Balancing wildlife and bioenergy values on private forestlands in the eastern Upper Peninsula of Michigan

There is interest in developing a reliable, sustainable, domestic U.S. biofuels industry. A domestic biofuels industry has the potential to provide economic, environmental, and national security benefits on a local, regional, national, and global level. The Mascoma Corporation plans to develop a cellulosic ethanol facility in Michigan’s eastern Upper Peninsula. The primary feedstock of the plant site would be trees sourced within a 150 mile supply radius. In the eastern Upper Peninsula, this radius encompasses Alger, Chippewa, Delta, Luce, Mackinac, and Schoolcraft counties. In these six counties there are 1,320,500 acres of NIPF (non-industrial private forestlands). These acres account for 40% of the total timberland in these six counties. Thus it is likely that in order for the successful implementation of a cellulosic ethanol facility the support of local NIPF owners will be necessary. This thesis presents research on how eastern Upper Peninsula forest landowners think about and manage their land. It is based on 48 in-depth interviews with these landowners. The goal was to determine how landowner values and beliefs, on a variety of issues including wildlife management, land management, biofuels development, and climate change, are expressed through both their current management decisions, and possibly their future land management decisions. Some of the values articulated by the landowners in this study included biodiversity protection, conservation of healthy game populations, and the production of high-value timber. Understanding the values and beliefs of landowners in the eastern Upper Peninsula of Michigan is critical for successfully developing a sustainable regional woody bioenergy.

APPLICATION OF AN IMPUTATION METHOD FOR GEOSPATIAL INVENTORY OF FOREST STRUCTURAL ATTRIBUTES ACROSS MULTIPLE SPATIAL SCALES IN THE LAKE STATES, U.S.A.

Credible spatial information characterizing the structure and site quality of forests is critical to sustainable forest management and planning, especially given the increasing demands and threats to forest products and services. Forest managers and planners are required to evaluate forest conditions over a broad range of scales, contingent on operational or reporting requirements. Traditionally, forest inventory estimates are generated via a design-based approach that involves generalizing sample plot measurements to characterize an unknown population across a larger area of interest. However, field plot measurements are costly and as a consequence spatial coverage is limited. Remote sensing technologies have shown remarkable success in augmenting limited sample plot data to generate stand- and landscape-level spatial predictions of forest inventory attributes. Further enhancement of forest inventory approaches that couple field measurements with cutting edge remotely sensed and geospatial datasets are essential to sustainable forest management. We evaluated a novel Random Forest based k Nearest Neighbors (RF-kNN) imputation approach to couple remote sensing and geospatial data with field inventory collected by different sampling methods to generate forest inventory information across large spatial extents. The forest inventory data collected by the FIA program of US Forest Service was integrated with optical remote sensing and other geospatial datasets to produce biomass distribution maps for a part of the Lake States and species-specific site index maps for the entire Lake State. Targeting small-area application of the state-of-art remote sensing, LiDAR (light detection and ranging) data was integrated with the field data collected by an inexpensive method, called variable plot sampling, in the Ford Forest of Michigan Tech to derive standing volume map in a cost-effective way. The outputs of the RF-kNN imputation were compared with independent validation datasets and extant map products based on different sampling and modeling strategies. The RF-kNN modeling approach was found to be very effective, especially for large-area estimation, and produced results statistically equivalent to the field observations or the estimates derived from secondary data sources. The models are useful to resource managers for operational and strategic purposes.

From Mill Gates to Magic City: U.S. Steel and Welfare Capitalism in Gary, Indiana, 1906-1930

Gary, Indiana is a city with indelible ties to industrial paternalism. Founded in 1906 by United States Steel Corporation to house workers of the trust’s showpiece mill, the emergence of this model company town was both the culmination of lessons learned from its predecessors’ mistakes and innovative corporate planning. U.S. Steel’s Progressive Era adaptation of welfare capitalism characterized the young city through a combination of direct community involvement and laissez-faire social control. This thesis examines the reactionary implementation of paternalist policies in Gary between 1906 and 1930 through the purviews of three elements under corporate influence: housing, education, and social welfare. Each category demonstrates how both the corporation and citizenry affected and adapted Gary’s physical and cultural landscape, public perceptions, and community identity. Parallel to the popular narrative throughout is that of Gary’s African-American community, and the controversial circumstances of this population’s segregated development.