Table 3.

Effects of female traits and climatic variables on the number of recruits

Sources of variation	Estimate	SE	z	P
Conditional model (N = 7315 broods of 5513 females)
Intercept	− 1.43	0.13	− 11.25	< 0.001
Female age	0.03	0.04	0.73	0.47
Female body condition	− 0.03	0.02	− 1.89	0.059
Within-year temperature: incubation	0.00	0.02	− 0.13	0.90
Between-year temperature: incubation	0.01	0.10	− 0.01	0.99
Within-year precipitation: incubation	0.02	0.02	1.20	0.23
Between-year precipitation: incubation	0.11	0.07	1.51	0.13
Within-year temperature: nestlings	0.06	0.03	2.31	0.021
Between-year temperature: nestlings	0.03	0.10	0.26	0.79
Within-year precipitation: nestlings	0.00	0.02	− 0.05	0.96
Between-year precipitation: nestlings	− 0.06	0.08	− 0.75	0.45
Laying date	− 0.32	0.05	− 6.76	< 0.001
Clutch size	0.04	0.02	2.13	0.033
Female ID random	0.22
Plot ID random	0.69
Year of study random	0.43
Pseudo-R2marginal/conditional	0.02/0.22

Output of the generalized linear mixed model with Poisson error distribution and the log-link function testing how female age (categorical predictor), female body condition, the within- and between-year effects of ambient temperature and sum of precipitation experienced during the incubation and nestling period, laying date, and clutch size (all as continuous predictors), affect the number of recruits. All continuous explanatory terms were standardized. The female identity, study plot identity, and year of study were included as random factors. Significant terms P < 0.05 are in bold