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CADDIS Volume 1: Stressor Identification

Step 5: Identify Probable Causes

At this point you should have all of the evidence organized and be ready to reach your final determination. The final determination is reached by comparing the evidence across candidate causes. Comparison supports your conclusions by:

  • Ensuring that each candidate is treated fairly and that any biases in data collection and analysis are acknowledged,
  • Identifying the candidate cause with the relatively strongest support when evidence is sparse, and
  • Identifying the data or information that would most improve confidence in your conclusions.

If several specific effects were analyzed, conduct your comparison separately for each effect. Then, evaluate whether one cause is responsible for all of the specific effects, or if several causes are operating.

There is no magic formula. All of the candidate causes must be compared to determine if there is more than one probable cause and to determine the level of confidence in the overall determination. Typical combinations of status and confidence are described in the first section below, followed by a suggestions for documenting conclusions.

Typical outcomes of comparisons

One candidate cause is diagnosed or probable; other candidate causes are unlikely or refuted

Celebrate! Document your conclusions and rationale.

You have compelling evidence that different specific effects were caused by different causal agents; other candidate causes are unlikely or refuted

Celebrate! Document your conclusions and rationale. Revisit how each specific effect is related to the impairment that originally triggered the investigation. You may be able focus management action on the causal agent(s) that will provide the biggest gains in improving condition. Revisit the conceptual models to see if the different causal agents can be traced back to a common source.

You have sparse evidence across all candidate causes

If the evidence for all the candidate causes is too sparse to confidently identify a probable cause, you may still be able to identify the candidate cause that has the strongest support relative to the others. To do this, consider what you know about ecology in general and about this particular ecosystem, impairment, and the candidate causes. All the evidence is important, as noted previously. However, the likelihood that the magnitude, intensity and duration of exposure were sufficient to cause the effect weigh heavily here. If one candidate cause emerges as having the strongest support, it may make sense to identify it and indicate uncertainty about the others. Consider the consequences of not identifying the cause with the strongest support: if not identified, it may be that no action will be taken at all. A thoughtful adaptive management approach can provide additional evidence for causal analysis while also improving some conditions at the site.

You have uneven evidence across candidate causes

If you have a strong case for one candidate cause, but the other candidate causes are uncertain because there are fewer data and less evidence to evaluate, then there may be bias in data collection, either from the site or from the literature. You must remain objective and question assumptions, biases, and motives at every opportunity. If the lack of data is from the field, look for data sets collected by other groups or agencies. You might also want to recommend changes to your monitoring program. If the lack of data is from the literature, consult other case studies and invest the time now to develop a useful literature summary so that you can strengthen future case studies.

You have insufficient evidence across all candidate causes

If, after considering all of the evidence, none of candidate causes provide a satisfactory explanation for the effects, you have several options for iterating the process or collecting additional information.

  • Consider the specific biological effect again. Errors in the biological survey or assessment may have resulted in mischaracterization of the effect. For instance, bioassessment criteria for high-gradient streams may have been applied to a low-gradient stream. Defining the biological effect more specifically, or defining more than one effect, makes it easier to find relevant evidence.

  • There may be other possible candidate causes that have not yet been considered. Re-examine your conceptual models. Consult experts outside your specialty. Talk to stakeholders and local people.

  • Consider if jointly acting events cause the effect. For example, excessive high algal biomass plus three consecutive cloudy days might result in unusually low levels of dissolved oxygen. Multiple causes are discussed further below.

  • Perhaps the data have not properly captured episodic events. Try to narrow the geographic scope of the assessment to make it easier to find potential sources. Investigate the types of sources and land-use activities to better characterize the possibility of episodic events.

  • If all else fails and you are unable to isolate a probable cause, identify the cause or causes that are most likely by using best professional judgment and indicate what new data would strengthen a determination of the probable cause. Consult with decision-makers to determine if additional data collection is warranted.

The evidence suggests that multiple causes are operating

When evidence supports more than one candidate cause, there are potentially multiple causes. Although this issue should have been addressed when defining the case and listing the candidate causes, it should be reconsidered here if the results are unclear. New evidence or new understanding may reveal relationships among agents that were not apparent in the beginning.

If multiple causes seem to be operating:

It may be appropriate to consider whether the impairment was properly defined in Step 1.

  • The apparent multiple causes may actually be individual causes of multiple effects.  Consider partitioning the impairment if, for example one cause is inducing tumors in fish and another is reducing benthic insect abundance.
  • The apparent multiple causes may actually be operating in different areas of the aquatic system.  Consider partitioning the impairment in space.

It may be appropriate to consider whether the candidate causes were properly defined or whether they should have been combined as described in Listing Multiple Stressors as Candidate Causes.

Otherwise, report that the impairment apparently has multiple causes and consider recommending a remedial strategy.

  • Remediate a dominant and potentially sufficient cause.  An apparently dominant cause may be sufficient alone to induce the impairment and its actions may be masking the more subtle effects of other causes.
  • Remediate a necessary cause.  If one cause is necessary for occurrence of the impairment, then remediating only it is adequate.
  • Remediate a feasible cause.  If it is not clear how multiple causes interact, perform the easiest remediation and monitor the results.
  • Remediate all causes.  In some cases, it is feasible to remediate all of the multiple causes.

You have insufficient data

This looks like an empty scoring table with only a few pluses and minuses or with comments about the uncertainty of the data. One option is to recommend the collection of additional data. Data collection is most likely when the costs of data collection are low, the costs of remediation are high, the situation is contentious, and the existing data do not suggest which is the most probable cause.

You have no data

This is highly unlikely. At the minimum you should have information on land use/land cover and sources within your watershed. Use this information to conduct a screening-level Stressor Identification to identify the most useful data to collect from the case. Then consult with decision-makers to determine if data collection is warranted.

Documenting conclusions

The bottom line of the analysis identifies the probable cause or causes and provides the reasoning for selecting it or them over the other candidate causes (see example conclusions). Reflect back on the reason for the causal analysis and provide the level of information that will help inform decision making (The Role of Stressor Identification in Various Water Management Programs). Is the assessment for permitting, meeting aquatic life criteria, or for providing information that may lead to solutions for more than minimum recovery? Is the level of confidence sufficient to make a determination? Decide and document your rationale. Then communicate your findings in the final part of Step 5, Complete Causal Analysis.

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