Quantifying macroinvertebrate thermal niches supports the development and refinement of temperature regulatory thresholds in Pacific Northwest streams. The Macroinvertebrate Thermal Tolerance Index (MTTI; Hubler et al. 2024) was proposed as an estimate of local thermal suitability using taxa-specific thermal tolerances (weighted average optima, WAO) and local assemblage structure. Taxon-specific WAO values are estimated using a geographically defined distribution dataset and thus application of WAO estimates across regions may reveal either consistent estimates or biases caused by biological and analytical factors. In this study, we compared WAO and MTTI estimates from ~7,200 Idaho BURP observations (1993–2021) with estimates calculated from the combined Oregon-Washington dataset used to develop the MTTI. We aimed to: (1) quantify patterns in thermal optima and breadth for macroinvertebrate taxa between regions (ID vs. OR-WA); (2) evaluate the utility and transferability of the MTTI across regional versus sub-regional scales; and (3) identify potential methodological refinements.
We estimated the WAO of 221 shared operational taxonomic units (OTUs) observed in ~1,200 BMI assemblage samples. OTUs were categorized by thermal response curve shape (e.g., cold-water/warm-water specialists vs. generalists) and site-specific MTTI scores were compared to predicted stream temperatures. Model fit declined when WAO from one region was applied to another, as expected. While most Idaho taxa exhibited concordant response curves with WA-OR, OTUs were more frequently classified cold-water specialists in the ID dataset. Pairwise comparison of WAOs calculated for taxa occurring in ID and WA-OR revealed lower WAO in ID than WA-OR, suggesting sampling frames imposed by state-wide monitoring programs may bias WAO estimation. Specifically, we speculate that, on average, ID observations capture the cold portion of each OTU's range, causing underestimation of WAO. Our results indicate that thermal tolerance indices are constrained by the range of stream temperatures included in sampling and thus suggest robust MTTI estimates require sampling a fuller thermal gradient of BMI taxa present to reduce biases associated with sampling the edges of a given taxon’s thermal range. Furthermore, taxonomic uncertainty may have contributed to patterns, and we suggest integrating genetic barcoding with traditional morphological approaches to improve taxonomic resolution and comparability across assessment programs.