Suitability of open digital species records for assessing biodiversity patterns in cities: a case study using avian records

Openly available species observation records on various online platforms achieve good coverage in urban areas. Thus, such digital data could provide a basis for biodiversity assessments in cities. Here, we investigated suitability of open digital species occurrence data, compared with systematically field surveyed data, in Freiburg, Germany (a Western city) and Dhaka, Bangladesh (a global-South city). We focused on resident bird species richness as an indicator of local biodiversity. We collected avian records for urban areas from ‘ornitho.de’ in Freiburg and ‘gbif.org’ in Dhaka. Additionally, we conducted point count surveys at several urban locations in both cities. Using these records, we prepared three grid (cell size 250 m × 250 m) based datasets—open digital dataset (i.e. records compiled from well-surveyed grid cells), field surveyed dataset (i.e. records of systematic bird surveys) and combined dataset (i.e. digital data and field data combined). We compared the relationship of resident bird richness with different habitat factors by applying linear regression models, separately using each of the three datasets. We assessed suitability of data from online platforms by comparing the variables retained after model selection based on digital data versus field surveyed data. We found that field surveyed data and combined data did not alter general understanding of the key driving factors of bird richness patterns we obtained from open digital data. This held for both case examples, Freiburg vs. Dhaka, respectively. This suggests that open digital data from well-surveyed urban locations can provide a suitable basis to assess drivers of biodiversity patterns within cities.