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Biological Invasions

, Volume 11, Issue 4, pp 1017–1031 | Cite as

Consensual predictions of potential distributional areas for invasive species: a case study of Argentine ants in the Iberian Peninsula

  • Núria Roura-Pascual
  • Lluís Brotons
  • A. Townsend Peterson
  • Wilfried Thuiller
Original Paper

Abstract

Invasive species are known to influence the structure and function of invaded ecological communities, and preventive measures appear to be the most efficient means of controlling these effects. However, management of biological invasions requires use of adequate tools to understand and predict invasion patterns in recently introduced areas. The present study: (1) estimates the potential geographic distribution and ecological requirements of the Argentine ant (Linepithema humile Mayr), one of the most conspicuous invasive species throughout the world, in the Iberian Peninsula using ecological niche modeling, and (2) provides new insights into the process of selection of consensual areas among predictions from several modeling methodologies. Ecological niche models were developed using 5 modeling techniques: generalized linear models (GLM), generalized additive models (GAM), generalized boosted models (GBM), Genetic Algorithm for Rule-Set Prediction (GARP), and Maximum Entropy (Maxent). Models for the eastern and western portions of the Iberian Peninsula were built using subsets of occurrence and environmental data to investigate the potential for ecological niche differences between the invading populations. Our results indicate geographic differences between predictions of different approaches, and the utility of ensemble predictions in identifying areas of uncertainty regarding the species’ invasive potential. More generally, our models predict coastal areas and major river corridors as highly suitable for Argentine ants, and indicate that western and eastern Iberian Peninsula populations occupy similar environmental conditions.

Keywords

Biological invasions Consensual areas Ecological differences Genetic Algorithm for Rule-Set Prediction (GARP) Generalized additive models (GAM) Generalized boosted models (GBM) Generalized linear models (GLM) Iberian Peninsula Invasive ants Linepithema humile Maximum Entropy (Maxent) 

Notes

Acknowledgments

Special thanks to P. Pons, C. Gómez and E. Knox-Davis for their comments on the manuscript, and M. Clavero, S. Phillips, and J. Hortal for statistical guidance. X. Espadaler provided useful comments on historical data of the Argentine ant invasion in the Iberian Peninsula. This research was funded by the Ministry of Education and Science CGL2004-05240-C02-02/BOS and MEC/FEDER2007-64080-C02-02/BOS of the Spanish Government in support of N. Roura-Pascual, and is a contribution to the European Research Group GDRE “Mediterranean and mountain systems in a changing world”. N. Roura-Pascual benefited from a Beatriu de Pinós postdoctoral grant (2006 BP-A 10124) from Catalan Agency for Management of University and Research Grants, and L. Brotons from a Ramon y Cajal contract from the Spanish government. W. Thuiller was partly funded by the EU FP6 MACIS specific targeted project (Minimisation of and Adaptation to Climate change: Impacts on biodiversity N° 044399) and EU FP6 ECOCHANGE integrated project (Challenges in assessing and forecasting biodiversity and ecosystem changes in Europe).

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Copyright information

© Springer Science+Business Media B.V. 2008

Authors and Affiliations

  • Núria Roura-Pascual
    • 1
    • 2
  • Lluís Brotons
    • 3
  • A. Townsend Peterson
    • 4
  • Wilfried Thuiller
    • 5
  1. 1.Departament de Ciències AmbientalsUniversitat de GironaGironaSpain
  2. 2.Centre for Invasion Biology, Department of Botany and ZoologyStellenbosch UniversityMatielandSouth Africa
  3. 3.Àrea de BiodiversitatCentre Tecnològic Forestal de CatalunyaSolsonaSpain
  4. 4.Natural History Museum and Biodiversity Research CenterThe University of KansasLawrenceUSA
  5. 5.Laboratoire d’Ecologie Alpine, UMR-CNRS 5553Université J. FourierGrenoble Cedex 9France

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