Skip to Main Content
Modeling individual tree survialAuthor(s): Quang V. Cao
Source: In: Proceedings of the 18th biennial southern silvicultural research conference. e-Gen. Tech. Rep. SRS-212. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southern Research Station. 614 p.
Publication Series: Proceedings - Paper (PR-P)
Station: Southern Research Station
PDF: View PDF (704.0 KB)
DescriptionInformation provided by growth and yield models is the basis for forest managers to make decisions on how to manage their forests. Among different types of growth models, whole-stand models offer predictions at stand level, whereas individual-tree models give detailed information at tree level. The well-known logistic regression is commonly used to predict tree survival probability. In addition to the maximum likelihood approach, a new approach called CDF regression was introduced here to estimate parameters of the tree survival equation.
Each of the two above approaches was evaluated as follows: (1) unadjusted, (2) disaggregated from the wholestand model, and (3) disaggregated from the combined estimator. Results from this study showed that the tree survival model, when adjusted from the combined estimator, produced the best-ranked two alternatives. The new method, CDF Regression, coupled with the combined estimator, was better than the Maximum Likelihood method in estimating parameters of the logistic regression equation.
- You may send email to email@example.com to request a hard copy of this publication.
- (Please specify exactly which publication you are requesting and your mailing address.)
- We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
- This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
CitationCao, Quang V. 2016. Modeling individual tree survival. In: Proceedings of the 18th biennial southern silvicultural research conference. e-Gen. Tech. Rep. SRS-212. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southern Research Station. 6 p.
- Additivity and maximum likelihood estimation of nonlinear component biomass models
- Additive nonlinear biomass equations: A likelihood-based approach
- A survival model for individual shortleaf pine trees in even-aged natural stands
XML: View XML