Amy K. Wray , Aimee C. Agnew , Mary E. Brown , E.M. Dean , Nicole D. Hernandez , Audrey Jordon , Cayla R. Morningstar , Sara E. Piccolomini , Harrison A. Pickett , Wesley M. Daniel , Brian E. Reichert
{"title":"Understanding gaps in early detection of and rapid response to invasive species in the United States: A literature review and bibliometric analysis","authors":"Amy K. Wray , Aimee C. Agnew , Mary E. Brown , E.M. Dean , Nicole D. Hernandez , Audrey Jordon , Cayla R. Morningstar , Sara E. Piccolomini , Harrison A. Pickett , Wesley M. Daniel , Brian E. Reichert","doi":"10.1016/j.ecoinf.2024.102855","DOIUrl":null,"url":null,"abstract":"<div><div>While concepts regarding invasive species establishment patterns and eradication possibilities have long been a topic of invasion biology, the specific terminology referring to early detection of and rapid response to (EDRR) invasive species emerged in scientific literature during the early 2000s. Since then, the EDRR approach has expanded to include a suite of detection, planning, and management tools. By conducting a systematic literature review, we attempt to characterize the field of EDRR in the United States and its territories as reflected by publication records. Specifically, we assessed publication data such as the number of publications per year, the most common journals where papers were published, and the relationship between author's keywords for studies focusing on aquatic and terrestrial habitats. For publications that used invasive species occurrence or abundance data (whether collected for the purposes of the respective publication or acquired from another data source), we manually vetted additional information such as focal taxa, data collection years and locations, sources of other data used, and whether data or code were deposited in open access formats. We also conducted network analyses for the author institutions that coauthored papers together most frequently and for the references most cited by EDRR publications. Overall, we found that silos existed in terms of which author institutions worked together, which existing literature was cited, and which topics were frequently explored. We also found evidence of substantial gaps in data access and use. For example, although a wide variety of data sources for invasive species occurrences are available, these sources were seldom cited by published literature, and newly collected data were not often deposited into invasive species databases or other open-source data repositories. Considering the continued advocation for a centralized national EDRR information system, our study indicates that facilitating access to data, decision support tools, and other informational resources represents a key opportunity for improving EDRR capabilities.</div></div>","PeriodicalId":51024,"journal":{"name":"Ecological Informatics","volume":"84 ","pages":"Article 102855"},"PeriodicalIF":5.8000,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ecological Informatics","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1574954124003972","RegionNum":2,"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}
引用次数: 0
Abstract
While concepts regarding invasive species establishment patterns and eradication possibilities have long been a topic of invasion biology, the specific terminology referring to early detection of and rapid response to (EDRR) invasive species emerged in scientific literature during the early 2000s. Since then, the EDRR approach has expanded to include a suite of detection, planning, and management tools. By conducting a systematic literature review, we attempt to characterize the field of EDRR in the United States and its territories as reflected by publication records. Specifically, we assessed publication data such as the number of publications per year, the most common journals where papers were published, and the relationship between author's keywords for studies focusing on aquatic and terrestrial habitats. For publications that used invasive species occurrence or abundance data (whether collected for the purposes of the respective publication or acquired from another data source), we manually vetted additional information such as focal taxa, data collection years and locations, sources of other data used, and whether data or code were deposited in open access formats. We also conducted network analyses for the author institutions that coauthored papers together most frequently and for the references most cited by EDRR publications. Overall, we found that silos existed in terms of which author institutions worked together, which existing literature was cited, and which topics were frequently explored. We also found evidence of substantial gaps in data access and use. For example, although a wide variety of data sources for invasive species occurrences are available, these sources were seldom cited by published literature, and newly collected data were not often deposited into invasive species databases or other open-source data repositories. Considering the continued advocation for a centralized national EDRR information system, our study indicates that facilitating access to data, decision support tools, and other informational resources represents a key opportunity for improving EDRR capabilities.
期刊介绍:
The journal Ecological Informatics is devoted to the publication of high quality, peer-reviewed articles on all aspects of computational ecology, data science and biogeography. The scope of the journal takes into account the data-intensive nature of ecology, the growing capacity of information technology to access, harness and leverage complex data as well as the critical need for informing sustainable management in view of global environmental and climate change.
The nature of the journal is interdisciplinary at the crossover between ecology and informatics. It focuses on novel concepts and techniques for image- and genome-based monitoring and interpretation, sensor- and multimedia-based data acquisition, internet-based data archiving and sharing, data assimilation, modelling and prediction of ecological data.