Species loss is highly scale-dependent, following the species-area relationship. We analysed spatio-temporal patterns of species’ extirpation on a multitaxonomic level using Berlin, the capital city of Germany. Berlin is one of the largest cities in Europe and has experienced a strong urbanisation trend since the late 19th century. We expected species’ extirpation to be exceptionally high due to the long history of urbanisation. Analysing regional Red Lists of Threatened Plants, Animals, and Fungi of Berlin (covering 9498 species), we found that 16 % of species were extirpated, a rate 5.9 times higher than at the German scale, and 47.1 times higher than at the European scale. Species’ extirpation in Berlin is comparable to that of another German city with a similarly broad taxonomic coverage, but much higher than in regional areas with less human impact. The documentation of species’ extirpation started in the 18th century and is well documented for the 19th and 20th centuries. We found an average annual extirpation of 3.6 species in the 19th century, 9.6 species in the 20th century, and the same number of extirpated species as in the 19th century were documented in the 21th century, despite the much shorter time period. Our results showed that species’ extirpation is higher at small than on large spatial scales, and might be negatively influenced by urbanisation, with different effects on different taxonomic groups and habitats. Over time, we found that species’ extirpation is highest during periods of high human alterations and is negatively affected by the number of people living in the city. But, there is still a lack of data to decouple the size of the area and the human impact of urbanisation. However, cities might be suitable systems for studying species’ extirpation processes due to their small scale and human impact.

Data extraction:

To determine the proportion of extirpated species for Germany, we manually summarised the numbers of species classified in category 0 ‘extinct or extirpated’ and calculated the percentage in relation to the total number of species listed in the Red Lists of Threatened Species for Germany, taken from the website of the Red List Centre of Germany (Rote Liste Zentrum, 2024a). For Berlin, we used the 37 current Red Lists of Threatened Plants, Animals, and Fungi from the city-state of Berlin, covering the years from 2004 to 2023, taken from the official capital city portal of the Berlin Senate Department for Mobility, Transport, Climate Protection and Environment (SenMVKU, 2024a; see overview of Berlin Red Lists used in Table 1). We extracted all species that are listed as extinct/extirpated, i.e. classified in category 0, and additionally, if available, the date of the last record of the species in Berlin. The Red List of macrofungi of the order Boletales by Schmidt (2017) was not included in our study, as this Red List has only been compiled once in the frame of a pilot project and therefore lacks the category 0 ‘extinct or extirpated’. We used Python, version 3.7.9 (Van Rossum and Drake, 2009), the Python libraries Pandas (McKinney et al., 2010), and Camelot-py, version 0.11.0 (Vinayak Meta, 2023) in Jupyter Lab, version 4.0.6 (Project Jupyter, 2016) notebooks. In the first step, we created a metadata table of the Red Lists of Berlin to keep track of the extraction process, maintain the source reference links, and store summarised data from each Red List pdf file. At the extraction of each file, a data row was added to the metadata table which was updated throughout the rest of the process. In the second step, we identified the page range for extraction for each extracted Red List file. The extraction mechanism for each Red List file depended on the printed table layout. We extracted tables with lined rows with the Lattice parsing method (Camelot-py, 2024a), and tables with alternating-coloured rows with the Stream method (Camelot-py, 2024b). For proofing the consistency of extraction, we used the Camelot-py accuracy report along with the Pandas data frame shape property (Pandas, 2024). After initial data cleaning for consistent column counts and missing data, we filtered the data for species in category 0 only. We collated data frames together and exported them as a CSV file. In a further step, we proofread whether the filtered data was tallied with the summary tables, given in each Red List. Finally, we cleaned each Red List table to contain the species, the current hazard level (category 0), the date of the species’ last detection in Berlin, and the reference (codes and data available at: Github, 2023). When no date of last detection was given for a species, we contacted the authors of the respective Red Lists and/or used former Red Lists to find information on species’ last detections (Burger et al., 1998; Saure et al., 1998; 1999; Braasch et al., 2000; Saure, 2000). Determination of the recording time windows of the Berlin Red Lists We determined the time windows, the Berlin Red Lists look back on, from their methodologies. If the information was missing in the current Red Lists, we consulted the previous version (see all detailed time windows of the earliest assessments with references in Table B2 in Appendix B).

Data classification:

For the analyses of the percentage of species in the different hazard levels, we used the German Red List categories as described in detail by Saure and Schwarz (2005) and Ludwig et al. (2009). These are: Prewarning list, endangered (category 3), highly endangered (category 2), threatened by extinction or extirpation (category 1), and extinct or extirpated (category 0). To determine the number of indigenous unthreatened species in each Red List, we subtracted the number of species in the five categories and the number of non-indigenous species (neobiota) from the total number of species in each Red List. For further analyses, we pooled the taxonomic groups of the 37 Red Lists into more broadly defined taxonomic groups: Plants, lichens, fungi, algae, mammals, birds, amphibians, reptiles, fish and lampreys, molluscs, and arthropods (see categorisation in Table 1). We categorised slime fungi (Myxomycetes including Ceratiomyxomycetes) as ‘fungi’, even though they are more closely related to animals because slime fungi are traditionally studied by mycologists (Schmidt and Täglich, 2023). We classified ‘lichens’ in a separate category, rather than in ‘fungi’, as they are a symbiotic community of fungi and algae (Krause et al., 2017). For analyses of the percentage of extirpated species of each pooled taxonomic group, we set the number of extirpated species in relation to the sum of the number of unthreatened species, species in the prewarning list, and species in the categories one to three. We further categorised the extirpated species according to the habitats in which they occurred. We therefore categorised terrestrial species as ‘terrestrial’ and aquatic species as ‘aquatic’. Amphibians and dragonflies have life stages in both, terrestrial and aquatic habitats, and were categorised as ‘terrestrial/aquatic’. We also categorised plants and mosses as ‘terrestrial/aquatic’ if they depend on wetlands (see all habitat categories for each species in Table C1 in Appendix C). The available data considering the species’ last detection in Berlin ranked from a specific year, over a period of time up to a century. If a year of last detection was given with the auxiliary ‘around’ or ‘circa’, we used for further analyses the given year for temporal classification. If a year of last detection was given with the auxiliary ‘before’ or ‘after’, we assumed that the nearest year of last detection was given and categorised the species in the respective century. In this case, we used the species for temporal analyses by centuries only, not across years. If only a timeframe was given as the date of last detection, we used the respective species for temporal analyses between centuries, only. We further classified all of the extirpated species in centuries, in which species were lastly detected: 17th century (1601-1700); 18th century (1701-1800); 19th century (1801-1900); 20th century (1901-2000); 21th century (2001-now) (see all data on species’ last detection in Table C1 in Appendix C). For analyses of the effects of the number of inhabitants on species’ extirpation in Berlin, we used species that went extirpated between the years 1920 and 2012, because of Berlin’s was expanded to ‘Groß-Berlin’ in 1920 (Buesch and Haus, 1987), roughly corresponding to the cities’ current area. Therefore, we included the number of Berlin’s inhabitants for every year a species was last detected (Statistische Jahrbücher der Stadt Berlin, 1920, 1924-1998, 2000; see all data on the number of inhabitants for each year of species’ last detection in Table C1 in Appendix C).

Materials and Methods from Keinath et al. (2024): 'High levels of species’ extirpation in an urban environment – A case study from Berlin, Germany, covering 1700-2023'.