Automated telemetry reveals age specific differences in flight duration and speed are driven by wind conditions in a migratory songbird

Table 1 AICc model selection results for path analytic models examining factors affecting flight duration across the ocean and along the coast

Path model equations	K	AICc	ΔAICc	W	Cumulative W	Fisher’s C
tailwind ~ stage + age	16	71.64	0	0.56	0.56	22.09
flight duration ~ tailwind + tailwind²	16	71.64	0	0.56	0.56	22.09
tailwind ~ stage + age	17	72.37	0.73	0.39	0.95	17.97
flight duration ~ age + tailwind + tailwind²	17	72.37	0.73	0.39	0.95	17.97
tailwind ~ stage + age	18	76.69	5.05	0.04	0.99	17.11
flight duration ~ stage + age + tailwind + tailwind²	18	76.69	5.05	0.04	0.99	17.11
tailwind ~ stage + age	19	79.00	7.36	0.01	1	13.86
flight duration ~ stage + age + tailwind + tailwind² + crosswind	19	79.00	7.36	0.01	1	13.86
tailwind ~ stage + age	20	83.79	12.15	0	1	12.68
crosswind ~ age
flight duration ~ stage + age + tailwind + tailwind² + crosswind
tailwind ~ stage + age	21	86.73	15.09	0	1	9.19
crosswind ~ stage + age
flight duration ~ stage + age + tailwind + tailwind² + crosswind
tailwind ~ stage + age	14	120.04	48.40	0	1	79.31

k represents the number of parameters in each path model. W and Cumulative W represent Akaike weights and cumulative model weights, respectively. Fisher’s C statistic = −2*ln(model likelihood). The null model is defined by the top model with paths to flight duration removed. ² indicates curvilinear parameter coefficient

ISSN: 2051-3933