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.