PRESERVATION BIASES AFFECT CHARCOAL-BASED PALEOFIRE INTERPRETATIONS

Fire is a disturbance whose controls and impacts span multiple spatial and temporal scales. Robust paleofire proxies and archives allow us to understand how it has varied and affected terrestrial ecosystems throughout geologic history. Sedimentary charcoal particles are one of the most ubiquitous fire proxies. Although much research has sought to understand the complexities of charcoal as a proxy, less has considered how the geologic archives containing it might impact paleofire interpretations. Using a big-data, meta-analytical approach, we assess how sedimentary biases and stratigraphic completeness affect paleofire signals inferred from charcoal preserved in deposits spanning several temporal scales (from decades to millions of years) during the Cenozoic. We find that the “Sadler effect,” which is the observation that sedimentation rates decrease systematically when measured over longer timescales due to the incorporation of sedimentary hiatuses, is pervasive in these paleofire records. The presence of this sedimentary bias is exhibited by negative power law relationships between charcoal accumulation rate (CHAR) and sample age range, showing that longer time spans of measurement are more likely to incorporate longer period hiatuses into sediment records. We exhibit the potential impact of this finding with two case studies. First, we show that sedimentary biases could partially explain the late Neogene surge in fire activity that is commonly inferred from sedimentary charcoal records in the North Pacific. This finding has key implications for our understanding of fire’s role in modern biogeography, plant physiology, and ecology. Next, we show that sedimentary biases affect Holocene charcoal records and explore how they could impact metrics derived from peak analysis (e.g., fire frequency, return interval) of these records. To our knowledge, our results are the first to identify this preservation bias in paleofire records. Altogether, this work has important implications for paleofire research and stresses the need to incorporate consideration of preservation biases into the paleofire toolbox. As a solution, we therefore provide an interpretative framework which outlines necessary steps to identify and quantify preservation bias in paleofire records and intervals.