Testing a new automated macrocharcoal detection method applied to a transect of lacustrine sediment cores in eastern Canada. (1st November 2022) - Lesven, Jonathan; Druguet Dayras, Milva; Borne, Romain; Remy, Cécile C.; Gillet, François; Bergeron, Yves; Arsenault, André; Millet, Laurent; Rius, Damien
Abstract: Over the past decades, the abundance and area of macrocharcoal (i.e. ≥ 150 μm in diameter) fragments from sedimentary sequences have been quantified using visual or semi-automated methods to reconstruct fire histories. However, the lack of uniformity between counting methods used in each study could introduce methodological biases influencing fire frequency reconstructions, and therefore impact their interpretation and limit their comparisons. To overcome this issue, we propose here a new automated method to quantify the number of macrocharcoal fragments and measure their areas from high-definition image capture, based on the analysis of colorimetric parameters. We tested the efficiency of our method and reconstructed charcoal influx over the last 8000 years by comparing visual and automatic counting methods along a north-south transect from eastern Canada, estimating number and size, and the associated local and regional fire frequencies. Results show that our automated method is efficient in detecting charcoal particles, except for highly minerogenic samples, and suggest that the traditional visual inspection tends to overestimate the size of macrocharcoal fragments. Local fire frequencies varied greatly depending on the macrocharcoal detection method used. At the regional scale they seem closer, and our automated method reproduces similar trends to published studies in our study area. However, it does represent a methodological advancement, particularly for recent centuries, that should be considered for future paleoecological studies. Highlights: An open-source program was developed on ImageJ software to detect macrocharcoals. ImageJ software allows an efficient detection of macrocharcoals. Charcoal number and area are highly correlated, but local fire history differs. Manual counting method strongly overestimates total charcoal area. Methodological choice impacts fire history more at local than regional scale.