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.

AN EXPERIMENTAL STUDY OF PARTIAL LOW RISK DEPLOYMENT IN A FIXED VEHICLE ENVIRONMENT

This study will look at the passenger air bag (PAB) performance in a fix vehicle environment using Partial Low Risk Deployment (PLRD) as a strategy. This development will follow test methods against actual baseline vehicle data and Federal Motor Vehicle Safety Standards 208 (FMVSS 208). FMVSS 208 states that PAB compliance in vehicle crash testing can be met using one of three deployment methods. The primary method suppresses PAB deployment, with the use of a seat weight sensor or occupant classification sensor (OCS), for three-year old and six-year old occupants including the presence of a child seat. A second method, PLRD allows deployment on all size occupants suppressing only for the presents of a child seat. A third method is Low Risk Deployment (LRD) which allows PAB deployment in all conditions, all statures including any/all child seats. This study outlines a PLRD development solution for achieving FMVSS 208 performance. The results of this study should provide an option for system implementation including opportunities for system efficiency and other considerations. The objective is to achieve performance levels similar too or incrementally better than the baseline vehicles National Crash Assessment Program (NCAP) Star rating. In addition, to define systemic flexibility where restraint features can be added or removed while improving occupant performance consistency to the baseline. A certified vehicles’ air bag system will typically remain in production until the vehicle platform is redesigned. The strategy to enable the PLRD hypothesis will be to first match the baseline out of position occupant performance (OOP) for the three and six-year old requirements. Second, improve the 35mph belted 5th percentile female NCAP star rating over the baseline vehicle. Third establish an equivalent FMVSS 208 certification for the 25mph unbelted 50th percentile male. FMVSS 208 high-speed requirement defines the federal minimum crash performance required for meeting frontal vehicle crash-test compliance. The intent of NCAP 5-Star rating is to provide the consumer with information about crash protection, beyond what is required by federal law. In this study, two vehicles segments were used for testing to compare and contrast to their baseline vehicles performance. Case Study 1 (CS1) used a cross over vehicle platform and Case Study 2 (CS2) used a small vehicle segment platform as their baselines. In each case study, the restraints systems were from different restraint supplier manufactures and each case contained that suppliers approach to PLRD. CS1 incorporated a downsized twins shaped bag, a carryover inflator, standard vents, and a strategic positioned bag diffuser to help disperse the flow of gas to improve OOP. The twin shaped bag with two segregated sections (lobes) to enabled high-speed baseline performance correlation on the HYGE Sled. CS2 used an A-Symmetric (square shape) PAB with standard size vents, including a passive vent, to obtain OOP similar to the baseline. The A-Symmetric shape bag also helped to enabled high-speed baseline performance improvements in HYGE Sled testing in CS2. The anticipated CS1 baseline vehicle-pulse-index (VPI) target was in the range of 65-67. However, actual dynamic vehicle (barrier) testing was overshadowed with the highest crash pulse from the previous tested vehicles with a VPI of 71. The result from the 35mph NCAP Barrier test was a solid 4-Star (4.7 Star) respectfully. In CS2, the vehicle HYGE Sled development VPI range, from the baseline was 61-62 respectively. Actual NCAP test produced a chest deflection result of 26mm versus the anticipated baseline target of 12mm. The initial assessment of this condition was thought to be due to the vehicles significant VPI increase to 67. A subsequent root cause investigation confirmed a data integrity issue due to the instrumentation. In an effort to establish a true vehicle test data point a second NCAP test was performed but faced similar instrumentation issues. As a result, the chest deflect hit the target of 12.1mm; however a femur load spike, similar to the baseline, now skewed the results. With noted level of performance improvement in chest deflection, the NCAP star was assessed as directional for 5-Star capable performance. With an actual rating of 3-Star due to instrumentation, using data extrapolation raised the ratings to 5-Star. In both cases, no structural changes were made to the surrogate vehicle and the results in each case matched their perspective baseline vehicle platforms. These results proved the PLRD is viable for further development and production implementation.

FLOOD RISK ASSESSMENT UNDER HISTORICAL AND PREDICTED LAND USE CHANGE USING CONTINUOUS HYDROLOGIC MODELING

Current procedures for flood risk estimation assume flood distributions are stationary over time, meaning annual maximum flood (AMF) series are not affected by climatic variation, land use/land cover (LULC) change, or management practices. Thus, changes in LULC and climate are generally not accounted for in policy and design related to flood risk/control, and historical flood events are deemed representative of future flood risk. These assumptions need to be re-evaluated, however, as climate change and anthropogenic activities have been observed to have large impacts on flood risk in many areas. In particular, understanding the effects of LULC change is essential to the study and understanding of global environmental change and the consequent hydrologic responses. The research presented herein provides possible causation for observed nonstationarity in AMF series with respect to changes in LULC, as well as a means to assess the degree to which future LULC change will impact flood risk. Four watersheds in the Midwest, Northeastern, and Central United States were studied to determine flood risk associated with historical and future projected LULC change. Historical single framed aerial images dating back to the mid-1950s were used along with Geographic Information Systems (GIS) and remote sensing models (SPRING and ERDAS) to create historical land use maps. The Forecasting Scenarios of Future Land Use Change (FORE-SCE) model was applied to generate future LULC maps annually from 2006 to 2100 for the conterminous U.S. based on the four IPCC-SRES future emission scenario conditions. These land use maps were input into previously calibrated Soil and Water Assessment Tool (SWAT) models for two case study watersheds. In order to isolate effects of LULC change, the only variable parameter was the Runoff Curve Number associated with the land use layer. All simulations were run with daily climate data from 1978-1999, consistent with the 'base' model which employed the 1992 NLCD to represent 'current' conditions. Output daily maximum flows were converted to instantaneous AMF series and were subsequently modeled using a Log-Pearson Type 3 (LP3) distribution to evaluate flood risk. Analysis of the progression of LULC change over the historic period and associated SWAT outputs revealed that AMF magnitudes tend to increase over time in response to increasing degrees of urbanization. This is consistent with positive trends in the AMF series identified in previous studies, although there are difficulties identifying correlations between LULC change and identified change points due to large time gaps in the generated historical LULC maps, mainly caused by unavailability of sufficient quality historic aerial imagery. Similarly, increases in the mean and median AMF magnitude were observed in response to future LULC change projections, with the tails of the distributions remaining reasonably constant. FORE-SCE scenario A2 was found to have the most dramatic impact on AMF series, consistent with more extreme projections of population growth, demands for growing energy sources, agricultural land, and urban expansion, while AMF outputs based on scenario B2 showed little changes for the future as the focus is on environmental conservation and regional solutions to environmental issues.

DEVELOPMENT AND VALIDATION OF THE ANTERIOR CRUCIATE LIGAMENT INJURY-RISK-ESTIMATION QUIZ (ACL-IQ)

Over 2 million Anterior Cruciate Ligament (ACL) injuries occur annually worldwide resulting in considerable economic and health burdens (e.g., suffering, surgery, loss of function, risk for re-injury, and osteoarthritis). Current screening methods are effective but they generally rely on expensive and time-consuming biomechanical movement analysis, and thus are impractical solutions. In this dissertation, I report on a series of studies that begins to investigate one potentially efficient alternative to biomechanical screening, namely skilled observational risk assessment (e.g., having experts estimate risk based on observations of athletes movements). Specifically, in Study 1 I discovered that ACL injury risk can be accurately and reliably estimated with nearly instantaneous visual inspection when observed by skilled and knowledgeable professionals. Modern psychometric optimization techniques were then used to develop a robust and efficient 5-item test of ACL injury risk prediction skill—i.e., the ACL Injury-Risk-Estimation Quiz or ACL-IQ. Study 2 cross-validated the results from Study 1 in a larger representative sample of both skilled (Exercise Science/Sports Medicine) and un-skilled (General Population) groups. In accord with research on human expertise, quantitative structural and process modeling of risk estimation indicated that superior performance was largely mediated by specific strategies and skills (e.g., ignoring irrelevant information), independent of domain general cognitive abilities (e.g., metal rotation, general decision skill). These cognitive models suggest that ACL-IQ is a trainable skill, providing a foundation for future research and applications in training, decision support, and ultimately clinical screening investigations. Overall, I present the first evidence that observational ACL injury risk prediction is possible including a robust technology for fast, accurate and reliable measurement—i.e., the ACL-IQ. Discussion focuses on applications and outreach including a web platform that was developed to house the test, provide a repository for further data collection, and increase public and professional awareness and outreach (www.ACL-IQ.org). Future directions and general applications of the skilled movement analysis approach are also discussed.