A Land Use and Resource Allocation (LURA) modeling system for projecting localized forest CO 2 effects of alternative macroeconomic futures

Abstract

The United States has recently set ambitious national goals for greenhouse gas (GHG) reductions over the coming decades. A portion of these reductions are based on expected sequestration and storage contributions from land use, land use change, and forestry (LULUCF). Significant uncertainty exists in future forest markets and thus the potential LULUCF contribution to US GHG reduction goals. This study seeks to inform the discussion by modeling US forest GHG accounts per different simulated demand scenarios across a grid of over 130,000 USDA Forest Service Forest Inventory and Analysis (FIA) forestland plots over the conterminous United States. This spatially disaggregated future supply is based on empirical yield functions for log volume, biomass and carbon. Demand data is based on a spatial database of over 2300 forest product manufacturing facilities representing 11 intermediate and 13 final solid and pulpwood products. Transportation costs are derived from fuel prices and the locations of FIA plot from which a log is harvested and mill or port destination. Trade between mills in intermediate products such as sawmill residues or planer shavings is also captured within the model formulation. The resulting partial spatial equilibrium model of the US forest sector is solved annually for the period 2015-2035 with demand shifted by energy prices and macroeconomic indicators from the US EIA's Annual Energy Outlook for a Reference, Low Economic Growth, and High Economic Growth case. For each macroeconomic scenario simulated, figures showing historic and scenario-specific live tree carnon emissions and sequestration are generated. Maps of the spatial allocation of both forest harvesting and related carbon fluxes are presented at the National level and detail is given for both regions and ownerships.

Developing Detailed Shared Socioeconomic Pathway (SSP) Narratives for the Global Forest Sector

“…Previous research has utilized global IPCC scenarios to inform global forest market projections modeling (Buongiorno et al, 2011;Raunikar et al, 2010), and results from the global analyses were then used to simulate U.S. forest harvests and product supply across alternative policy scenarios (Nepal et al, 2012). More recent research uses U.S. focused projections of macroeconomic growth, housing starts, and woody biomass demand to project localized CO 2 emissions associated with forest growth and harvests (Latta et al, 2018). However, these studies lack the level of detail presented in our FSPs, especially in terms of how income growth and SSP policy assumptions can influence technological change and forest management changes at the intensive and extensive margins.…”

“…Furthermore, there is uncertainty in how the demand for forest products will evolve in the future, which may lead to different harvest patterns and land use dynamics over time (Popp et al, 2017). Undoubtedly, societal factors like population, income, and trade, will influence the carbon sequestration potential of the forest sector, and there is a growing literature that seeks to understand how market and policy forces may drive forest carbon trajectories, even at local scales (e.g., Latta et al, 2018).…”

Can changes in forest management contribute to the reduction of CO2 in the atmosphere? Literature review, discussion and Polish example

“…For example, a more recent study by Wear and Coulston (2015) showed a decline in annual net sequestration in the U.S. by approximately 45% over the next 25 years. This includes some regions (such as the Southeastern U.S.) that transition from the net sink to the source status (Latta et al 2018). Intensifying biomass removal from forests reduces forest carbon stocks and carbon sink capacity, and thus, may partly offset the climate benefits of forest bioenergy (Haberl et al 2012;Holtsmark 2012a;Repo et al 2011Repo et al , 2012Schlamadinger et al 1995;Schulze et al 2012;Walker et al 2010;Zanchi et al 2011).…”

A Multi-Criteria Decision Analysis Approach to Facility Siting in a Wood-Based Depot-and-Biorefinery Supply Chain Model

“…Forest Service Forest Inventory and Analysis (FIA) plots represent biomass source nodes (United States Forest Service, 2016). The Land Use Resource Allocation (LURA) bioeconomic model determines the projected 20-year average annual forest residue volume available at each FIA plot based on future timber market influences (Martinkus et al, 2017a;Latta et al, 2018). Similar to Chung and Anderson (2012), each FIA point is assumed to be a forest landing and is projected onto the nearest road for use in the TTCM.…”