Figure legends:
Fig. 1: Patterns of empirical and simulated migratory connectivity and seasonal climate tracking. Empirical migratory connectivity and variation in seasonal climate tracking is better captured by a model based on energy efficiency than by the simulation model based on climate tracking. Top row: empirical patterns; middle row: patterns simulated by ORSIM; bottom row: patterns simulated by the climate tracking model. Panels (a), (e) and (i) show the connections between population migration destinations (i.e. migratory connectivity), and the other panels show the relationship between migration distance and (b,f,j) two-dimensional climate (temperature + precipitation), (c,g,k) thermal overlap (temperature only), and (d,h,l) precipitation overlap (precipitation only). Population acronyms are a combination of a latitudinal region: N=north and S=south; and a longitudinal region: W=west, R=Rockies, C=central and E=east. If no latitudinal letter is indicated in an acronym, it means that the population somewhat spans both north and south. If two longitudinal letters are indicated in an acronym, it means that the population somewhat spans both regions. Black curves are loess smooth splines with a span of 1.
Fig. 2: Relationship between empirical and simulated patterns. Expectation from energy efficiency simulated by ORSIM versus empirical (a) migration distance, and seasonal overlap of (b) two-dimensional climate, (c) temperature and (d) precipitation. Black lines indicate the 1:1 lines. Points below the 1:1 line in b-d indicate populations that seasonally track climate more than expected by ORSIM. Point size in b-d indicates the rank among values for the null model randomizing wintering destinations in regions around ORSIM expectation (1 minus scaled rank between 0–1). The figure shows that a model based on energy efficiency explains most of the empirical variation in migration distance and thermal overlap, but for precipitation it seems to be more affected by regional precipitation tracking.