Fig. 2
From: Mechanistic movement models identify continuously updated autumn migration cues in Arctic caribou
The effect of temperature at three different snow depth levels for each year from the population-level fit of the dynamic-parameter correlated random walk movement model fitted to caribou location data of the Western Arctic Herd, Alaska, 2010–2018. For each year, the predicted effect of temperature (x-axis) on the movement parameter (\(\widehat{{\gamma }_{\text{i}}}\); y-axis) is plotted across 3 levels of snow depth (no snow = 0 cm, average snow = 11 cm, and deep snow = 46 cm). Each black curve is given by the equation \({\widehat{{\gamma }_{\text{i}}}}^{(l)}={logit}^{-1}({{{\varvec{Z}}}_{{\varvec{i}}}}^{{\varvec{T}}}{{\widehat{{\varvec{\beta}}}}_{{\varvec{p}}}}^{\left({\varvec{l}}\right)})\) for the lth Markov-Chain Monte Carlo iteration (termed posterior realizations), and the red line indicates the mean. Annual plots are cut off to the observed range of values for each year