Table 3.

Posterior predictive checks (PPCs) of the fitted models (GLMM, generalized linear mixed model; HMM, hierarchical mixture model without environmental covariates; HMM_Chla, hierarchical mixture model with chlorophyll a covariate; HMM_Chla, _SIE , hierarchical mixture model with chlorophyll a and sea ice extent covariates). PPCs are based on 1000 repetitions of the dataset. Reported p-values correspond to Pr(T_rep > T_obs), where T is the chosen statistic, either the minimum, maximum or kurtosis of the weaning mass distribution. Extreme p-values (i.e. close to 0 or 1) betray misfit, while p-values around 0.5 indicate a good fit. A naive coefficient of determination R² for the whole model (not just for the year level) is also reported. The selected model is in bold.

statistic	GLMM	HMM	HMMChla	HMMChlaSIE
minimum	0.45	0.42	0.48	0.46
maximum	0.67	0.38	0.32	0.25
kurtosis	0.80	0.57	0.53	0.58
R2	0.07	0.31	0.33	0.33