Addressing Biological Invasions in Agriculture with Big Data in an Informatics Age

Big data approaches are rapidly expanding across many fields of science and are seeing increasing application, yet the use of big data in research related to invasive species lags. Big data can play a key role in predicting, detecting, preventing, controlling, and eradicating biological invasions. Here, we assess terms in the literature related to big data, biological invasions, and agriculture and review sources of big data, including museum records, crowdsourcing observations, natural history collections, and DNA-based information. These sources can be combined with environmental data to build models, predict the origins of invasive species, and develop control methods. To harness the power of data for agricultural biological invasions, several action areas are recommended to streamline processes and improve data sources.

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Publication Details

Journal
Agriculture
Published
2025-05-28
DOI
https://doi.org/10.3390/agriculture15111157
Citations
3
Primary Topic
Identification and Quantification in Food
Type
article
Field-Weighted Citation Impact
2.42

Funders

Controls
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article

Addressing Biological Invasions in Agriculture with Big Data in an Informatics Age

Rebecca Clement, Nicholas C. Manoukis, Hyoseok Lee, Christopher L. Owen et al.
3 citations
Agriculture
Identification and Quantification in Food
2.42
article

Addressing Biological Invasions in Agriculture with Big Data in an Informatics Age

Rebecca Clement, Nicholas C. Manoukis, Hyoseok Lee, Christopher L. Owen, Yelena M. Pacheco, Faith VanToll Ross, Mark S. Sisterson
article en
3 citations

Abstract

Big data approaches are rapidly expanding across many fields of science and are seeing increasing application, yet the use of big data in research related to invasive species lags. Big data can play a key role in predicting, detecting, preventing, controlling, and eradicating biological invasions. Here, we assess terms in the literature related to big data, biological invasions, and agriculture and review sources of big data, including museum records, crowdsourcing observations, natural history collections, and DNA-based information. These sources can be combined with environmental data to build models, predict the origins of invasive species, and develop control methods. To harness the power of data for agricultural biological invasions, several action areas are recommended to streamline processes and improve data sources.

AgricultureVol. 15(11)
Oak Ridge Associated Universities (US), Animal and Plant Health Inspection Service (US), Natural Resources Conservation Service (US), Agricultural Research Service (US), United States Department of Agriculture (US), National Museum of Natural History (US), San Joaquin Valley Agricultural Sciences Center (US), Daniel K. Inouye U.S. Pacific Basin Agricultural Research Center (US)
U.S. Department of Energy, U.S. Department of Agriculture, Oak Ridge Associated Universities, Oak Ridge Institute for Science and Education, Agricultural Research Service
Openalex Percentile: Top 11%
Identification and Quantification in Food
2.42
DOIOpen Access PDFOpenAlex
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