Causal Analysis/Diagnosis Decision Information System (CADDIS)

• Data Analysis Methods
• Fundamentals of Data Analysis
• Get Data Analysis Tools

M.6. Predicting Environmental Conditions From Biological Observations

M.6.1. How Do I Predict Environmental Conditions from Biological Observations?

Different taxa generally require different environmental conditions to persist. If we know the environmental requirements for different taxa, we can predict environmental conditions at a site based on the occurrences of these taxa. These biologically-based predictions can be useful in cases where environmental data are not available or are difficult to obtain. They can also provide valuable supporting evidence in a stressor identification analysis.

The environmental requirements of different taxa can be represented with taxon-environment relationships. A taxon-environment relationship quantifies the relationship between a taxon's probability of occurrence and the value of one or more environmental variables (Figure M.6-1). These taxon-environment relationships can be estimated from field data and then combined statistically with observations of the presence or absence of taxa at a new site to predict environmental conditions.

Figure M.6-1. Taxon-environment relationships, showing the probability of capture of Heterlimnius (a riffle beetle) and Malenka (a stonefly) as a function of stream temperature. Open circles show the probability of taxon occurrence estimated from approximately 20 sites. Solid lines show the logistic regression fit to the data and dashed lines show the 90% confidence intervals about the mean line.

M.6.2. Can I Use My Data to Make These Predictions?

You can predict environmental conditions from biological observations at a site of interest if an appropriate set of taxon-environment relationships is already available, or if you have a data set that can be used to compute them.

Taxon-environment relationships can be estimated from field data using logistic regression. Logistic regression estimates relationships between the presence/absence of particular taxa and the values of different environmental variables. Relatively large data sets (i.e., > 500 samples) of matched environmental and biological observations are required for these models. Taxon-environment relationships that relate the occurrence of different macroinvertebrate taxa and certain environmental variables (such as stream temperature and bedded fine sediment) have been computed for western streams and are available for use in the R library bio.infer. Technical details and programs for calculating and using taxon-environment relationships to predict environmental conditions are available in a separate CADDIS Web module.

Figure M.6-2. Comparison between biologically-based predictions (inferred temperatures) and measured stream temperatures in western Oregon (dashed line shows a 1:1 correspondence).

M.6.3. How Do I Use These Predictions in Stressor Identification?

Predictions of environmental conditions based on biological observations can be incorporated into the SI process as the verified prediction type of evidence in Step 3: Evaluate Data from the Case. That is, if the level of a certain stressor is elevated at a site, we would hypothesize that the biologically-based prediction for that stressor would also be elevated. If the biologically-based prediction is in fact elevated, as predicted, then the evidence would support the case for that stressor as a candidate cause.

Assessing whether a prediction of environmental condition differs from reference expectations may require you to control for natural variation in the biologically-based predictions. For example, stream temperature usually decreases as site elevation increases. Therefore, a biologically-based prediction of stream temperature at the site must be compared with a site-specific reference expectation to determine whether stream temperature is higher or lower than expected.

For example, regional data from the western U.S. were used to model relationships between the occurrence of different benthic macroinvertebrates and stream temperature. These taxon-environment relationships were then used to predict stream temperatures from an independent data set collected in western Oregon. Average summer daytime temperature was also measured in western Oregon with continuous temperature loggers. Agreement between biologically-based predictions and directly measured stream temperatures was strong (Figure M.6-2).

Figure M.6-3. Biologically-based predictions of stream temperature (inferred temperature) versus elevation in western Oregon. Blue open circles show reference site data, circles A and B show test sites. Lines show the 90% prediction intervals for the regression model relating stream temperature with elevation.

A simple linear regression model was used to quantify the relationship between biologically-based predictions of stream temperature and elevation at reference sites. This relationship can then be used to define site-specific reference conditions for stream temperature at a test site, given site elevation. If the biologically-based prediction of temperature at a test site deviates significantly from the reference expectations (Figure M.6-3, point A), this finding would support elevated stream temperature as a possible cause of impairment. If the biologically-based prediction of temperature at a test site is very similar to reference expectations (Figure M.6-3, point B), this finding would weaken the argument that elevated temperature caused the biological impairment.

M.6.4. Helpful Tips

• Environmental variables often covary (e.g., both % fine sediment and stream temperature tend to increase with decreasing elevation). Thus, when developing taxon-environment relationships, covarying environmental factors must be considered. In many cases, it is useful to model different environmental variables simultaneously.

• Technical details and programs for calculating and using taxon-environment relationships to predict environmental conditions are provided in a separate CADDIS Web module.