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CADDIS Volume 4: Data Analysis

Predicting Environmental Conditions from Biological Observations (PECBO) Appendix

Topics in Computing Inferences

Categorical Tolerance Data

Categorical tolerance data assign taxa into a few distinct groups (e.g. tolerant and sensitive). These groups are best established using curve classification techniques. Once these classifications are assigned, the compositional characteristics of tolerant and sensitive taxa at a site can be summarized using three types of biological metrics: richness of tolerant and sensitive taxa, proportion of total taxa that are tolerant or sensitive, and relative abundance of tolerant and sensitive taxa.

To demonstrate this approach, curve classification was used to assign genera to tolerance categories with respect to elevated temperature, using data collected in the EMAP-West study. These tolerance categories were then used to compute the richness, proportion of total taxa, and relative abundance of sensitive and tolerant taxa in an independent dataset, collected from western Oregon. In the example shown below, the relative abundances of high temperature sensitive and high temperature tolerant taxa are plotted versus observed stream temperature in OR.

Relatively strong relationships were observed between each of the metric values and the observed stream temperature. In general, the metrics for sensitive taxa exhibited less variability in their relationships with the measured environmental condition than the metrics for tolerant taxa. This difference may be a result of differences in the total number of taxa that are classified as sensitive versus tolerant.

relabn response
Figure 20. Relationship between the relative abundance of high temperature sensitive (left) and high temperature tolerant (right) taxa and stream temperature (°C) in Oregon. Solid line shows position of a smoothing spline fit through the data.

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