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Predicting invasiveness of Australian acacias on the basis of their native climatic affinities, life history traits and human use

Authors

  • Pilar Castro-Díez,

    Corresponding author
    1. Departamento de Ecología, Universidad de Alcalá, Campus Universitario, Ctra. Madrid-Barcelona Km. 33.6, E-28871 Alcalá de Henares, Madrid, Spain
      Pilar Castro-Díez, Departamento de Ecología, Universidad de Alcalá, Campus Universitario, Ctra. Madrid-Barcelona Km. 33.6, E-28871 Alcalá de Henares, Madrid, Spain.
      E-mail: mpilar.castro@uah.es
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  • Oscar Godoy,

    1. Departamento de Ecología, Universidad de Alcalá, Campus Universitario, Ctra. Madrid-Barcelona Km. 33.6, E-28871 Alcalá de Henares, Madrid, Spain
    2. Laboratorio Internacional de Cambio Global MNCN-CSIC, Serrano 115. E28006 Madrid, Spain
    3. Department of Ecology, Evolution and Marine Biology, University of California, Santa Barbara, California 93106 USA
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  • Asunción Saldaña,

    1. Departamento de Ecología, Universidad de Alcalá, Campus Universitario, Ctra. Madrid-Barcelona Km. 33.6, E-28871 Alcalá de Henares, Madrid, Spain
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  • David M. Richardson

    1. Centre for Invasion Biology, Department of Botany and Zoology, Stellenbosch University, Private Bag X1, Matieland 7602, South Africa
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Pilar Castro-Díez, Departamento de Ecología, Universidad de Alcalá, Campus Universitario, Ctra. Madrid-Barcelona Km. 33.6, E-28871 Alcalá de Henares, Madrid, Spain.
E-mail: mpilar.castro@uah.es

Abstract

Aim  Many Australian Acacia species have been widely planted around the world. Some taxa are among the most aggressive of invasive alien plants and cause severe ecosystem degradation. We aimed to predict invasiveness of taxa in a large set of Australian Acacia species on the basis of easy-to-assess predictors.

Location  Global.

Methods  We considered three groups of predictors: (1) climatic affinities of species in their native ranges; (2) life history traits; and (3) human usage factors. Logistic multiple regressions were applied to construct predictive models for 85 Australian acacias (species in Acacia subgenus Phyllodineae) that are known to have been transported outside of their native range (17 known to be invasive and 68 non-invasive). The best model was then applied to predict the probability of an additional 34 Acacia species with unknown invasive status.

Results  Water availability in the native range and human uses were significant predictors of invasiveness in all models. Life history index (proportional to plant height, leaf area and seed mass) and climatic amplitude were also positive predictors of invasiveness when human use was not considered. The best model, based on human uses and water availability, correctly classified 92% of the species. Results suggest that Acacia species that evolved under low climatic stress have a greater chance of becoming invasive.

Main conclusions  Species that are useful to humans are more likely to be disseminated to and within new regions, thus increasing the risk of invasion. Combining ecological, evolutionary and human-use criteria is useful for quantifying the risk of Australian acacias becoming invasive. Acacia species can attain invasive status by virtue of intrinsic traits and/or through increased use by humans. Therefore, we predict that the invasion risk of species coming from native areas with high water availability will rise sharply if the interest in exploiting these species increases.

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