The Long-term Illinois River fish population monitoring program, Annual Report

Report issued on: March 2003Annual ReportINHS Technical Report prepared for Illinois Department of Natural Resource

Estimating Life Loss for Dam Safety Risk Assessment

Estimating Life Loss for Dam Safety Risk Assessment explores the need for a new life-loss model in dam safety risk assessment, historical foundations on which that model can be built, and issues that are critical for a successful life-loss model to address. After critiquing existing life-loss models, the work presents a summary of historical insights that were derived by characterizing flood events on the level of subpopulations at risk, using nearly l 00 carefully defined variables. Building upon both conceptual and historical insights, the work culminates by presenting the conceptual basis for a new life-loss model that remains under development. Chapter I introduces the topic of dam safety risk assessment and the central role that life-loss estimation plays in that field. Chapter II discusses important preliminary considerations in model development. Chapter Ill provides a detailed review of previous life-loss models that pertained to floods, including a critique of each. Chapter IV explores the DeKay-McClelland model in detail and raises serious concerns regarding its future use. Chapter V defines nearly l 00 variables and their respective categories for use in characterizing flood events. Chapter VI provides a detailed outline of historical insights that relate to flood events in one of 18 logical categories. Chapter VII proposes the framework for a new conceptual life-loss model-a model that is still under development and has yet to be refined or offered for testing-with sufficient details to indicate how it was developed and how it might be used. Chapter VIII provides a summary, conclusions, and recommendations for future research. Appendices A through D provide material related to over 900 pages of unpublished working documents developed while characterizing 38 flood events and nearly 200 subpopulations at risk. Appendix E offers a summary of existing software that, given additional development, might prove useful to life-loss estimation in dam safety risk assessment

RETURNS TO SCALE AND SIZE IN AGRICULTURAL ECONOMICS: REPLY

Research Methods/ Statistical Methods,

An Assessment of Small Unmanned Aerial Systems in Support of Sustainable Forestry Management Initiatives

Sustainable forest management practices are receiving renewed attention in the growing effort to make efficient long-term use of natural resources. Sustainable management approaches require accurate and timely measurement of the world’s forests to monitor volume, biomass, and changes in sequestered carbon. It is in this context that remote sensing technologies, which possess the capability to rapidly capture structural data of entire forests, have become a key research area. Laser scanning systems, also known as lidar (light detection and ranging), have reached a maturity level where they may be considered a standard data source for structural measurements of forests; however, airborne lidar mounted on manned aircraft can be cost-prohibitive. The increasing performance capabilities and reduction of cost associated with small unmanned aerial systems (sUAS), coupled with the decreasing size and mass of lidar sensors, provide the potential for a cost-effective alternative. Our objectives for this study were to assess the extensibility of established airborne lidar algorithms to sUAS data and to evaluate the use of more cost-effective structure-from-motion (SfM) point cloud generation techniques from imagery obtained by the sUAS. A data collection was completed by both manned and sUAS lidar and imaging systems in Lebanon, VA and Asheville, NC. Both systems produced adequately dense point clouds with the manned system exceeding 30 pts/m^2 and the sUAS exceeding 400 pts/m^2. A cost analysis, two carbon models and a harvest detection algorithm were explored to test performance. It was found that the sUAS performed similarly on one of the two biomass models, while being competitive at a cost of $8.12/acre, compared to the manned aircraft’s cost of$8.09/acre, excluding mobilization costs of the manned system. On the biomass modeling front, the sUAS effort did not include enough data for training the second model or classifier, due to a lack of samples from data corruption. However, a proxy data set was generated from the manned aircraft, with similar results to the full resolution data, which then was compared to the sUAS data from four overlapping plots. This comparison showed good agreement between the systems when ingested into the trained airborne platform’s data model (RMSE = 1.77 Mg/ha). Producer’s accuracy, User’s accuracy, and the Kappa statistic for detection of harvested plots were 94.1%, 92.2% and 89.8%, respectively. A leave-one-out and holdout cross validation scheme was used to train and test the classifier, using 1000 iterations, with the mean values over all trials presented in this study. In the context of an investigative study, this classifier showed that the detection of harvested and non-harvested forest is possible with simple metrics derived from the vertical structure of the forest. Due to the closed nature of the forest canopy, the SfM data did not contain many ground returns, and thus, was not able to match the airborne lidar’s performance. It did, however, provide fine detail of the forest canopy from the sUAS platform. Overall, we concluded that sUAS is a viable alternative to airborne manned sensing platforms for fine-scale, local forest assessments, but there is a level of system maturity that needs to be attained for larger area applications

Salmonella enterica Serovar Typhimurium 14028s Genomic Regions Required for Colonization of Lettuce Leaves.

Contamination of edible produce leaves with human bacterial pathogens has been associated with serious disease outbreaks and has become a major public health concern affecting all aspects of the market, from farmers to consumers. While pathogen populations residing on the surface of ready-to-eat produce can be potentially removed through thorough washing, there is no disinfection technology available that effectively eliminates internal bacterial populations. By screening 303 multi-gene deletion (MGD) mutants of Salmonella enterica serovar Typhimurium (STm) 14028s, we were able to identify ten genomic regions that play a role in opening the stomatal pore of lettuce leaves. The major metabolic functions of the deleted regions are associated with sensing the environment, bacterium movement, transport through the bacterial membrane, and biosynthesis of surface appendages. Interestingly, at 21 days post inoculation, seven of these mutants showed increased population titers inside the leaf, two mutants showed similar titers as the wild type bacterium, whereas one mutant with a large deletion that includes the Salmonella pathogenicity island 2 (SPI-2) showed significantly impaired persistence in the leaf apoplast. These findings suggest that not all the genomic regions required for initiation of leaf colonization (i.e., epiphytic behavior and tissue penetration) are essential for continuing bacterial survival as an endophyte. We also observed that mutants lacking either SPI-1 (Mut3) or SPI-2 (Mut9) induce callose deposition levels comparable to those of the wild type STm 14028s; therefore, these islands do not seem to affect this lettuce defense mechanism. However, the growth of Mut9, but not Mut3, was significantly impaired in the leaf apoplastic wash fluid (AWF) suggesting that the STm persistence in the apoplast may be linked to nutrient acquisition capabilities or overall bacterial fitness in this niche, which are dependent on the gene(s) deleted in the Mut9 strain. The genetic basis of STm colonization of leaves investigated in this study provides a foundation from which to develop mitigation tactics to enhance food safety