**4. Conclusions**

It should be noted that there has been vigorous debate on the appropriateness of actions that should result from interpreting statistical deviation in terms of process or QC [6], including that practitioners should avoid over-interpretation. This includes suggestions that unnecessary adjustments in processes could actually increase frequency of anomalous results. The implication here is that someone interpreting and developing recommendations from QC analysis who is not knowledgeable about the field of practice or study risks having a program just working toward a number, rather than truly trying to improve a process or determine the quality of environmental data for use in assessing ecological outcomes.

Recognition of the causes, magnitude, and effects of variability and error is attained through consistent observation and measurement and can simultaneously provide direction on the need for and types of corrective actions. Appropriately developed and implemented MQO, as part of consistent and routine measurement and monitoring programs, not only function to keep them on-track, but in the long run can also lead to more cost- and time-efficient processes.
