Moose omics dataframe

With accelerated land conversion and global heating at northern latitudes,
it becomes crucial to understand, how life histories of animals in extreme
environments adapt to these changes. Animals may either adapt by adjusting
foraging behaviour or through physiological responses, including adjusting
their energy metabolism or both. Until now, it has been difficult to study
such adaptations in free ranging animals due to methodological constraints
that prevent extensive spatiotemporal coverage of ecological and
physiological data. Through a novel approach of combining
DNA-metabarcoding and nuclear magnetic resonance (NMR)-based metabolomics,
we aim to elucidate the links between diets and metabolism in Scandinavian
moose Alces alces over three biogeographic zones using a unique dataset of
265 marked individuals. Based on 17 diet items, we identified four
different classes of diet types that match browse species availability in
respective ecoregions in northern Sweden. Individuals in the boreal zone
consumed predominantly pine and had the least diverse diets, while
individuals with highest diet diversity occurred in the coastal areas.
Males exhibited lower average diet diversity than females. We identified
several molecular markers indicating metabolic constraints linked to diet
constraints in terms of food availability during winter. While animals
consuming pine had higher lipid, phospocholine and glycerophosphocholine
concentrations in their serum than other diet types, birch- and
willow/aspen-rich diets exhibit elevated concentrations of several amino
acids. The individuals with highest diet diversity had increased levels of
ketone bodies, indicating extensive periods of starvation for these
individuals. Our results show how the adaptive capacity of moose at the
eco-physiological level varies over a large eco-geographic scale and how
it responds to land use pressures. In light of extensive ongoing climate
and land use changes, these findings pave the way for future scenario
building for animal adaptive capacity.