Understanding the origin and analysis of sediment-charcoal records with a simulation model

Interpreting sediment-charcoal records is challenging because there is little information linking charcoal production from fires to charcoal accumulation in lakes. We present a numerical model simulating the major processes involved in this pathway. The model incorporates the size, location, and frequency of fires, primary and secondary charcoal transport, sediment mixing, and sediment sampling. We use the model as a tool to evaluate assumptions of charcoal dispersal and taphonomy and to assess the merits of inferring local and regional fire history by decomposing charcoal records into low-frequency (‘background’) and high-frequency (‘peak’) components. Under specific dispersal scenarios, the model generates records similar in appearance to sediment-charcoal records from Alaskan boreal forests. These scenarios require long-distance dispersal (e.g. 10⁰–10¹ km), consistent with observations from wildfires but longer than previously inferred from experimental dispersal data. More generally, charcoal accumulation in simulated records mainly reflects area burned within the charcoal source area. Variability in charcoal peak heights is primarily explained by the size of charcoal source areas relative to the size of simulated fires, with an increase in this ratio resulting in increased variability in peak heights. Mixing and multi-year sampling add noise to charcoal records, obscuring the relationship between area burned and charcoal accumulation. This noise highlights the need for statistical treatments of charcoal records. Using simulated records we demonstrate that long-term averages of charcoal accumulation (>10×mean fire return interval) correlate well with area burned within the entire charcoal source area. We further demonstrate how decomposing simulated records to isolate the peak component emphasizes fire occurrence at smaller spatial scales (<1 km radius), despite the importance of long-distance charcoal dispersal in simulating charcoal records similar to observations. Together, these results provide theoretical support for the analysis of charcoal records using the decomposition approach.