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Predicting invasions in Australia by a Neotropical shrub under climate change: the challenge of novel climates and parameter estimation

Authors

  • Rieks D. Van Klinken,

    Corresponding author
    1. CSIRO Entomology, Long Pocket Laboratories, 120 Meiers Road, Indooroopilly, Queensland 4068, Australia,
    2. Cooperative Research Centre for Australian Weed Management
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  • Ben E. Lawson,

    1. School of Biological Sciences, The University of Queensland, St Lucia, Brisbane 4072, Australia,
    2. Cooperative Research Centre for Australian Weed Management
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  • Myron P. Zalucki

    1. School of Biological Sciences, The University of Queensland, St Lucia, Brisbane 4072, Australia,
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Rieks van Klinken, CSIRO Entomology, 120 Meiers Road, Indooroopilly, Queensland 4068, Australia.
E-mail: rieks.vanklinken@csiro.au

ABSTRACT

Aim  To test how well species distributions and abundance can be predicted following invasion and climate change when using only species distribution and abundance data to estimate parameters.

Location  Models were developed for the species' native range in the Americas and applied to Australia.

Methods  We developed a predictive model for an invasive neotropical shrub (Parkinsonia aculeata) using a popular ecophysiological bioclimatic modelling technique (CLIMEX) fitted against distribution and abundance data in the Americas. The effect of uncertainty in model parameter estimates on predictions in Australia was tested. Alternative data sources were used when model predictions were sensitive to uncertainty in parameter estimates. The resulting best-fit model was run under two climate change scenarios.

Results  Of the 19 parameters used, 9 could not be fitted using data from the native range. However, only parameters that lowered temperature or increased moisture requirements for growth noticeably altered the model prediction in Australia. Differences in predictions were dramatic, and reflect climates in Australia that were not represented in the Americas (novel climates). However, these poorly fitted parameters could be fitted post hoc using alternative data sources prior to predicting responses to climate change.

Conclusions  Novel climates prevented the development of a predictive model which relied only on native-range distribution and abundance data because certain parameters could not be fitted. In fact, predictions were more sensitive to parameter uncertainty than to climate change scenarios. Where uncertainty in parameter estimates affected predictions, it could be addressed through the inclusion of alternative data sources. However, this may not always be possible, for example in the absence of post-invasion data.

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