Estimating Regional Wood Supply Based on Stakeholder Consensus for Forest Restoration in Northern Arizona

Thinning treatments focused on small-diameter trees have been designed to restore fire-adapted ponderosa pine ecosystems. Estimating the volume of wood byproducts derived from treatments can assist with agency planning of multiyear thinning contracts that sustain existing and attract new wood product businesses. Agency, local government, industry, and environmental representatives were engaged to assess the level of agreement on restoration treatments in northern Arizona. Participants unanimously agreed on appropriate management across two-thirds of the 2.4 million ac analysis area and defined desired posttreatment conditions using forest structure information derived from remotely sensed data. Results indicate that an estimated 850 million ft 3 of stem volume and 8.0 million green tn of tree crown biomass could be generated from tree thinning to reestablish fire-adapted conditions and stimulate new economic opportunities while meeting social and environmental criteria. Wood supply defined by stakeholders exceeded current utilization levels by 88% when extrapolated over the next 10 years.

[1]  Robert W. Malmsheimer,et al.  Forest service land management litigation 1989-2002 , 2006 .

[2]  W. Cohen,et al.  Estimating the age and structure of forests in a multi-ownership landscape of western Oregon, U.S.A. , 1995 .

[3]  M. M. Moore,et al.  RESTORATION OF PRESETTLEMENT AGE STRUCTURE OF AN ARIZONA PONDEROSA PINE FOREST , 1999 .

[4]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[5]  D. R. Cutler,et al.  Utah State University From the SelectedWorks of , 2017 .

[6]  Gretchen G. Moisen,et al.  Comparing five modelling techniques for predicting forest characteristics , 2002 .

[7]  W. Romme,et al.  The Interaction of Fire, Fuels, and Climate across Rocky Mountain Forests , 2004 .

[8]  Margaret M. Moore,et al.  Southwestern Ponderosa Forest Structure: Changes Since Euro-American Settlement , 1994, Journal of Forestry.

[9]  T. Swetnam,et al.  Warming and Earlier Spring Increase Western U.S. Forest Wildfire Activity , 2006, Science.

[10]  A. Taylor,et al.  Widespread Increase of Tree Mortality Rates in the Western United States , 2009, Science.

[11]  F. Fischer.  Citizens, Experts, and the Environment: The Politics of Local Knowledge , 2000 .

[12]  R. Seager,et al.  Model Projections of an Imminent Transition to a More Arid Climate in Southwestern North America , 2007, Science.

[13]  Peter Z. Fulé,et al.  Measuring forest restoration effectiveness in reducing hazardous fuels , 2001 .

[14]  Paul E. Gessler,et al.  Integrating Landsat TM and SRTM-DEM derived variables with decision trees for habitat classification and change detection in complex neotropical environments , 2008 .

[15]  C. Allen,et al.  ECOLOGICAL RESTORATION OF SOUTHWESTERN PONDEROSA PINE ECOSYSTEMS: A BROAD PERSPECTIVE , 2002 .

[16]  Julio L. Betancourt,et al.  APPLIED HISTORICAL ECOLOGY: USING THE PAST TO MANAGE FOR THE FUTURE , 1999 .

[17]  M. Nilsson,et al.  Combining national forest inventory field plots and remote sensing data for forest databases , 2008 .

[18]  John S. Dryzek,et al.  Discursive Democracy: Politics, Policy, and Political Science , 1992 .

[19]  Janet L. Ohmann,et al.  Predictive mapping of forest composition and structure with direct gradient analysis and nearest- neighbor imputation in coastal Oregon, U.S.A. , 2002 .

[20]  Daniel G. Neary,et al.  Forest bioenergy system to reduce the hazard of wildfires: White Mountains, Arizona. , 2007 .

[21]  Mark Ducey,et al.  Spatial patterns of forest characteristics in the western United States derived from inventories. , 2007, Ecological applications : a publication of the Ecological Society of America.

[22]  Charles W. McHugh,et al.  Simulation of long-term landscape-level fuel treatment effects on large wildfires , 2006 .

[23]  Moote,et al.  Issues in Forest Restoration: What to Expect from Collaboration in Natural Resource Management: A Research Synthesis for Practitioners , 2008 .

[24]  Brett G. Dickson,et al.  SRTM-DEM and Landsat ETM+ data for mapping tropical dry forest cover and biodiversity assessment in Nicaragua , 2008 .

[25]  Philip N. Omi,et al.  Effect of thinning and prescribed burning on crown fire severity in ponderosa pine forests , 2002 .

[26]  Evan E. Hjerpe,et al.  Economic impacts of southwestern national forest fuels reductions , 2008 .

[27]  Brett G. Dickson,et al.  Participatory landscape analysis to guide restoration of ponderosa pine ecosystems in the American Southwest , 2006 .

[28]  Andrew P. Robinson,et al.  The relationship between effective plant area index and Landsat spectral response across elevation, solar insolation, and spatial scales in a northern Idaho forest , 2004 .

[29]  Frank N. Laird,et al.  Participatory Analysis, Democracy, and Technological Decision Making , 1993 .

[30]  J. Evans,et al.  Gradient modeling of conifer species using random forests , 2009, Landscape Ecology.