Պահպանված է:
| Հիմնական հեղինակներ: | , |
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| Ձևաչափ: | Recurso digital |
| Լեզու: | |
| Հրապարակվել է: |
Zenodo
2022
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| Խորագրեր: | |
| Առցանց հասանելիություն: | https://doi.org/10.5281/zenodo.18178554 |
| Ցուցիչներ: |
Ավելացրեք ցուցիչ
Չկան պիտակներ, Եղեք առաջինը, ով նշում է այս գրառումը!
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Բովանդակություն:
- (Uploaded by Plazi for the IPBES Invasive Alien Species Assessment) 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. Information 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 occurrence 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 distinguish 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.