Mapping the status of global taxonomic knowledge of Orthoptera (Arthropoda, Insecta)

Abstract

The status of taxonomic knowledge varies across the Globe. Quantifying and mapping the geographic patterns of taxonomic status is essential to prioritise regions that require greater attention from the taxonomic community. Here, we compiled all valid orthopteran species names and their synonyms, extracted from the Catalogue of Life (CoL) and allocated them geographically, based on data from the Global Biodiversity Information Facility (GBIF) and the Orthoptera Species File (OSF). This allowed us to create measures of taxonomic effort, based on the date of species descriptions and the number of associated synonyms and combine them across space. Our analyses show that the descriptions of currently valid species increased exponentially since the 19th century, with a temporary decline following World War II, while synonyms outpaced the number of valid species until the 1980s. The number of taxonomists also increased over time, with declines after World Wars, followed by a significant rise from the 1950s onwards, continuing through the 21st century (with > 100 taxonomists currently active). Per-taxonomist description rates transitioned from highly variable before the 20th century to consistent rates of 5–10 species annually with collaborative efforts. Tropical regions and the Southern Hemisphere hold the majority of recently described species names with fewer associated synonyms, indicating a predominance of alpha taxonomy and highlighting the need for greater taxonomic efforts. In contrast, temperate regions, particularly in Europe and south-western Asia, contain the majority of older names and synonyms, indicating a predominance of beta taxonomy and regions that have been more thoroughly studied. Our findings are discussed in the context of sociopolitical factors, scientific investments and the history of taxonomy. Finally, we propose a framework that makes the links between taxonomy and macroecology accessible for biodiversity in the era of Big Data.