Use of thermal preference metrics to examine state biomonitoring data for climate change effects

Abstract

Abstract Analyses of long-term data are an important component of climate-change research because they can help further our understanding of the effects of climate change and can help establish expectations for biological responses to future climate changes. We used macroinvertebrate data to assess whether biological trends associated with directional climate change could be detected in routine biomonitoring data from Maine, North Carolina, and Utah. We analyzed data from 8 long-term biomonitoring sites that had 9 to 22 y of data, and focused on thermal-preference metrics based on cold- and warm-water-preference trait groups. The thermal-preference metrics were derived primarily from weighted-average or generalized-linear-model inferences based on data from each state database and are region specific. Long-term trends varied across sites and regions. At some sites, the thermal-preference metrics showed significant patterns that could be interpreted as being related to directional climate change, whereas at others, patterns were not as expected or were not evident. The strongest trends occurred at 2 Utah sites that had ≥14 y of data. At these sites, cold-water taxa were negatively correlated with air temperature, and, when years were grouped into hottest- and coldest-year samples, were strongly reduced in the hottest-year samples. Results suggest that thermal-preference metrics show promise for application in a biomonitoring context to differentiate climate-related responses from other stressors.