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Patterns of Spread in Biological Invasions Dominated by Long-Distance Jump Dispersal: Insights from Argentine Ants

Andrew V. Suarez, David A. Holway and Ted J. Case
Proceedings of the National Academy of Sciences of the United States of America
Vol. 98, No. 3 (Jan. 30, 2001), pp. 1095-1100
Stable URL: http://www.jstor.org/stable/3054827
Page Count: 6
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Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Patterns of Spread in Biological Invasions Dominated by Long-Distance Jump Dispersal: Insights from Argentine Ants
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Abstract

Invading organisms may spread through local movements (giving rise to a diffusion-like process) and by long-distance jumps, which are often human-mediated. The local spread of invading organisms has been fit with varying success to models that couple local population growth with diffusive spread, but to date no quantitative estimates exist for the relative importance of local dispersal relative to human-mediated long-distance jumps. Using a combination of literature review, museum records, and personal surveys, we reconstruct the invasion history of the Argentine ant (Linepithema humile), a wide-spread invasive species, at three spatial scales. Although the inherent dispersal abilities of Argentine ants are limited, in the last century, human-mediated dispersal has resulted in the establishment of this species on six continents and on many oceanic islands. Human-mediated jump dispersal has also been the primary mode of spread at a continental scale within the United States. The spread of the Argentine ant involves two discrete modes. Maximum distances spread by colonies undergoing budding reproduction averaged 150 m/year, whereas annual jump-dispersal distances averaged three orders of magnitude higher. Invasions that involve multiple dispersal processes, such as those documented here, are undoubtedly common. Detailed data on invasion dynamics are necessary to improve the predictive power of future modeling efforts.

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