Data from: A test of the green wave hypothesis in omnivorous brown bears across North America
Cite this dataset
Merkle, Jerod et al. (2023). Data from: A test of the green wave hypothesis in omnivorous brown bears across North America [Dataset]. Dryad. https://doi.org/10.5061/dryad.4tmpg4fgq
Abstract
Herbivorous animals tend to seek out plants at intermediate phenological states to improve energy intake while minimizing consumption of fibrous material. In some ecosystems, the timing of green-up is heterogeneous and propagates across space in a wave-like pattern, known as the green wave. Tracking the green wave allows individuals to prolong access to higher-quality forage. While there is a plethora of empirical support for such behavior in herbivorous taxa, the green wave hypothesis (GWH) is nuanced based on factors such as body morphometrics and digestive capacity. Furthermore, little is known about whether other taxa, such as omnivores, track the green wave. Our objective was to assess whether the GWH can be extended to explain the movements of omnivores. Using GPS collar data from seven populations (n = 127 individuals) of brown bears (Ursus arctos) across their entire North American range, we first tested whether bears tracked the green wave. Using conditional resource selection functions, we found that variation in proxies of vegetative forage quality better-explained movement and habitat selection than proxies of forage biomass in over half of the bears in our study, providing evidence of green wave tracking. Second, we assess factors that explained variation in green wave tracking using linear mixed-effects models. Green wave tracking in brown bears was explained by the variation in availability of green-up within spring home ranges, and how green-up transitioned across those home ranges. Our results demonstrate that the GWH can partially explain movement of a non-migratory omnivorous species, extending the generality of the GWH as a broad predictor of animal space use. The green wave is another resource wave brown bears track, and our findings help predict brown bear space use, which can be used to guide conservation and habitat restoration efforts.
Methods
This dataset was developed by merging GPS location data from collared grizzly bears with environmental data. See methods section of Bowersock et al. 2023 in Ecography for details.
Usage notes
Both datasets do not require specific programs or software to open. They are in the comma-delimited format (CSV).
Funding