Mapeando o (des)conhecimento da biodiversidade de Orthoptera (Arthropoda, Insecta)

Abstract

In the era of bioinformatics, it has become possible to identify taxonomic, spatial, and temporal gaps in biodiversity knowledge through digitally accessible data. In this thesis, we use these data to globally assess different types of incompleteness and trends in the mappable knowledge of Orthoptera (Arthropoda, Insecta), the sixth most species-rich order of insects, commonly known as grasshoppers, crickets, and katydids. In Chapter I, we mapped the state of taxonomic knowledge of Orthoptera, using the year of species description as an indicator of alpha taxonomy and the number of synonyms associated with each species as an indicator of beta taxonomy. These indicators were spatially combined, revealing that alpha taxonomy predominates in tropical regions and the Southern Hemisphere, while beta taxonomy is more prevalent in temperate regions of the Northern Hemisphere. In Chapter II, we mapped knowledge gaps in Orthoptera by assessing taxonomic, sampling, and temporal completeness, as well as the spatial and temporal evenness of inventories, integrating them into an ignorance map. Our results revealed significant deficiencies in the biogeographic knowledge of Orthoptera, characterized by taxonomically unrefined data, inventory gaps, low temporal coverage, and an imbalance in the number of records, especially in tropical regions. In Chapter III, we integrated socioecological drivers, such as human population density, protected area density, socioeconomic development, and known species richness of Orthoptera over time, to explain gaps in Orthoptera knowledge across different biogeographic subdivisions (Global, Nearctic, Neotropical, Palearctic, Afrotropical, Indo-Malayan, and Australasian) using structural equation models (SEM). Our results revealed that both known species richness and ignorance of Orthoptera are directly influenced by anthropogenic, conservationist, socioeconomic, and local factors over time. Finally, we discuss these patterns, providing insights into large-scale knowledge of Orthoptera.