Data on milk composition in bighorn sheep

This .csv file contains data to reproduce multivariate analyses of milk composition in bighorn sheep. We provided the R code to run most analyses in the article's Supplementary Material

Data from: Causes and short-term consequences of variation in milk composition in wild sheep

1.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. 2.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. 3.Latent variables are a powerful tool to overcome this complexity. Recent statistical advances have enabled a new class of multivariate models – Multivariate Hierarchical Modeling (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. 4.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. 5.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. 6.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. 7.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

Three-Dimensional Distribution of UBF and Nopp140 in Relationship to Ribosomal DNA Transcription During Mouse Preimplantation Development1

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Lags in phenological acclimation of mountain grasslands after recent warming

International audience1. In the current biodiversity crisis, one of the crucial questions is how quickly plant communities can acclimate to climate warming and longer growing seasons to buffer the impairment of community functioning. Answering this question is pivotal especially for mountain grasslands that experience harsh conditions but provide essential ecosystem services to people

Temporal association of ventricular arrhythmias and respiratory events in heart failure patients with central sleep apnoea

In contrast to obstructive sleep apnoea, the peak of sympathetic tone in central sleep apnoea occurs during the hyperventilation phase. To explore the temporal association of premature ventricular complex (PVC) burden in the context of the apnoea/hypopnoea-hyperpnoea cycle, the duration of apnoea/hypopnoea was defined as 100 %. We assessed the PVC burden throughout the apnoea/hypopnoea-hyperpnoea cycle during the periods of ±150 % in 50 % increments before and after the apnoea/hypopnoea phase. In this subanalysis of 54 SERVE-HF patients, PVC burden was 32 % higher in the late hyperventilation period (50–100 % after apnoea/hypopnoea) compared to the apnoea/hypopnoea phase

Energy and physiological tolerance explain multi‐trophic soil diversity in temperate mountains

International audienceAim: Although soil biodiversity is extremely rich and spatially variable, both in terms of species and trophic groups, we still know little about its main drivers. Here, we contrast four long-standing hypotheses to explain the spatial variation of soil multi-trophic diversity: energy, physiological tolerance, habitat heterogeneity and resource heterogeneity.Location: French Alps.Methods: We built on a large-scale observatory across the French Alps (Orchamp) made of seventeen elevational gradients (similar to 90 plots) ranging from low to very high altitude (280-3,160 m), and encompassing large variations in climate, vegetation and pedological conditions. Biodiversity measurements of 36 soil trophic groups were obtained through environmental DNA metabarcoding. Using a machine learning approach, we assessed (1) the relative importance of predictors linked to different ecological hypotheses in explaining overall multi-trophic soil biodiversity and (2) the consistency of the response curves across trophic groups.Results: We showed that predictors associated with the four hypotheses had a statistically significant influence on soil multi-trophic diversity, with the strongest support for the energy and physiological tolerance hypotheses. Physiological tolerance explained spatial variation in soil diversity consistently across trophic groups, and was an especially strong predictor for bacteria, protists and microfauna. The effect of energy was more group-specific, with energy input through soil organic matter strongly affecting groups related to the detritus channel. Habitat and resource heterogeneity had overall weaker and more specific impacts on biodiversity with habitat heterogeneity affecting mostly autotrophs, and resource heterogeneity affecting bacterivores, phytophagous insects, enchytraeids and saprotrophic fungi.Main Conclusions: Despite the variability of responses to the environmental drivers found across soil trophic groups, major commonalities on the ecological processes structuring soil biodiversity emerged. We conclude that among the major ecological hypotheses traditionally applied to aboveground organisms, some are particularly relevant to predict the spatial variation in soil biodiversity across the major soil trophic groups

Biogeography of intraspecific trait variability in matgrass (Nardus stricta): High phenotypic variation at the local scale exceeds large scale variability patterns

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