Reconstructing acritarch size distributions in chert: A quantitative approach for using probability models

Accurately reconstructing microfossil size distributions from thin sections is crucial for understanding early life history. Thin section preparation of chert samples often results in partial slicing of microfossils, leading to the underestimation of the observed sizes of acritarchs. This study develops a probability-based algorithm to address this bias and reconstruct more accurate size distributions. A Python program is introduced, allowing rapid and user-friendly computation without the need for complex manual calculations. This approach provides a novel solution to improve the accuracy of microfossil size data, thereby enhancing our understanding of acritarchs preserved in chert and their implications for the evolution of early life.