Movement patterns drive within-mudflat distribution of an intertidal amphipod
Bibliographic record
Abstract
Spatial structuring in species distribution can be caused by effects of biotic or abiotic factors on the vital rates (survival, growth or reproduction) or movement of individuals.Here, we studied the distribution patterns of a dominant infaunal invertebrate, the amphipod Corophium volutator, on an intertidal mudflat and evaluated the relative contribution of vital rates and movement on the formation of intermediate-scale patterns (10 to 100 m).We found a clumped distribution at scales ranging from 0.2 to 100 m and occasionally the presence of large-scale gradients.At intermediate scales, variation in density in the mud associated better with variation in movement variables (density of swimmers and immigration) than demographic variables.Predictions from local population models not including migration often largely underestimated increases in local density, leaving immigration as the only mechanism explaining variation in density.Amphipod swimming was directed, and the direction of swimming corresponded to overall density gradients observed on the mudflat.We concluded that movement of C. volutator is an important process causing and maintaining intermediate-scale distribution patterns.Spatial variability in supply of individuals, likely linked to timing of swimming coupled with hydrodynamic conditions, translates into notable variation in population density distributions.
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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 | 0.001 | 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) | 0.000 | 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 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".