DOI: 10.5061/dryad.sqv9s4n92
title: Urbanization impacts short- but not long-distance natal dispersal in a common orb web spider

description: Urban environments represent a theatre for life history evolution. Species
 able to survive in cities can adapt to the local and often divergent
 environmental conditions compared to rural or (semi-)natural environments.
 Dispersal determines establishment, gene flow, and thus the potential for
 local adaptation. Since habitats in urban environments are highly
 fragmented, and show substantial turnover, contrasting adaptive effects on
 dispersal are expected. Fragmentation selects against dispersal while
 patch turn-over is expected to promote the evolution of dispersal. We here
 show both processes to act in concert when different scales are
 considered. Dispersal behavior of juvenile, lab-reared garden spiders from
 three mid-sized European cities were tested under standardized conditions.
 While long-distance dispersal showed to be overall rare, short-distance
 dispersal strategies increased with urbanization at small scales, but
 declined when urbanization was quantified at large scales. We discuss the
 putative drivers behind these differences in natal dispersal and highlight
 its importance for urban evolution and ecology.
description: Spider collection and
 husbandry Adult females <em>A. diadematus</em>
 were collected in the field in both Belgium and Denmark. In Belgium, 57
 females were randomly sampled in the larger area of Ghent following a
 gradient of urbanization (see locations in Supplementary Figure 1) in
 October 2020 and 2021. At these dates, female <em>A.
 diadematus</em> have all mated but not yet laid eggs. In Denmark, 65
 adult females were sampled at 4 locations following a paired sampling
 design: spiders were collected in the city (Aarhus and Aalborg, urban
 locations) and their close countryside (rural locations).
 Females were housed
 individually in the lab after which temperature was gradually reduced
 (to mimic natural conditions) to stimulate egg laying. Housing conditions
 were very similar in Belgium and Denmark (details can be found in
 supplementary information). To ensure successful hatching,
 <em>A.
 diadematus</em> eggs
 need a cold period of at least 4 weeks (Canard, 1984). After this cold
 period, the temperature
 was stepwise increased to 21°C (Supplementary Table 1 for exact rearing
 conditions). One egg sac
 can contain several hundred juveniles (i.e., spiderlings), and egg
 hatching typically starts within one week after reaching 21°C. After
 hatching, spiderlings stay together close to the egg sac forming
 aggregations or clutches. With time, spiderlings start to interact and
 diffuse, which increases the distance between spiderlings and thus the
 size of the aggregation. Aggregation size was measured for the Belgium
 spiders and used as a proxy for competition.  Dispersal assays
 We applied a modified
 experimental setup of Bonte et al. (2003). The setup consists of two pots
 with five wooden sticks fixed with a plaster layer that are placed on a
 platform which is subject to a chaotic airflow generated by a fan at one
 meter with the wind velocities ranging between 0.3 m/s and 2 m/s. The
 ambient temperature was 21°C, but the setup was additionally lighted by a
 100W incandescent lamp which mimics the effect of the sun (Supplementary
 Figure 2). Five spiders are placed individually at the top of each stick
 with a soft brush. Individuals displaying either rappelling (i.e., spider
 climb on an anchored silk thread) or ballooning (spiders disperse aerially
 attached to a non-anchored silk thread) were directly removed from the
 setup. Individuals only showing pre-dispersal tiptoeing behavior or using
 silk from other spiders to move between sticks were left on the platform
 for ten minutes to display ballooning or rappelling. The observation was
 stopped after ten minutes. After each assay, all spider silk was removed
 to minimise the effects of
 the previous clutch on the frequency of dispersal in spiderlings in the
 new batch (see De Meester
 & Bonte 2010). After the assay, spiderlings were placed back in
 their clutch. Dispersal experiments were executed
 approximately two to three weeks after hatching, an age at which spiderlings have
 usually all left the eggsac and formed characteristic aggregations. A
 total of 372 spiderlings from 65 clutches were tested once for Denmark. A
 total of 1682 spiderlings from 57 clutches were tested 2-3 times at
 intervals of 4–7 days for Belgium.
 Quantification of
 urbanization For the Ghent region (Belgium), we determined
 urbanization levels for the different sampling locations by calculating
 the percentage built-up areas (BUA). We used the object-oriented reference
 map of Flanders as a vectorial layer (Large-scale Reference Database 2018)
 that defines building contours. Roads, public squares and parking lots
 infrastructure are not included, therefore, an estimate of 15% built-up
 area can be considered highly urbanized. BUA was determined for multiple
 scales, using buffers of 50, 100, 250, 500, 1000, 2000 and 4000 m radius
 around the sampling location. BUA values for the sampling locations in the
 Ghent region are strongly correlated (Supplementary Figure 3). For
 Denmark, data on urbanization levels around the study sites was obtained
 in a similar way, this time using OpenStreetMap (OpenStreetMap
 contributors, 2022) as a data source. All polygons in the broader study
 areas with key="building" were extracted using the
 <em>osmdata</em>
 R package (Padgham et al.
 2017) and used to estimate the percentage of built-up area around each
 site at the same spatial scales. Statistical analyses
 Dispersal at the individual
 level is a binary yes/no response and follows a binomial distribution at
 the clutch-level (proportion of offspring dispersing). Individuals were
 scored after displaying their first behavior (ballooning/rappelling), and
 responses were, in principle, not independent at the trial level. However,
 since individual spiderlings may also show no responses, the correlation
 between ballooning and rappelling frequencies at the clutch level is low
 (r = -0.37). Because spiderlings from the Danish locations did not show
 ballooning at all, we decided to analyze rappelling and ballooning
 frequencies separately. We used mixed logistic regressions with
 urbanization as a fixed effect and the clutch ID as random effects.
 Because of design differences between Ghent and Danish samples, we
 analyzed them in separate and slightly different models. First, because
 Ghent spiderlings were tested multiple times, aggregation size was added
 as a covariate and proxy for the current level of competition. Second,
 compared to the random sampling design in the Ghent data, the paired
 design from the Denmark data breaks down to four locations with different
 levels of urbanization. Therefore, for the Ghent data, we ran 7 models
 separately for the different spatial scales of urbanization and selected
 the best model according to AIC criteria, while for the Danish data we
 analyzed urbanization as a factor (2-levels) variable. We qualitatively
 contrasted this output with the Ghent results. Ripley-K statistics
 (<em>Spatstat</em> package, Baddeley et al. 2015) were used to quantify the level of spatial
 correlation of both the urbanization rates and dispersal responses. For
 dispersal traits showing spatial autocorrelation (ballooning) spatial
 regressions were done using the <em>glmmTMB</em> package (Brooks et al. 2017). These showed the absence of spatial correlation
 in urbanization rates at small spatial scales (Supplementary Figure 4),
 implying random sampling across the city of Ghent. Evidently, when
 scaling-up, correlations become prominent as we only have one city and
 samples show spatial correlation according to the maximal scale of
 urbanization. Raw data and urbanization estimates are available on Zenodo.
 Maps were constructed in QGIS (version 3.283., QGIS Geographic Information
 System. QGIS Association) using the OpenStreetMap plugin (OpenStreetMap
 contributors, 2022), and the contours of Belgium were outlined using
 geoBoundaries (Runfola et al. 2020). 
description: # Urbanization impacts short- but not long-distance natal dispersal in a
 common orb web spider
 [https://doi.org/10.5061/dryad.sqv9s4n92](https://doi.org/10.5061/dryad.sqv9s4n92) ## Description of the data, file structure and R-scripts This README file was generated on 2023-09-27 by Dries Bonte   **GENERAL INFORMATION**   1\. Title of Dataset: Data and R\-scripts from:Urbanization impacts short\- but not long\-distance natal dispersal in a common orb web spider\. 2\. Author Information                 A. Principal Investigator Contact Information                  Name: Dries Bonte                  Institution: Ghent University                  Address: K.L. Ledeganckstraat 35                  Email: dries.bonte@ugent.be   3\. Date of data collection \(single date\, range\, approximate date\): 2020\-2022 4\. Geographic location of data collection: Ghent\, Belgium and Aarhus\, Denmark 5\. Information about funding sources that supported the collection of the data: FWO SpinCity G08022N   **SHARING/ACCESS INFORMATION**   1\. Licenses/restrictions placed on the data: CC0 1\.0 Universal \(CC0 1\.0\) Public Domain 2\. Links to publications that cite or use the data: Bonte\, D\. et al\. \(2023\)\. Urbanization impacts short\- but not long\-distance natal dispersal in a common orb web spider\. Oikos 3\. Links to other publicly accessible locations of the data: None 4\. Links/relationships to ancillary data sets: None 5\. Was data derived from another source? No 6\. Recommended citation for this dataset: Bonte\, D\. et al\. \(2023\)\. Data from: Urbanization impacts short\- but not long\-distance natal dispersal in a common orb web spider\. DRYAD\. [https://doi.org/10.5061/dryad.sqv9s4n92](https://doi.org/10.5061/dryad.sqv9s4n92)   **DATA & FILE OVERVIEW**   1\. File List: We provide data \(csv\-format\) and R\-scripts used for their analysis \(R\-files\)\. We organise our data and scripts according to the different objectives\.   **A. Determining the built-up area (BUA) at different scales.**   R-script to calculate the surface from aerial photographs: create\_merged\_buffers\_submission.R and subsequent calculate\_BU\_submission.R   The retrieved data are here: *correlation\_urbanisation\_scales.csv*   Assessing the correlations in BUA among the buffers and scales from this raw-data: *correlation\_urbanisation\_scales.R*.   **B. Assessing spatial correlation in the traits**   Dispersal data and BUA-data are combined with their geographic position in the raw data: *dispersal\_spatial\_analysis.csv.* The script to eventually get the spatial autocorrelograms: *dispersal\_spatial\_analysis.R*   **C.** **Linking dispersal to urbanisation by linear models and model selection are analysed for Aarhus and Ghent separately**         a.  Data and scripts for Ghent: *dispersal\_urbanisation\_behavioural\_data\_Belgium.csv* and Markdown for script and model selection: *urbanisation\_behaviour\_Belgium.Rmd* b.  Data and scripts for Aarhus: *dispersal\_urbanisation\_behavioural\_data\_Denmark.csv* and Markdown for script and model selection: *urbanisation\_behaviour\_Denmark.Rmd*   2\. Relationship between files\, if important: The R\-scripts and data are coupled as mentioned higher\. The variable ID links geographic and behavioural data   3\. Additional related data collected that was not included in the current data package: None   4\. Are there multiple versions of the dataset? No                 A. If yes, name of file(s) that was updated: NA                                 i. Why was the file updated? NA                                 ii. When was the file updated? NA   #########################################################################   DATA-SPECIFIC INFORMATION FOR: *correlation\_urbanisation\_scales.csv*   1\. Number of variables: 8 2\. Number of cases/rows: 58 3\. Variable List: * first seven variables u50, u100, u250, u500, u1000, u2000, u4000 represent the proportion built-up area in the respective radius (50-4000m) for the location where mother spiders were collected * ID:  ID of the mother collected 4\. Missing data codes: None 5\. Specialized formats or other abbreviations used: None   ######################################################################### DATA-SPECIFIC INFORMATION FOR: dispersal\_spatial analysis.csv   1\. Number of variables: 13 2\. Number of cases/rows: 58 3\. Variable List: * ID: ID of the mother spider * LATITUDE: latitude of the location of the collected mother * LONGITUDE: longitude of the location of the collected mother * fB: frequency ballooning offspring * fR: frequency rappelling offspring * fT: frequency tiptoeing offspring * last seven variables u50, u100, u250, u500, u1000, u2000, u4000 represent the proportion built-up area in the respective radius (50-4000m) for the location where mothers were collected 4\. Missing data codes: None 5\. Specialized formats or other abbreviations used: None   ######################################################################### DATA-SPECIFIC INFORMATION FOR: dispersal\_urbanisation\_behavioural\_data\_Belgium.csv These are the data for all tested offspring batches, so including number of events on total tested. 1\. Number of variables: 22 2\. Number of cases/rows: 160 3\. Variable List: * ID:  ID of the collected mother spider * period: week when the offspring were tested (1 or 2 weeks after moult) * fB: frequency ballooning offspring * NB: total number of offspring displaying ballooning * Btot: total number of offspring tested in this batch * fR: frequency rappelling offspring * NR: total number of offspring displaying rappelling * Rtot: total number of offspring tested in this batch * fT: frequency tiptoeing offspring * NT: total number of offspring displaying tiptoe behaviour * RT: total number of offspring tested in this batch * nest: size of the nest (categorical; see methods for ranges) * seven variables u50, u100, u250, u500, u1000, u2000, u4000 represent the proportion built-up area in the respective radius (50-4000m) for the location where mothers were collected * Location: name of the city (Ghent) * urban.cat: urban category according to criteria Aarhus (U: urban; R: rural)      4\. Missing data codes: NA \(data not applicable\)   #########################################################################   DATA-SPECIFIC INFORMATION FOR: dispersal\_urbanisation\_behavioural\_data\_Denmark.csv These are the data for all tested offspring batches, so including number of events on total tested. 1\. Number of variables: 19 2\. Number of cases/rows: 66 3\. Variable List: * ID:  ID of the collected mother spider * fB: frequency ballooning offspring * NB: total number of offspring displaying ballooning * Btot: total number of offspring tested in this batch * fR: frequency rappelling offspring * NR: total number of offspring displaying rappelling * Rtot: total number of offspring tested in this batch * fT: frequency tiptoeing offspring * NT: total number of offspring displaying tiptoe behaviour * RT: total number of offspring tested in this batch * seven variables u50, u100, u250, u500, u1000, u2000, u4000 represent the proportion built-up area in the respective radius (50-4000m) for the location where mothers were collected. Note that these data are not used in the analyses; they are only provided in comparison with the Belgian sites * Location: name of the city (Aarhus) * urban.cat: urban category according to criteria Aarhus (U: urban; R: rural)   4\. Missing data codes: NA \(data not applicable\)   #########################################################################