10.5061/DRYAD.31ZCRJDNW
Mally, Richard
0000-0001-5996-9471
Czech University of Life Sciences Prague
Turner, Rebecca M.
0000-0002-7885-3092
Scion
Blake, Rachael E.
National Socio-Environmental Synthesis Center
Fenn-Moltu, Gyda
0000-0002-6148-8076
University of Lausanne
Bertelsmeier, Cleo
University of Lausanne
Brockerhoff, Eckehard G.
Swiss Federal Institute for Forest, Snow and Landscape Research
Hoare, Robert J. B.
Landcare Research
Nahrung, Helen F.
University of the Sunshine Coast
Roques, Alain
National Research Institute for Agriculture, Food and Environment
Pureswaran, Deepa S.
Canadian Forest Service
Yamanaka, Takehiko
National Agriculture and Food Research Organization
Liebhold, Andrew M.
0000-0001-7427-6534
US Forest Service
Moths and butterflies on alien shores – global biogeography of non-native
Lepidoptera
Dryad
dataset
2022
FOS: Biological sciences
biological invasions
commodities
establishment
border interceptions
International trade
invasion disharmony
non-native region
Propagule pressure
OP RDE*
CZ.02.1.01/0.0/0.0/16_019/0000803
New Zealand Ministry of Business, Innovation and Employment*
C09X1501
US Forest Service
https://ror.org/03zmjc935
21-IG-11132762-241
Te Pūnaha Matatini
https://ror.org/00wtgbr91
Programme de la famille Sandoz-Monique de Meuron pour la relève
universitaire, canton Vaud*
Swiss National Science Foundation
https://ror.org/00yjd3n13
SNF 310030_192619
National Socio-Environmental Synthesis Center*
DBI-1639145
European Research Council
https://ror.org/0472cxd90
771271
2022-04-28T00:00:00Z
2022-04-28T00:00:00Z
en
https://doi.org/10.5281/zenodo.5245301
https://doi.org/10.5281/zenodo.4555787
253394 bytes
3
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Lepidoptera is a highly diverse, predominantly herbivorous insect order,
with species transported to outside their native range largely facilitated
by the global trade of plants and plant-based goods. Analogous to island
disharmony, we examine invasion disharmony, where species filtering during
invasions increases systematic compositional differences between native
and non-native species assemblages, and test whether some families are
more successful at establishing in non-native regions than others. We
compared numbers of non-native, unintentionally introduced Lepidoptera
species with the land area of 11 regions worldwide (Hawaii, North America,
Galapagos, Europe, South Africa, South Korea, Japan, Nansei Islands,
Ogasawara Islands, Australia, New Zealand). Differences among native and
non-native assemblages in the distribution of species among families were
investigated using ordination analysis. We tested whether invasion
disharmony is explained by propagule pressure (proxied by species richness
in border interceptions) and if families were associated with specific
trade commodities. In total, 741 non-native Lepidoptera species,
accounting for 0.47% of the global diversity of lepidopterans, are
established in at least one of the 11 regions. Crambidae, Pyralidae,
Tineidae and Gracillariidae were particularly successful invaders, whereas
the two most species-rich families, Erebidae and Geometridae, were
under-represented among non-native Lepidoptera. Much of the variation in
species numbers in the native, and less so in the non-native assemblages
could be attributed to land area. Although native assemblages were similar
among nearby regions, non-native assemblages were not, suggesting
geography had little effect on invasion disharmony. Comparison of
established with intercepted species revealed that macromoth families were
generally under-represented in establishments, whereas several micromoth
families were under-represented in interceptions. This discrepancy may
relate to greater detectability of larger species or high propagule
pressure via associations with specific invasion pathways. Invasion
disharmony in Lepidoptera appears to be driven by processes unrelated to
the success of native assemblages. While native assemblages developed
through long-term evolutionary radiation, the composition of non-native
assemblages is driven by differential invasion pathways and traits
affecting the establishment of founder populations that vary among
families.
Lists of native and non-native established Lepidoptera species were
compiled from 11 different regions (North America (Canada, continental
USA), the Hawaiian Archipelago, the Galapagos Archipelago, Europe
(including its major islands and the European part of Russia), South
Africa, South Korea, Japan (excluding the following two regions), the
Nansei Islands, the Ogasawara Islands, Australia, New Zealand). The data
on non-native established Lepidoptera are part of a larger database,
"International Non-native Insect Establishment Data", that is
periodically updated and freely available (Turner et al. 2021a). Taxonomic
delimitation of Lepidoptera families and total species numbers per family
follows recently published works (van Nieukerken et al. 2011; Zahiri et
al. 2011, 2012, 2013; Kaila et al. 2013, 2020; Sohn et al. 2013; Heikkilä
et al. 2014; Regier et al. 2014, 2015; Kristensen et al. 2015). The
polyphyletic Batrachedridae (Heikkilä et al., 2014) were kept in the
circumscription of van Nieukerken et al. (2011). Chrysodeixis chalcites
and Ch. eriosoma (Noctuidae) were treated as one species, as current
species delimitation methods (morphology, DNA Barcode data) cannot
separate them into distinct species. Taxonomic “cleaning” using the GBIF
taxonomic database (GBIF Secretariat 2019) and the P package ‘taxize’,
version 2 (Chamberlain & Szöcs 2013) ensured standardization of
the datasets from the different regions and avoid duplication through
synonyms and misspellings. Code used for this taxonomic cleaning is
available in the Zenodo repository (Blake & Turner 2021). The
small number of names that was not recognized in the GBIF backbone
taxonomy was searched for manually via searches in alternative databases
(Beccaloni et al. 2003; Nuss et al. 2003–2022; De Prins & De Prins
2006–2022, 2011–2022; Gilligan et al. 2018) and manual online researching
of names. Data on Lepidoptera species intercepted at sea- and airports
were sourced from regions that largely overlapped with the regions
investigated for the establishments: North America (mainland USA, Canada),
Hawaii, the western countries of the European and Mediterranean Plant
Protection Organization (EPPO), UK, South Africa, Japan, South Korea,
Australia and New Zealand. These data were pooled to quantify species
richness for Lepidoptera families. The border interception data are
described in detail in Brockerhoff et al. (2014), Turner et al. (2021b)
and Saccaggi et al. (2021). Data on trade commodities associated with
Lepidoptera intercepted during inspections and identified at least to
genus level were derived from the interception data described above. The
commodity dataset represented a geographical and temporal subset, with
commodities not recorded for all interceptions, and with the commodity
data from New Zealand from an earlier period (1960–2000) (see Appendix S1
in Mally et al. 2022). Data were pooled from interceptions at sea- and
airports of six regions (USA incl. Hawaii; Canada; EPPO; Japan; Australia;
New Zealand), and span different timeframes from 1950 to the late 2010s.
Data from each region were pooled to quantify species richness for each
Lepidoptera family. The data span 14 classes of commodities, based on the
Harmonized Commodity Description and Coding System developed by the World
Customs Organization (https://www.trade.gov/harmonized-system-hs-codes):
Plant products, Animal products, Wood products, Foodstuffs, Transport,
Metal products, Machinery/Electrical, Mineral products, Stone/Glass,
Chemical products, Plastics/Rubber, Textiles, Footwear/Headgear, and
Miscellaneous. To limit the impact of stochastic effects, analyses were
restricted to families with more than 100 commodity records. Plant product
commodities of these families were itemised to 10 subclasses for a more
fine-scaled analysis of pathways: Cereals (HS-10), Coffee/tea/spices
(HS-09), Flours (HS-11), Fruit/nuts (HS-08), Gum/resin (HS-13), Live
plants/cut flowers (HS-06), Vegetable fibres (HS-53),
Seeds/grains/medicinal (HS-12), Vegetable products (HS-14), and Vegetables
(HS-07). Data collection and processing of commodities data is described
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