Landscape Genomics: Conifer Genomics Module 16

Plant Breeding and Genomics June 21, 2013 Print Friendly and PDF

Authors:

Nicholas Wheeler, University of California Davis; David B. Neale, University of California Davis

This is the 16th module in a series of 17 developed by Conifer Translational Genomics Network (CTGN) and the Conifer Reference Genome Sequencing (PineRefSeq) Project. This module by PineRefSeq focuses on landscape genomics.

Introduction

Landscape genomics can be used to identify genetic and environmental factors that play a role in how organisms adapt to their surroundings. Landscape genomics offers land managers a tool for addressing decisions regarding reforestation, habitat restoration, conservation, and assisted migration. Difficult enough in the best of times, such decisions are complicated today by anticipated changes to our global climates in the decades to come. Landscape genomics is a newly emerging discipline that combines the fields of population genetics and landscape ecology to study patterns of demographic and adaptive genetic variation across highly diverse landscapes. The science of landscape genomics is driven by the merger of rapidly developing technologies in both genomics and GIS (Geographic Information Systems).

 

Module 16 — Landscape Genomics

See other Conifer Genomics Modules

 

 

You can also watch the video on YouTube

Download the transcript

Cite This Learning Module

Wheeler, N., and Neale, D.B. Landscape Genomics [Online Learning Module]. Pine Reference Sequence. eXtension Foundation. Available at: http://www.extension.org/pages/67919 (verified April 24, 2013)

Funding Statement

The Conifer Reference Genome Sequencing (PineRefSeq) Projectdeveloped this resources with funding provided by the USDA/NIFA Grant #2011-67009-30030. Development of this page was supported in part by the National Institute of Food and Agriculture (NIFA) Solanaceae Coordinated Agricultural Project, agreement 2009-85606-05673, administered by Michigan State University. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the United States Department of Agriculture.

Attachments:

landscape_genomics.pdf (6.01 MB)

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This work is supported by the USDA National Institute of Food and Agriculture, New Technologies for Ag Extension project.