scholarly journals Working to Address Complex Forest Issues: A Collaborative Case Study between the Mescalero Apache Nation and USDA Forest Service

2017 ◽  
Vol 115 (5) ◽  
pp. 456-457
Author(s):  
Quentin R. Hays
2016 ◽  
Vol 62 (5) ◽  
pp. 525-534 ◽  
Author(s):  
Neil R. Ver Planck ◽  
Alexander L. Metcalf ◽  
Andrew O. Finley ◽  
James C. Finley

2003 ◽  
Vol 10 (5) ◽  
pp. 515-542 ◽  
Author(s):  
B. Kent ◽  
P. Kaval ◽  
J. Berry ◽  
M. Retzlaff ◽  
D. Hormaechea ◽  
...  

1993 ◽  
Vol 17 (4) ◽  
pp. 197-199 ◽  
Author(s):  
Coleman A. Doggett

Abstract Large-scale forest disasters require rapid quantitative damage assessments. A method is presented of quickly acquiring statistically quantifiable damage data. The method involves systematic ground sampling coupled with the use of a geographic information system (GIS), which maps damage by criteria classes and determines acreage within each criteria class. These data are then expanded by average per-acre timber volumes obtained from USDA Forest Service statewide inventories and by mean losses within defined classes to determine volume losses. Volume losses are converted to dollar values by multiplying volumes by Timber Mart South (Norris 1989) stumpage values. South. J. Appl. For. 17(4):197-199.


2016 ◽  
Author(s):  
Brett J. Butler ◽  
Brenton J. Dickinson ◽  
Jaketon H. Hewes ◽  
Sarah M. Butler ◽  
Kyle Andrejczyk ◽  
...  

1997 ◽  
Author(s):  
Richard Birdsey ◽  
Robert Mickler ◽  
David Sandberg ◽  
Richard Tinus ◽  
John Zerbe ◽  
...  

2016 ◽  
Author(s):  
D. M. Finch ◽  
D. A. Boyce ◽  
J. C. Chambers ◽  
C. J. Colt ◽  
K. Dumroese ◽  
...  

2005 ◽  
Vol 35 (10) ◽  
pp. 2382-2386 ◽  
Author(s):  
Paul C Van Deusen

Weighted estimation formulas are developed for producing stratified estimates of means and variances where data come from plots that can contain multiple forest conditions. Each plot is mapped to allow the analyst to focus on specific forest types or conditions. The weights required to accommodate mapped plots are somewhat more complicated than the weights for unmapped plots. In particular, these weights depend on the mapped condition of interest. The implication is that a single plot weight or expansion factor will not suffice for all analyses as it does for unmapped plots. The methods are demonstrated using USDA Forest Service inventory data.


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