DOI: 10.5061/dryad.jm63xsjjb
title: Weak effect of urbanisation on bdelloid rotifers living in lichens

description: Human activities have an overwhelming impact on the natural environment,
 leading to a deep biodiversity crisis whose effects range from genes to
 ecosystems. We here analysed the effect of such anthropogenic impacts on
 bdelloid rotifers (Rotifera: Bdelloidea), for whom these effects are
 poorly understood. We targeted bdelloid rotifers living in lichen patches
 across urbanisation gradients in Flanders and Brussels (Belgium).
 Urbanisation was measured as the percentage of built-up area across
 different spatial scales, at circles from 50 m to 3,200 m of radius around
 the lichen. Urbanisation effects on biodiversity were assessed on
 abundance, species richness, and community-weighted mean body size of
 bdelloid rotifers, as well as on genetic diversity of one of the most
 common and widespread bdelloid species, Adineta vaga. Overall, no negative
 effect of urbanisation was found at any diversity level and at any spatial
 scale. Counterintuitively, built-up area quantified at the largest spatial
 scale had a positive effect on abundance. These results leave open the
 question of whether negative effects of urbanisation are present for
 bdelloid rotifers, or if such effects are only visible at even larger
 spatial scales.
description: Communities of bdelloid rotifers were sampled by collecting one
 lichen patch in each subplot. We selected lichens of the genus
 <em>Xanthoria</em>, for which bdelloid rotifer communities
 have been previously studied in Europe (Fontaneto et al. 2011). Lichens of
 the genus <em>Xanthoria</em> are among the most abundant in
 urban and rural areas, apparently unaffected by urbanisation levels
 (Nekrošienė 2012). Sampling was performed in June and July 2013. Suitable
 <em>Xanthoria</em> patches could be found in all but two
 subplots: total sample size is thus 79 lichens and not 81. 
 The selection of the lichen was haphazard: the first suitable
 lichen patch encountered in each subplot was collected. Dry lichen thalli
 between 5 and 10 cm<sup>2</sup> were cut from the substrate
 with a knife and kept in zip lock bags. For each lichen sample, an area of
 2.5 cm<sup>2</sup> was hydrated with distilled water in a
 plastic petri dish.  All active bdelloid rotifers that
 recovered from dormancy within the four hours following hydration in the
 lab were sorted and identified to species level according to Donner
 (1965). Previous studies on bdelloid rotifers in these lichens (Fontaneto
 et al. 2011) revealed that animals start recovering between 10 and 40
 minutes after hydration of the sample and that no more additional bdelloid
 rotifers usually recover after four hours. The very few dormant stages
 still found in the sample that did not recover after that time were
 considered dead, impossible to identify at any taxonomic rank, and
 excluded from the analyses. All living bdelloids were
 isolated, counted, and identified to species level to obtain data on (1)
 abundance and (2) species richness. The other descriptor of
 community-level diversity was (3) community-level body size (Merckx et al.
 2018b), calculated as community-weighted mean body size, which is the
 average of the species-specific body length for all sampled species in a
 community, weighted by species abundance in the community. Measurements of
 body length for the observed species, obtained from the observed animals,
 are reported in Merckx et al. (2018b). The most common
 and abundant species in all samples, <em>Adineta vaga</em>,
 was selected to obtain metrics of genetic diversity. DNA was extracted
 from each of the individuals found in a separate extraction of bdelloids
 from the part of each lichen patch that was not used for the morphological
 identifications. We amplified the barcoding fragment of the mitochondrial
 marker cytochrome c oxidase subunit I, COI, using Folmer primers with
 optimised protocols for this species (Debortoli et al. 2016). COI
 sequences were trimmed to a total common length of 605bp and aligned using
 default settings in MAFFT v7 (Katoh et al. 2019), confirming correct amino
 acid translation. Species identity was confirmed through online BLAST
 searches (Ye et al. 2006). The number of <em>A. vaga</em>
 haplotypes for each population of the species in a lichen patch was used
 as a metric of genetic diversity.
description: # Weak effect of urbanisation on bdelloid rotifers living in lichens
 Here we report all the
 datasets and R scripts that we used to test our hypotheses about rotifer
 community abundance and assemblage in a context of increasing
 urbanisation. ## Description of the data and file structure 1. The main
 dataset, contained in the file “ESM_04-speedy_bdello.csv” describes each
 of the 79 samples collected for this study. * Column 1, “lichen.patch”,
 uniquely defines the sampled lichen patch. It coincides with column 28,
 “sampleID”. * Columns 2-22 report individual quantity of each bdelloid
 rotifer species. For example: in the lichen sample Gg8 only 2 individuals
 of *Macrotrachela ehrenbergii* were identified. * Column 23, “abundance”,
 reports the total abundance of rotifers found in the lichen patch. For
 example, in the sample Gg8 only 2 rotifers were found, hence quantity is
 2. * Column 24, “richness”, informs on how many different species were
 found in the patch of lichen collected. For sample Gg8 the richness value
 is 1 as only one species was found, *Macrotrachela ehrenbergii* * Column
 25, “mean_size” is the community-weighted mean body size, calculated as
 the average of the species-specific body length for all sampled species in
 a community, weighted by species abundance in the community, as explained
 in the manuscript. * Column 26, “Waypoint”, gives the exact GPS
 coordinates of the spot where the lichen was collected, unlike the
 coordinates, which identify the 3x3 km plot. * Column 27, “sample” was the
 alpha-numeric code used to identify the tube of the sample collected for
 laboratory analyses. * Column 28, “sampleID”, coincides with Column 1. *
 Column 29 states when the sample was collected in DD-MM-YYYY format. *
 Columns 30, “Plot”, identifies the 3x3km plot. * Columns 31, “Subplot”,
 identifies the 200x200m subplot. * Column 32, “ID”, is a number that
 identifies the lichen collected. The unique lichen patch would be a fusion
 of columns 30-31-32, i.e, “G-g-16” as seen in column 28, “SampleID”. So,
 for example, sample “Gg16” was sample n.16 collected in plot “G” and
 subplot “g”. * Columns 33-35 are the geographical coordinates in degrees
 of the 3x3km plot location. Altitude, "Alt", is expressed in
 metres above sea level. * Column 36, “PatchID” summarises information on
 the urbanisation level of the plot sampled. For example, P16SG. P= Plot,
 16= ID (see column 32), S= Subplot, G= refers to urbanisation level of
 subplot as seen in column 38. * Columns 37-38, “plot colour” and “subplot
 colour” are categorical variables that summarize the level of the
 urbanisation of the plot and the subplot (Red-High level, Yellow-Medium
 level and Green-Low level.). * Columns 39, “Substrate” is a categorical
 variable that admits 2 categories: “artificial”, meaning that the lichen
 was collected from an artificial surface or “tree” meaning the lichen was
 found on a tree. * Column 40, “Substrate 2” works in a similar manner but
 gives more information on the substrate: i.e., genus of the tree or type
 of artificial surface (roof, metal, concrete etc.). * Columns 41-48,
 “BU50, BU100, BU200” etc. quantify the level of urbanization present in
 the plot as explained in the Methods section. 2. Each row of the dataset
 contained in the excel file “ESM_07 - Speedy_COI.csv” uniquely identifies
 the sample, animal and patch collected and gives the sequence of the COI
 mitochondrial marker of each rotifer of the species *Adineta vaga* 3. The
 dataset contained in the file “ESM_08 - Speedy_COI_data.csv” is identical
 to the file “ESM_04-speedy_bdello.csv” plus two more columns: “Haplotypes”
 which tells the number of haplotypes found and “Sequenced_animals” which
 tells the number of animals sequenced. ## Code 1.     The R file
 “ESM_03-speedy_bdello.R” allows to run the ecological analyses as they are
 presented in the manuscript. 2.     The R file “ESM_05 - Speedy_COI.R”
 allows to run the analyses of genetic diversity as they are presented in
 the manuscript. 3.     The FAS file “ESM_06 - Speedy_COI.FAS” gives the
 COI alignment to be used for the analyses on genetic diversity following
 the R script “ESM_05 - Speedy_COI.R”.