Item talk:Q44527

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           title:
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             title:
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                 level occurrence of fungal disease in an exotic annual grass"
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usgs_staff_profile:

 meta:
   url: https://www.usgs.gov/staff-profiles/cara-v-applestein
   timestamp: '2024-01-30T09:51:42.526849'
   status_code: 200
 profile:
   name: Cara V Applestein
   name_qualifier: null
   titles:
   - Ecologist
   organizations:
   - !!python/tuple
     - Forest and Rangeland Ecosystem Science Center
     - https://www.usgs.gov/centers/forest-and-rangeland-ecosystem-science-center
   email: capplestein@usgs.gov
   orcid: 0000-0002-7923-8526
   intro_statements:
   - I am a quantitative ecologist using Bayesian methods to understand landscape
     recovery after fire in sagebrush-steppe ecosystems.
   expertise_terms:
   - Restoration
   - Fire ecology
   - Bayesian modeling
   - Invasive species
   - Landscape ecology
   professional_experience:
   - '2013-2016: Center for Natural Land Management, Conservation Project Manager,
     Temecula, CA'
   education:
   - Ph.D., Ecology, Evolution, and Behavior, Boise State University (2023)
   - M.S., Conservation Biology, University of Maryland (2012)
   - B.S., Environmental Science, Dickinson College, Carlisle, PA (2011)
   affiliations: []
   honors: []
   abstracts: []
   personal_statement: Throughout my career, I've sought to bridge the gap between
     restoration practitioners and scientists by working closely with land managers
     to provide science and predictive models useful for understanding the efficacy
     of restoration practices. Before working for USGS, I was a conservation project
     manager for the Center for Natural Land Management where I worked closely with
     land managers to research the efficacy of different seeding methods and prescribed
     fire regimes for restoring wet prairie in western Washington. My current research
     focuses on understanding weather effects on post-fire vegetation recovery, understanding
     mechanisms of invasion, and determining the utility of remote sensing products
     for land management decision.