Optimal Seed Deployment Under Climate Change Using Spatial Models: Application to Loblolly Pine in the Southeastern US. Issue 519 (3rd July 2017)
- Record Type:
- Journal Article
- Title:
- Optimal Seed Deployment Under Climate Change Using Spatial Models: Application to Loblolly Pine in the Southeastern US. Issue 519 (3rd July 2017)
- Main Title:
- Optimal Seed Deployment Under Climate Change Using Spatial Models: Application to Loblolly Pine in the Southeastern US
- Authors:
- Farjat, Alfredo
Reich, Brian J.
Guinness, Joseph
Whetten, Ross
McKeand, Steven
Isik, Fikret - Abstract:
- ABSTRACT: Provenance tests are a common tool in forestry designed to identify superior genotypes for planting at specific locations. The trials are replicated experiments established with seed from parent trees collected from different regions and grown at several locations. In this work, a Bayesian spatial approach is developed for modeling the expected relative performance of seed sources using climate variables as predictors associated with the origin of seed source and the planting site. The proposed modeling technique accounts for the spatial dependence in the data and introduces a separable Matérn covariance structure that provides a flexible means to estimate effects associated with the origin and planting site locations. The statistical model was used to develop a quantitative tool for seed deployment aimed to identify the location of superior performing seed sources that could be suitable for a specific planting site under a given climate scenario. Cross-validation results indicate that the proposed spatial models provide superior predictive ability compared to multiple linear regression methods in unobserved locations. The general trend of performance predictions based on future climate scenarios suggests an optimal assisted migration of loblolly pine seed sources from southern and warmer regions to northern and colder areas in the southern USA. Supplementary materials for this article are available online.
- Is Part Of:
- Journal of the American Statistical Association. Volume 112:Issue 519(2017)
- Journal:
- Journal of the American Statistical Association
- Issue:
- Volume 112:Issue 519(2017)
- Issue Display:
- Volume 112, Issue 519 (2017)
- Year:
- 2017
- Volume:
- 112
- Issue:
- 519
- Issue Sort Value:
- 2017-0112-0519-0000
- Page Start:
- 909
- Page End:
- 920
- Publication Date:
- 2017-07-03
- Subjects:
- Assisted migration -- Bayesian statistics -- Provenance tests -- Seed source movements -- Spatial statistics
Statistics -- Periodicals
Statistics -- Periodicals
Statistiques -- Périodiques
États-Unis -- Statistiques -- Périodiques
519.5 - Journal URLs:
- http://www.jstor.org/journals/01621459.html ↗
http://www.ingentaconnect.com/content/asa/jasa ↗
http://www.tandfonline.com/loi/uasa20 ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1080/01621459.2017.1292179 ↗
- Languages:
- English
- ISSNs:
- 0162-1459
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4694.000000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 8333.xml