scholarly journals A Unique Academic–Government Collaboration Yields First Report of Detailed Habitat Description for Haemaphysalis longicornis (Ixodida: Ixodidae) in Madison County, KY

Author(s):  
J T Vogt ◽  
B D Allen ◽  
D Paulsen ◽  
R T Trout Fryxell

Abstract Haemaphysalis longicornis Neumann, Asian longhorned tick, was collected in Madison County, Kentucky, United States as part of an ongoing collaborative-tick surveillance project. This is the first collection of this invasive tick that includes ancillary data on habitat and landscape features derived from the USDA Forest Service, Forest Inventory and Analysis program.

2005 ◽  
Vol 35 (12) ◽  
pp. 2968-2980 ◽  
Author(s):  
Ronald E McRoberts ◽  
Geoffrey R Holden ◽  
Mark D Nelson ◽  
Greg C Liknes ◽  
Dale D Gormanson

Forest inventory programs report estimates of forest variables for areas of interest ranging in size from municipalities, to counties, to states or provinces. Because of numerous factors, sample sizes are often insufficient to estimate attributes as precisely as is desired, unless the estimation process is enhanced using ancillary data. Classified satellite imagery has been shown to be an effective source of ancillary data that, when used with stratified estimation techniques, contributes to increased precision with little corresponding increase in cost. Stratification investigations conducted by the Forest Inventory and Analysis program of the USDA Forest Service are reviewed, and a new approach to stratification using satellite imagery is proposed. The results indicate that precision may be substantially increased for estimates of both forest area and volume per unit area.


2004 ◽  
Vol 18 (1) ◽  
pp. 23-46 ◽  
Author(s):  
Ronald E. McRoberts ◽  
William H. McWilliams ◽  
Gregory A. Reams ◽  
Thomas L. Schmidt ◽  
Jennifer C. Jenkins ◽  
...  

2002 ◽  
Vol 17 (4) ◽  
pp. 207-208
Author(s):  
David L. Azuma ◽  
Larry Bednar

Abstract This note outlines a method for evaluating plot size selection for an inventory of western juniper woodlands in eastern Oregon. The Forest Inventory and Analysis (FIA) program of the USDA Forest Service in Portland, Oregon, used this method to evaluate several plot sizes to measure seedlings and saplings in the 1998 inventory of eastern Oregon. By choosing a 5 m radius plot, the probability of tallying no seedlings or saplings on four subplots is less than 10% for the three sample densities (0.01, 0.02, and 0.03 trees/m2) used. West. J. Appl. For. 17(4):207–208.


1991 ◽  
Vol 8 (2) ◽  
pp. 47-57 ◽  
Author(s):  
Jerold T. Hahn ◽  
Mark H. Hansen

Abstract This paper presents tree volume models developed for major timber species in the Central States (Indiana, Illinois, Missouri, and Iowa). Models for estimating gross tree volume (either cubic foot or board foot International ¼-in. log rule) and percent cull were developed for 23 species or species groups. These models estimate volume based on observed dbh and tree site index. Nonlinear regression techniques were used to fit a Weibull-type function to estimate gross volume with a data set containing observations from more than 50,000 trees measured throughout the region. A simple linear model was used to estimate percent cull in a tree for each of several tree classes. These models are being used in the statewide inventories now underway in Missouri and Iowa and may be used by anyone desiring volume-per-tree estimates that are comparable to USDA Forest Service Forest Inventory and Analysis estimates in these areas. North. J. Appl. For. 8(2):47-57


1998 ◽  
Vol 22 (4) ◽  
pp. 216-221 ◽  
Author(s):  
W.A. Bechtold ◽  
S.J. Zarnoch ◽  
W.G. Burkman

Abstract Equations used by USDA Forest Service Forest Inventory and Analysis projects to predict individual tree heights on the basis of species and dbh were improved by the addition of mean overstory height. However, ocular estimates of total height by field crews were more accurate than the statistically improved models, especially for hardwood species. Height predictions from the improved equations attained the desired measurement quality objective only 57% of the time, while ocular estimates achieved the desired accuracy 75% of the time. South. J. Appl. For. 22(4):216-221.


1992 ◽  
Vol 16 (2) ◽  
pp. 82-88
Author(s):  
Dennis M. May ◽  
Chris B. LeDoux

Abstract Reported forest inventory statistics gathered by the USDA Forest Service, Southern Forest Experiment Station, Forest Inventory and Analysis (SOFIA) have been criticized because not all of the inventory volume reported is truly available for harvest. In response to this criticism, a procedure has been developed for assessing timber availability from reported inventory statistics for upland hardwood forests. The procedure uses forest inventory and ownership statistics gathered by SOFIA, a stump-to-mill cost prediction model developed by the USDA Forest Service, Northeastern Forest Experiment Station, and published wood price reports. Under the specific assumptions and conditions set forth in a demonstration of the procedure, a quarter of Tennessee's reported upland hardwood forest, containing about 40% of the reported inventory volume, was estimated to be available for harvest. The usefulness of the procedure in assessing available timber supplies for individual mills was also demonstrated. South. J. Appl. For. 16(2):82-88.


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.


Ecosphere ◽  
2011 ◽  
Vol 2 (1) ◽  
pp. art6 ◽  
Author(s):  
Linda S. Heath ◽  
James E. Smith ◽  
Christopher W. Woodall ◽  
David L. Azuma ◽  
Karen L Waddell

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