ORBIT aims at synthesizing taxonomic information in the form of comprehensive factsheets for each of the approximately 2,000 species of bees recorded in Europe. Each factsheet will summarize the species’ taxonomy and will provide pictures of diagnostic characters, as well as pictures of the bees in their habitats, when available (Task 1). The taxonomic research will summarise available information for every species, including:

  • scientific names (family, tribe, genus, species) and common names,
  • key bibliographic references,
  • distribution in Europe,
  • morphological diagnosis of both genders,
  • biology and ecology (including host plants, nesting biology, parasites, and habitat requirements),
  • photos/drawings of morphological characters and photographs in natura.

These factsheets will be accessible through a fully open-access internet platform (Task 2) whose conceptualization, layout and contents will be developed with the European Community and after a workshop conducted at the beginning of the project (Task 3).

Overview of the project tasks

The first step will be to compile this information (Subtask 1.1). However, for many species, new taxonomic data needs to be produced ex nihilo, including macrophotographs or drawings of diagnostic characters (Subtask 1.2).

The identification of bees is typically hierarchical: species are arranged in species-groups sharing common morphological traits, and then in subgenera and in genera, etc.

Families, subfamilies, tribe, genera and subgenera are supra-specific groups. We aim to produce illustrated keys, diagnoses and illustrations of diagnostic characters to
supra-specific groups (subtask 1.3).

For communication purpose and for all citizen science programs, illustrations of living specimens will be selected to illustrate the bee diversity and to stimulate monitoring (Subtask 1.4).

In all bee families, cryptic species that are highly similar to each other, exist. In these species, morphological identifications are difficult and often require the use of genetic data.

For this reason, we incorporate the generation of DNA barcodes in order to ensure proper identification of specimens (Subtask 1.5).

Finally, the data, including illustrations, pictures and biological information, needs to be harmonised and organised in a comprehensive database (Subtask 1.6) before being fed into the online platform (Task 2).