The fossil record is notoriously incomplete. The spatial distribution of fossils reflects in part the geography of biodiversity gradients, areas of sediment deposition and present-day rock exposure, and locations of wealthy nations with long-standing investments in Western science. Importantly for paleobiologists, the geographic location and size of fossil sampling gaps varies through time, between environments, and from one group of organisms to another. This spatial structure in recorded fossil occurrences has many consequences for ecological and evolutionary investigations. If the fossil record is taken at face value, results and conclusions will be inaccurate, sometimes to the point of being misleading. Therefore, it is essential to standardize the spatial distribution of fossil occurrences (the total area covered by sites and the spread across sites) before addressing research questions about diversity dynamics, geographic range size, or other ecological variables. We review sources of spatial structure in the fossil record, means to account for them, and possible consequences of leaving them unaddressed. Several of the tools we discuss are compiled into a new software package named divvy, in the R language of data analysis. We call for the paleobiology community to take up spatial standardization as a routine consideration in studying the informative but patchy fossil record.

The fossil record is spatiotemporally heterogeneous: taxon occurrence data have patchy spatial distributions, and this patchiness varies through time. Large-scale quantitative paleobiology studies that fail to account for heterogeneous sampling coverage will generate uninformative inferences at best and confidently draw wrong conclusions at worst. Explicitly spatial methods of standardization are necessary for analyses of large-scale fossil datasets, because nonspatial sample standardization, such as diversity rarefaction, is insufficient to reduce the signal of varying spatial coverage through time or between environments and clades. Spatial standardization should control both geographic area and dispersion (spread) of fossil localities. In addition to standardizing the spatial distribution of data, other factors may be standardized, including environmental heterogeneity or the number of publications or field collecting units that report taxon occurrences. Using a case study of published global Paleobiology Database occurrences, we demonstrate strong signals of sampling; without spatial standardization, these sampling signatures could be misattributed to biological processes. We discuss practical issues of implementing spatial standardization via subsampling and present the new R package divvy to improve the accessibility of spatial analysis. The software provides three spatial subsampling approaches, as well as related tools to quantify spatial coverage. After reviewing the theory, practice, and history of equalizing spatial coverage between data comparison groups, we outline priority areas to improve related data collection, analysis, and reporting practices in paleobiology.