Bethany A. Bradley, Annette E. Evans, Helen R. Sofaer, Montserrat Vilà, David T. Barnett, Evelyn M. Beaury, Dana M. Blumenthal, Jeffrey D. Corbin, Jeffrey S. Dukes, Regan Early, Inés Ibáñez, Ian S. Pearse, Laís Petri, Cascade J. B. Sorte
{"title":"美国非本地植物区系地理的数量分类","authors":"Bethany A. Bradley, Annette E. Evans, Helen R. Sofaer, Montserrat Vilà, David T. Barnett, Evelyn M. Beaury, Dana M. Blumenthal, Jeffrey D. Corbin, Jeffrey S. Dukes, Regan Early, Inés Ibáñez, Ian S. Pearse, Laís Petri, Cascade J. B. Sorte","doi":"10.1111/geb.70041","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Aim</h3>\n \n <p>Non-native plants have the potential to harm ecosystems. Harm is classically related to their distribution and abundance, but this geographical information is often unknown. Here, we assess geographical commonness as a potential indicator of invasive status for non-native flora in the United States. Geographical commonness could inform invasion risk assessments across species and ecoregions.</p>\n </section>\n \n <section>\n \n <h3> Location</h3>\n \n <p>Conterminous United States.</p>\n </section>\n \n <section>\n \n <h3> Time Period</h3>\n \n <p>Through 2022.</p>\n </section>\n \n <section>\n \n <h3> Major Taxa Studied</h3>\n \n <p>Plants.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>We compiled and standardised occurrence and abundance data from 14 spatial datasets and used this information to categorise non-native species as uncommon or common based on three dimensions of commonness: area of occupancy, habitat breadth and local abundance. To assess consistency in existing categorizations, we compared commonness to invasive status in the United States. We identified species with higher-than-expected abundance relative to their occupancy, habitat breadth or residence time. We calculated non-native plant richness within United States ecoregions and estimated unreported species based on rarefaction/extrapolation curves.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>This comprehensive database identified 1874 non-native plant species recorded in 4,844,963 locations. Of these, 1221 species were locally abundant (> 10% cover) in 797,759 unique locations. One thousand one hundred one non-native species (59%) achieved at least one dimension of commonness, including 565 species that achieved all three. Species with longer residence times tended to meet more dimensions of commonness. We identified 132 species with higher-than-expected abundance. Ecoregions in the central United States have the largest estimated numbers of unreported, abundant non-native plants.</p>\n </section>\n \n <section>\n \n <h3> Main Conclusions</h3>\n \n <p>A high proportion of non-native species have become common in the United States. However, existing categorizations of invasive species are not always consistent with species' abundance and distribution, even after considering residence time. Considering geographical commonness and higher-than-expected abundance revealed in this new dataset could support more consistent and proactive identification of invasive plants and lead to more efficient management practices.</p>\n </section>\n </div>","PeriodicalId":176,"journal":{"name":"Global Ecology and Biogeography","volume":"34 4","pages":""},"PeriodicalIF":6.3000,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Quantitative Classification of the Geography of Non-Native Flora in the United States\",\"authors\":\"Bethany A. Bradley, Annette E. Evans, Helen R. Sofaer, Montserrat Vilà, David T. Barnett, Evelyn M. Beaury, Dana M. Blumenthal, Jeffrey D. Corbin, Jeffrey S. Dukes, Regan Early, Inés Ibáñez, Ian S. Pearse, Laís Petri, Cascade J. B. Sorte\",\"doi\":\"10.1111/geb.70041\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Aim</h3>\\n \\n <p>Non-native plants have the potential to harm ecosystems. Harm is classically related to their distribution and abundance, but this geographical information is often unknown. Here, we assess geographical commonness as a potential indicator of invasive status for non-native flora in the United States. Geographical commonness could inform invasion risk assessments across species and ecoregions.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Location</h3>\\n \\n <p>Conterminous United States.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Time Period</h3>\\n \\n <p>Through 2022.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Major Taxa Studied</h3>\\n \\n <p>Plants.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <p>We compiled and standardised occurrence and abundance data from 14 spatial datasets and used this information to categorise non-native species as uncommon or common based on three dimensions of commonness: area of occupancy, habitat breadth and local abundance. To assess consistency in existing categorizations, we compared commonness to invasive status in the United States. We identified species with higher-than-expected abundance relative to their occupancy, habitat breadth or residence time. We calculated non-native plant richness within United States ecoregions and estimated unreported species based on rarefaction/extrapolation curves.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <p>This comprehensive database identified 1874 non-native plant species recorded in 4,844,963 locations. Of these, 1221 species were locally abundant (> 10% cover) in 797,759 unique locations. One thousand one hundred one non-native species (59%) achieved at least one dimension of commonness, including 565 species that achieved all three. Species with longer residence times tended to meet more dimensions of commonness. We identified 132 species with higher-than-expected abundance. Ecoregions in the central United States have the largest estimated numbers of unreported, abundant non-native plants.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Main Conclusions</h3>\\n \\n <p>A high proportion of non-native species have become common in the United States. However, existing categorizations of invasive species are not always consistent with species' abundance and distribution, even after considering residence time. Considering geographical commonness and higher-than-expected abundance revealed in this new dataset could support more consistent and proactive identification of invasive plants and lead to more efficient management practices.</p>\\n </section>\\n </div>\",\"PeriodicalId\":176,\"journal\":{\"name\":\"Global Ecology and Biogeography\",\"volume\":\"34 4\",\"pages\":\"\"},\"PeriodicalIF\":6.3000,\"publicationDate\":\"2025-04-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Global Ecology and Biogeography\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/geb.70041\",\"RegionNum\":1,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ECOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Global Ecology and Biogeography","FirstCategoryId":"93","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/geb.70041","RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECOLOGY","Score":null,"Total":0}
A Quantitative Classification of the Geography of Non-Native Flora in the United States
Aim
Non-native plants have the potential to harm ecosystems. Harm is classically related to their distribution and abundance, but this geographical information is often unknown. Here, we assess geographical commonness as a potential indicator of invasive status for non-native flora in the United States. Geographical commonness could inform invasion risk assessments across species and ecoregions.
Location
Conterminous United States.
Time Period
Through 2022.
Major Taxa Studied
Plants.
Methods
We compiled and standardised occurrence and abundance data from 14 spatial datasets and used this information to categorise non-native species as uncommon or common based on three dimensions of commonness: area of occupancy, habitat breadth and local abundance. To assess consistency in existing categorizations, we compared commonness to invasive status in the United States. We identified species with higher-than-expected abundance relative to their occupancy, habitat breadth or residence time. We calculated non-native plant richness within United States ecoregions and estimated unreported species based on rarefaction/extrapolation curves.
Results
This comprehensive database identified 1874 non-native plant species recorded in 4,844,963 locations. Of these, 1221 species were locally abundant (> 10% cover) in 797,759 unique locations. One thousand one hundred one non-native species (59%) achieved at least one dimension of commonness, including 565 species that achieved all three. Species with longer residence times tended to meet more dimensions of commonness. We identified 132 species with higher-than-expected abundance. Ecoregions in the central United States have the largest estimated numbers of unreported, abundant non-native plants.
Main Conclusions
A high proportion of non-native species have become common in the United States. However, existing categorizations of invasive species are not always consistent with species' abundance and distribution, even after considering residence time. Considering geographical commonness and higher-than-expected abundance revealed in this new dataset could support more consistent and proactive identification of invasive plants and lead to more efficient management practices.
期刊介绍:
Global Ecology and Biogeography (GEB) welcomes papers that investigate broad-scale (in space, time and/or taxonomy), general patterns in the organization of ecological systems and assemblages, and the processes that underlie them. In particular, GEB welcomes studies that use macroecological methods, comparative analyses, meta-analyses, reviews, spatial analyses and modelling to arrive at general, conceptual conclusions. Studies in GEB need not be global in spatial extent, but the conclusions and implications of the study must be relevant to ecologists and biogeographers globally, rather than being limited to local areas, or specific taxa. Similarly, GEB is not limited to spatial studies; we are equally interested in the general patterns of nature through time, among taxa (e.g., body sizes, dispersal abilities), through the course of evolution, etc. Further, GEB welcomes papers that investigate general impacts of human activities on ecological systems in accordance with the above criteria.