How to reach optimal estimates of confidence intervals in microscopic counting of phytoplankton?

Abstract

Abstract Present practices in the microscopic counting of phytoplankton to estimate the reliability of results rely on the assumption of a random distribution of taxa in sample preparations. In contrast to that and in agreement with the literature, we show that aggregated distribution is common and can lead to over-optimistic confidence intervals, if estimated according to the shortcut procedure of Lund et al. based on the number of counted cells. We found a good linear correlation between the distribution independent confidence intervals for medians and those for parametric statistics so that 95% confidence intervals can be approximated by using a correction factor of 1.4. Instead, the recommendation to estimate confidence intervals from the total number of counted cells according to Lund et al. should be categorically rejected. We further propose the adoption of real-time confidence intervals during microscopic counting as the criterion to define how long counting should be continued. Then each sample can be counted in its individual way to reach the necessary reliability independent of highly different samples. Such a dynamic counting strategy would be the most significant development in the quality control of phytoplankton counting since the early pioneers established the present counting practices in the late 1950s.