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  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">5</journal-id>
      <journal-id journal-id-type="index">urn:lsid:arphahub.com:pub:8D1BC1DD-8175-5933-B147-C839B202D5BA</journal-id>
      <journal-id journal-id-type="aggregator">urn:lsid:zoobank.org:pub:C132FA7C-A22D-4474-AAAF-B7A6889D0FF9</journal-id>
      <journal-title-group>
        <journal-title xml:lang="en">NeoBiota</journal-title>
        <abbrev-journal-title xml:lang="en">NB</abbrev-journal-title>
      </journal-title-group>
      <issn pub-type="ppub">1619-0033</issn>
      <issn pub-type="epub">1314-2488</issn>
      <publisher>
        <publisher-name>Pensoft Publishers</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.3897/neobiota.109.184222</article-id>
      <article-id pub-id-type="publisher-id">184222</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
        <subj-group subj-group-type="biological_taxon">
          <subject>Animalia</subject>
          <subject>Arthropoda</subject>
          <subject>Hexapoda</subject>
          <subject>Insecta</subject>
          <subject>Invertebrata</subject>
        </subj-group>
        <subj-group subj-group-type="scientific_subject">
          <subject>Biological Invasions</subject>
          <subject>Species Inventories</subject>
        </subj-group>
        <subj-group subj-group-type="geological_era">
          <subject>Cenozoic</subject>
          <subject>Neogene</subject>
        </subj-group>
        <subj-group subj-group-type="geographical_area">
          <subject>Asia</subject>
          <subject>China</subject>
          <subject>Taiwan</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>The endless invasions: Spatiotemporal patterns of non-native insects in China</article-title>
      </title-group>
      <contrib-group content-type="authors">
        <contrib contrib-type="author" corresp="no">
          <name name-style="western">
            <surname>Peng</surname>
            <given-names>Shuo</given-names>
          </name>
          <uri content-type="orcid">https://orcid.org/0000-0001-6445-961X</uri>
          <xref ref-type="aff" rid="A1">1</xref>
          <role content-type="http://credit.niso.org/contributor-roles/writing-original-draft/">Writing - original draft</role>
          <role content-type="http://credit.niso.org/contributor-roles/writing-review-editing/">Writing - review and editing</role>
          <role content-type="http://credit.niso.org/contributor-roles/data-curation/">Data curation</role>
          <role content-type="http://credit.niso.org/contributor-roles/formal-analysis/">Formal analysis</role>
          <role content-type="http://credit.niso.org/contributor-roles/investigation/">Investigation</role>
          <role content-type="http://credit.niso.org/contributor-roles/methodology/">Methodology</role>
          <role content-type="http://credit.niso.org/contributor-roles/visualization/">Visualization</role>
        </contrib>
        <contrib contrib-type="author" corresp="no">
          <name name-style="western">
            <surname>Zhang</surname>
            <given-names>Yibo</given-names>
          </name>
          <uri content-type="orcid">https://orcid.org/0000-0003-4530-9776</uri>
          <xref ref-type="aff" rid="A2">2</xref>
          <role content-type="http://credit.niso.org/contributor-roles/writing-review-editing/">Writing - review and editing</role>
        </contrib>
        <contrib contrib-type="author" corresp="no">
          <name name-style="western">
            <surname>Hui</surname>
            <given-names>Cang</given-names>
          </name>
          <uri content-type="orcid">https://orcid.org/0000-0002-3660-8160</uri>
          <xref ref-type="aff" rid="A3">3</xref>
          <xref ref-type="aff" rid="A4">4</xref>
          <role content-type="http://credit.niso.org/contributor-roles/writing-review-editing/">Writing - review and editing</role>
        </contrib>
        <contrib contrib-type="author" corresp="no">
          <name name-style="western">
            <surname>Haddi</surname>
            <given-names>Khalid</given-names>
          </name>
          <uri content-type="orcid">https://orcid.org/0000-0002-2655-4365</uri>
          <xref ref-type="aff" rid="A5">5</xref>
          <role content-type="http://credit.niso.org/contributor-roles/writing-review-editing/">Writing - review and editing</role>
        </contrib>
        <contrib contrib-type="author" corresp="no">
          <name name-style="western">
            <surname>Qin</surname>
            <given-names>Yujia</given-names>
          </name>
          <uri content-type="orcid">https://orcid.org/0000-0002-0903-9089</uri>
          <xref ref-type="aff" rid="A1">1</xref>
          <role content-type="http://credit.niso.org/contributor-roles/writing-review-editing/">Writing - review and editing</role>
        </contrib>
        <contrib contrib-type="author" corresp="no">
          <name name-style="western">
            <surname>Li</surname>
            <given-names>Zhihong</given-names>
          </name>
          <uri content-type="orcid">https://orcid.org/0000-0002-1281-2108</uri>
          <xref ref-type="aff" rid="A1">1</xref>
          <role content-type="http://credit.niso.org/contributor-roles/writing-review-editing/">Writing - review and editing</role>
        </contrib>
        <contrib contrib-type="author" corresp="yes">
          <name name-style="western">
            <surname>Zhao</surname>
            <given-names>Zihua</given-names>
          </name>
          <email xlink:type="simple">zhzhao@cau.edu.cn</email>
          <uri content-type="orcid">https://orcid.org/0000-0003-2353-2862</uri>
          <xref ref-type="aff" rid="A1">1</xref>
          <role content-type="http://credit.niso.org/contributor-roles/conceptualization/">Conceptualization</role>
          <role content-type="http://credit.niso.org/contributor-roles/writing-review-editing/">Writing - review and editing</role>
          <role content-type="http://credit.niso.org/contributor-roles/methodology/">Methodology</role>
        </contrib>
      </contrib-group>
      <aff id="A1">
        <label>1</label>
        <addr-line content-type="verbatim">State Key Laboratory of Agricultural and Forestry Biosecurity, MARA Key Laboratory of Surveillance and Management for Plant Quarantine Pests, College of Plant Protection, China Agricultural University, Beijing, China</addr-line>
        <institution>State Key Laboratory of Agricultural and Forestry Biosecurity, MARA Key Laboratory of Surveillance and Management for Plant Quarantine Pests, College of Plant Protection, China Agricultural University</institution>
        <addr-line content-type="city">Beijing</addr-line>
        <country>China</country>
        <uri content-type="ror">https://ror.org/04v3ywz14</uri>
      </aff>
      <aff id="A2">
        <label>2</label>
        <addr-line content-type="verbatim">State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing, China</addr-line>
        <institution>State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences</institution>
        <addr-line content-type="city">Beijing</addr-line>
        <country>China</country>
        <uri content-type="ror">https://ror.org/0313jb750</uri>
      </aff>
      <aff id="A3">
        <label>3</label>
        <addr-line content-type="verbatim">Department of Mathematical Sciences, Centre for Invasion Biology, Stellenbosch University, Matieland, South Africa</addr-line>
        <institution>Department of Mathematical Sciences, Centre for Invasion Biology, Stellenbosch University</institution>
        <addr-line content-type="city">Matieland</addr-line>
        <country>South Africa</country>
      </aff>
      <aff id="A4">
        <label>4</label>
        <addr-line content-type="verbatim">Mathematical and Physical Biosciences, African Institute for Mathematical Sciences, Muizenberg, South Africa</addr-line>
        <institution>Mathematical and Physical Biosciences, African Institute for Mathematical Sciences</institution>
        <addr-line content-type="city">Muizenberg</addr-line>
        <country>South Africa</country>
        <uri content-type="ror">https://ror.org/02c02vy89</uri>
      </aff>
      <aff id="A5">
        <label>5</label>
        <addr-line content-type="verbatim">Departamento de Entomologia, Universidade Federal de Lavras, Lavras, Brazil</addr-line>
        <institution>Departamento de Entomologia, Universidade Federal de Lavras</institution>
        <addr-line content-type="city">Lavras</addr-line>
        <country>Brazil</country>
        <uri content-type="ror">https://ror.org/0122bmm03</uri>
      </aff>
      <author-notes>
        <fn fn-type="corresp">
          <p>Corresponding author: Zihua Zhao (<email xlink:type="simple">zhzhao@cau.edu.cn</email>)</p>
        </fn>
        <fn fn-type="edited-by">
          <p>Academic editor: Alain Roques</p>
        </fn>
      </author-notes>
      <pub-date pub-type="collection">
        <year>2026</year>
      </pub-date>
      <pub-date pub-type="epub">
        <day>28</day>
        <month>09</month>
        <year>2026</year>
      </pub-date>
      <volume>109</volume>
      <fpage>203</fpage>
      <lpage>215</lpage>
      <uri content-type="arpha" xlink:href="http://openbiodiv.net/169D34B1-2233-5FA4-8279-096B3FBAF8C6">169D34B1-2233-5FA4-8279-096B3FBAF8C6</uri>
      <history>
        <date date-type="received">
          <day>04</day>
          <month>01</month>
          <year>2026</year>
        </date>
        <date date-type="accepted">
          <day>27</day>
          <month>08</month>
          <year>2026</year>
        </date>
      </history>
      <permissions>
        <copyright-statement>Shuo Peng, Yibo Zhang, Cang Hui, Khalid Haddi, Yujia Qin, Zhihong Li, Zihua Zhao</copyright-statement>
        <license license-type="creative-commons-attribution" xlink:href="http://creativecommons.org/licenses/by/4.0/" xlink:type="simple">
          <license-p>This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</license-p>
        </license>
      </permissions>
      <abstract>
        <label>Abstract</label>
        <p>Biological invasions have been defined as one striking indicator of the Anthropocene epoch, with more species being translocated beyond their native range by human activities. The inventory of non-native species in a region provides basic information for further exploration of biological invasions. We compiled a checklist of non-native insects in China and then analyzed their diversity at species level and invasion patterns. In total, 241 species of non-native insects were recorded in China, belonging to 8 orders and 181 genera. <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="order" reg="Coleoptera">Coleoptera</tp:taxon-name-part></tp:taxon-name>, <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="order" reg="Hemiptera">Hemiptera</tp:taxon-name-part></tp:taxon-name>, and <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="order" reg="Lepidoptera">Lepidoptera</tp:taxon-name-part></tp:taxon-name> were the top three largest orders. Asia and North America donated most species of non-native insects, with Oceania contributing the fewest. The spatial distribution of non-native insects showed a decrease from coastal areas to inland regions, and inland border regions of Yunnan and Xinjiang had more first records of non-native species. Additionally, the number of non-native insect species has increased exponentially since 1900. Non-native insects were most likely introduced into China by stowaway and by contaminant, with a preference for terrestrial ecosystem. The overview of non-native insects in China provides a comprehensive perspective on their invasion patterns, helping to elucidate the dynamics of non-native insects and contributing to a balanced understanding of their global patterns.</p>
      </abstract>
      <kwd-group>
        <label>Key words:</label>
        <kwd>Invasion pathways</kwd>
        <kwd>non-native insects</kwd>
        <kwd>spatial patterns</kwd>
        <kwd>temporal dynamics</kwd>
      </kwd-group>
      <funding-group>
        <funding-statement>This research is supported by the National Key R&amp;D Program (No. 2024YFC2607600), the earmarked fund for China Agriculture Research System (CARS-02-32), and the 2115 Talent Development Program of China Agricultural University.</funding-statement>
      </funding-group>
    </article-meta>
    <notes>
      <sec sec-type="Citation" id="sec1">
        <title>Citation</title>
        <p>Peng S, Zhang Y, Hui C, Haddi K, Qin Y, Li Z, Zhao Z (2026) The endless invasions: Spatiotemporal patterns of non-native insects in China. NeoBiota 109: 203–215. <ext-link xlink:type="simple" ext-link-type="doi" xlink:href="10.3897/neobiota.109.184222">https://doi.org/10.3897/neobiota.109.184222</ext-link></p>
      </sec>
    </notes>
  </front>
  <body>
    <sec sec-type="Introduction" id="sec2">
      <title>Introduction</title>
      <p>Human-driven abiotic and biotic changes have exceeded what can be shaped by nature, defining the Anthropocene epoch strikingly characterized by species translocation beyond their native regions by human activities (<xref ref-type="bibr" rid="B38">Waters et al. 2016</xref>). The translocated species naturalize in new regions, causing significant environmental issues, social problems and economic losses (<xref ref-type="bibr" rid="B18">Lambertini et al. 2011</xref>; <xref ref-type="bibr" rid="B3">Bellard et al. 2016</xref>). Global changes have been occurring at an unprecedented rate, and human-mediated exchanges of non-native species have been intensifying for many centuries (<xref ref-type="bibr" rid="B13">Hulme et al. 2009</xref>; <xref ref-type="bibr" rid="B4">Blackburn et al. 2015</xref>), leading to a continuous rise in the number of non-native species across taxonomic groups, with no evidence of saturation in their overall accumulation (<xref ref-type="bibr" rid="B31">Seebens et al. 2017</xref>). The rapid expansion of global trade, transportation infrastructure, and land-use intensification has accelerated the process of human-driven biological invasions (<xref ref-type="bibr" rid="B24">Pauchard and Alaback 2004</xref>; <xref ref-type="bibr" rid="B13">Hulme et al. 2009</xref>; <xref ref-type="bibr" rid="B30">Seebens et al. 2015</xref>), subsequently reshaping biogeographic realms (<xref ref-type="bibr" rid="B6">Capinha et al. 2015</xref>; <xref ref-type="bibr" rid="B19">Lewis and Maslin 2015</xref>), and has accelerated regional biotic homogenization (<xref ref-type="bibr" rid="B39">Winter et al. 2009</xref>). Biological invasions incurred an average annual cost of US$26.8 billion from 1970 to 2017, with management costs accounting for an important proportion of this total (<xref ref-type="bibr" rid="B11">Diagne et al. 2021</xref>). Moreover, their negative impacts on the ecological environment and human well-being are increasingly severe, imposing substantial burdens on local development, particularly in developing countries (<xref ref-type="bibr" rid="B22">Mack et al. 2000</xref>; <xref ref-type="bibr" rid="B28">Pyšek et al. 2020</xref>).</p>
      <p>A deeper understanding of the biogeography of non-native species is essential for describing invasion processes. Identifying non-native species, clarifying their key invasion traits, and compiling comprehensive regional inventories provide a reliable foundation for analyses of species diversity and biogeography (<xref ref-type="bibr" rid="B16">Khuroo et al. 2012</xref>; <xref ref-type="bibr" rid="B14">Inderjit et al. 2018</xref>; <xref ref-type="bibr" rid="B27">Pyšek et al. 2018</xref>). Assembling regional checklists of non-native species depends on rigorous field surveys and reliable basic data (<xref ref-type="bibr" rid="B2">Baard and Kraaij 2014</xref>; <xref ref-type="bibr" rid="B1">Ansong et al. 2019</xref>), which will strengthen the understanding of global invasion patterns, drivers, and consequences (<xref ref-type="bibr" rid="B26">Pyšek et al. 2008</xref>; <xref ref-type="bibr" rid="B35">van Kleunen et al. 2019</xref>; <xref ref-type="bibr" rid="B23">Omer et al. 2021</xref>).</p>
      <p>Exacerbated by global change, biological invasions pose a severe threat to China, where the number of non-native species has been heavily underestimated (<xref ref-type="bibr" rid="B36">Wan and Yang 2016</xref>; <xref ref-type="bibr" rid="B25">Peng et al. 2025</xref>). Over the past decades, increasing research efforts on biological invasions in China have provided a foundation for compiling a checklist of non-native species. A comprehensive accounting of non-native species, coupled with the identification of their ecological and invasion traits, is fundamental to effective management of biological invasions. The emergence of standardized terminology and integration workflows has also facilitated the development of national checklists of non-native species (<xref ref-type="bibr" rid="B33">Seebens et al. 2020</xref>). Therefore, by considering both population size and invasion consequences, here we first identified non-native insect species in China and assembled an integrated checklist. Then, we described the species diversity, spatial patterns and invasion trends. Our objective is to develop a comprehensive understanding of the dynamics of non-native insect species and to identify their spatial and temporal patterns of invasion in China. This regional assessment will strengthen the management of biological invasions in China and contribute to a more balanced and comprehensive understanding of global invasion patterns.</p>
    </sec>
    <sec sec-type="methods" id="sec3">
      <title>Methods</title>
      <sec sec-type="Study region" id="sec4">
        <title>Study region</title>
        <p>The study area covers the entire territory of China, including Taiwan. China is located in eastern Asia along the western Pacific Ocean, and spans approximately 9.6 million km<sup>2</sup>. It has extensive land borders exceeding 20,000 km and a coastline of 18,000 km (<xref ref-type="bibr" rid="B36">Wan and Yang 2016</xref>). China shares borders with multiple countries and encompasses a wide range of biogeographical regions. In addition, it covers multiple climate zones, including tropical, subtropical, warm temperate, temperate, and cold temperate regions. This climatic and environmental heterogeneity supports high biodiversity and diverse native flora and fauna. However, with increasing globalization and rapid economic development in China, the likelihood of non-native species introduction and establishment has increased, posing potential ecological threats.</p>
      </sec>
      <sec sec-type="Data compilation" id="sec5">
        <title>Data compilation</title>
        <p>Initially, a checklist of non-native insect species was compiled to integrate related information. A specific definition of non-native species was established to ensure the accuracy of the checklist. Non-native insect species recorded in the checklist were defined as species that had been translocated beyond their native range and introduced into China. Species whose native ranges were also documented to include China were considered to have disputed non-native status and were excluded from the checklist and all subsequent analyses. Specifically, most introduced natural enemies were excluded from the checklist, as they are utilized under regulatory control. Furthermore, species with only specimen records but lacking evidence on domestic distribution, origin, and introduction pathways were excluded. All the non-native insects recorded in the checklist were well documented and were assembled from various sources, including online databases, public books, scientific literature, and government reports. The catalogue of non-native insect species of China was primarily obtained from the public database <abbrev xlink:title="Global Invasive Species Database">GISD</abbrev> (Global Invasive Species Database, <ext-link xlink:href="http://www.iucngisd.org/gisd/" ext-link-type="uri">http://www.iucngisd.org/gisd/</ext-link>). Two comprehensive books focusing on the basic information of invasive non-native species in China (<xref ref-type="bibr" rid="B42">Xu and Qiang 2018</xref>; <xref ref-type="bibr" rid="B15">Jiang et al. 2019</xref>) provided us with partial checklists of non-native insects during the collection. Then, a subset of species records from the dataset provided by <xref ref-type="bibr" rid="B33">Seebens et al. (2020)</xref> were extracted, which represented an integrated global dataset of non-native species distributions. Recent checklist-related studies from China have also been included (<xref ref-type="bibr" rid="B41">Xian et al. 2018</xref>; <xref ref-type="bibr" rid="B29">Roques et al. 2020</xref>). In addition, combinations of keywords such as “non-native insect”, “alien”, “invasive”, and “China” were used to obtain the most recent records of non-native insect species in China from Google Scholar and CNKI. All the scientific names included in the checklist were standardized using <abbrev xlink:title="Global Biodiversity Information Facility">GBIF</abbrev> (Global Biodiversity Information Facility, <ext-link xlink:href="https://www.gbif.org/" ext-link-type="uri">https://www.gbif.org/</ext-link>). Synonyms were then verified and harmonized in R (version 4.4.2) with the package rgbif. Duplicate records were removed to obtain the final version of the checklist.</p>
      </sec>
      <sec sec-type="Taxonomy, regions of origin, and first records" id="sec6">
        <title>Taxonomy, regions of origin, and first records</title>
        <p>Taxonomic information was based on <abbrev xlink:title="Global Biodiversity Information Facility">GBIF</abbrev> and supplemented with literature. Regions of origin were compiled from multiple sources including the public database <abbrev xlink:title="Global Invasive Species Database">GISD</abbrev> and supplemented with data from CABI Compendium Invasive Species (<ext-link xlink:href="https://www.cabidigitallibrary.org/" ext-link-type="uri">https://www.cabidigitallibrary.org/</ext-link>). The previously mentioned books and publications also contributed substantial data on regions of origin (<xref ref-type="bibr" rid="B42">Xu and Qiang 2018</xref>; <xref ref-type="bibr" rid="B15">Jiang et al. 2019</xref>; <xref ref-type="bibr" rid="B29">Roques et al. 2020</xref>). All the records were standardized and then categorized at continental levels. Some distinctive regions were reassigned to specific continents, such as the Caribbean Islands (assigned to North America), to ensure consistency in geographical classification.</p>
        <p>For the first recorded domestic distributions, each non-native insect was assigned to one of China’s 34 provincial-level administrative regions. Abundant distribution records were obtained from <xref ref-type="bibr" rid="B42">Xu and Qiang (2018)</xref> and <xref ref-type="bibr" rid="B15">Jiang et al. (2019)</xref>, which also provided information on the first recorded year for many species. Additional information on the first recorded years was supplemented using data from <xref ref-type="bibr" rid="B43">Xu et al. (2012)</xref>, <xref ref-type="bibr" rid="B36">Wan and Yang (2016)</xref> and Seebens et al. (<xref ref-type="bibr" rid="B31">2017</xref>, <xref ref-type="bibr" rid="B32">2018</xref>). When conflicting records were encountered, the earliest year was retained for temporal analyses. Then, the data were merged and standardized into single-year values. Finally, data on the first domestic distribution were available for 175 species, while data on the year of first record were available for 196 species.</p>
      </sec>
      <sec sec-type="Pathways and habitats" id="sec7">
        <title>Pathways and habitats</title>
        <p>Pathways were obtained from <abbrev xlink:title="Global Invasive Species Database">GISD</abbrev>, CABI Compendium Invasive Species and published literature. All descriptions related to invasion pathways were classified into the categories provided by <abbrev xlink:title="Global Invasive Species Database">GISD</abbrev>, including “released”, “escape”, “transport-contaminant”, “transport-stowaway”, “corridors” and “unaided”. Data on the habitats were extracted from <abbrev xlink:title="Global Invasive Species Database">GISD</abbrev>, CABI Compendium Invasive Species, <abbrev xlink:title="Global Biodiversity Information Facility">GBIF</abbrev> and the database provided by <xref ref-type="bibr" rid="B33">Seebens et al. (2020)</xref>. As different sources used different descriptions of the habitats, the following four types “freshwater”, “marine”, “terrestrial” and “brackish” were integrated.</p>
      </sec>
      <sec sec-type="Data analysis and visualization" id="sec8">
        <title>Data analysis and visualization</title>
        <p>The analysis and visualizations were done in R (version 4.4.2) and OriginPro 2026b (Version 10.3.5.222, OriginLab Corporation, Northampton, MA, USA). The invasion trend was illustrated using nonlinear curve fitting (exponential growth function with rate constant parameter). The origin map was created using ArcGIS (version 10.8).</p>
      </sec>
    </sec>
    <sec sec-type="Results" id="sec9">
      <title>Results</title>
      <sec sec-type="Species composition" id="sec10">
        <title>Species composition</title>
        <p>A total of 241 non-native insect species were identified, belonging to 8 orders, 69 families, and 181 genera (see Suppl. material <xref ref-type="supplementary-material" rid="S1">1</xref>). The largest three groups, <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="order" reg="Coleoptera">Coleoptera</tp:taxon-name-part></tp:taxon-name> (76 species, 31.5%), <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="order" reg="Hemiptera">Hemiptera</tp:taxon-name-part></tp:taxon-name> (67 species, 27.8%), and <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="order" reg="Lepidoptera">Lepidoptera</tp:taxon-name-part></tp:taxon-name> (30 species, 12.4%), accounted for 71.8% of all non-native insects. <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="order" reg="Coleoptera">Coleoptera</tp:taxon-name-part></tp:taxon-name> was the most diverse order, represented by 17 families, 58 genera and 76 species, and <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="order" reg="Orthoptera">Orthoptera</tp:taxon-name-part></tp:taxon-name> was the least diverse group (Table <xref ref-type="table" rid="T1">1</xref>). The composition of different orders varied greatly at different taxonomic levels, and the number of families ranged from 1 to 17, with the number of species ranging from 1 to 76. At the genus level, <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="subgenus" reg="Bactrocera">Bactrocera</tp:taxon-name-part></tp:taxon-name></italic> (6 species) and <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Phenacoccus">Phenacoccus</tp:taxon-name-part></tp:taxon-name></italic> (5 species) were the genera with the most species.</p>
        <table-wrap id="T1" position="float" orientation="portrait">
          <label>Table 1.</label>
          <caption>
            <p>The species composition of non-native insects in China.</p>
          </caption>
          <table>
            <tbody>
              <tr>
                <th rowspan="1" colspan="1">
                  <bold>Composition</bold>
                </th>
                <th rowspan="1" colspan="1">
                  <bold>
                    <tp:taxon-name>
                      <tp:taxon-name-part taxon-name-part-type="order" reg="Coleoptera">Coleoptera</tp:taxon-name-part>
                    </tp:taxon-name>
                  </bold>
                </th>
                <th rowspan="1" colspan="1">
                  <bold>
                    <tp:taxon-name>
                      <tp:taxon-name-part taxon-name-part-type="order" reg="Hemiptera">Hemiptera</tp:taxon-name-part>
                    </tp:taxon-name>
                  </bold>
                </th>
                <th rowspan="1" colspan="1">
                  <bold>
                    <tp:taxon-name>
                      <tp:taxon-name-part taxon-name-part-type="order" reg="Lepidoptera">Lepidoptera</tp:taxon-name-part>
                    </tp:taxon-name>
                  </bold>
                </th>
                <th rowspan="1" colspan="1">
                  <bold>
                    <tp:taxon-name>
                      <tp:taxon-name-part taxon-name-part-type="order" reg="Hymenoptera">Hymenoptera</tp:taxon-name-part>
                    </tp:taxon-name>
                  </bold>
                </th>
                <th rowspan="1" colspan="1">
                  <bold>
                    <tp:taxon-name>
                      <tp:taxon-name-part taxon-name-part-type="order" reg="Diptera">Diptera</tp:taxon-name-part>
                    </tp:taxon-name>
                  </bold>
                </th>
                <th rowspan="1" colspan="1">
                  <bold>
                    <tp:taxon-name>
                      <tp:taxon-name-part taxon-name-part-type="order" reg="Blattodea">Blattodea</tp:taxon-name-part>
                    </tp:taxon-name>
                  </bold>
                </th>
                <th rowspan="1" colspan="1">
                  <bold>
                    <tp:taxon-name>
                      <tp:taxon-name-part taxon-name-part-type="order" reg="Thysanoptera">Thysanoptera</tp:taxon-name-part>
                    </tp:taxon-name>
                  </bold>
                </th>
                <th rowspan="1" colspan="1">
                  <bold>
                    <tp:taxon-name>
                      <tp:taxon-name-part taxon-name-part-type="order" reg="Orthoptera">Orthoptera</tp:taxon-name-part>
                    </tp:taxon-name>
                  </bold>
                </th>
                <th rowspan="1" colspan="1">
                  <bold>Total</bold>
                </th>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">
                  <bold>Family</bold>
                </td>
                <td rowspan="1" colspan="1">17</td>
                <td rowspan="1" colspan="1">17</td>
                <td rowspan="1" colspan="1">16</td>
                <td rowspan="1" colspan="1">7</td>
                <td rowspan="1" colspan="1">5</td>
                <td rowspan="1" colspan="1">4</td>
                <td rowspan="1" colspan="1">2</td>
                <td rowspan="1" colspan="1">1</td>
                <td rowspan="1" colspan="1">69</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">
                  <bold>Genus</bold>
                </td>
                <td rowspan="1" colspan="1">58</td>
                <td rowspan="1" colspan="1">50</td>
                <td rowspan="1" colspan="1">28</td>
                <td rowspan="1" colspan="1">18</td>
                <td rowspan="1" colspan="1">13</td>
                <td rowspan="1" colspan="1">6</td>
                <td rowspan="1" colspan="1">7</td>
                <td rowspan="1" colspan="1">1</td>
                <td rowspan="1" colspan="1">181</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">
                  <bold>Species</bold>
                </td>
                <td rowspan="1" colspan="1">76</td>
                <td rowspan="1" colspan="1">67</td>
                <td rowspan="1" colspan="1">30</td>
                <td rowspan="1" colspan="1">24</td>
                <td rowspan="1" colspan="1">23</td>
                <td rowspan="1" colspan="1">10</td>
                <td rowspan="1" colspan="1">10</td>
                <td rowspan="1" colspan="1">1</td>
                <td rowspan="1" colspan="1">241</td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
      </sec>
      <sec sec-type="Continent of origin" id="sec11">
        <title>Continent of origin</title>
        <p>The origins of non-native insects were distributed across continents except Antarctica. Overall, Asia was the dominant source continent for non-native insect species in China, contributing the largest number of species (87 species), followed by North America (59 species). Europe, Africa, and South America were also important source regions, contributing 30, 31, and 35 non-native insect species, respectively. Regions located in Oceania contributed fewer non-native insect species (Fig. <xref ref-type="fig" rid="F1">1</xref>).</p>
        <fig id="F1">
          <object-id content-type="arpha">103ECDFA-FF48-55A8-8124-0C7941C9061C</object-id>
          <label>Figure 1.</label>
          <caption>
            <p>The continent of origin of non-native insects in China.</p>
          </caption>
          <graphic xlink:href="neobiota-109-203_article-184222__-g001.jpg" id="oo_1792392.jpg">
            <uri content-type="original_file">https://binary.pensoft.net/fig/1792392</uri>
          </graphic>
        </fig>
      </sec>
      <sec sec-type="Spatial patterns and invasion pathways" id="sec12">
        <title>Spatial patterns and invasion pathways</title>
        <p>The spatial pattern was mapped using 208 records of the first recorded domestic distribution for 175 non-native insects. Some species such as <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Blattella">Blattella</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="germanica">germanica</tp:taxon-name-part></tp:taxon-name></italic> and <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Bruchus">Bruchus</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="rufimanus">rufimanus</tp:taxon-name-part></tp:taxon-name></italic> were first recorded in more than one province. First detections of non-native insects were recorded in 25 regions, covering most regions of China. Provinces in the southeast coastal areas had more records than provinces in the northwest inland areas. The number of first records decreased closer to inland areas. Yunnan (19) and Xinjiang (13) had a larger number of first recorded domestic distributions though located in inland areas. Among our 208 records, the non-native insects were mostly first recorded in Taiwan (39 records, 18.8%), Guangdong (35 records, 16.8%) and Hainan (23 records, 11.1%) (Fig. <xref ref-type="fig" rid="F2">2</xref>). For the invasion pathways, transport-contaminant and transport-stowaway were the most common. For habitat type, the majority of non-native insects were inhabitants of terrestrial ecosystems (see Suppl. material <xref ref-type="supplementary-material" rid="S1">1</xref>).</p>
        <fig id="F2">
          <object-id content-type="arpha">035A4178-2447-5C3A-BF56-4E9E4D62AD6B</object-id>
          <label>Figure 2.</label>
          <caption>
            <p>The spatial distribution of first records of non-native insects in China.</p>
          </caption>
          <graphic xlink:href="neobiota-109-203_article-184222__-g002.jpg" id="oo_1792393.jpg">
            <uri content-type="original_file">https://binary.pensoft.net/fig/1792393</uri>
          </graphic>
        </fig>
      </sec>
      <sec sec-type="Temporal trend" id="sec13">
        <title>Temporal trend</title>
        <p>In total, 196 non-native insect species in China could be traced to their first recorded year. The earliest recorded non-native insect, <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="genus" reg="Daktulosphaira">Daktulosphaira</tp:taxon-name-part> <tp:taxon-name-part taxon-name-part-type="species" reg="vitifoliae">vitifoliae</tp:taxon-name-part></tp:taxon-name></italic> (Fitch, 1855) (<tp:taxon-name><tp:taxon-name-part taxon-name-part-type="order" reg="Hemiptera">Hemiptera</tp:taxon-name-part></tp:taxon-name>, <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="family" reg="Phylloxeridae">Phylloxeridae</tp:taxon-name-part></tp:taxon-name>), was recorded in 1892. The number of newly recorded non-native insects increased substantially, with a particularly marked rise in recent years. Both the number of families and species experienced a similar exponential increase. The number of first records remained low in the 1900s, but has increased rapidly since 1980. Remarkably, 144 non-native insects have been recorded since 1978, including 79 recorded since 2001 (Fig. <xref ref-type="fig" rid="F3">3a</xref>).</p>
        <fig id="F3">
          <object-id content-type="arpha">11500D61-9A5A-58C8-B21A-99CCE83764AB</object-id>
          <label>Figure 3.</label>
          <caption>
            <p>The invasion trend of non-native insects in China. <bold>a</bold>. The temporal trend of non-native insects in China; <bold>b</bold>. The proportion of species among the seven most frequently recorded families.</p>
          </caption>
          <graphic xlink:href="neobiota-109-203_article-184222__-g003.jpg" id="oo_1792394.jpg">
            <uri content-type="original_file">https://binary.pensoft.net/fig/1792394</uri>
          </graphic>
        </fig>
        <p>Among the top seven recorded families, <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="family" reg="Pseudococcidae">Pseudococcidae</tp:taxon-name-part></tp:taxon-name> and <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="family" reg="Chrysomelidae">Chrysomelidae</tp:taxon-name-part></tp:taxon-name> contained the largest number of recorded non-native insect species, accounting for 40.5% of the species in these seven families. They were followed by <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="family" reg="Curculionidae">Curculionidae</tp:taxon-name-part></tp:taxon-name> (19.0%), <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="family" reg="Aleyrodidae">Aleyrodidae</tp:taxon-name-part></tp:taxon-name> (10.7%) and <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="family" reg="Thripidae">Thripidae</tp:taxon-name-part></tp:taxon-name> (10.7%), forming the top five families with the largest number of non-native insects. Then, <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="family" reg="Dryophthoridae">Dryophthoridae</tp:taxon-name-part></tp:taxon-name> (9.5%) and <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="family" reg="Formicidae">Formicidae</tp:taxon-name-part></tp:taxon-name> (9.5%) were also well-represented taxonomic groups. Meanwhile, many families, such as <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="family" reg="Apidae">Apidae</tp:taxon-name-part></tp:taxon-name> or <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="family" reg="Asterolecaniidae">Asterolecaniidae</tp:taxon-name-part></tp:taxon-name>, were represented by only a single species (Fig. <xref ref-type="fig" rid="F3">3b</xref>).</p>
      </sec>
    </sec>
    <sec sec-type="Discussion" id="sec14">
      <title>Discussion</title>
      <p>The number of recorded non-native insects in China is much lower than that in Europe and North America, which may partly be explained by the fact that Europe and North America are recognized as hotspots for non-native insects (<xref ref-type="bibr" rid="B34">van Kleunen et al. 2015</xref>; <xref ref-type="bibr" rid="B31">Seebens et al. 2017</xref>). Developed trade and intensive human activities have further facilitated the spread of species in Europe and North America (<xref ref-type="bibr" rid="B10">Dawson et al. 2017</xref>). In addition, Europe has well-established systems for species documentation, whereas relatively less effort has been devoted to recording non-native species in China, which may contribute to the underestimation of the actual diversity of non-native insects in China (<xref ref-type="bibr" rid="B9">DAISIE 2009</xref>). In recent years, strengthened quarantine measures in China have also served as an important line of defense. Predators and parasitoids are less frequently represented in current checklists, possibly reflecting the relatively limited documentation of these groups in the available literature. The bias highlights the need for greater attention to non-native insects beyond major agricultural pests in order to achieve a more comprehensive understanding of biological invasions. <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="order" reg="Coleoptera">Coleoptera</tp:taxon-name-part></tp:taxon-name> is a dominant insect group worldwide, which contributes to its leading role in non-native insect groups (<xref ref-type="bibr" rid="B5">Bouchard et al. 2017</xref>). The ecological traits of wood-boring and stored-product <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="order" reg="Coleoptera">Coleoptera</tp:taxon-name-part></tp:taxon-name> also promote their invasions, as traded commodities provide suitable shelters that protect them during transport (<xref ref-type="bibr" rid="B5">Bouchard et al. 2017</xref>). A greater variety of invasion pathways and habitats, higher reproductive capacity and voltinism, and more complex genomic features jointly contribute to the higher invasion success of non-native insects (<xref ref-type="bibr" rid="B45">Zhao et al. 2023</xref>). Several important genera, such as <italic><tp:taxon-name><tp:taxon-name-part taxon-name-part-type="subgenus" reg="Bactrocera">Bactrocera</tp:taxon-name-part></tp:taxon-name></italic>, have already been introduced to and successfully invaded different regions of China due to their ecological advantages and have caused significant economic losses (<xref ref-type="bibr" rid="B37">Wang et al. 2023</xref>; <xref ref-type="bibr" rid="B46">Zhao et al. 2024</xref>). Some non-native insects can be introduced with plants, and they are more difficult to detect, increasing their likelihood of successful invasion (<xref ref-type="bibr" rid="B34">van Kleunen et al. 2015</xref>; <xref ref-type="bibr" rid="B21">Liebhold et al. 2018</xref>). Groups with a larger number of non-native species, such as <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="order" reg="Coleoptera">Coleoptera</tp:taxon-name-part></tp:taxon-name>, already hold a dominant status and pose substantial invasion risks. In contrast, groups with fewer recorded species, such as <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="order" reg="Thysanoptera">Thysanoptera</tp:taxon-name-part></tp:taxon-name> and <tp:taxon-name><tp:taxon-name-part taxon-name-part-type="order" reg="Orthoptera">Orthoptera</tp:taxon-name-part></tp:taxon-name>, have received less attention but still carry considerable potential for future invasions.</p>
      <p>The dominant contribution of Asia suggests that geographic barriers play an important role in shaping the transport of non-native insects, and that reduced barriers and shorter geographic distance can facilitate invasions (<xref ref-type="bibr" rid="B44">Zhang et al. 2024</xref>). The significant contributions of North America highlight the influence of frequent and developed intercontinental communication and human activities (<xref ref-type="bibr" rid="B7">Chapman et al. 2017</xref>). North America is a hotspot of non-native insects, which also contributes to this pattern (<xref ref-type="bibr" rid="B31">Seebens et al. 2017</xref>). It also highlights the importance of climate matching, as these regions share several major climate types with Asia (<xref ref-type="bibr" rid="B23">Omer et al. 2021</xref>). Its unique island faunas make Oceania an uncommon source region, and species originating there may face limitations in naturalizing elsewhere.</p>
      <p>The spatial pattern of first domestic records is highly consistent with the current distribution pattern, with southeastern regions exhibiting significantly higher densities of non-native species than northwestern regions (<xref ref-type="bibr" rid="B40">Wu et al. 2006</xref>; <xref ref-type="bibr" rid="B8">Chen et al. 2021</xref>). Human activities such as economic development and trade largely shape this pattern, a phenomenon also observed in studies of non-native plants in Japan, where invasion hotspots coincide with highly developed urban areas (<xref ref-type="bibr" rid="B17">Kusumoto et al. 2021</xref>). Many studies have demonstrated the strong relationship between human activities and biological invasions (<xref ref-type="bibr" rid="B12">Hulme 2009</xref>; <xref ref-type="bibr" rid="B20">Liebhold et al. 2016</xref>). More frequent and intense activities, as well as increased trade activities in these regions, such as Guangdong and Hainan, can facilitate the invasion process. Taiwan’s unique biogeographic composition makes it particularly susceptible to newly arriving non-native species. At the same time, the strong public and scientific interest in biodiversity research and conservation in Taiwan cannot be overlooked. Yunnan and Xinjiang had more records of first domestic detections, which may be explained by the higher intensity of cross-regional activities resulting from their shared borders with multiple countries. Border regions also tend to face higher risks of biological invasions (<xref ref-type="bibr" rid="B44">Zhang et al. 2024</xref>). Most non-native insects are translocated through contaminant or stowaway pathways, highlighting the key role of cross-border transport activities in the invasion process. These pathways often represent the final route through which insect invasions occur (<xref ref-type="bibr" rid="B25">Peng et al. 2025</xref>).</p>
      <p>The continuously increasing temporal trend is consistent with our expectations and is strongly associated with intensifying human activities. This unsaturated state implies the likelihood of further invasions (<xref ref-type="bibr" rid="B31">Seebens et al. 2017</xref>). The low number of first records in the 1990s may be a consequence of limited awareness of invasive species and limited records, as well as the economic and social constraints of that period. Increased attention to non-native species has also resulted in more records, contributing to the rising trend. Rapid socioeconomic development has clearly facilitated the invasion process, as evidenced by the marked increases in first-record rates after 1978 and 2001. Following China’s landmark Reform and Opening policy (in 1978) and its subsequent accession to the World Trade Organization (in 2001), the resulting surge in economic growth greatly expanded opportunities for non-native insects to be transported into China and subsequently establish themselves as invaders (<xref ref-type="bibr" rid="B36">Wan and Yang 2016</xref>). However, existing regulations and control measures have not been sufficiently effective, as biological invasions continue to intensify despite past efforts (<xref ref-type="bibr" rid="B31">Seebens et al. 2017</xref>). More non-native insect species remain undetected and unrecorded, indicating that their overall number is underestimated.</p>
      <p>The systematic compilation of non-native species inventories and the thorough characterization of their invasion patterns lay the foundation for evidence-based management and control of invasive non-native species. Here, we provide a preliminary checklist of non-native insects in China and explore the spatial and temporal patterns. Our research provides scientific evidence to support governmental management of non-native species and offers valuable data from China to inform global analyses of invasion patterns in non-native insects. In the future, multidisciplinary approaches will facilitate a more complete understanding of the diversity and status of non-native species, enable the development of more comprehensive invasion maps, and help identify the most influential drivers. These advances will support collaborative efforts among countries to address the environmental challenges posed by biological invasions.</p>
    </sec>
  </body>
  <back>
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    <sec sec-type="Additional information" id="sec15">
      <title>Additional information</title>
      <sec sec-type="Conflict of interest" id="sec16">
        <title>Conflict of interest</title>
        <p>The authors have declared that no competing interests exist.</p>
      </sec>
      <sec sec-type="Ethical statement" id="sec17">
        <title>Ethical statement</title>
        <p>No ethical statement was reported.</p>
      </sec>
      <sec sec-type="Artificial Intelligence (AI) use" id="sec18">
        <title>Artificial Intelligence (AI) use</title>
        <p>The authors accept full responsibility for the content of the manuscript, including the disclosure of any use of AI.</p>
        <p>No AI tools were used in the preparation of this manuscript.</p>
      </sec>
      <sec sec-type="Funding" id="sec19">
        <title>Funding</title>
        <p>This research is supported by the National Natural Science Foundation of China (Grant No. U24A20412), the earmarked fund for China Agriculture Research System (CARS-02-32), and the 2115 Talent Development Program of China Agricultural University.</p>
      </sec>
      <sec sec-type="Author contributions" id="sec20">
        <title>Author contributions</title>
        <p>Shuo Peng: Data curation; Formal analysis; Investigation; Methodology; Visualization; Writing – original draft, Writing-review &amp; editing. Yibo Zhang: Writing-review &amp; editing. Cang Hui: Writing-review &amp; editing. Khalid Haddi: Writing-review &amp; editing. Yujia Qin: Writing-review &amp; editing. Zhihong Li: Writing-review &amp; editing. Zihua Zhao: Conceptualization, Methodology, Writing-review &amp; editing.</p>
      </sec>
      <sec sec-type="Author ORCIDs" id="sec21">
        <title>Author ORCIDs</title>
        <p>S. Peng <ext-link xlink:href="https://orcid.org/0000-0001-6445-961X" ext-link-type="uri">https://orcid.org/0000-0001-6445-961X</ext-link></p>
        <p>Y. Zhang <ext-link xlink:href="https://orcid.org/0000-0003-4530-9776" ext-link-type="uri">https://orcid.org/0000-0003-4530-9776</ext-link></p>
        <p>C. Hui <ext-link xlink:href="https://orcid.org/0000-0002-3660-8160" ext-link-type="uri">https://orcid.org/0000-0002-3660-8160</ext-link></p>
        <p>K. Haddi <ext-link xlink:href="https://orcid.org/0000-0002-2655-4365" ext-link-type="uri">https://orcid.org/0000-0002-2655-4365</ext-link></p>
        <p>Y. Qin <ext-link xlink:href="https://orcid.org/0000-0002-0903-9089" ext-link-type="uri">https://orcid.org/0000-0002-0903-9089</ext-link></p>
        <p>Z. Li <ext-link xlink:href="https://orcid.org/0000-0002-1281-2108" ext-link-type="uri">https://orcid.org/0000-0002-1281-2108</ext-link></p>
        <p>Z. Zhao <ext-link xlink:href="https://orcid.org/0000-0003-2353-2862" ext-link-type="uri">https://orcid.org/0000-0003-2353-2862</ext-link></p>
      </sec>
      <sec sec-type="Data availability" id="sec22">
        <title>Data availability</title>
        <p>All of the data that support the findings of this study are available in the main text or Supplementary Information.</p>
      </sec>
    </sec>
    <sec sec-type="supplementary-material">
      <title>Supplementary materials</title>
      <supplementary-material id="S1" position="float" orientation="portrait" xlink:type="simple">
        <object-id content-type="arpha">5EC975EA-FDA5-5A80-A219-F8B958FE049B</object-id>
        <label>Supplementary material 1</label>
        <caption>
          <p>An inventory of non-native insect species and spatiotemporal records in China</p>
        </caption>
        <statement content-type="dataType">
          <label>Data type</label>
          <p>xlsx</p>
        </statement>
        <media xlink:href="neobiota-109-203_article-184222__-s001.xlsx" mimetype="application" mime-subtype="vnd.openxmlformats-officedocument.spreadsheetml.sheet" position="float" orientation="portrait" id="oo_1792395.xlsx">
          <uri content-type="original_file">https://binary.pensoft.net/file/1792395</uri>
        </media>
        <permissions>
          <license>
            <license-p>This dataset is made available under the Open Database License (<ext-link ext-link-type="uri" xlink:href="http://opendatacommons.org/licenses/odbl/1.0/">http://opendatacommons.org/licenses/odbl/1.0/</ext-link>). The Open Database License (ODbL) is a license agreement intended to allow users to freely share, modify, and use this Dataset while maintaining this same freedom for others, provided that the original source and author(s) are credited.</license-p>
          </license>
        </permissions>
        <attrib specific-use="authors"> Shuo Peng, Yibo Zhang, Cang Hui, Khalid Haddi, Yujia Qin, Zhihong Li, Zihua Zhao</attrib>
      </supplementary-material>
    </sec>
  </back>
</article>
