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Environmental data are the foundation for all natural resource operations. They are the scientific basis for environmental impact analyses by public lands management agencies. Mining, energy generation and transmission, and livestock grazing all depend on the environmental impact assessment being based on appropriately collected, analyzed, and interpreted data. Point source water discharges require permits: a National Pollution Discharge Elimination System (NPDES) permit for discharge directly to any surface water or a Water Pollution Control Facility (WPCF) permit for discharge to the ground and not directly to surface or ground waters.
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Every company with a dozen or more employees can gain many benefits from having—and using—an environmental management system (EMS) tailored to their specific needs. The EMS does not require ISO 14001 certification to provide direct and indirect cost savings benefits.
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R.A. Fisher, a British biologist and statistician created the statistical foundation for testing experimental hypotheses in the 1930s. Environmental data are observational measurements, not experimental measurements. Therefore, the analytical models applied to experimental data produce incorrect results when applied to environmental data.
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Most people are familiar with statistical hypothesis tests such as the t-test and ANOVA to analyze whether two or more samples (from a parametric distribution) came from the same population. The nonparametric equivalents (Wilcoxon and Kruskal-Wallis tests) are less familiar but equally robust. What is not always clear is that these models are applied to one or more response variables; e.g., chemical concentrations that result from natural or anthropogenic causes. They do not answer the question of why these values were observed.
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The Resource Conservation and Recovery Act (RCRA) as implemented by EPA and state regulations requires monitoring of ground water chemistry and statistical analyses of these data. The latest revision of the EPA’s statistical guidance document is 887 pages long (plus supplements) and has been augmented by a Webinar because the statistical analyses are not simple or easily understood by non-statisticians/data analysts. Some commercial software is sold to perform these analyses, but like all other statistical software it does not ensure that the user completely understands how to select models to apply or can properly interpret the results.
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Understanding relationships between organisms and their habitats is important to operators and regulators, as well as being critical to managing species with low population levels. Pacific salmon in the Columbia River system and sage grouse and Lahontan cutthroat trout in the Great Basin are among many examples where understanding the factors limiting the presence or number of individuals in a defined area need to be quantified in a technically sound and legally defensible way.
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The relationship between a company requiring environmental permits and environmental regulators is equivalent to that of a prospective house buyer and a real estate agent. Until the early 1990s all real estate agents and brokers were required by statute to represent only the seller’s interests; most still are. This means a buyer has to be aware of the agent’s agenda (get more money for the seller and his commission) and act to protect his interests.
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Across the western US drought, wildland fires, cheatgrass, Western juniper, Lahontan cutthroat trout, bull trout, salmon, bald eagles, desert tortoise, and sage grouse all affect where and how natural resource companies operate. Project planning and approvals can be greatly facilitated by application of advanced statistical and spatial models to environmental data. Causal relationships between explanatory variables such as habitat, food, and predators to response variables (species numbers and distributions) are explained by linear regression models.
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Natural ecosystems are complex and highly variable at multiple size scales. Because of the difficulties of accurately summarizing complexity and variability in an index number, regulators often require a reference area for comparison with a proposed or reclaimed project area. Agreement on a suitable reference area may be a requirement prior to permitting or bond-release decisions for mining and logging operations. It is common for selection of an acceptable reference area to take a long time.
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Total maximum daily loads, TMDLs, are the tool used by environmental regulators to address nonpoint source pollution under the Clean Water Act.
The CWA’s policies and goals are that, “It is the national policy that programs for the control of nonpoint sources of pollution be developed and implemented in an expeditious manner so as to enable the goals of this Act to be met through the control of both point and nonpoint sources of pollution.