Table 1 Hierarchical organization of a typical vertebrate lifetime track (LiT)
From: A hierarchical path-segmentation movement ecology framework
Scale/segment | Time | Space | Categories | Data | Some approaches and methods |
|---|---|---|---|---|---|
Constraint level: type of analysis | |||||
FuMEs\(^*\) | 0.1–few secs | 0–1000 cm | Stride, trot, run, twist, jump, flap | Accelerometer video | Machine learning\(^{*\dag }\), Newtonian mechanics |
Highly constrained: biomechanical analyses | |||||
Meta- FuMEs\(^*\) | Resolution of relocation data\(^{*\ddag }\) | Average step length | Bivariate SL and TA distributions | SL and TA means, variances and correlations\(^{\dag \dag }\) | Cluster analysis ensemble filtering |
Base level: movement ecology analyses | |||||
Short duration CAMs\(^\dag\) | 0.1–10 min | A few meters to a few kms | Resting, browsing, riding thermals | secs to mins, | Path segmentation\(^{**}\) |
Highly flexible: sub-hourly/hourly analysis | metaFuMEs and covariate data | ||||
Long duration CAMs\(^\dag\) | 10–100 min | A few meters to many kms | Feeding traveling | mins to hours, | |
Highly flexible: sub-diel analysis | Short CAMs and Covariate data | ||||
DARs\(^\ddag\) | Fixed 24-h | Diel range | Central-place foraging Ranging | 24 h of data CAM eequences | Periodograms (Fourier, wavelets) |
Time constrained: diel cycle analysis | |||||
LiMPs\(^\S\) | Several days to a few months | Home ranges and their shifts over time | Philopatry, dispersal, migration, nomadic, recursion | DAR sequences | Clustering methods, ideal-free/despotic distribution analyses |
Strongly constrained: lunar and seasonal cycle analyses | |||||
Partial or whole LiTs\(^\#\) | Paths encompassing several LiMPs | Habitat types | Territorial ranging, migratory nomadic | LiMP sequences | GIS toolbox, deep-learning\(^{*\dag }\), pattern anal. |
Moderately constrained: question-at-hand analysis | |||||