Diversity estimates play a key role in ecological assessments. Species richness and abundance are commonly used to generate complex diversity indices that are dependent on the quality of these estimates. As such, there is a long‐standing interest in the development of monitoring techniques, their ability to adequately assess species diversity, and the implications for generated indices. To determine the ability of substratum community assessment methods to capture species diversity, we evaluated four methods: photo quadrat, point intercept, random subsampling, and full quadrat assessments. Species density, abundance, richness, Shannon diversity, and Simpson diversity were then calculated for each method. We then conducted a method validation at a subset of locations to serve as an indication for how well each method captured the totality of the diversity present. Density, richness, Shannon diversity, and Simpson diversity estimates varied between methods, despite assessments occurring at the same locations, with photo quadrats detecting the lowest estimates and full quadrat assessments the highest. Abundance estimates were consistent among methods. Sample‐based rarefaction and extrapolation curves indicated that differences between Hill numbers (richness, Shannon diversity, and Simpson diversity) were significant in the majority of cases, and coverage‐based rarefaction and extrapolation curves confirmed that these dissimilarities were due to differences between the methods, not the sample completeness. Method validation highlighted the inability of the tested methods to capture the totality of the diversity present, while further supporting the notion of extrapolating abundances. Our results highlight the need for consistency across research methods, the advantages of utilizing multiple diversity indices, and potential concerns and considerations when comparing data from multiple sources.

Foraminifers are widespread, highly abundant protists and active participants in marine carbon cycling. Their biomass might represent almost half of the total meiobenthic biomass in the deep sea. Foraminiferal biomass is frequently assessed through geometric models and biovolume estimates due to its non-destructive nature, which allows estimates of individuals from palaeoecological, museum, and living samples. To increase the accuracy of foraminiferal biovolume and biomass assessment we evaluate and propose geometric models for 207 foraminiferal taxa and the species’ average cell occupancy of the test. Individual test dimensions were measured to calculate volume (µm³), and the percent of cell occupancy (PCO) of the test was measured to assess the biovolume (µm³). These data were converted into individual biomass measurements (µg Corg ind−1). Our high intra- and interspecific PCO variance suggest that a mean PCO for each species represents the natural variability of occupancy more accurately than a predetermined fixed percentage for the whole assemblage, as previously asserted in the literature. Regression equations based on the relationship between test dimensions and volumes are presented. The geometric models, the PCO adjustment, and the equations will reduce time, effort, and discrepancies in foraminiferal biovolume and biomass assessments. Therefore, these results can improve the use and reliability of foraminiferal biomass in the future, facilitating its use in (1) distinct approaches including carbon flux estimations, (2) determining the effects of climate change on the marine trophic webs, and (3) environmental monitoring programs.