Marine planktonic diatoms export carbon to the deep ocean, playing a key role in the global carbon cycle. Although commonly thought to have diversified over the Cenozoic as global oceans cooled, only two conflicting quantitative reconstructions exist, both from the Neptune deep-sea microfossil occurrences database. Total diversity shows Cenozoic increase but is sample size biased; conventional subsampling shows little net change. We calculate diversity from a separately compiled new diatom species range catalog, and recalculate Neptune subsampled-in-bin diversity using new methods to correct for increasing Cenozoic geographic endemism and decreasing Cenozoic evenness. We find coherent, substantial Cenozoic diversification in both datasets. Many living cold water species, including species important for export productivity, originate only in the latest Miocene or younger. We make a first quantitative comparison of diatom diversity to the global Cenozoic benthic ∂18O (climate) and carbon cycle records (∂13C, and 20-0 Ma pCO2). Warmer climates are strongly correlated with lower diatom diversity (raw: rho = .92, p<.001; detrended, r = .6, p = .01). Diatoms were 20% less diverse in the early late Miocene, when temperatures and pCO2 were only moderately higher than today. Diversity is strongly correlated to both ∂13C and pCO2 over the last 15 my (for both: r>.9, detrended r>.6, all p<.001), but only weakly over the earlier Cenozoic, suggesting increasingly strong linkage of diatom and climate evolution in the Neogene. Our results suggest that many living marine planktonic diatom species may be at risk of extinction in future warm oceans, with an unknown but potentially substantial negative impact on the ocean biologic pump and oceanic carbon sequestration. We cannot however extrapolate our my-scale correlations with generic climate proxies to anthropogenic time-scales of warming without additional species-specific information on proximate ecologic controls.

Thirty years ago, the Neptune Database was created to synthesize microfossil occurrences from the deep-sea drilling record. It has been used in numerous studies by both biologists and paleontologists of the evolution and distribution in space and time of marine microplankton. After decades of discontinuous development in various institutions, a significant overhaul of the system was made during the last decade, leading to the database being expanded and made available again online under the name Neptune Sandbox Berlin (NSB). In particular, the addition of an extensive stratigraphic layer has resulted in the database now being used by a wider geoscience community than its previous incarnations. We summarize here the complete history of the Neptune database development and provide a complete description of the new system, NSB, its associated website and age-model making software (NSB_ADP_wx).

A first reasonably comprehensive evaluated list of radiolarian names in current use is presented, covering Cenozoic fossil to Recent species of the primary fossilising subgroup Polycystinea. It is based on those species names that have appeared in the literature of the Deep Sea Drilling Project and its successor programs, the Ocean Drilling Program and Integrated Ocean Drilling Program, plus additional information from the published literature, and several unpublished taxonomic database projects. 1192 names are recognised as valid, and several hundred additional names including synonyms and mispellings are given as well. A brief list of valid names is provided in the main paper, while the full list, with synonyms, author, year of publication, family assignment, geologic age interval and notes is provided as a SOM spreadsheet table.

The deep-sea microfossil record is characterized by an extraordinarily high density and abundance of fossil specimens, and by a very high degree of spatial and temporal continuity of sedimentation. This record provides a unique opportunity to study evolution at the species level for entire clades of organisms. Compilations of deep-sea microfossil species occurrences are, however, affected by reworking of material, age model errors, and taxonomic uncertainties, all of which combine to displace a small fraction of the recorded occurrence data both forward and backwards in time, extending total stratigraphic ranges for taxa. These data outliers introduce substantial errors into both biostratigraphic and evolutionary analyses of species occurrences over time. We propose a simple method-Pacman-to identify and remove outliers from such data, and to identify problematic samples or sections from which the outlier data have derived. The method consists of, for a large group of species, compiling species occurrences by time and marking as outliers calibrated fractions of the youngest and oldest occurrence data for each species. A subset of biostratigraphic marker species whose ranges have been previously documented is used to calibrate the fraction of occurrences to mark as outliers. These outlier occurrences are compiled for samples, and profiles of outlier frequency are made from the sections used to compile the data; the profiles can then identify samples and sections with problematic data caused, for example, by taxonomic errors, incorrect age models, or reworking of sediment. These samples/sections can then be targeted for re-study.

The deep-sea microfossil record is characterized by an extraordinarily high density and abundance of fossil specimens, and by a very high degree of spatial and temporal continuity of sedimentation. This record provides a unique opportunity to study evolution at the species level for entire clades of organisms. Compilations of deep-sea microfossil species occurrences are, however, affected by reworking of material, age model errors, and taxonomic uncertainties, all of which combine to displace a small fraction of the recorded occurrence data both forward and backwards in time, extending total stratigraphic ranges for taxa. These data outliers introduce substantial errors into both biostratigraphic and evolutionary analyses of species occurrences over time. We propose a simple method—Pacman—to identify and remove outliers from such data, and to identify problematic samples or sections from which the outlier data have derived. The method consists of, for a large group of species, compiling species occurrences by time and marking as outliers calibrated fractions of the youngest and oldest occurrence data for each species. A subset of biostratigraphic marker species whose ranges have been previously documented is used to calibrate the fraction of occurrences to mark as outliers. These outlier occurrences are compiled for samples, and profiles of outlier frequency are made from the sections used to compile the data; the profiles can then identify samples and sections with problematic data caused, for example, by taxonomic errors, incorrect age models, or reworking of sediment. These samples/sections can then be targeted for re-study.