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The mixed Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.), Masson's pine (Pinus massoniana Lamb.), and hardwood forest is a major forest type in China and of national and international importance in terms of its provision of both timber and ecosystem services. However, over-harvesting has threatened its long-term productivity and sustainability. We examined the impacts of timber harvesting intensity on soil physical and chemical properties 10 and 15 years after cutting using the research plots established with a randomized block design. We considered five treatments, including clear cutting and low (13.0% removal of growing stock volume), medium (29.1%), high (45.8%), and extra-high (67.1) intensities of selective cutting with non-cutting as the control. The impact on overall soil properties derived from principal component analysis showed increasing with a rise in cutting intensity, and the most critical impact was on soil nutrients, P and K in particular. Soil nutrient loss associated with timber harvesting even at a low cutting intensity could lead to nutrient deficits in this forest although most of the soil physical properties could be recovered under the low and medium intensities of cutting. These results indicate that clear cutting and the selective cutting of extra-high and high intensities should be avoided in this type of forest in the region. [ABSTRACT FROM AUTHOR]

This study examines the statistical association of wildfire risk with climatic conditions and non-climate variables in 48 continental US states. Because the response variable "wildfire risk" is a fractional variable bounded between zero and one, we use a non-linear panel data model to recognize the bounded nature of the response variable. We estimate the non-linear panel data model (fractional probit) using the Generalized Estimating Equation (GEE) approach to ensure that the parameter estimation is efficient. The statistical model, coupled with the future climates projected by Global Climate Models (GCMs), is then employed to assess the impact of global climate change on wildfire risk. Our regression results show that wildfire risk is positively related to spring, summer, and winter temperatures and human population density whereas it is negatively associated with precipitation. The simulation results based on GCMs and the regression model indicate that climate change will intensify wildfire risk throughout the entire US, especially in the South Central region, posing an increasing wildfire threat and thus calling for more effective wildfire management strategies. [ABSTRACT FROM AUTHOR]

This work considers a two-stage stochastic integer programming (SIP) approach for optimizing fuel treatment planning under uncertainty in weather and fire occurrence for rural forests. Given a set of areas for potentially performing fuel treatment, the problem is to decide the best treatment option for each area under uncertainty in future weather and fire occurrence. A two-stage SIP model is devised whose objective is to minimize the here-and-now cost of fuel treatment in the first-stage, plus the expected future costs due to uncertain impact from potential fires in the second-stage calculated as ecosystem services losses. The model considers four fuel treatment options: no treatment, mechanical thinning, prescribed fire, and grazing. Several constraints such as budgetary and labor constraints are included in the model and a standard fire behavior model is used to estimate some of the parameters of the model such as fuel levels at the beginning of the fire season. The SIP model was applied to data for a study area in East Texas with 15 treatment areas under different weather scenarios. The results of the study show, for example, that unless the expected ecosystem services values for an area outweigh fuel treatment costs, no treatment is the best choice for the area. Thus the valuation of the area together with the probability of fire occurrence and behavior strongly drive fuel treatment choices. [ABSTRACT FROM AUTHOR]

US imports of wood and paper products from countries with emerging economies such as China and Brazil have dramatically increased in recent decades, partially displacing US domestic production. Such displacements may have reduced the direct production costs of these products, yet generated indirect economic and environmental impacts that are not well understood or taken into account. This study uses general equilibrium modeling to assess and compare the economy-wide impacts and greenhouse gas (GHG) consequences between US domestic production and imports from China and Brazil. Both the United States and China will benefit from enhancing US production of wood and paper products. In addition, strengthening the US wood products industries can help reduce GHG emissions and conserve tropical natural forests as China and Brazil import or use more tropical logs to produce wood products than the United States. These findings reveal the economic and environmental advantages of increasing US production of forest products, particularly wood products. [ABSTRACT FROM AUTHOR]

Wildfires are a threat to public safety, property, and forests. Wildfire managers deploy fighting resources to fire bases before fires occur and dispatch them to fires during the initial attack to minimize the number of escaped fires that can cause unacceptable costs and losses. To address the deployment and dispatch problem, we combine fire behavior simulation and a two-stage stochastic integer programming model called the explicit fire growth response model (EFGRM) to make deployment decisions in the first stage before fires occur and make dispatch decisions regarding the optimal mix of resources to send to multiple fires in each fire day scenario in the second stage after fires occur. The objective is to minimize the number of escaped fires, cost of resource deployment, expected suppression cost, and net value change. We use our methodology to position dozers in Texas District 12 (TX12), a fire planning unit in East Texas managed by the Texas Forest Service (TFS). The results reveal that the initial distribution of dozers in TX12 at the time of this study was not consistent with the historical density of fires. The results of our methodology suggest a different distribution of dozers across TX12. [ABSTRACT FROM AUTHOR]

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Disturbance-generated biomass results from endogenous and exogenous natural and cultural disturbances that affect the health and productivity of forest ecosystems. These disturbances can create large quantities of plant biomass on predictable cycles. A systems analysis model has been developed to quantify aspects of system capacities (harvest, transportation, and processing), spatial aspects of the biomass generation process, and deterioration impacts on biomass quality in the various inventory states (field stands, field-harvested inventories, transportation prepared inventories, and production facility inventories). Optimal decision alternatives can be used to guide responses to reclamation, utilization, mitigation, and control. This is particularly advantageous in insect and disease outbreaks, in which the process may last several years, with varying levels of intensity. The prescriptive system description, assuming capacities are fixed, results in a linear programming model. The time-dependent capacity decision model results in a mixed-integer programming model. The analytical model is developed in detail in this analysis. [ABSTRACT FROM AUTHOR]

Presents the results of a survey on African-American forestland owners in Alabama's black belt. Landowner characteristics; Stewardship of forest resources; Forest land management.