@article{baker_van houtven_phelan_latta_clark_austin_sodiya_ohrel_buckley_gentile_et al._2023, title={Projecting US forest management, market, and carbon sequestration responses to a high-impact climate scenario}, volume={147}, ISSN={["1872-7050"]}, url={http://dx.doi.org/10.1016/j.forpol.2022.102898}, DOI={10.1016/j.forpol.2022.102898}, abstractNote={The impact of climate change on forest ecosystems remains uncertain, with wide variation in potential climate impacts across different radiative forcing scenarios and global circulation models, as well as potential variation in forest productivity impacts across species and regions. This study uses an empirical forest composition model to estimate the impact of climate factors (temperature and precipitation) and other environmental parameters on forest productivity for 94 forest species across the conterminous United States. The composition model is linked to a dynamic optimization model of the U.S. forestry sector to quantify economic impacts of a high warming scenario (Representative Concentration Pathway 8.5) under six alternative climate projections and two socioeconomic scenarios. Results suggest that forest market impacts and consumer impacts could range from relatively large losses (−$2.6 billion) to moderate gain ($0.2 billion) per year across climate scenarios. Temperature-induced higher mortality and lower productivity for some forest types and scenarios, coupled with increasing economic demands for forest products, result in forest inventory losses by end of century relative to the current climate baseline (3%–23%). Lower inventories and reduced carbon sequestration capacity result in additional economic losses of up to approximately $4.1 billion per year. However, our results also highlight important adaptation mechanisms, such forest type changes and shifts in regional mill capacity that could reduce the impact of high impact climate scenarios.}, journal={FOREST POLICY AND ECONOMICS}, publisher={Elsevier BV}, author={Baker, Justin S. and Van Houtven, George and Phelan, Jennifer and Latta, Gregory and Clark, Christopher M. and Austin, Kemen G. and Sodiya, Olakunle E. and Ohrel, Sara B. and Buckley, John and Gentile, Lauren E. and et al.}, year={2023}, month={Feb} }
 @article{sodiya_parajuli_abt_gray_2022, title={Spatial Analysis of Forest Product Manufacturers in North Carolina}, volume={69}, ISSN={0015-749X 1938-3738}, url={http://dx.doi.org/10.1093/forsci/fxac045}, DOI={10.1093/forsci/fxac045}, abstractNote={Abstract
               Spatial analysis of industrial locations is an important tool for cluster-based economic development that helps identify hot spots for attracting new businesses in a particular region. The forest product industry in North Carolina (NC) is the top employer among all manufacturing sectors, with a substantial contribution to the state economy. Using geographic information system tools, we examined the current spatial distribution of the primary and secondary forest product manufacturers (FPM) and available forest resources to identify major hot spots in NC. Additionally, by estimating count data models, this study evaluated factors influencing the location of FPMs across counties in NC. Our results suggested that primary FPMs exhibit a higher spatial dependency relative to secondary FPMs. Similarly, regression results suggested that the counties near cities with high population, hot spots of raw materials, and better county economy are more likely to host both primary and secondary FPMs in the counties of NC. The findings of this study shed light on how the clustering of forest product manufacturing firms may influence competition between FPMs, sustainable supply of raw materials, and supply-chain networks in forest-dependent rural regions.}, number={1}, journal={Forest Science}, publisher={Oxford University Press (OUP)}, author={Sodiya, Olakunle E and Parajuli, Rajan and Abt, Robert C and Gray, Joshua}, year={2022}, month={Dec}, pages={24–36} }