1. Monitoring Principles Stella Swanson, Ph.D.

2. Principle #1: Know Why We Are Monitoring Four basic reasons to monitor:  Compliance Monitoring: to demonstrate compliance with license requirements  Monitoring in Support of Certification: e.g. ISO; reclamation certificate  Operational Monitoring for Adaptive Management: e.g. effluent treatment data in support of continuous improvement goals of the Environmental Management Plan  Regional Cumulative Effects: e.g. joint industry/government studies of airsheds

3. Principle #2: Monitoring Is Not Research Monitoring cannot answer all questions. It is important to know when a question must be answered by research.

4. Research Versus Monitoring Research Objective: investigate fundamental scientific questions Focus: test theory Outcomes: scientific papers, further development of theory Applications: input to monitoring programs, models, design of mitigation, reclamation refinements to regulations Monitoring Objective: demonstrate effectiveness of environmental management and regulations Focus: specific questions regarding status, trends or compliance Outcomes: databases, monitoring reports Applications: feedback to operations

5. Research Versus Monitoring Example Research Objective: study the effects of naphthenic acids plus salinity Focus: test Hypothesis that naphthenic acids plus salinity will act together to cause more effects than either one separately by conducting laboratory and field observations Applications: predicting multiple stressor effects Monitoring Objective: test toxicity of pit lake water using standard test species Focus: confirm predictions developed from research Applications: feedback to EMS and decisions re: requirements for treatment and/or additional dilution of pit lake water

6. Research Versus Monitoring Quick-Check If it’s an interesting “what if” question, it’s probably research If it’s a question of “let’s check to be sure” it’s probably monitoring

7. When Will Research Be Required? examples of questions that cannot be answered without research: –Baseline: year-to-year variation in phytoplankton populations in regional lakes –Monitoring: what is the cause/effect relationship between variation in zooplankton community structure and exposure to OSPW

8. Principle #3: Know the Questions We are Asking Monitoring must address specific questions Three main categories: 1. Status: point-in-time 2. Trends: temporal and spatial 3. Effects: project effects; cumulative effects

9. Status Questions - Examples Compliance monitoring: Are monthly means and yearly maximum within license limits? Certification monitoring: Do littoral zone performance criteria (e.g. macrophyte biomass) meet design requirements? Operational monitoring: Did the adjustment to the flow- through rate produce the expected results? Regional monitoring: Did the unusually wet spring affect the length of time that turbidity persisted in the lake?

10. Trend Questions - Examples Compliance monitoring: Are there seasonal trends in parameters that are governed by license limits? Certification monitoring: Is macrophyte cover and benthic invertebrate biomass in the lake increasing as predicted? Operational monitoring: Has the flow-through rate adjustment made because of site-wide water management constraints affected naphthenic acid degradation rate? Regional monitoring: Have there been similar year-to-year trends in zooplankton populations in regional lakes as has been observed in the pit lake?

11. Effects Questions - Examples Compliance monitoring: Do chronic toxicity test results using the required suite of tests stay within license requirements? Certification monitoring: Do long-term monitoring quadrats in the littoral zone show the expected gradual build-up of a detrital layer on the sediments? Operational monitoring: Does the number of waterfowl interactions with pit lake water and sediments warrant change in mitigation measures ? Regional monitoring: Has there been a statistically significant change in fish growth rates or age distribution over the past 5 years in regional lakes compared to the pit lake?

12. Principle #4: Be Clear About Purpose of Indicators Intrinsic importance; e.g. waterfowl Early warning; e.g. acute toxicity tests minimal time lag in response to stress discrimination low screening tool: accept false positives Sensitive indicator; e.g. proportion of metal-sensitive invertebrate species high fidelity in showing adverse effect must be relevant to state of ecosystem Process/functional indicator; e.g. primary production

13. Principle #5: Use Consistent Criteria for Selecting Indicators High Signal-to-Noise Ratio Rapid Response Reliability/Specificity of Response Ease/Economy of Monitoring Ecological Relevance Effectiveness of Feedback to Regulation and Adaptive Management

14. Application of Criteria for Indicator Selection Varies Compliance monitoring: rapid response Certification monitoring: reliability Operational monitoring: high signal-to-noise ratio; feedback to management Regional monitoring: reliability; ecological relevance; feedback to management Ease/Economy is always an important criterion and is correlated with the state of knowledge

15. Principle #6: Define Acceptable Change q Status q Trends q Effects Definition will depend upon the type of monitoring:

16. Defining Acceptable Change: Status Monitoring Compliance monitoring: compare to license limits Certification monitoring: compare to certification requirements Operational monitoring: compliance with Environmental Management Plan objectives Regional monitoring: compare to baseline

17. Defining Acceptable Change: Trend Monitoring Compliance monitoring: e.g. spatial extent of water quality change within defined limits of mixing zone; temporal maxima within license limits Certification monitoring: e.g. 5-year record of littoral development Operational monitoring: e.g. consistent improvement in ability to predict seasonal lake water quality Regional monitoring: e.g. consistent decline in metal concentrations with distance from point sources as predicted in EIAs

18. Defining Acceptable Change: Effects Monitoring Statistical definitions: e.g. “critical effect size” of two standard deviations from a reference mean –require reliable data on natural variability from valid reference areas –require professional judgment because the links between observations or experimental results and effects on population persistence, community structure or ecosystem function can be highly uncertain.

19. Defining Acceptable Change: Effects Monitoring probabilistic definitions: e.g. “a 10% chance, or less, that 20% or more of the total population of forage fish would receive an exposure greater than the Ecological Benchmark Value” (Oregon DEQ 1998) –require the estimation of the probability of exposure –require estimation of local population abundance –require sufficient data to determine the EBV

20. Summary Know Why We are Monitoring Monitoring is Not Research Know the Questions We are Asking –Status; Trends; Effects Be Clear about the Purpose of Indicators Use Consistent Criteria for Selecting Indicators Define Acceptable Change