Model-based time-series analysis of FIA panel data absent re-measurements / Raymond L. Czaplewski and Mike T. Thompson.

Format:

Book

Government document

Author/Creator:

Czaplewski, Raymond L., author.

Thompson, Michael T., author.

Contributor:

Rocky Mountain Research Station (Fort Collins, Colo.), issuing body.

Series:

Research paper RMRS ; 102.

Research paper RMRS ; 102

Language:

English

Subjects (All):

Forest Inventory and Analysis Program (U.S.).

Lodgepole pine--Diseases and pests--United States.

Lodgepole pine.

Lodgepole pine--Mortality--Estimates--United States--Mathematical models.

Tree declines--United States--Measurement--Mathematical models.

Tree declines.

Mountain pine beetle--United States.

Mountain pine beetle.

Time-series analysis.

Lodgepole pine--Diseases and pests.

United States.

Physical Description:

1 online resource (13 pages) : illustrations (some color).

Other Title:

Model-based time-series analysis of Forest Inventory and Analysis panel data absent re-measurements

Place of Publication:

Fort Collins, CO : United States Department of Agriculture, Forest Service, Rocky Mountain Research Station, 2013.

Summary:

An epidemic of lodgepole pine (Pinus contorta) mortality from the mountain pine beetle (Dendroctonus ponderosae) has swept across the Interior West. Aerial surveys monitor the areal extent of the epidemic, but only Forest Inventory and Analysis (FIA) field data support a detailed assessment at the tree level. Dynamics of the lodgepole pine population occur at a more rapid rate than the FIA 10-year re-measurement cycle. A model-based approach links population-level estimates from each annual FIA panel estimate. A simple multivariate model predicts the statewide rates of annual change among live uninfected trees, live infected trees, mortality trees, and standing dead trees. A multivariate weighted sum of panel estimates and model predictions of the same attributes improve estimates for each year. Biological structure incorporated into the model improves logical consistency among the various categories of tree-level estimates and smooths annual fluctuations caused by random sampling error. We present concepts in simple terms and illustrate results with FIA data from 2002 to 2008.

Notes:

Title from Web page (viewed on Nov. 6, 2013).

"May 2013."

Includes bibliographical references (page 13).

OCLC:

862167663