Macroecological c onstraints on species' ‘movement profiles’: Body mass does not explain it all
Samantha Straus, Coreen Forbes, Chelsea J. Little, Rachel M. Germain, Danielle A. Main, Mary I. O'Connor, Patrick L. Thompson, Adam T. Ford, Dominique Gravel, Laura Melissa Guzman- Ecology
- Ecology, Evolution, Behavior and Systematics
- Global and Planetary Change
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.