Observations of moose behaviour and foraging choices in summer ...
Understanding how the nutritional properties of food resources drive foraging choices is important for the management and conservation of wildlife populations. For moose (Alces alces), recent experimental and observational studies during the winter have shown macronutrient balancing between availabl...
Main Authors: | , , , , , , , |
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Format: | Dataset |
Language: | English |
Published: |
Dryad
2024
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Subjects: | |
Online Access: | https://dx.doi.org/10.5061/dryad.08kprr598 https://datadryad.org/stash/dataset/doi:10.5061/dryad.08kprr598 |
Summary: | Understanding how the nutritional properties of food resources drive foraging choices is important for the management and conservation of wildlife populations. For moose (Alces alces), recent experimental and observational studies during the winter have shown macronutrient balancing between available protein (AP) and highly metabolizable macronutrients (total non-structural carbohydrates [TNC] and lipids). Here, we combined the use of continuous-recording camera collars with plant nutrient analyses and forage availability measurements to obtain a detailed insight into the food and nutritional choices of three wild moose in Norway over a five-day period in summer. We found that moose derived their macronutrient energy primarily from carbohydrates (74.2%), followed by protein (13.1%), and lipids (12.7%). Diets were dominated by deciduous tree browse (71%). Willows (Salix spp.) were selected for and constituted 51% of the average diet. Moose consumed 25 different food items during the study period of which nine ... : Data were collected on the island of Vega (119 km2, 65°40’ N, 11°55’ E) in Nordland County, northern Norway, during the period from 1 July 2022 to 5 July 2022. Three male moose (ID: 1652,1764, E2808) between 2 and 7 years of age were outfitted with camera collars (VERTEX Plus; Vectronic Aerospace GmbH). Cameras were programmed to record 25 sec of video every three minutes during the study period. The video footage was manually analyzed and behaviours quantified as seconds of observation time in each video. ... |
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