DOI: 10.5061/dryad.dr7sqv9zr
title: Invasion success and tolerance to urbanization in birds

description: Cities are considered hotspot of biological invasions, yet it remains
 unclear why non-indigenous species are so successful in environments that
 most local native species do not tolerate. Here, we explore the intriguing
 possibility that humans may be unintentionally introducing species
 preadapted to persist in such environments. Combining data on historical
 introductions with information of avian assemblages along urban-wildland
 gradients, we found that avian species that in their native range
 proliferate in human-altered environments have been more likely to be
 transported and introduced to new locations than species confined to the
 wildland. We also found that such urban dwellers had higher chances to
 become established because they already had adaptations to cope with novel
 environments. These findings suggest that the pathway of introduction
 selects for species preadapted to persist in novel environments, providing
 an explanation for why non-indigenous birds are so successful in cities.
 Because the tendency to introduce species associated with human-altered
 environments continues, there is an urgent need to develop new regulations
 to prevent future introductions.
description: We drew on openly available data sources. For Dataset S1, we
 assess for "occurrence of birds in human-altered
 environments"<strong> </strong>by using the habitat
 classification scheme from the International Union for Conservation of
 Nature (IUCN). This classification scheme includes data for habitat
 occurrence of 9,903 bird species (see IUCN habitat classification scheme
 3.1;
 http://www.iucnredlist.org/technical-documents/classification-schemes).
 The IUCN data allowed us to classify bird species as occurring or not
 across any type of artificial terrestrial habitat such as arable land,
 pastureland, plantations, rural, urban and subtropical/tropical heavily
 degraded former forest (n = 4,515 species occurring in these human-altered
 environments,<strong> </strong>"humanDisturbed"
 column in Dataset S1). We also classified species as occurring or not in
 urban areas - the most modified environments (n = 905 species,
 "urban" column in Dataset S1). We also assess for "bird
 tolerance to urban areas in the native range". Because occurrences of
 avian species in urban environments depends in part from their abundance
 in nearby rural and natural habitats, we used a dataset of avian
 assemblages available from the Dryad Digital Repository:
 https://doi.org/10.5061/dryad.2rbnzs7jf to compute two metrics of urban
 tolerance. The first metric was estimated as the log-log difference in the
 mean number of individuals of a species recorded between highly urbanized
 habitat (HUR) and nearby natural vegetation (NVG) of a given study
 location (‘hereafter’ urban tolerance index or UTI, Sol et al. 2017). High
 positive values of the index indicate high tolerance to the environmental
 alterations associated with urbanization, while low negative values
 indicate species less tolerant to urbanization (Evans et al.
 2011)("UTI" column in Dataset S1). Values close to zero are more
 uncertain as they may indicate either no effect of urbanization or that
 the species is too scarce in the region to assess its tolerance (Sol et
 al., 2014). To tackle this issue, we used a second, more restrictive,
 metric to estimate urban tolerance based on community simulations. This
 allowed us to effectively separate species that tolerate urbanization
 (exploiters) from those that do not (avoiders). A species was considered
 an urban ‘exploiter’ if its observed abundance in the highly urbanized
 habitat was equal to or greater than the 95th percentile of the abundance
 expected by chance, and an urban ‘avoider’ if it was equal to or lower
 than the 5th percentile; the species for which information was
 insufficient to be assigned to one or another category (i.e. their
 abundances in urban areas were distributed as expected by random) were not
 considered. Because we were interested in the intrinsic ability of a
 species to tolerate urbanization, we considered a species as an exploiter
 when at least one of its native populations was classified in this
 category ("tolerance" column in Dataset S1). Additionally, we
 estimated bird “invasion potential” (i.e. tendency of a species to succeed
 wherever it is introduced) as the species-level random coefficients of a
 generalized linear mixed model that includes establishment success as the
 dependent variable, introduction effort as fixed effect, and taxonomy
 (Orders, Families within orders and Species within families) and country
 of introduction as random effects (Sol et al. 2005, 2012b). For this, we
 used a global data source of historical avian introductions from a
 previous study (Sol et al. 2012b). This dataset provides information on
 establishment success (i.e. whether a given introduction event was
 successful or failed to produce a self-sustaining population) and
 introduction effort for 832 events for 202 bird species (Data available at
 https://doi.org/10.1126/science.1221523 as Supporting Information). A high
 score in the invasion potential means that the species tends to succeed
 wherever it is introduced and a low score that it tends to fail when
 differences in introduction effort are controlled statistically
 ("invasion.potential" column in the Dataset S1). Finnaly, we
 gathered information from previously assembled data sets for species
 traits that preadapt birds to cope with novel environments (Sol et al.
 2012b, 2017a, Sayol et al. 2016) and could also affect urban tolerance
 (Sol et al. 2014, 2017a). The traits considered were: i) the brood value
 ("broodValue" column in Dataset S1), an index that represents
 the value of current reproduction with respect to the value of future
 reproduction (Bókony et al. 2009), estimated as log10{1/(broods per year x
 lifespan)}; ii) relative brain size, which is a surrogate of behavioral
 flexibility (Lefebvre et al. 1997, Reader and Laland 2002) and was
 estimated as the residuals of a phylogenetically corrected least squares
 log-log regression between brain ("Brain" column in Dataset S1)
 and body size ("Body" column in Dataset S1) using the phyl.resid
 function of the phytools r-package (Revell 2009); and iii) niche breadth,
 characterized by the frequency of use (not used = 0, occasionally used =
 0.1, frequently used = 0.5 and almost exclusively used = 1) of different
 categories of habitat and diet, expressed as Rao's quadratic entropy
 (De Cáceres et al. 2011). The categories used to define habitat breadth
 were forest, woodland, open vegetation (including tundra and grassland)
 and aquatic habitats (including marshes and wetlands; see Wilman et al.
 (2014))("HA" column in Dataset S1) . For diet breadth
 ("DA" column in Dataset S1), we considered the percentage of use
 of invertebrates, endotherms, ectotherms, fishes, scavengers, fruits,
 nectar, seeds, plants and unknow items. For Dataset S2,
 we used CITES information on bird trade. Because patterns of introduction
 change over time, pathways that were rare in the past, like the trade in
 pet birds, are now the most common (Abellán et al. 2016, Dyer et al.
 2017). To test whether there is an ongoing trend to introduce species that
 are associated with humans in their native ranges, we used information on
 the total number of live individuals per species that were legally traded
 from 1975 to 2013 according to the Convention on International Trade in
 Endangered Species of Wild Fauna and Flora (CITES) data (n = 1074 species;
 "Imports" column in Dataset S2)(www.cites.org). While CITES
 information is not exempt of potential bias such as underrepresentation of
 some taxonomic groups or occasional failures in the estimation of the
 number of individuals involved in trade, it still represents the only
 global formal convention tracking data on international trade in wildlife
 in a structured and verifiable way (Reino et al. 2017). Indeed previous
 analyses have shown a direct link between trade and introduction numbers
 (Reino et al. 2017, Cardador et al. 2019). For each CITES trade event,
 information on the number of traded individuals came from the importer
 country (28.7%), the exporter country (19.6%) or both (51.7%). This is not
 likely to affect our results, since when available, information provided
 by the importer and the exporter countries was highly correlated (Pearson
 correlation coefficient: r = 0.91, P &gt; 0.001, n = 7,606). In these
 cases, the maximum number of individuals reported was used for analyses
 (Dataset S2).
description: In addition to Dataset S1 and S2, we provide Dataset S3
 containing the code and country for each study location, and aslo their
 latitude and longitude. We provide an R script to replicate the main
 analyses of the manuscript "Invasion success and tolerance to
 urbanization in birds" using these dataset and other available
 dataset (doi are provided in the r script).