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Palynology, the study of pollen and spores, plays a crucial role in various scientific disciplines, including earth sciences (paleovegetation and paleoclimatology), botany, allergy, archaeology, forensic sciencs and cosmetics. This study delves into the critical question in fossil pollen analysis studies: the minimum count of pollen grains required for accurate estimation of vegetation composition. Various statistical methods have been proposed over the years to address this question. Our research introduces an alternative technique, the orderly count, tailored to the nature of palynological analysis. We apply this method to diverse sediment catchments, including peat bogs, marine and lake sediments, from different geographical locations. Additionally, we revisit the reliability coefficients and propose adjustments for more accurate results. Our findings suggest that relying on statistical methods without considering the specific characteristics of palynological data may lead to low reliability. We advocate for the integration of dissimilarity criteria and the orderly count in sample size assessments for enhanced accuracy in palynological analyses. Our study emphasizes the importance of choosing appropriate methodologies aligned with the unique aspects of palynology to ensure robust and reliable results. |
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