Using movement behaviour to define biological seasons for woodland caribou

Terrestrial mammals are strongly influenced by seasonal changes in environmental conditions. Studies of animal space use behaviour are therefore inherently seasonal in nature. We propose an individual-based quantitative method for identifying seasonal shifts in caribou movement behaviour and we demo...

Full description

Bibliographic Details
Published in:Rangifer
Main Authors: Tyler D. Rudolph, Pierre Drapeau
Format: Article in Journal/Newspaper
Language:English
Published: Septentrio Academic Publishing 2012
Subjects:
Online Access:https://doi.org/10.7557/2.32.2.2277
https://doaj.org/article/162b6b16ce8040e9a56e4f3398d1ffdc
Description
Summary:Terrestrial mammals are strongly influenced by seasonal changes in environmental conditions. Studies of animal space use behaviour are therefore inherently seasonal in nature. We propose an individual-based quantitative method for identifying seasonal shifts in caribou movement behaviour and we demonstrate its use in determining the onset of the winter, spring dispersal, and calving seasons. Using pooled data for the population we demonstrate an alternate approach using polynomial regression with mixed effects. We then compare individual onset dates with population-based estimates and those adopted by expert consensus for our study area. Distributions of individual-based onset dates were normally distributed with prominent modes; however, there was considerable variation in individual onset times. Population-based estimates were closer to the peaks of individual estimates than were expert-based estimates, which fell outside the onetailed 90% and 95% sample quantiles of individually-fitted distributions for spring and winter, respectively. Both expertand population-based estimates were later for winter and earlier for both spring and calving than were individual-based estimates. We discuss the potential consequences of neglecting to corroborate conventionally used dates with observed seasonal trends in movement behaviour. In closing, we recommend researchers adopt an individual-based quantitative approach and a variable temporal window for data set extraction.