期刊
PLOS ONE
卷 9, 期 9, 页码 -出版社
PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0106374
关键词
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资金
- Colorado Parks and Wildlife Game Cash Funds
- USFWS Federal Aid Research Grants
- Colorado Parks and Wildlife Habitat Partnership Program
- Mule Deer Foundation
- Colorado Parks and Wildlife Big Game Auction and Raffle Grants
The relationships between habitat, body condition, life history characteristics, and fitness components of ungulates are interwoven and of interest to researchers as they strive to understand the impacts of a changing environment. With the increased availability of portable ultrasound machines and the refinement of hormonal assays, assessment of ungulate body condition has become an accessible monitoring strategy. We employed body condition scoring, estimation of % ingesta-free body fat (%IFBF), assessment of free thyroid hormones (FT4 and FT3), and assessment of pregnancy, as metrics to determine if landscape-level habitat treatments affected body condition of adult (>= 1.5 years old) female mule deer (Odocoileus hemionus). All body condition related metrics were measured on 2 neighboring study areas - a reference area that had received no habitat treatments and a treatment study area that had received mechanical removal of pinyon pine (Pinyus edulis) - Utah juniper (Juniperus osteosperma) forest, chemical control of weeds, and reseeding with preferred mule deer browse species. A consistent trend of higher %IFBF was observed in the treatment study area ((%) over bar IFBF = 7: 38, SD = 1.31) than in the reference study area ((%) over bar IFBF = 6.97, SD = 2.16), although variation of estimates was larger than hypothesized. A similar pattern was observed with higher thyroid hormones concentrations being observed in the treatment study area, but large amounts of variation within concentration estimates were also observed. The consistent pattern of higher body condition related estimates in our treatment study area provides evidence that large mammalian species are sensitive to landscape change, although variation within estimates underlie the challenge in detecting population level impacts stemming from environmental change.
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