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SUMMARY:The least cost path from landscape genetics to landscape genomics 
 - challenges and opportunities to explore Next Generation Sequencing data 
 in a spatially explicit context
DTSTART:20180620T150000
DTEND:20180620T154500
DTSTAMP:20260916T043951Z
UID:d33f20f04fbf50ca20b0de810e7f1e5a7f572ac4c14cf42597b978b5
CATEGORIES:Conferences - Seminars
DESCRIPTION:Dr Samuel A. Cushman\nDr Samuel Cushman is the Director of the
  Center for Lanscape Science of the Rocky Mountain Research Station (RMRS)
 \, Forest and Woodland Ecosystems\, located at Flagstaff\, Arizona. He is 
 also Adjunct Professor at the Northern Arizona University. Sam is among th
 e pioneers who established the field of landscape genetics during the last
  15 years\, and his main interests are on the development of statistics a
 nd software for landscape pattern analysis\, vegetation distribution\, gro
 wth\, regeneration along biophysical gradients and effects of management\,
  fire and climate regimes on vegetation pattern and process at landscape l
 evels. Sam Cushman is also Specialty Chief Editor for Frontiers Evolutiona
 ry and Population Genetics. Prior to working for the U.S. Forest Service\,
  Sam Cushman earned a PhD at the University of Massachusetts in Organismic
  and Evolutionary Biology\, an M.S. in landscape ecology at Western Washin
 gton University\, and a B.S. in ecology at the Evergreen State College.\nD
 r Cushman will present the important transition of landscape genetics stud
 ies toward landscape genomics\, and explore a number of critical related c
 hallenges and opportunities. To-date\, landscape genetics has generally fo
 cused on spatial analyses of small genetic datasets taken from clusters of
  individuals in putative “populations” or distributed individuals acro
 ss landscapes. The recent emergence of large-scale genomic datasets contai
 ning hundreds of thousands of markers produced by next generation sequenci
 ng (NGS) methods poses tremendous opportunity and challenge to the field o
 f molecular ecology.\n\nRead : The least cost path from landscape genetics
  to landscape genomics
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STATUS:CONFIRMED
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