Benefits of using non-checklist bird portal data

Non-checklist data from ornithological citizen science portals provide unprecedented insights into bird migration phenologies.

• Nadja Weisshaupt

Millions of bird observations have been entered on online bird portals in the past 20 years, such as the first in the portal history, the Swedish Artportalen, or the Finnish Tiira, the Swiss Ornitho and its European siblings. This wealth of observations - available either as checklists or arbitrary individual entries - could be potentially used for scientific research about avifaunal dynamics, as a complement to traditional monitoring programs through bird surveys and ringing by volunteers and scientists. While several hundred publications have been written on a variety of topics based on eBird checklists worldwide, unstructured non-checklist observations, which represent the vast majority of European bird observations, have received little attention and praise by academia.

Flock of bramblings Figure 1. Flocks of diurnal migrants are easily observed by field ornithologists aka citizen scientists, like this flock of about 4000 bramblings Fringilla montifringilla in Southern Finland in October 2020 (Source: Nadja Weisshaupt).

In the paper Weisshaupt et al. (2021), we analysed 10 years of ornithological non-checklist data including over 400 million individuals of 115 bird species to obtain migration phenologies, i.e. start, peak and end of spring and autumn migration, and we discuss challenges and benefits of non-checklist data, amongst others in comparison to checklist data approaches. Overall, non-checklist data proved to be well suited to determine descriptors of migration phenology in Northern Europe which are challenging to attain by any other currently available means. The methodology is flexible and easily applicable also to non-checklist data from other bird portals.

The unprecedented spatiotemporal coverage makes non-checklist data a valuable complement to current migration databases from bird observatories. It could be used in climate change studies or in combination with radar data to relieve the species identification problem in aeroecology (Weisshaupt et al. 2020).