Macroecological variation in movement profiles: body size does not explain it all
Bibliographic record
Abstract
Abstract Animals couple habitats by three types of movement: dispersal, migration, and foraging, which dynamically link populations, communities, and ecosystems. Spatial distances of movement tend to correlate with each other, reflecting shared allometric scaling with body size, but may diverge due to biomechanical, phylogenetic, and ecological constraints. While these constraints have been investigated within specific taxa, the macroecological and macroevolutionary constraints on movement distances, and causes of those constraints, are still unknown. Here, we synthesized distances of all three movement types across 300+ vertebrate species, and investigated how the relationships between movement types and body size were modified by movement medium, taxonomy, and trophic guild (carnivore, herbivore, etc.). We found that the strength of relationships between movement types and body size varied among environments, taxa, and trophic guilds. Movement profiles interacted with physiological, taxonomic, and ecological traits to depart from expected body mass scaling. Overall, we find that there are systematic patterns to movement distances, and that movement types with very distinct ecological consequences (foraging, migration) can be correlated and subject to similar constraints. This implies that the scales of population dynamics in ecological communities are not entirely determined by the environment and likely reflect general biomechanical, evolutionary and metabolic constraints.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".