Ronquillo, C. | bioRxiv Science

bioRxiv2026

Diversity without borders: partitioning continuous spaces using probabilistic equivalent numbers

Equivalent numbers represent biodiversity as the effective number of equally distinct units, typically species, and can be partitioned across scales. In practice, they summarize each unit of biodiversity by a single value and compare units pairwise, misrepresenting units that are better described as distributions and the relationships between several units that share the same space. We introduce an equivalent-number index for assemblages of units represented as probability density functions (PDFs) over a continuous space, estimated as the integral of the pointwise maximum across abundance-weighted PDFs. Resulting equivalent PDF numbers fulfil elementary properties of classical equivalent numbers, and support additive partitioning across any number of nested scales. We illustrate the framework with case studies across three domains: (1) measuring trait diversity considering intraspecific variability in grasslands, (2) partitioning realized bioclimatic niches among clades of Carnivora, and (3) understanding seasonal changes in the partitioning of fish home ranges in geographic space.

ecology↗

bioRxiv2024

Mobilisation of data from natural history collections can increase the quality and coverage of biodiversity information

AimQuantify potential gains to insect data on the Global Biodiversity Information Facility (GBIF) through further digitisation of natural history collections, assess to what degree this would fill biases in spatial and environmental record coverage, and deepen understanding of environmental bias with regard to climate rarity. LocationAfrotropical realm (mainland only) Time period1814-2022 Major taxa studiedCatharsius Hope, 1837 (Coleoptera: Scarabaeidae) MethodsWe compared inventory completeness of Afrotropical Catharsius GBIF data to a dataset which combined these with records from a recent taxonomic revision. We analysed how this improved dataset reduced regional and environmental bias in the distribution of occurrence records using an approach that identifies well-surveyed spatial units of 100x100km as well as emerging techniques to classify rarity of climates. ResultsThe number of cells for which inventory completeness could be calculated, as well as coverage of climate types by "well-sampled" cells, increased three-fold when using the combined set compared to the GBIF set. Improvements to sampling in Central and Western Africa were particularly striking. Coverage of rare climates was similarly improved, as not a single well-sampled cell from the GBIF data alone occurred in the rarest climate types. Inclusion of further records from natural history collections increased the total number of occurrences, but also filled persisting spatial and environmental data gaps on GBIF. Main conclusionsThese findings support existing literature that suggests data gaps on GBIF are still pervasive, especially for insects and in the tropics and, so, is not yet ready to serve as a standalone data source for all taxa. Biases in spatial coverage of records translate to uneven sampling of environmental conditions, hindering our ability to describe the full breadth of species niches, especially so in climates that occur infrequently. However, we show that natural history collections hold the necessary information to fill many of these gaps, and their further digitisation should be a priority.

zoology↗