Mine waste contamination limits soil respiration rates: a case study using quantile regression

We present an application of a statistical approach, quantile regression (QR), which identifies trends in soil processes otherwise masked by spatial and temporal variability. QR identifies limits on processes and changes in the variance of a response along an environmental gradient. We quantified in situ soil respiration, pH, and heavy metal concentrations across a mine waste contamination gradient that spanned greater than an order of magnitude of metal concentrations. Respiration values were monitored at study sites over 2 years. We used QR to show that soil respiration was limited with respect to both heavy metals and pH, and that both increased metals and increased acidity constrained variation in soil respiration values. Maximum respiration values declined by 48% over the Metals Contamination Index (MCI) range and by 72% over the pH range. The use of QR avoided the necessity of discriminating between multiple sources of variation in a spatially and temporally variable system. It is often unrealistic or too time consuming and expensive to attempt to measure all of the relevant predictor variables in the field. The simpler approach offered by QR is to explore factors that limit a process, recognizing that not all of the factors contributing to a soil function will be measured. An application of this approach to the evaluation of a mine waste remediation procedure is discussed.