A case history of regional geoscience data integration and analysis for the purpose of mineral resource appraisal, kasmere lake area, Manitoba

The methods used to generate a unified cell structured data base for geological, mineral occurrence, geochemical, and three different types of geophysical data are reviewed. The extremes of both excess and paucity of data were encountered and procedures for data compression and interpolation between known values were required. In the latter case a weighted moving average was used to take advantage of knowledge of the regional geological structure in an informal kriging. Classical approaches based on training data sets were investigated and found to be wanting in the area due to the inadequate mineral occurrence data base. The few data cells containing mineral occurrences were known with certainty; however, many of the cells classified as non-mineral occurrence containing, due to the immature exploration history, probably contained mineral occurrences of equal or greater significance. This inadequacy in the mineral occurrence data base confounded formal statistical analysis. An empirical scoring approach was developed which draws on general exploration criteria. This methodology, based on the geochemical and geophysical data, was used to prepare an Athabasca type uranium deposit favorability index. The favorable areas are examined in terms of the known geology. Results show that the majority fell in areas that would also be considered favorable by geologic models for Athabasca type uranium deposits. This empirical approach, based on geochemical and geophysical interpretive procedures, may have particular potential in poorly explored areas lacking good training sets.Paper presented at the 10th Geochautauqua: Computer Applications in the Earth Sciences, 23–24 October 1981, Ottawa, Canada.     

A statistical analysis of the low-energy geosynchronous plasma environment—I. Electrons

There has been a long-standing lack of detailed statistical information on the low-energy (1-eV–100-keV) geosynchronous plasma environment. In this paper, data on the electron environment between ～30 eV and 80 keV were analyzed from a statistical standpoint. Specifically, ～50 days of 10-min averages of the first 4 moments of the distribution function from the University of California at San Diego low-energy plasma detectors on the ATS-5 and ATS-6 geosynchronous satellites were analyzed in terms of: occurrence frequency, local time variations, K_p variations and variations at a given local time following injection. The 4 moments were intercompared and simple expressions capable of simulating their relationships empirically derived. In conjunction with this analysis, the accuracy of the 4-moment representation was tested and, for the electrons, found to be of value in specifying the background electron environment at geosynchronous orbit.     

The effect of earthquake duration on the damage of structures

This paper presents a theoretical analysis of the effect of duration on the damage of structures subjected to earthquakes. The earthquake excitation is modelled by a non-stationary random process whose response spectrum is probabilistically consistent with a design response spectrum specified independently of the duration. Damage is assumed to accumulate with the cyclic application of large strains in the structural members. Two types of structure are examined: one representative of a steel structure and the other reprsentative of a reinforced concrete structure. The level of expected damage is found to be a strong function of both the ductility of the response and the duration of the excitation. Results are presented for systems with linear stiffness and a particular form of softening behaviour.     

The chi-square plot: a tool for multivariate outlier recognition

In large multi-element regional surveys statistically derived threshold levels of the form that define, for example, the top 2% of the data for each element as worthy of further investigation have led to the generation of inordinately large lists of geochemical samples for detailed study. This problem is compounded when a number of geological and secondary environments exists of sufficiently different character that separate thresholds should be estimated for each. Additionally, single-element thresholds for multi-element surveys can, in certain circumstances, lead to obviously out-of-character individuals not being recognized.Numerical approaches to the problem of anomaly recognition have commonly used a principal-component or regression analysis procedure as their basis. These, as indeed do all such approaches, have a common drawback in that the outliers being sought can distort the analysis being used to detect them. In addition, regression models have the further problem that there may be outliers in both the response and explanatory variables.A relatively simple approach would be to prepare a multivariate cumulative probability plot where each multi-element geochemical sample is represented as a single value. The resulting diagram would be interpreted much as a univariate probability plot where the presence of more than one straight-line segment is taken as evidence of multiple populations, and outliers as individuals or small groups are separated from the remaining data by gaps on the plot.Such a diagram may be prepared by plotting the rank-ordered values of the generalized or Mahalanobis distance, a multivariate distance measure, versus values of the chi-square statistic. This procedure is based on the covariance matrix of the data, a measure that underlies both principal-component and regression model approaches. In order to work effectively a statistically robust starting covariance matrix is essential.The procedure is described in detail with two examples, one a synthetic bivariate data set containing known outliers, and the other a small, well studied stream sediment data set from Norway extensively used in methodological comparison studies. The result of the procedure is to identify statistical outliers, which are candidates for interpretation as true geochemical anomalies, and to isolate a multi-element subset that is representative of the geochemical background.     

Responses of Native and Invasive Floating Aquatic Plant Communities to Salinity and Desiccation Stress in the Southeastern US Coastal Floodplain Forests

Low-lying coastal ecosystems along the northern Gulf of Mexico are already experiencing the effects of elevated salinity from sea-level rise and are predicted to face extreme events such as extended saltwater inundation, intense Atlantic hurricanes, and episodic drought. The ability of coastal plant communities to survive stresses from these events depends largely on how these communities respond to the stresses. Our understanding of how plant communities dominated by native vs. invasive plants respond to extreme events is limited. Utilizing controlled greenhouse experiments, we assessed the responses of floating aquatic macrophyte communities, dominated by native or invasive plants, of the coastal floodplains, Louisiana, USA, to a gradient of chronic salinity, mimicking sea-level rise; a gradient of acute salinity, mimicking hurricane storm surges; and a gradient of desiccation stress, mimicking episodic drought. We found that salinity and desiccation stress effects on plant communities depended on the degree of plant invasion; plant community cover decreased precipitously as severity of stress increased. Specifically, extreme salinity led to a decrease in plant cover of >?90% when communities were dominated by invasive plants, whereas increased desiccation stress led to decreased plant cover of 100% when communities were dominated by native species. At low to moderate salinity, invasive dominated plant communities performed better than native dominated. These responses to salinity and desiccation stress may drive large-scale shifts in plant community structure, including loss of species. Our results underscore the importance of evaluating plant community responses to environmental extremes to determine the potential for future effects on dynamics and functioning of low-lying coastal floodplain ecosystems experiencing effects of climate change.     

Climate‐invariant area–slope relations in channel heads initiated by surface runoff

We use a dataset of 38 field‐mapped channel heads from a semi‐arid environment in western Colorado to examine relationships between contributing drainage area (A) and local hillslope gradient (θ) in relation to dominant process of initiation (surface runoff versus subsurface flow). Channel heads resulting primarily from subsurface flow have significantly greater values of A, longer basin lengths, and shallower local gradients than channel heads resulting primarily from surface runoff. We also compare the data from western Colorado to six analogous datasets from more humid regions in other portions of the United States and in southeast Australia. Comparison of the confidence intervals for the exponent values of A–θ regression lines reveals that the confidence intervals for the exponent of western Colorado channel heads with both surface and subsurface flow overlap with the confidence intervals for the exponent of all other datasets. This suggests that A–θ relationships do not differ significantly between diverse geographic locations. Copyright © 2017 John Wiley & Sons, Ltd.