Predicting mayfly recovery in acid mine-impaired streams using logistic regression models of in-stream habitat and water chemistry.

Mayflies (Order Ephemeroptera) require high quality water and habitat in streams to thrive, so their appearance after restoration is an indicator of ecological recovery. To better understand the importance of restoring in-stream habitat versus water chemistry for macroinvertebrate communities, we developed taxon-specific models of occurrence for five mayfly genera (Caenis, Isonychia, Stenonema, Stenacron, and Baetis) inhabiting streams in the Appalachian Mountains, USA. Presence/absence records from past decades were used to develop single and multiple logistic predictive models based on catchment characteristics (drainage area, gradient), in-stream habitat variables (e.g., substrate, channel morphology, pool and riffle quality), and water chemistry. Model performance was evaluated using (a) classification rates and Hosmer-Lemeshow values for test sets of data withheld from the original model-building dataset and (b) a field comparison of predicted versus observed mayfly occurrences at 53 sites in acid mine drainage-impaired watersheds in 2012. The classification accuracies of final models for Caenis, Stenacron, and Baetis ranged from 50 to 75%. In-stream habitat features were not significant predictor variables for these three taxa, only water chemistry. Models for Isonychia and Stenonema had higher classification rates (81%) and included both habitat and chemical variables. However, actual occurrences of Isonychia and Stenonema at study sites in 2012 were low, consistent with the calculated probability of occurrence (Po) < 0.60. Caenis occurred at test sites 35% of the time when the model predicted a Po > 0.40. Stenacron showed the greatest consistency of actual versus predicted occurrences, occurring at 56% of sites when the Po (based on pH and conductivity) was > 0.50 and only at 1 site when Po < 0.5. The results demonstrate how predictive models of individual indicator taxa could be valuable for evaluating the relative impacts of restoring physical habitat versus water chemistry during stream remediation.

Use of leaf litter breakdown and macroinvertebrates to evaluate gradient of recovery in an acid mine impacted stream remediated with an active alkaline doser.

The spatial congruence of chemical and biological recovery along an 18-km acid mine impaired stream was examined to evaluate the efficacy of treatment with an alkaline doser. Two methods were used to evaluate biological recovery: the biological structure of the benthic macroinvertebrate community and several ecosystem processing measures (leaf litter breakdown, microbial respiration rates) along the gradient of improved water chemistry. We found that the doser successfully reduced the acidity and lowered dissolved metals (Al, Fe, and Mn), but downstream improvements were not linear. Water chemistry was more variable, and precipitated metals were elevated in a 3-5-km "mixing zone" immediately downstream of the doser, then stabilized into a "recovery zone" 10-18 km below the doser. Macroinvertebrate communities exhibited a longitudinal pattern of recovery, but it did not exactly match the water chemistry gradient Taxonomic richness (number of families) recovered about 6.5 km downstream of the doser, while total abundance and % EPT taxa recovery were incomplete except at the most downstream site, 18 km away. The functional measures of ecosystem processes (leaf litter breakdown, microbial respiration of conditioned leaves, and shredder biomass) closely matched the measures of community structure and also showed a more modest longitudinal trend of biological recovery than expected based on pH and alkalinity. The measures of microbial respiration had added diagnostic value and indicated that biological recovery downstream of the doser is limited by factors other than habitat and acidity/alkalinity, perhaps episodes of AMD and/or impaired energy/nutrient inputs. A better understanding of the factors that govern spatial and temporal variations in acid mine contaminants, especially episodic events, will improve our ability to predict biological recovery after remediation.