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The data presented in this article are related to the research article entitled “How is wood-based pellet production affecting forest conditions in the southeastern United States?” (Dale et al., 2017) [1]. This article describes how United States Forest Service (USFS) Forest Inventory and Analysis (FIA) data from multiple state inventories were aggregated and used to extract ten annual timberland variables for trend analysis in two case study bioenergy fuelshed areas. This dataset is made publically available to enable critical or extended analyses of changes in forest conditions, either for the fuelshed areas supplying the ports of Savannah, Georgia and Chesapeake, Virginia, or for other southeastern US forested areas contributing biomass to the export wood pellet industry. Keywords: Bioenergy, Renewable energy, Forest management, Wood pellets, Sustainability

Exports of woody pellets from the southeastern United States (US) for European power plants have expanded since 2009, leading to concerns about major negative environmental effects. US exports of wood pellets have grown from essentially nothing in 2008 to 4.6 million metric tons in 2015, with 99% of US pellets being shipped to Europe. To examine effects of this recent expansion of the pellet industry on forest conditions, we use US Department of Agriculture Forest Service (USFS) Forest Inventory and Analysis (FIA) annual survey data for 2002–2014 to analyze changes in timberland trends since 2009 for two fuelsheds supplying pellets to the ports of Chesapeake, Virginia, and Savannah, Georgia. This analysis reveals that the Chesapeake fuelshed had significant increases in acreage of large trees and harvestable carbon after 2009. Furthermore, the timberland volume within plantations increased in the Chesapeake fuelshed after 2009. The Savannah fuelshed had significant increases in volume, areas with large trees, and all carbon pools after 2008. Increases in carbon in live trees for the Chesapeake fuelshed and all carbon pools for the Savannah fuelshed for the years before and after 2009 provide empirical support to prior estimates that production of wood-based pellets in the southeast US can enhance greenhouse gas sequestration. Both fuelsheds retained more naturally regenerating stands than plantations; however the number of standing dead trees increased within naturally regenerating stands and declined within plantations (but only significantly for the Savannah fuelshed). While the decrease in the number of standing dead trees per hectare for the Savannah fuelshed plantations after 2009 warrants investigation into its effects on biodiversity, others have recommended thinning and hardwood mid-story control within pine plantations to provide habitat for regionally declining bird species, which is consistent with use of biomass for energy and reducing the risk of fire. While all energy use affects the environment, these results show that benefits accrue when sustainable forest management provides wood pellets for energy that keep fossil fuel in the ground. By contrast urbanization is the greatest cause of forest loss in the SE US. It is essential to consistently monitor and assess forest conditions to assess changes, for exports of wood-based pellets for the southern US are expected to grow. Even though use of pellets for energy has more than doubled, the pellet industry constitutes

We propose a causal analysis framework to increase understanding of land-use change (LUC) and the reliability of LUC models. This health-sciences-inspired framework can be applied to determine probable causes of LUC in the context of bioenergy. Calculations of net greenhouse gas (GHG) emissions for LUC associated with biofuel production are critical in determining whether a fuel qualifies as a biofuel or advanced biofuel category under regional (EU), national (US, UK), and state (California) regulations. Biofuel policymakers and scientists continue to discuss to what extent presumed indirect land-use change (ILUC) estimates should be included in GHG accounting for biofuel pathways. Current estimates of ILUC for bioenergy rely largely on economic simulation models that focus on causal pathways involving global commodity trade and use coarse land-cover data with simple land classification systems. This paper challenges the application of such models to estimate global areas of LUC in the absence of causal analysis. The proposed causal analysis framework begins with a definition of the change that has occurred and proceeds to a strength-of-evidence approach that includes plausibility of relationship, completeness of causal pathway, spatial co-occurrence, time order, analogous agents, simulation model results, and quantitative agent–response relationships. We discuss how LUC may be allocated among probable causes for policy purposes and how the application of the framework has the potential to increase the validity of LUC models and resolve controversies about ILUC, such as deforestation, and biofuels.

An approach for rapid appraisal of agricultural landscapes was developed and applied to the Yaqui Valley, Mexico, in order to assess progress toward sustainability. Indicators were prioritized with input from stakeholders, and then data were collected to gauge progress toward targets for those metrics. This study identifies and addresses some of the practical challenges and limitations that arise when assessments must rely on readily accessible information. The sources and quality of information to determine baseline and target values and to support future monitoring are reviewed for indicators of soil quality, productivity, biodiversity, vulnerability, poverty, transparency, and economic implications of crop diversity. Appraisal results suggest land management practices that conserve and increase the efficiency of water and nutrient use contribute to achieving goals endorsed by stakeholders. And in this arid, irrigated region, risks for soil compaction and salinization must be monitored and minimized. The approach illustrates how common gaps in reliable and scale-appropriate data can be addressed by focusing on stakeholder priorities and best available information. The approach can be applied in other regions and landscapes to identify and test strategies designed to move toward increasing agricultural sustainability.

The mpi_EPIC model employs a parallel design developed for intensive modeling.The model dramatically accelerated global high-resolution agroecosystem modeling.A case study of global simulation for a crop was conducted for productivity analysis. Agroecosystem models that can incorporate management practices and quantify environmental effects are necessary to assess sustainability-associated food and bioenergy production across spatial scales. However, most agroecosystem models are designed for a plot scale. Tremendous computational capacity on simulations and datasets is needed when large scales of high-resolution spatial simulations are conducted. We used the message passing interface (MPI) parallel technique and developed a master-slave scheme for an agroecosystem model, EPIC on global food and bioenergy studies. Simulation performance was further enhanced by applying the Vampir framework. On a Linux-based supercomputer, Cray XT7 Titan, we used 2048 cores and successfully shortened the running time from days to 30min for a global 30years of modeling of a bioenergy crop at the resolution of half-degree (62,482 grids) with the message passing interface based EPIC (mpi_EPIC). The results illustrate that mpi_EPIC using parallel design can balance simulation workloads and facilitate large-scale, high-resolution analyses of agricultural production systems, management alternatives and environmental effects.

This article presents data from a recent mail survey of forest landowners regarding their land ownership characteristics and motivations, past and future management activities, and owner perceptions of bioenergy and its impact on forests. The data presented in this article are related to the research article entitled ‘Opportunities and Attitudes of Private Forest Landowners in Supplying Woody Biomass for Renewable Energy’ [1]. The survey was conducted in the Atlantic Coastal Plain of the United States, where two primary ports exporting wood pellets to Europe are located. Specifically, the data include responses on forest characteristics, forest management activities, knowledge and interest in woody biomass for energy production, and sociodemographic variables. Additionally, landowner decisions for supplying wood for traditional forest products and biomass for energy were modeled. More than 2900 forest landowners were contacted, with 707 owners providing completed surveys. Keywords: Woody biomass supply, Bioenergy, Private forest management, Renewable fuel, Sustainability

Woody biomass has been identified as a source of dispatchable, renewable energy. Private lands supply the majority of the wood-based pellets that is produced in the southeastern United States (SE US) and shipped to countries in the European Union (EU) for energy generation. To assess the perspectives of potential suppliers of woody biomass in the SE US, nonindustrial private forest landowners were surveyed in the fuelsheds of the two primary ports for wood pellets exported to the EU. The survey assessed owners' characteristics, attitudes, and future management plans. Survey results were examined to explore the relationships among these factors and owners' intentions for providing material for wood-based energy. The results indicate that forest landowners have multiple reasons for maintaining their forest land, with more than 40% of the owners ranking timber production as a very important reason. Furthermore, the majority of landowners would be willing to provide woody biomass for producing bioenergy. Among factors that would enhance landowners' willingness to provide woody biomass for energy, technical assistance to improve stand productivity and future value was the most popular option, followed by reducing fire and disease risk, long-term markets, and high prices. Landowner willingness to provide woody material for bioenergy also varied depending on demographics including age and gender, property characteristics including holding size and distance to residence, and perceptions regarding the impact on forest value of wood pellet demand and the viability of bioenergy as an alternative to fossil energy.

The global indirect land use change (ILUC) implications of biofuel use in the United States of America (USA) from 2001 to 2010 are evaluated with a dynamic general equilibrium model. The effects of biofuels production on agricultural land area vary by year; from a net expansion of 0.17 ha per 1000 gallons produced (2002) to a net contraction of −0.13 ha per 1000 gallons (2018) in Case 1 of our simulation. In accordance with the general narrative about the implications of biofuel policy, agricultural land area increased in many regions of the world. However, oil-export dependent economies experienced agricultural land contraction because of reductions in their revenues. Reducing crude oil imports is a major goal of biofuel policy, but the land use change implications have received little attention in the literature. Simulations evaluating the effects of doubling supply elasticities for land and fossil resources show that these parameters can significantly influence the land use change estimates. Therefore, research that provides empirically-based and spatially-detailed agricultural land-supply curves and capability to project future fossil energy prices is critical for improving estimates of the effects of biofuel policy on land use.

Landscape indicators, when combined with information about environmental conditions (such as habitat potential, biodiversity, carbon and nutrient cycling, and erosion) and socioeconomic forces, can provide insights about changing ecosystem services. They also provide information about opportunities for improving natural resources management. Landscape indicators rely on data regarding land cover, land management and land functionality. Challenges in using landscape indicators to assess change and effects include (1) measures of land management and attributes that are reliable, robust and consistent for all areas on the Earth do not exist, and thus land cover is more frequently utilized; (2) multiple types of land cover and management are often found within a single landscape and are constantly changing, which complicates measurement and interpretation; and (3) while causal analysis is essential for understanding and interpreting changes in indicator values, the interactions among multiple causes and effects over time make accurate attribution among many drivers of change particularly difficult. Because of the complexity, sheer number of variables, and limitations of empirical data on land changes, models are often used to illustrate and estimate values for landscape indicators, and those models have several problems. Recommendations to improve our ability to assess the effects of changes in land management include refinement of questions to be more consistent with available information and the development of data sets based on systematic measurement over time of spatially explicit land qualities such as carbon and nutrient stocks, water and soil quality, net primary productivity, habitat and biodiversity. Well-defined and consistent land-classification systems that are capable of tracking changes in these and other qualities that matter to society need to be developed and deployed. Because landscapes are so dynamic, it is crucial to develop ways for the scientific community to work together to collect data and develop tools that will enable better analysis of causes and effects and to develop robust management recommendations that will increases land's capacity to meet societal needs in a changing world.

Indicators are needed to assess both socioeconomic and environmental sustainability of bioenergy systems. Effective indicators can help to identify and quantify the sustainability attributes of bioenergy options. We identify 16 socioeconomic indicators that fall into the categories of social well-being, energy security, trade, profitability, resource conservation, and social acceptability. The suite of indicators is predicated on the existence of basic institutional frameworks to provide governance, legal, regulatory and enforcement services. Indicators were selected to be practical, sensitive to stresses, unambiguous, anticipatory, predictive, estimable with known variability, and sufficient when considered collectively. The utility of each indicator, methods for its measurement, and applications appropriate for the context of particular bioenergy systems are described along with future research needs. Together, this suite of indicators is hypothesized to reflect major socioeconomic effects of the full supply chain for bioenergy, including feedstock production and logistics, conversion to biofuels, biofuel logistics and biofuel end uses. Ten indicators are highlighted as a minimum set of practical measures of socioeconomic aspects of bioenergy sustainability. Coupled with locally prioritized environmental indicators, we propose that these socioeconomic indicators can provide a basis to quantify and evaluate sustainability of bioenergy systems across many regions in which they will be deployed.

Land-use change (LUC) estimated by economic models has sparked intense international debate. Models estimate how much LUC might be induced under prescribed scenarios and rely on assumptions to generate LUC values. It is critical to test and validate underlying assumptions with empirical evidence. Furthermore, this modeling approach cannot answer if any specific indirect effects are actually caused by biofuel policy. The best way to resolve questions of causation is via scientific methods. Kim and Dale attempt to address the question of if, rather than how much, market-induced land-use change is currently detectable based on the analysis of historic evidence, and in doing so, explore some modeling assumptions behind the drivers of change. Given that there is no accepted approach to estimate the global effects of biofuel policy on land-use change, it is critical to assess the actual effects of policies through careful analysis and interpretation of empirical data. Decision makers need a valid scientific basis for policy decisions on energy choices.

Indicators are needed to assess environmental sustainability of bioenergy systems. Effective indicators will help in the quantification of benefits and costs of bioenergy options and resource uses. We identify 19 measurable indicators for soil quality, water quality and quantity, greenhouse gases, biodiversity, air quality, and productivity, building on existing knowledge and on national and international programs that are seeking ways to assess sustainable bioenergy. Together, this suite of indicators is hypothesized to reflect major environmental effects of diverse feedstocks, management practices, and post-production processes. The importance of each indicator is identified. Future research relating to this indicator suite is discussed, including field testing, target establishment, and application to particular bioenergy systems. Coupled with such efforts, we envision that this indicator suite can serve as a basis for the practical evaluation of environmental sustainability in a variety of bioenergy systems.

Forest industry experts were consulted on the potential for hardwood tree species to serve as feedstock for bioenergy in the southeastern United States. Hardwoods are of interest for bioenergy because of desirable physical qualities, genetic research advances, and growth potential. Yet little data is available regarding potential productivity and costs. This paper describes required operations and provides a realistic estimate of the costs of producing bioenergy feedstock based on commercial experiences. Forestry practitioners reported that high productivity rates in southeastern hardwood plantations are confined to narrow site conditions or require costly inputs. Eastern cottonwood and American sycamore grow quickly on rich bottomlands, but are also prone to pests and disease. Sweetgum is frost hardy, has few pest or disease problems, and grows across a broad range of sites, yet growth rates are relatively low. Eucalypts require fewer inputs than do other species and offer high potential productivity but are limited by frost to the lower Coastal Plain and Florida. Further research is required to study naturally regenerated hardwood biomass resources. Loblolly pine has robust site requirements, growth rates rivaling hardwoods, and lower costs of production. More time and investment in silviculture, selection, and breeding will be needed to develop hardwoods as competitive biofuel feedstock species. Because of existing stands and fully developed operations, the forestry community considers loblolly pine to be a prime candidate for plantation bioenergy in the Southeast.

Family history of hypertension (positive and negative) and gender groups were compared on cardiovascular responses at rest, during stressors and during recovery. Two tasks were employed, mental arithmetic and an anger recall interview. Both levels and reactivity measures of blood pressure, heart rate, cardiac output and total peripheral resistance were included. In addition, participants filled out several questionnaires measuring state feelings during the task and recovery periods, trait anger/hostility and emotions. Both men and women with a positive family history of hypertension exhibited higher tonic levels of blood pressure and heart rate at rest, recovery and during both tasks. They also exhibited greater heart rate reactivity during the mental arithmetic task and greater blood pressure reactivity to both tasks when post-math recovery, but not initial rest, was used as a covariate. Positive family history individuals reported less trust and gregariousness, more depression and aggression, less awareness of somatic responses to the tasks and less effort to relax during the post-task rest periods. Finally, significant correlations were found between low anger expression, low anger experience and high anger control and task SBP levels in positive family history individuals.