DOI: 10.5061/dryad.bcc2fqznq
title: Data from: Biodiversity and local features of 103 public urban squares in Munich, Germany

description: This dataset contains biodiversity and square features of 103 public urban
 squares (Platz in German) in Munich, Germany. Data were collected to
 investigate how designed features of urban squares influences the
 biodiversity occurring there. Data were collected between April 2017 and
 July 2020. Square features were characterised using Colour-infrared Aerial
 images (CIR, Bavarian Agency for Digitisation, High-Speed Internet and
 Surveying, Munich) and land register maps and measurements using a
 telemeter and a tape measure. Biodiversity of arthropods, bats, birds,
 bryophytes, pollinators, small mammals, and spontaneous vegetation was
 determined using taxa-specific sampling methods and deriving richness and
 abundance (or activity) for each taxon.  
description: Arthropods were sampled using suction sampling for sealed
 surfaces, grass, and flowerbeds. Trees and shrubs were sampled using
 knockdown sampling. Sampled arthropods were collected in jars and sorted
 to order level in the laboratory. Bats were sampled
 using an ecoObs Batcorder 3.1 ultrasonic recorder (quality = 20, threshold
 = -36 dB, post-trigger = 800 ms, critical frequency = 14kHz). Recording
 took place from one hour before sunset to one hour post sunrise four times
 on single nights. Bat calls were identified to species level where
 possible and where not, the lowest level species group was attributed
 based on the acoustic properties. Birds (separately
 considering the feral pigeon, <em>Columba livia
 domestica</em>) were determined visually and aurally by observing
 all birds within a 25m radius along transects for a total of 20 minutes on
 each square in spring, fall, and winter. Bryophytes
 (including mosses and liverworts) was determined by collecting bryophytes
 on three different types (wood, soil, and stone). Each substrate type was
 sampled for a maximum of 20 minutes each and sampling stopped if no new
 species were detected for several minutes. Collected samples were dried
 overnight at 50°C and were identified to species level where possible,
 otherwise identified as species groups or morphospecies using relevant
 guidebooks and comparison with herbarium specimens.
 Pollinators on each square was determined by counting visits of
 pollinator functional groups (Coleoptera, <em>Bombus</em>,
 Lepidoptera, <em>Apis mellifera</em>, Syrphidae, Diptera,
 Apoidae, and Vespidae) to each of five different phytometers representing
 different pollination syndromes.<em> </em>Phytometers were:
 <em>Nicotiana sanderae</em>, <em>Salvia
 farinacea</em>, <em>Lobelia erinus</em>,
 <em>Sanvitalia procumbens</em>, <em>Lobularia
 maritima</em>. Due to disease, the <em>Lobularia
 maritima</em> were replaced by <em>Euphorbia
 hypericifolia</em>, part way through the sampling. Phytometers were
 observed for 30 minutes at three different times of day: morning, midday,
 and afternoon. Small and pest mammal species (mice and
 rats) were determined using footprint tunnels baited with cat food
 containing ink pads and blank paper for recording tracks. Tunnels were in
 place for five consecutive nights on each square with ten tunnels per
 square covering different combinations of surfaces (sealed or gravel and
 grass) and linear structures (hedge and wall). The tunnels were checked
 daily and the track sheets replaced if necessary. Tracks were later
 identified to species level or species group based on characteristics of
 the footprint. Spontaneous herbaceous vegetation was
 determined by observing eight surface types frequently mown grass
 (&lt;15cm), infrequently mown grass (&gt;15cm), tree plates, woody
 structures other than trees, planting beds, planters, pavement cracks,
 unsealed surfaces and additionally furnishings, e.g., benches) on each
 square for 15-minutes each. All observed plants were identified to species
 level. Multidiversity (Allan et al. 2014) was
 determined by scaling the species richness to the highest observed
 richness across all squares and averaging the proportional richness across
 all taxonomic groups. References
 Allan E, Bossdorf O, Dormann CF, et al (2014) Interannual
 variation in land-use intensity enhances grassland multidiversity. Proc
 Natl Acad Sci 111:308–313.
 https://doi.org/10.1073/pnas.1312213111
description: # Data from: Biodiversity and local features of 103 public urban squares
 in Munich, Germany
 [https://doi.org/10.5061/dryad.bcc2fqznq](https://doi.org/10.5061/dryad.bcc2fqznq) ## Description of the data and file structure **Biodiversity and local features of 103 public urban squares in Munich, Germany.** Data were collected to investigate how designed features of urban squares influence the biodiversity occurring there. Data were collected between April 2017 and July 2020. Complete methods can be found in the associated manuscript and supplementary information. ### Files and variables 100_squares_data.csv contains the square features, abundance (or activity) and richness of arthropods, bats, birds, bryophytes, pollinators, small mammals, spontaneous herbaceous vegetation, and multidiversity. Missing values are indicated as "NA". The first five rows of the .csv file contain the metadata. Row 1: Column label (repeated in row 6) Row 2: A short description of the variable. Row 3: A short description of the method used to calculate the variable. Row 4: The datatype (string, binary, numeric). Row 5: The unit of the variable. squareId unique short id of the square Four letter code based on the full name of the square. string name full name of the square Extracted from Google Maps string district governmental unit of Munich to which the square belongs Extracted from the table of Sebastian Dengler's thesis string waterPresence source of water (e.g. fountains) on the square Zero or one based on presence of fountains on the square binary numberStreets number of streets that are touching the square boundaries Data extracted from Google Maps numeric size total area of each square Area in sqm /10000 numeric distance distance to the city center (Marienplatz)\ Calculated as eucledian distance between the centroids of the squares and the centroid of Marienplatz numeric km greenBufferProp proportion of the vegetated area in a 1km-buffer around squares to characterize the surrounding of squares Using color-infrared aerial images (20 cm x 20 cm resolution per pixel) we calculated the NDVI. We defined a threshold of NDVI values larger than 0.2 to characterize vegetated pixel and calculated the proportion of vegetated pixels for 1km buffers around each square. numeric proportion shrubVolume average shrub volume per squaremeter ground Areas of shrubby vegetation were recorded separatly for four different height classes (&lt;1m, 1-2m, 2-3m, &gt;3m). The total shrub volume on a square was calculated by multiplying the absolute areas with the respective heights, and the total volume was devided by the area of the square resulting in an average shrub volume per squaremeter square. numeric m3/m2 flowersArea absolute area of planted flower beds and flower tubs on a square Sum of areas of flower beds and flower tubs. Aerial images (google earth and land register maps were used for estimating the ground area covered by unsealed surfaces. When areas were covered with trees, or patches were not clearly identifiable on the areal images, they were measured on the squares with a measuring tape and telemeter. numeric m2 grassProp proportion of grass covered area on a square Area of a square coverd by grass devided by total area of the square. numeric proportion treeRichness species richness of trees on the square All trees on a square with dbh&gt;7cm have been identified to species and the number of tree species occuring on a square has been calculated. numeric n treeDensity density of trees on a square Absolute number of trees multiplied with 100 divided by area of the square: tabund*100/area (m2) to standardize tree abundance for the differing size of squares. numeric 1/100m2 treeMedianDbh average size of trees on a square Median of the the diameter at breast height (dbh) calculated for all trees on a square with dbh&gt;7cm. numeric cm treeDbhVar variability of size of trees on a square Coefficient of variation of the the diameter at breast height (dbh) calculated for all trees on a square with dbh&gt;7cm. numeric unitless oldTreeAbundance absolute number of old trees on a square All trees with a dbh&gt;60cm have been defined as old trees and their number counted per square numeric n oldTreeProp proportion of old trees on a square Old tree abundance devided by total tree abundance: oldtabund/tabund numeric proportion numberHumans average number of people on a square At three times (morning, noon, afternoon; on different days) a photo was taken from the center of squares in all four cardinal directions. The number of people was counted on each picture. Numbers were summed for the four pictures per sampling day and averaged over the three sampling days. numeric n alan artificial light at night Calculated as average grey value per square using Luojia-1 satellite images fromNovember 16, 2018. numeric mean multidiversity multidiversity Calculated by scaling the species richness to the highest observed richness across all squares and averaging the proportional richness across all taxonomic groups. numeric mean arthropodAbundance abundance of arthropod orders numeric n arthropodRichness richness of arthropod orders numeric n batRichness richness of bat species and species groups numeric n batActivity artivity of bat species or species groups Determined by calculating the total number of minutes per sampling period in which a call of that species was recorded. numeric n pigeonAbundance abundance of Columba livia domestica numeric n birdAbundance abundance of birds numeric n birdRichness richness of birds numeric n meanDomestic average number of domestic animals (cats and dogs) Determined as the average number of cats or dogs observed during the bird surveys. numeric mean bryophyteRichness richness of bryophytes numeric n pollinatorAbundance abundance of pollinator orders numeric n pollinatorRichness richness of pollinator orders numeric n flowerAbundance abundance of racemes, spikes and umbels Calculated as the number of racemes, spikes and umbels in a three-meter radius around phytometers used for pollinator monitoring. numeric n flowerRichness richness of flowers Calculated as the richness of flowers in a three-meter radius around phytometers used for pollinator monitoring. numeric n wildMammalActivity activity of small wild mammals, predominately hedgehods The proportion of valid track sheets per square for which small mammals were detected. numeric proportion pestMammalActivity activity of pest small mammals, predominately rats and mice The proportion of valid track sheets per square for which small pest mammals were detected. numeric proportion vegetationRichness richess of spontaneous vegetation numeric n ## Code/software No code or software is required to view our data.