Forestry trial data can be used to evaluate climate-based species distribution models in predicting tree invasions

By

Motloung, Rethabile
Robertson, Mark
Rouget, Mathieu
Wilson, John

Type

Article

Date of Publication

2014

Original Publication

NeoBiota : advancing research on alien species and biological invasions

Volume

20

Pages

31-48

Subjects

alien trees , Australian acacias , classification tree , Forestry , invasions , model evaluation , Southern African Plant Invaders Atlas , Species distribution models

Contributed by

Pensoft Publishers

Language

English

Published by

Sophia, Bulgaria Pensoft Publishers

Identifiers

DOI: https://doi.org/10.3897/neobiota.20.5778

 

Abstract

Climate is frequently used to predict the outcome of species introductions based on the results from species distribution models (SDMs). However, despite the widespread use of SDMs for pre- and post-border risk assessments, data that can be used to validate predictions is often not available until after an invasion has occurred. Here we explore the potential for using historical forestry trials to assess the performance of climate-based SDMs. SDMs were parameterized based on the native range distribution of 36 Australian acacias, and predictions were compared against both the results of 150 years of government forestry trials, and current invasive distribution in southern Africa using true skill statistic, sensitivity and specificity. Classification tree analysis was used to evaluate why some Australian acacias failed in trials while others were successful. Predicted suitability was significantly related to the invaded range (sensitivity = 0.87) and success in forestry trials (sensitivity = 0.80), but forestry trial failures were under-predicted (specificity = 0.35). Notably, for forestry trials, the success in trials was greater for species invasive somewhere in the world. SDM predictions also indicate a considerable invasion potential of eight species that are currently naturalized but not yet widespread. Forestry trial data clearly provides a useful additional source of data to validate and refine SDMs in the context of risk assessment. Our study identified the climatic factors required for successful invasion of acacias, and accentuates the importance of integration of status elsewhere for risk assessment.