Moose omics dataframe
Fohringer, Christian (2022), Moose omics dataframe, Dryad, Dataset, https://doi.org/10.5061/dryad.9s4mw6mfr
- 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.
Datum = capture date when animal was sampled
AgeCapt = animal age at capture
Pregnancy = pregnancy status ( (0=unknown, 1=pregn, 2=not pregn, M=male)
NrCalfs = number of calves at heel; blank fields are unknowns or males
Special = main diet type (>60%) based on diet compostion assessed via DNA-metabarcoding; 'Generalist' diets do not contain items at proportions >60%.
H_freq_all = diet diversity based on full diet composition
Height = elevation of capture location (a.s.l.)
7 main diet items included as proportions
97 metaboltes included based on the ppm value