Mapping of Forest Alliances and Associations Using Fuzzy Systems and Nearest Neighbor Classifiers

The study and management of biological communities depends on systems of classification and mapping for the organization and communication of resource information. Recent advances in remote sensing technology may enable the mapping forest plant associations using image classification techniques. But few areas outside Europe have alliances and associations described in detail sufficient to support remote sensing-based modeling. Northwestern Montana has one of the few plant association treatments in the United States compliant with the recently established National Vegetation Classification system. This project examined the feasibility of mapping forest plant associations using Landsat Enhanced Thematic Mapper data and advanced remote sensing technology and image classification techniques. Suitable reference data were selected from an extensive regional database of plot records. Fifteen percent of the plot samples were reserved for validation of map products, the remainder of plots designated as training data for map modeling. Key differentia for image classification were identified from a suite of spectral and biophysical variables. Fuzzy rules were formulated for partitioning physiognomic classes in the upper levels of our image classification hierarchy. Nearest neighbor classifiers were developed for classification of lower levels, the alliances and associations, where spectral and biophysical contrasts are less distinct. Maps were produced to reflect nine forest alliances and 24 associations across the study area. Error matrices were constructed for each map based on stratified random selections of map validation samples. Accuracy for the alliance map was estimated at 60%. Association classifiers provide between 54 and 86% accuracy within their respective alliances. Alternative techniques are proposed for aggregating classes and enhancing decision tree classifiers to model alliances and associations for interior forest types

Mu2e Technical Design Report

The Mu2e experiment at Fermilab will search for charged lepton flavor violation via the coherent conversion process mu- N --> e- N with a sensitivity approximately four orders of magnitude better than the current world's best limits for this process. The experiment's sensitivity offers discovery potential over a wide array of new physics models and probes mass scales well beyond the reach of the LHC. We describe herein the preliminary design of the proposed Mu2e experiment. This document was created in partial fulfillment of the requirements necessary to obtain DOE CD-2 approval.Comment: compressed file, 888 pages, 621 figures, 126 tables; full resolution available at http://mu2e.fnal.gov; corrected typo in background summary, Table 3.

Relationships between plant associations and environment within McDonald-Dunn Forest

I studied the relationship of environmental variables to six plant associations on McDonald and Paul M. Dunn Forests. Indirect gradient analysis was used to determine relationships. The plant associations were developed in a companion study by C.J. Hubbard (1991). McDonald-Dunn Forests are located north and northwest of Corvallis, Oregon. The Forests comprise approximately 11,000 acres. These lands are owned by Oregon State University and managed by a staff within the College of Forestry. This study, and the companion study by Hubbard (1991), was funded and supported by the Forest management team in order to provide information that would facilitate a more integrated-resource management process. Data for this study was collected on one hundred and fifteen plots stratified to represent the diversity of physiography, soils series, and timber types found within the Forest. Plots were located within as mature a stand condition as could be found, considering past disturbance. Data collected on each 5,382 square foot plot (500 square meters) included physiography (e.g., elevation, slope, and aspect) ; vegetation cover (e.g., grass, forbs, shrubs, and trees); and soils (e.g., soils series, texture, and depth). Other variables used in this study were taken from the Forest's 1985 timber inventory. Inventory variables included total live basal area for conifers, periodic annual increment, and height and diameter for conifers. Environmental conditions vary within McDonald and Dunn Forests. Elevations increase generally toward the northwestern portion of McDonald Forest, especially toward McCulloch peak. Elevations decrease toward the southern portion of McDonald Forest. The Dunn Forest has lower elevations than McDonald Forest. Elevations decrease to the north within the Dunn Forest from Forest Peak to the lower Soap Creek drainage. Slope, rock percent, baregroud percent, and gravel percent also increase as elevations increase. There are relationships between environmental variables and plant associations within McDonald-Dunn Forest. The structure and composition of the vegetation occur in response to environmental conditions. Elevation, direction and angle of slope, quality of soil, and especially direct solar radiation share in explaining the variability of vegetative structive and composition within the McDonald-Dunn Forests. The underlying environmental gradient for McDonald-Dunn Forests is a light-influenced gradient. Elevation, slope, aspect, and amount of solar radiation have all interacted for eons to influence the soil development and vegetation gradient as it exists today

Laboratory Piping Tests on Fine Gravel

Results of an experimental study are presented in which the horizontal, critical gradient required for backward erosion piping of fine gravel was measured. A horizontal flume was constructed that allowed samples to be subjected to a vertical confining stress and unidirectional flow. The seepage gradient was gradually increased during each test, while the sample was monitored with an array of pore pressure transducers as well as visually through a clear acrylic top. The maximum, global gradient required during each test for piping to initiate and progress through the sample was recorded as the critical gradient. Sixteen tests were conducted. Values of the critical gradient were found to vary from a minimum of 0.30 in a loose state to a maximum of 0.51 in a dense state. The results of the experiments were compared to the predictive methods of Sellmeijer (original), Sellmeijer et al. (with multivariate adjustment), Schmertmann, Hoffmans, Lane, and Bligh. Only the method proposed by Schmertmann compared favorably with the experimental results.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Mu2e Run I Sensitivity Projections for the Neutrinoless mu(-) -> e(-) Conversion Search in Aluminum

The Mu2e experiment at Fermilab will search for the neutrinoless μ−→e− conversion in the field of an aluminum nucleus. The Mu2e data-taking plan assumes two running periods, Run I and Run II, separated by an approximately two-year-long shutdown. This paper presents an estimate of the expected Mu2e Run I search sensitivity and includes a detailed discussion of the background sources, uncertainties of their prediction, analysis procedures, and the optimization of the experimental sensitivity. The expected Run I 5σ discovery sensitivity is Rμe=1.2×10−15, with a total expected background of 0.11±0.03 events. In the absence of a signal, the expected upper limit is Rμe&lt;6.2×10−16 at 90% CL. This represents a three order of magnitude improvement over the current experimental limit of Rμe&lt;7×10−13 at 90% CL set by the SINDRUM II experiment.</jats:p