DOI: 10.5061/dryad.w0vt4b8nz
title: Flows of invasive ants worldwide to the United States

description: International trade and human movements have accidentally transported
 thousands of species worldwide at an unprecedented scale. The resulting
 biological invasions are among the greatest drivers of species extinctions
 and can cause enormous economic losses. Understanding how globalization
 affects the accidental transport of species is urgent to prevent new
 invasions. However, global trade networks have had mixed success so far in
 explaining intercontinental species movements. Here, we show that commonly
 used proxies of global trade flows such as general imports and
 agricultural imports differed greatly from flows of alien ants from their
 donor regions to the United States. The analysis of 97 individual
 commodity flows revealed instead that plants and fruit imports, which are
 a small subset of all agricultural commodities, were associated with
 invasion flows. All 95 other commodities differed from flows of alien
 ants, including most “agricultural” commodities which had extremely
 heterogenous geographic origins. This highlights the need to know
 precisely which commodities serve as introduction pathways for a
 particular taxonomic group in order to explain invasion flows and identify
 likely source regions of future invasions in a world of changing trade
 relationships.
description: <strong>Data</strong>
 <em>Species
 distributions</em> To determine the number of alien ant species
 that have established in the continental US (that is, the 48 contiguous
 states plus Alaska), we used the georeferenced database Antmaps
 (antmaps.org; an authoritative database maintained and updated regularly
 by experts based on new records in the peer-reviewed scientific
 literature; Janicki et al. 2016). Currently, 98 alien ant species have
 spread across the continental US and have established at least at one
 outdoor location worldwide (in order to qualify as “alien species”). One
 of these species, <em>Pheidole guineensis</em>, was excluded
 from the analyses because its native range is unknown, which prevented the
 mapping of invasion flows for this species. To calculate the geographic
 profile representing the “flow” of established ant species from their
 donor regions to the US, we defined the species’ native range as all
 countries containing native but no introduced populations. For species
 whose native range encompassed more than one world region, we weighted the
 flow from each of the world regions by the number of political regions
 where the species was recorded as native (that is, non-overlapping country
 or sub-country polygons representing states, counties, or islands, all of
 which are more homogenous in size than entire countries; Janicki et
 al. 2016). The most widespread species are occasionally introduced via
 bridgehead locations where they are already invasive and do not arrive
 directly from the native range (Bertelsmeier et al. 2018). Therefore,
 estimated “flows” between the native range of such species and the US may
 not reflect their actual introduction pathways. To avoid biases due to the
 bridgehead effect, we excluded the 46 most widespread species, with
 invaded ranges covering several world regions, from the analyses (WebTable
 1). <em>Trade data</em>
 To calculate import flows to
 the US for different categories of commodities, we used the UN Harmonized
 Commodity Description and Coding System (“Harmonized System” or HS), an
 international nomenclature for product classification. The HS comprises
 approximately 5300 article or product descriptions grouped into 97 broad
 categories (WebTable 2). Import data (reported in US dollars) for all 97
 broad categories of commodities were sourced from the US Census Bureau. We
 used import data for the 49 continental US states and 229 trade partner
 countries across the world, summed over the years 1991–2018. Data for this
 period comprised most of the exchanged commodity volumes since the
 beginning of the 20th century. We used records of inflation from the World
 Bank to convert trade records, which were expressed in US dollars for the
 year 2017. To standardize import profiles of geographic origins for each
 commodity, we divided imports arriving from each trading partner (in US
 dollars) by the total value of this commodity import to the US. This
 allowed representation of the relative contribution of different parts of
 the world to each commodity flow and avoided assigning greater weight to
 commodities with high monetary values. General import flows were
 calculated by summing all 97 individual commodity import flows, and
 agricultural trade flows were calculated by summing import flows of
 commodity categories 01–20. We also calculated a “plant and fruit” trade
 flow – often considered an important pathway for the transport of ants –
 by combining commodity categories 06, 07, and 08 (WebTable
 3). <strong> Statistical
 analyses</strong> To test whether the flows of general trade,
 agricultural trade, and plant and fruit trade differed from the flow of
 alien species to the US, we used chi-square tests with 2000 Monte Carlo
 replicates to determine P values.
 <em>Correspondence
 analysis</em> To analyze the similarities of import flows of
 the 97 commodity categories, we performed a correspondence analysis (CA)
 on the import profiles of geographic origins for all commodity categories,
 after row standardization (Greenacre and Primicerio 2013). Each row
 represented the compositional data of import flows for a commodity
 category, with columns consisting of world regions. Differences among
 commodity profiles of geographic origins were represented in the
 two-dimensional space of the factorial map. The first two axes represented
 59% of the total inertia. We added profiles of general trade, agricultural
 trade, and the plant and fruit trade flows, as well as the profile of
 alien species flows, to the CA space by projecting them as supplementary
 individuals (ie additional points that do not determine the axes, but can
 be plotted on the same factorial map using the same
 transformation). <em>Classification</em>
 To identify commodity flows
 that share the same geographic origins, we performed a classification of
 import profiles using a hierarchical cluster analysis. We first calculated
 Ward distances between the coordinates of the commodity categories in the
 CA space, keeping all five axes. Next, to test how many clusters
 constituted statistically significant groups among the 97 commodity
 profiles and four supplementary individuals (general trade, agricultural
 trade, plant and fruit trade, and alien species flows), we used a simple
 permutation test (Greenacre and Primicerio 2013) for determining
 homogeneous clusters of import profiles. This method allowed determination
 of the presence of nodes in the hierarchical clustering tree with levels
 lower than would be expected from dendrograms constructed on random
 permutations of the data. To generate distribution import flows from each
 world region under the null hypothesis that no differences exist among
 flows (ie geographic profiles for different commodities), we randomly
 permuted the data for each world region across commodity profiles (ie we
 performed column-wise permutations of the rows, where rows corresponded to
 commodities’ profiles and columns corresponded to world regions). The test
 was performed with 999 permutations. The primary objective of the
 permutation testing was to define the level at which the tree should be
 cut in order to obtain non-random levels of homogeneous clustering in the
 set of profiles.
description: See readme file.