The North Central Forest Inventory and Analysis timber product output database--a regional composite approach.

Compensating for missing plot observations in forest inventory estimation

Canadian Journal of Forest Research ◽

10.1139/x03-112 ◽

2003 ◽

Vol 33 (10) ◽

pp. 1990-1997 ◽

Cited By ~ 11

Author(s):

Ronald E McRoberts

Keyword(s):

Forest Inventory ◽

The United States ◽

Missing Observations ◽

Forest Inventory And Analysis ◽

North Central ◽

The North ◽

Private And Public ◽

Using Data ◽

Field Plots ◽

Permanent Field

The Enhanced Forest Inventory and Analysis program of the U.S. Forest Service has established a nationwide array of permanent field plots, each representing approximately 2400 ha. Each plot has been assigned to one of five interpenetrating, nonoverlapping panels, with one panel selected for measurement on a rotating basis each year. As with most large surveys, observations for some plots are not obtained. Several techniques for dealing with missing observations were compared with respect to the bias and precision of stratified estimates of mean volume per unit area using data from the State of Indiana in the north-central region of the United States for illustrative purposes. For the proportion of missing plots ranging from 1% to 10%, acceptable results were obtained for techniques that both ignored and replaced missing plot observations, but only when the techniques accounted for differences between plots in private and public ownerships.

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Determining Stocking, Forest Type, and Stand-Size Class From Forest Inventory Data

Northern Journal of Applied Forestry ◽

10.1093/njaf/9.3.82 ◽

1992 ◽

Vol 9 (3) ◽

pp. 82-89 ◽

Cited By ~ 5

Author(s):

Mark H. Hansen ◽

Jerold T. Hahn

Keyword(s):

Forest Inventory ◽

Forest Type ◽

Size Class ◽

Forest Inventory And Analysis ◽

North Central ◽

Point Field ◽

Lake States ◽

Individual Trees ◽

Field Plots

Abstract This paper describes the procedures used by North Central Forest Experiment Station's Forest Inventory and Analysis Work Unit (NCFIA) in determining stocking, forest type, and stand-size class. The stocking procedure assigns a portion of the stocking to individual trees measured on NCFIA 10-point field plots. Stand size and forest type are determined as functions of the stocking, size, and species of these trees and the physiographic classification of the site. One stand-size classification algorithm used in all states inventoried by NCFIA is described. Three separate forest type classification algorithms used in the Lake States (MI, MN, and WI), Plains States (KS, NE, ND, and SD) and Central States (IA, IL, IN, and MO) are presented. North. J. Appl. For. 9(3):82-89.

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Carbon Flux of Down Woody Materials in Forests of the North Central United States

International Journal of Forestry Research ◽

10.1155/2010/413703 ◽

2010 ◽

Vol 2010 ◽

pp. 1-9 ◽

Cited By ~ 13

Author(s):

C. W. Woodall

Keyword(s):

United States ◽

Forest Inventory ◽

Woody Debris ◽

Stand Age ◽

Future Research ◽

Study Region ◽

North Central ◽

The North ◽

C Stocks ◽

Central United States

Across large scales, the carbon (C) flux of down woody material (DWM) detrital pools has largely been simulated based on forest stand attributes (e.g., stand age and forest type). The annual change in forest DWM C stocks and other attributes (e.g., size and decay class changes) was assessed using a forest inventory in the north central United States to provide an empirical assessment of strategic-scale DWM C flux. Using DWM inventory data from the USDA Forest Service's Forest Inventory and Analysis program, DWM C stocks were found to be relatively static across the study region with an annual flux rate not statistically different from zero. Mean C flux rates across the study area were 0.25, 0.12, 0.01, and 0.04 (Mg/ha/yr) for standing live trees, standing dead trees, coarse woody debris, and fine woody debris, respectively. Flux rates varied in their both magnitude and status (emission/sequestration) by forest types, latitude, and DWM component size. Given the complex dynamics of DWM C flux, early implementation of inventory remeasurement, and relatively low sample size, numerous future research directions are suggested.

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