Ecologists seek to understand the fitness consequences of variation in physiological markers, under the hypothesis that physiological state is linked to variability in individual condition and life history. Thus, ecologists are often interested in estimating correlations between entire suites of correlated traits, or biomarkers, but sample size limitations often do not allow us to do this properly when large numbers of traits or biomarkers are considered. Latent variables are a powerful tool to overcome this complexity. Recent statistical advances have enabled a new class of multivariate models—multivariate hierarchical modelling (MHM) with latent variables—which allow to statistically estimate unstructured covariances/correlations among traits with reduced constraints on the number of degrees of freedom to account in the model. It is thus possible to highlight correlated structures in potentially very large numbers of traits. Here, we apply MHM to evaluate the relative importance of individual differences and environmental effects on milk composition and identify the drivers of this variation. We ask whether variation in bighorn sheep milk affects offspring fitness. We evaluate whether mothers show repeatable individual differences in the concentrations of 11 markers of milk composition, and we investigate the relative importance of annual variability, maternal identity and morphological traits in structuring milk composition. We then use variance estimates to investigate how a subset of repeatable milk markers influence lamb summer survival. Repeatability of milk markers ranged from 0.05 to 0.64 after accounting for year‐to‐year variations. Milk composition was weakly but significantly associated with maternal mass in June and September, summer mass gain and winter mass loss. Variation explained by year‐to‐year fluctuations ranged from 0.07 to 0.91 suggesting a strong influence of environmental variability on milk composition. Milk composition did not affect lamb survival to weaning. Using joint models in ecological, physiological or behavioural contexts has the major advantage of decomposing a (co)variance/correlation matrix while being estimated with fewer parameters than in a “traditional” mixed‐effects model. The joint models presented here complement a growing list of tools to analyse correlations at different hierarchical levels separately and may thus represent a partial solution to the conundrum of physiological complexity.
Climate change is expected to shift both the timing and duration of vegetation growth in temperate environments (Thackeray et al., 2010). Facing these changes, wild animals can modify their reproductive phenology to track vegetation availability (Parmesan, 2006;Walther et al., 2002) and match the greatest reproductive expenditure with the best food conditions, but only if cues for anticipated environmental conditions remain reliable. Mismatch refers to the desynchronized timing of critical events between interacting species (Kharouba & Wolkovich, 2020). The match-mismatch hypothesis was first proposed to explain how the growth and survival of larval cod (Gadus morhua) varied according to their synchrony with their food, plankton (Cushing, 1990). The hypothesis was extended to terrestrial environments to explain how seasonal cycles drive synchrony between different trophic levels (Stenseth & Mysterud,
Marine mammal populations worldwide greatly benefitted from conservation measures put in place since the 1970s following overexploitation, and many pinniped populations have recovered. However, threats due to bycatch, interspecific interactions or climate change remain, and detailed knowledge on vital rates, population dynamics and their responses to environmental changes is essential for efficient management and conservation of wild populations. In this study, we quantified pup abundance and survival of individually marked harbour seal (Phoca vitulina Linnaeus, 1758) pups during the preweaning period at Bic Island and Métis sites in the St. Lawrence Estuary from 1998 – 2019. We used mark-recapture models to evaluate competing hypotheses regarding variation in daily preweaning survival rates and capture probability during the pups’ first 30 days of life. Pup abundance increased from 76 (95% CI: [59, 101]) to 323 [95% CI: 233, 338] in the past two decades at Bic Island and from 66 [95% CI:47, 91] to 285 [95% CI: 204, 218] at Métis. Preweaning survival was generally higher at Bic (0.73 [95% CI: 0.58,0.82]) than at Métis (0.68 [95% CI: 0.52,0.79]). We hypothesize that differences between habitats and human disturbance contribute to lower preweaning survival at Métis, but behavioural studies are needed to understand the impacts of disturbance on mother-pup interactions during the nursing period.
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