Less is more? A novel method for identifying and evaluating non-informative tracers in sediment source mixing models

Abstract

Accelerated soil erosion poses a global hazard to soil health. Understanding soil and sediment behaviour through sediment fingerprinting enables the monitoring and identification of areas with high sediment delivery. Land-use specific sediment source apportionment is increasingly determined using the Bayesian mixing model MixSIAR with compound-specific stable isotopes (CSSI). Here, we investigate CSSIs of fatty acid (FA) tracer selection with a novel method to identify and investigate the effect of non-informative tracers on model performance.