Robert Abt

Led by the Department of Forest Biomaterials in collaboration with the Departments of Forestry, Business Management and Science Education at NC State University; this proposal will develop an educational program for a new generation of technology-to-commercialization researchers who will graduate with the expertise to perform risk analysis and develop risk management strategies across the value chain of biomass supply, biobased materials, and biofuels manufacturing to meet current and future national needs that will ultimately advance the nascent bioeconomy of the United States. Previous studies indicate that a limited number of companies in the forest product industry perform risk analysis for their decision-making process. We do believe that this small adoption rate is due to lack of awareness of the importance of risk analysis and risk management for effective/efficient R&D planning and investment and lack of expertise (people trained) to perform risk analysis across the whole supply chain. This proposal supports TESA in ����������������Agricultural Management and Economics���������������, in the discipline of Environmental Sciences/Management. Three Ph.D. students will be trained to analyze and propose mitigation strategies for current and future risks inherent to the bioeconomy. To considerably amplify the effect of this proposal, prospective fellows and project directors will deliver educational workshops in risk analysis and management targeting the biobased community across the U.S., while the proposal is expected to be completed in three years, project director expects to keep the program as a permanent teaching/research program. This proposed program supports USDA-NIFA Goal ����������������Catalyze exemplary and relevant research, education and extension programs���������������.

The primary objective of the proposed study is to understand the direct effects of sea level rise on markets for forest products in the United States, and through that, global markets and forest conditions nationwide

We will use the SubRegional Timber Supply model to quantify emissions leakage associated with deferred harvests for forest carbon offset supply within the Southeastern U.S. This work has relevance to U.S. climate policy and the growing forest carbon offset market.

As demands on our forests increase it is important to have tools available that can help us plan for the sustainable management of the resource. This is especially true with Southern hardwood forests that vary in species and quality, and can take decades to grow compared to softwood. The Southern Forest Resource Assessment Consortium (SOFAC) develops forest sector market models for application to forest resource assessments with the main model being the Sub- Regional Timber Supply (SRTS) model. This model has been widely used in the South and other forested regions to see how various forest conditions affect future forest resources. The core information for this model is USFS Forest Inventory and Analysis (FIA) and Timber Products Output (TPO) data. Although this model has been widely used and accepted it's analysis is mostly limited to generic hardwood and softwood groups and pulpwood and sawtimber size timber in the South. To address future resource concerns with the diverse hardwood forests species we need the ability to do more species specific and quality analyses across the hardwood regions. The goal of this project is to update the STRS model so that species specific, multi-regional scenarios can be developed to model future forest resources. This will be accomplished the following objectives. 1) Working with partners update the current SRTS model to be able to incorporate individual species and attributes across regions, including user guide. 2) Utilize new model to run pilot hardwood scenario(s) and analysis, and create document. 3) Provide hands-on training of new model 4) Through SOFAC provide support to model users and needed updates

This research extends the modeling systems developed through a series Joint Venture Agreements between the Forest Economics and Policy Research Work Unit and the North Carolina State University. The previous projects focused on developing modeling approaches for forecasting forest inventory plot conditions in response to various vectors of change including climate change, timber management, forest aging, forest disturbances, and land use changes for RPA and Futures Project Assessments. These projects successfully developed modeling frameworks for three major regions of the United States: South, North and West and analyzed a broad suite of forest forecasts under various assumptions regarding future scenarios for a variety of exogenous variables and writing reports on the relative impacts of these various factors. The current research focuses on enhancing the modeling systems and further analysis of key natural resource issues and forecasts of forest conditions in the United States.

In order to address the critical problems in wood procurement modeling for pulp and paper mills or major solid wood mills, the proposed Pilot project will develop a Decision Support System (DSS), called Stochastic Timber Supply Model (STSM), that integrates a Harvesting Schedule Model (HSM) for wood procurement with a Timber Supply Model (TSM). The purpose of this model would be to provide integrated, endogenous wood fiber supply analyses through harvest scheduling linked to timber supply and landowner characteristics. The STSM will incorporate landowner decisions in its response to market price changes, and provide explicit means to assess the variability of the input in the outcomes of TSMs. First, we will build a new DSS which users can add their forest asset data and analyze the interaction between individual supply and market variables with an option of a stochastic component. This will include market data for an individual mill or wood basket, then scaled up to a region. Second, we will investigate how minor changes in the NC State University SubRegional Timber Supply (SRTS) model inputs and assumptions can lead to different outcomes.

This project will assess the timber resource availability and sustainability in North Carolina. The specific objectives are to: ��������������� Assess historical trends in forest land-use changes and resource inventory in survey units in North Carolina using the Forest Inventory and Analysis (FIA) dataset. ��������������� Based on the current state of timber supply and demand, project annual timber inventory, removals, and prices by species types and grades using the Sub-Regional Timber Supply (SRTS) model. The projection analyses will be for the entire state, FIA survey units, and specific wood-basket regions. ��������������� Estimate demand and supply models of hardwood and softwood pulpwood markets for two micro-markets in North Carolina, and evaluate the impact of emergence of wood pellets industry in pulpwood stumpage. Based on the estimated market-specific price elasticity values, update the SRTS model (new elasticity values and 2017 TPO data) and examine the pulpwood resource sustainability in North Carolina micro-markets. ��������������� Assess the hardwood resource availability and sustainability in North Carolina from a mills������������������ perspective. We will conduct sensitivity analyses to refine just accessible hardwood resources and their sustainable uses. ��������������� [OPTIONAL] Identify the major hotspots where new forest-based industries could be best positioned to sustainably utilize forest resource feedstock for different products in North Carolina. Use a Hot Spot Analysis tool������������������available in ArcGIS������������������which calculates the Getis-Ord (GI) statistics in each FIA plot, taking into account the woody resources in its surrounding plots.

This research extends the modeling systems developed through a series Joint Venture Agreements between the Forest Economics and Policy Research Work Unit and the North Carolina State University. The previous projects focused on developing modeling approaches for forecasting forest inventory plot conditions in response to various vectors of change including climate change, timber management, forest aging, forest disturbances, and land use changes for RPA and Futures Project Assessments. These projects successfully developed modeling frameworks for three major regions of the United States: South, North and West and analyzed a broad suite of forest forecasts under various assumptions regarding future scenarios for a variety of exogenous variables and writing reports on the relative impacts of these various factors. The current research focuses on enhancing the modeling systems and further analysis of key natural resource issues and forecasts of forest conditions in the United States.

This research extends the modeling systems developed through a series Joint Venture Agreements between the Forest Economics and Policy Research Work Unit and the North Carolina State University. The previous projects focused on developing modeling approaches for forecasting forest inventory plot conditions in response to various vectors of change including climate change, timber management, forest aging, forest disturbances, and land use changes for RPA and Futures Project Assessments. These projects successfully developed modeling frameworks for three major regions of the United States: South, North and West and analyzed a broad suite of forest forecasts under various assumptions regarding future scenarios for a variety of exogenous variables and writing reports on the relative impacts of these various factors. The current research focuses on enhancing the modeling systems and further analysis of key natural resource issues and forecasts of forest conditions in the United States.

The purpose of this study is to explore the spatial and temporal forest type dynamics in the US South with a focus on pine plantations. There are three main components of this study. 1. A literature review of determinants of land use change in the US South. 2. A database of forest transitions by region (e.g. survey units) over time 3. A preliminary assessment of the potential to use these data to develop procurement strategies that would lower probability of conversion to plantations.