Using gene transcription to assess ecological and anthropological stressors in brown bears

EcoHealth
By: , and 

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Abstract

Increasingly, population- and ecosystem-level health assessments are performed using sophisticated molecular tools. Advances in molecular technology enable the identification of synergistic effects of multiple stressors on the individual physiology of different species. Brown bears (Ursus arctos) are an apex predator; thus, they are ideal candidates for detecting potentially ecosystem-level systemic perturbations using molecular-based tools. We used gene transcription to analyze 130 brown bear samples from three National Parks and Preserves in Alaska. Although the populations we studied are apparently stable in abundance and exist within protected and intact environments, differences in transcript profiles were noted. The most prevalent differences were among locations. The transcript patterns among groups reflect the influence of environmental factors, such as nutritional status, disease, and xenobiotic exposure. However, these profiles also likely represent baselines for each unique environment by which future measures can be made to identify early indication of population-level changes due to, for example, increasing Arctic temperatures. Some of those environmental changes are predicted to be potentially positive for brown bears, but other effects such as the manifestation of disease or indirect effects of oceanic acidification may produce negative impacts.

Study Area

Publication type Article
Publication Subtype Journal Article
Title Using gene transcription to assess ecological and anthropological stressors in brown bears
Series title EcoHealth
DOI 10.1007/s10393-017-1287-0
Year Published 2018
Language English
Publisher Springer
Contributing office(s) Western Ecological Research Center
Description 11 p.
First page 121
Last page 131
Country United States
State Alaska
Other Geospatial Gates National Park and Preserve, Katmai National Park and Preserve, Lake Clark National Park and Preserve
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