic heterogeneity.Results show that ~90% of colonization in experimental plots was by individuals of 4 to 32 mm shell length and was associated with both withintransplant and local (< 0.15 m from transplant) aggregation.Experimental gaps revealed a similarly aggregated wave-disturbance process, propagating small (0.5 m) gaps across >100 m.The passive displacement distribution of marked and wave-dislodged individuals further revealed movement distance ranging from 1 to 150 m and disturbance mortality from < 20 to 40%.Together our results reveal that colonization in subarctic mussel populations can be largely controlled by cycles of adult displacement and further aggregation at the landscape level (~100 m).Such positive feedbacks involved in disturbance and colonization could explain strong fluctuations in abundance and challenge the interpretation of intertidal populations as systems mostly limited by larval supply and post-recruitment survival.
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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 | 0.000 | 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 | 0.001 |
| 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".