This study analyzed the perceptions of four stakeholder groups (forest landowners, private forest consultants, forest management researchers or educators, and federal or state agency foresters), regarding their management practices and preferred geographic growing conditions of loblolly pine in Virginia by combining AHP (analytical hierarchy process) and regression modeling. By ranking the importance of different geographical conditions for managing loblolly pine, we aimed to identify ways to support loblolly growth as a potential feedstock for biofuel generation. We achieved this through collecting survey responses from 43 stakeholders during the 2019 Virginia Forestry Summit. The results showed that the landowner, researcher/educator, and federal/state agency stakeholder groups all indicated that proximity to a mill was the most important criteria, whereas the consultant stakeholder group indicated that proximity to a road was the most important criteria. All the stakeholder groups indicated that distance from protected land was the least important criteria, followed by proximity to a water body and flat land. The regression model revealed that acres of land managed and loblolly rotation age were correlated to the weight given to the distance to a mill criterion, where increased acreage and increased rotation age were associated with an increased prioritization of proximity to a mill. Distance from protected land, the lowest-ranking criteria, was shown to have an association with the level of experience with loblolly, where more experience was associated with a lower prioritization of proximity from protected land. A contingency analysis of the self-identified level of experience with loblolly in each stakeholder group revealed that federal/state agency foresters had the most experience, followed by consultants, landowners, and researchers/educators. The research supports the importance of understanding the variation of perceptions between and within stakeholder groups in order to develop the necessary infrastructural and policy support for the sustainable development of bioenergy.
Bioenergy has been globally recognized as one of the sustainable alternatives to fossil fuels. An assured supply of biomass feedstocks is a crucial bottleneck for the bioenergy industry emanating from uncertainties in land-use changes and future prices. Analytical approaches deriving from geographical information systems (GIS)-based analysis, mathematical modeling, optimization analyses, and empirical techniques have been widely used to evaluate the potential for bioenergy feedstock. In this study, we propose a three-phase methodology integrating fuzzy logic, network optimization, and ecosystem services assessment to estimate potential bioenergy supply. The fuzzy logic analysis uses multiple spatial criteria to identify suitable biomass cultivating regions. We extract spatial information based on favorable conditions and potential constraints, such as developed urban areas and croplands. Further, the network analysis uses the road network and existing biorefineries to evaluate feedstock production locations. Our analysis extends previous studies by incorporating biodiversity and ecologically sensitive areas into the analysis, as well as incorporating ecosystem service benefits as an additional driver for adoption, ensuring that biomass cultivation will minimize the negative consequences of large-scale land-use change. We apply the concept of assessing the potential for switchgrass-based bioenergy in Missouri to the proposed methodology.
Bioenergy is an essential piece of the United States' (US) energy portfolio. However, questions surrounding bioenergy sourcing and adoption at the producer level remain persistent challenges, hampering proliferation in areas not already available. To establish new industries, individual regions must be evaluated for various bioenergy feedstocks and incorporate elements for environmental, societal, and economic growth. This study assessed the overall potential for loblolly pine (Pinus taeda) in Virginia, US, for domestic bioenergy by utilizing stakeholder preferences for site selection and biomass potential from a regional growth and yield model. Our results show that bioenergy in the state requires widespread planting of loblolly pine to provide sufficient feedstock and that additional studies on the moisture content of pine across the region should be deployed to accurately map the expected quality of the feedstock. Additional outreach to landowners will be necessary since narrower land quality preferences compared to other stakeholder groups, though these narrower preferences do lead to overall higher yields and space efficiency. The least cost transportation for collecting log residues from sites to proposed burners ranged from $4.30 to $5.97 per ton in our research area. This analysis supports policy to increase plantings of loblolly pine to supplement the state forest industry and increase bioenergy. However, differences between stakeholder groups constitute a significant roadblock to establishment and may require further policy interventions.
Bioenergy is an essential piece of the United States’ (US) energy portfolio. However, questions surrounding bioenergy sourcing and adoption at the producer level remain persistent challenges, hampering proliferation in areas not already available. To establish new industries, individual regions must be evaluated for various bioenergy feedstocks and incorporate elements for environmental, societal, and economic growth. This study assessed the overall potential for loblolly pine (Pinus taeda) in Virginia, US, for domestic bioenergy by utilizing stakeholder preferences for site selection and biomass potential from a regional growth and yield model. Our results show that bioenergy in the state requires widespread planting of loblolly pine to provide sufficient feedstock and that additional studies on the moisture content of pine across the region should be deployed to accurately map the expected quality of the feedstock. Additional outreach to landowners will be necessary since narrower land quality preferences compared to other stakeholder groups, though these narrower preferences do lead to overall higher yields and space efficiency. Our analysis supports policy to increase plantings of loblolly pine to supplement the state forest industry and increase bioenergy. However, differences between stakeholder groups constitute a significant roadblock to establishment and may require further policy interventions.
Abstract Pests and disease have become an increasingly common issue as globalized trade brings non-native species into unfamiliar systems. Emerald ash borer (Agrilus planipennis), is an Asiatic species of boring beetle currently devastating the native population of ash (Fraxinus) trees in the northern forests of the United States, with 85 million trees having already succumbed across much of the Midwest. We have developed a reaction-diffusion partial differential equation model to predict the spread of emerald ash borer over a heterogeneous 2-D landscape, with the initial ash tree distribution given by data from the Forest Inventory and Analysis. As expected, the model predictions show that emerald ash borer consumes ash which causes the local ash population to decline, while emerald ash borer spreads outward to other areas. Once the local ash population begins to decline emerald ash borer also declines due to the loss of available habitat. Our model’s strength lies with its focus on the county scale and its linkage between emerald ash borer population growth and ash density. This enables one to make accurate predictions regarding emerald ash borer spread which allows one to consider various methods of control as well as to accurately study the economic effects of emerald ash borer spread.
