Macroecological constraints on species' ‘movement profiles’: Body mass does not explain it all
Bibliographic record
Abstract
Abstract Aim Animals couple habitats by three types of movement: dispersal, migration, and foraging, which dynamically link populations, communities, and ecosystems. Across these types, movement distances tend to correlate with each other, potentially reflecting allometric scaling with body mass, but ecological and evolutionary species' traits may constrain movement distances and weaken these correlations. Here, we investigate multivariate “movement profiles” to better understand patterns in movement across movement types, with the aim of improving predictions in ecology from populations to ecosystems. Location Global. Time period 1945–2019. Major taxa studied Vertebrates. Methods We synthesized distances of all three movement types (dispersal, migration, and foraging) across 300+ vertebrate species and investigated how the relationships between movement types and body mass were modified by evolutionary history and trophic guild. Results We found that the strength of relationships between movement types and body mass varied among taxa and trophic guilds, for example, strongly positive for mammals but weak for birds, or positive across trophic guilds for foraging and dispersal but not migration. Notably, movement profiles interacted with the effects of shared evolutionary history and trophic guild to diminish covariance between movement types. Main conclusions Overall, we find that movement types with distinct ecological consequences (foraging, migration) are often correlated, although some species seem able to overcome biomechanical, evolutionary, and metabolic constraints by reducing correlations among movement types. This integrative assessment of movement can improve ecological prediction by allowing estimation of unobserved movement distances for parameterization of models based on estimation of other movement types.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".