DASCO: A workflow to downscale alien species checklists using occurrence records and to re-allocate species distributions across realms

Information about occurrences of alien species is often provided in so-called checklists, which represents
lists of reported alien species in a region. In many cases, available checklists cover whole countries, which is
too coarse for many analyses and limits capabilities of assessing status and trends of biological invasions. In-
formation about point-wise occurrences is available in large quantities at online facilities such as GBIF and
OBIS, which, however, do not provide information about the invasion status of individual populations. To
close this gap, we here provide a semi-automated workflow called DASCO to downscale regional checklists
using occurrence records obtained from GBIF and OBIS. Within the workflow, coordinate-based occur-
rence records for species listed in the provided regional checklists are obtained from GBIF and OBIS, and
the status of being an alien population is assigned using the information in the provided checklists. In this
way, information in checklists is made available at the local scale, which can then be re-allocated to any
other spatial categorisation as provided by the user. In addition, habitats of species are determined to dis-
tinguish between marine, brackish, terrestrial, and freshwater species, which allows splitting the provided
checklists to the respective realms and ecoregions. By using checklists of global databases, we showcase
the usage of the DASCO workflow and revealed > 35 million occurrence records of alien populations in
terrestrial and marine regions worldwide, which were back-transformed to terrestrial and marine regions
for comparison. DASCO has the potential to be used as a basis for the widely applied species distribution
models or assessments of status and trends of biological invasions at large geographic scales. The workflow
is implemented in R and in full compliance with the FAIR data principles of open science.