Federal and state policy influence on woody biomass utilization

A considerable portion of public lands in the United States is at risk of uncharacteristically severe wildfires due to a history of fire suppression. Wildfires already have detrimental impacts on the landscape and on communities in the wildland-urban interface (WUI) due to unnatural and overstocked forests. Strategies to mitigate wildfire risk include mechanical thinning and prescribed burning in areas with high wildfire risk. The material removed is often of little or no economic value. Woody biomass utilization (WBU) could offset the costs of hazardous fuel treatments if removed material could be used for wood products, heat, or electricity production. However, barriers due to transportation costs, removal costs, and physical constraints (such as steep slopes) hinder woody biomass utilization. Various federal and state policies attempt to overcome these barriers. WBU has the potential to aid in wildfire mitigation and meet growing state mandates for renewable energy. This research utilizes interview data from individuals involved with on-the-ground woody biomass removal and utilization to determine how federal and state policies influence woody biomass utilization. Results suggest that there is not one over-arching policy that hinders or promotes woody biomass utilization, but rather woody biomass utilization is hindered by organizational constraints related to time, cost, and quality of land management agencies’ actions. However, the use of stewardship contracting (a hybrid timber sale and service contract) shows promise for increased WBU, especially in states with favorable tax policies and renewable energy mandates. Policy recommendations to promote WBU include renewal of stewardship contracting legislations and a re-evaluation of land cover types suited for WBU. Potential future policies to consider include the indirect role of carbon dioxide emission reduction activities to promote wood energy and future impacts of air quality regulations.

Risk assessment for invasive exotic plants using multi-criteria risk models

Invasive exotic plants have altered natural ecosystems across much of North America. In the Midwest, the presence of invasive plants is increasing rapidly, causing changes in ecosystem patterns and processes. Early detection has become a key component in invasive plant management and in the detection of ecosystem change. Risk assessment through predictive modeling has been a useful resource for monitoring and assisting with treatment decisions for invasive plants. Predictive models were developed to assist with early detection of ten target invasive plants in the Great Lakes Network of the National Park Service and for garlic mustard throughout the Upper Peninsula of Michigan. These multi-criteria risk models utilize geographic information system (GIS) data to predict the areas at highest risk for three phases of invasion: introduction, establishment, and spread. An accuracy assessment of the models for the ten target plants in the Great Lakes Network showed an average overall accuracy of 86.3%. The model developed for garlic mustard in the Upper Peninsula resulted in an accuracy of 99.0%. Used as one of many resources, the risk maps created from the model outputs will assist with the detection of ecosystem change, the monitoring of plant invasions, and the management of invasive plants through prioritized control efforts.

DOING MORE WITH SHORT PERIOD DATA: DETERMINING MAGNITUDES FROM CLIPPED AND OVER-RUN SEISMIC DATA AT MOUNT ST. HELENS

How can we calculate earthquake magnitudes when the signal is clipped and over-run? When a volcano is very active, the seismic record may saturate (i.e., the full amplitude of the signal is not recorded) or be over-run (i.e., the end of one event is covered by the start of a new event). The duration, and sometimes the amplitude, of an earthquake signal are necessary for determining event magnitudes; thus, it may be impossible to calculate earthquake magnitudes when a volcano is very active. This problem is most likely to occur at volcanoes with limited networks of short period seismometers. This study outlines two methods for calculating earthquake magnitudes when events are clipped and over-run. The first method entails modeling the shape of earthquake codas as a power law function and extrapolating duration from the decay of the function. The second method draws relations between clipped duration (i.e., the length of time a signal is clipped) and the full duration. These methods allow for magnitudes to be determined within 0.2 to 0.4 units of magnitude. This error is within the range of analyst hand-picks and is within the acceptable limits of uncertainty when quickly quantifying volcanic energy release during volcanic crises. Most importantly, these estimates can be made when data are clipped or over-run. These methods were developed with data from the initial stages of the 2004-2008 eruption at Mount St. Helens. Mount St. Helens is a well-studied volcano with many instruments placed at varying distances from the vent. This fact makes the 2004-2008 eruption a good place to calibrate and refine methodologies that can be applied to volcanoes with limited networks.