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Spatial Pattern and Determinants of the First Detection Locations of Invasive Alien Species in Mainland China

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  • Dingcheng Huang
  • Runzhi Zhang
  • Ke Chung Kim
  • Andrew V Suarez

Abstract

Background: The unintentional transport of species as a result of human activities has reached unprecedented rates. Once established, introduced species can be nearly impossible to eradicate. It is therefore essential to identify and monitor locations where invaders are most likely to establish new populations. Despite the obvious value of early detection, how does an agency identify areas that are most vulnerable to new invaders? Here we propose a novel approach by using the “first detection location” (FDL) of introduced species in China to quantify characteristics of areas where introduced species are first reported. Methodology/Principal Findings: We obtained FDLs for 166 species (primarily agricultural and forestry pests) that were unintentionally introduced into China prior to 2008 from literature searches. The spatial pattern and determinants of FDLs were examined at the provincial level. The spatial pattern of FDLs varied among provinces with more commerce and trade and economically developed provinces in coastal regions having more FDLs than interior provinces. For example, 74.6% of FDLs were distributed in coastal regions despite that they only cover 15.6% of the total area in China. Variables that may be indicators of “introduction pressure” (e.g. the amount of received commerce) had an overwhelming effect on the number of FDLs in each province (R2 = 0.760). Conclusions/Significance: Our results suggest that “introduction pressure” may be one of the most important factors that determine the locations where newly-introduced species are first detected, and that open and developed provinces in China should be prioritized when developing monitoring programs that focus on locating and managing new introductions. Our study illustrates that FDL approaches can contribute to the study and management of biological invasions not only for China but also for elsewhere.

Suggested Citation

  • Dingcheng Huang & Runzhi Zhang & Ke Chung Kim & Andrew V Suarez, 2012. "Spatial Pattern and Determinants of the First Detection Locations of Invasive Alien Species in Mainland China," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-7, February.
  • Handle: RePEc:plo:pone00:0031734
    DOI: 10.1371/journal.pone.0031734
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    References listed on IDEAS

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    1. Mehta, Shefali V. & Haight, Robert G. & Homans, Frances R. & Polasky, Stephen & Venette, Robert C., 2007. "Optimal detection and control strategies for invasive species management," Ecological Economics, Elsevier, vol. 61(2-3), pages 237-245, March.
    2. Horie, Tetsuya & Homans, Frances R., 2007. "Optimal Detection Strategies for an Established Invasive Forest Pest," 2007 Annual Meeting, July 29-August 1, 2007, Portland, Oregon 9695, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    3. Wen Lin & Guofa Zhou & Xinyue Cheng & Rumei Xu, 2007. "Fast Economic Development Accelerates Biological Invasions in China," PLOS ONE, Public Library of Science, vol. 2(11), pages 1-6, November.
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    1. Davide Rassati & Massimo Faccoli & Robert A Haack & Robert J Rabaglia & Edoardo Petrucco Toffolo & Andrea Battisti & Lorenzo Marini, 2016. "Bark and Ambrosia Beetles Show Different Invasion Patterns in the USA," PLOS ONE, Public Library of Science, vol. 11(7), pages 1-17, July.

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