Applied Ecosystem Services, LLC

There is no scientific criterion for soundness. The term, sound science, reportedly was created in the 1980s by tobacco industry lobbyists trying to prevent regulation of second-hand smoke. Since then the term has been used by governments, industry groups, and environmental NGOs. The term too often is interpreted as meaning data supporting a particular position on an issue. This is highly unfortunate because there is a real need to use valid scientific data and analyses as a basis for policy or regulatory decisions.

Climate warming, unpredictable weather, and other factors that you cannot control could harm your business’s profitable sustainability. Understanding environmental science and regulatory permits and compliance provide you with the knowledge and tools to quickly adapt to these changes. Acting now is especially important because the future is uncertain and the present is constantly changing. Avoiding environmental permit compliance actions is much better than resolving them after they appear. This commentary explains environmental science as it affects compliance with regulatory permit conditions and helps you defend against litigation alleging your operation adversely effects the natural environment.

How to measure sustainability comes up frequently in conversations among mining professionals. Questions asked include what protocol or algorithm should be used, and what measures should to be included. A lot of serious thought has been given this subject by experienced and insightful environmental managers. Yet there is still discomfort that the lists of measures or the procedure to be used may not be “correct.” Sport analogies may help you understand a solution process in which you can have full confidence.

When looking at streamlining the NEPA (National Environmental Policy Act) process without reducing quality everything is open to reconsideration. Quantifying subjectivity and reordering tasks can dramatically reduce the time to produce a technically sound and legally defensible EIS and Record of Decision (ROD), but there is more that can be done. Data collection and numerical modeling offer opportunities to increase EIS quality while decreasing the time involved. The data are used to characterize existing environments and predict alternative future environments.

Environmental chemistry data are expensive to obtain and valuable and need proper care in storage so they retain their value and return your investment in them. Expenses start with permit application preparation and baseline collections and continue through monitoring programs, analyses, and reporting. The proper storage of environmental data is in an appropriately designed database, but many organizations use spreadsheets instead because they are readily available and easy for individuals to learn and use.

Natural resource operators are directly affected by habitat preservation requirements for species listed under the ESA and state equivalents. One possible explanation is that environmental decision-makers do not have sufficient information, ecological training, or appropriate analytical tools so they fall back on the precautionary principle and declare that all actual and potential habitat for the species be left untouched for population sustainability. This is both unnecessary and wasteful as there are robust statistical and spatio-temporal models that can inform technically sound and legally defensible decisions, even with limited data.

Nonpoint source water pollution adversely impacting a beneficial use is regulated by discharge allocations from a Total Maximum Daily Load. Whether a waterbody requires a TMDL depends on how its condition is assessed. The Clean Water Act, as amended in 1987, specifies using environmental ambient conditions to assess waterbodies, but regulators focus on single chemical ions or compounds based on point source discharge regulations. The limitations of this approach and the benefits of a different approach are explained here.

It is widely accepted that raw data need to be converted to information (commonly by statistical analyses) and the results interpreted to form knowledge before informed decisions can be made. With biological data this process is not followed as frequently as it should. Modern spatial analyses and statistical models can provide valuable and useful information that is otherwise lost. Biological data are counts, presence/absence, proportions, and frequencies. They are not continuous variables with a true zero so the familiar parametric statistics cannot be used.

Every business complying with environmental laws can be profitable and sustainable while operating environmentally responsibly. Environmental aspects may not have the same importance to you as other business aspects, but it’s under your control to avoid issues that can cost time and money better spent elsewhere. You should take action now to limit your risk of costly or damaging environmental issues such as permit compliance enforcement. Acting now is especially important because the future is uncertain and the present is constantly changing.

Current regulation of water quality, based on the statutes they implement, fail to effectively describe the current state of water bodies. There are historical and political reasons for this condition but no excuse to continue as we have for the past almost 60 years. Our understanding of aquatic ecosystems and the development of appropriate statistical models for environmental data provide the means to more effectively regulate water quality to benefit natural ecosystems and human health.