Designing effective monitoring programs can be a significant challenge. Monitoring programs need to consider three types of protection, protection from: 1) “finding” an effect that is not real (false positive – type I statistical error); 2) from missing a real effect (false negative – type II statistical error); and from 3) pursuing an effect that while real is small enough to be meaningless. In some programs the protection is addressed for example in respect to the third type of protection, by defining a critical effect size. The key question with regard to all three is how to separate out “noise” in data due to natural variations from a “signal” that communicates a change of concern. A complex trade-off in any monitoring program is to ensure a focus is on meaningful changes and avoid chasing “ghost signals”, while still ensuring true effects aren’t missed.
There are more than a dozen cumulative effects monitoring programs across Canada which are in the process of developing triggers to adapt monitoring, and a variety of approaches and philosophies being considered within those programs. In this context, Canada’s Oil Sands Innovation Alliance (COSIA) decided to convene a workshop to bring together experts involved in developing these designs and we were delighted to facilitate their discussions seeking a common understanding of the various approaches that are currently in use, and their convergence on the principles for designing environmental monitoring triggers.