Quantifying uncertainty in the potential distribution of an invasive species: climate and the Argentine ant

Abstract

Maps of a species' potential range make an important contribution to conservation and invasive species risk analysis. Spatial predictions, however, should be accompanied by an assessment of their uncertainty. Here, we use multimodel inference to generate confidence intervals that incorporate both the uncertainty involved in model selection as well as the error associated with model fitting. In the case of the invasive Argentine ant, we found that it was most likely to occur where the mean daily temperature in mid-winter was 7-14 degrees C and maximum daily temperatures during the hottest month averaged 19-30 degrees C. Uninvaded regions vulnerable to future establishment include: southern China, Taiwan, Zimbabwe, central Madagascar, Morocco, high-elevation Ethiopia, Yemen and a number of oceanic islands. Greatest uncertainty exists over predictions for China, north-east India, Angola, Bolivia, Lord Howe Island and New Caledonia. Quantifying the costs of different errors (false negatives vs. false positives) was considered central for connecting modelling to decision-making and management processes.

Relative risk of invasive ants (Hymenoptera: Formicidae) establishing in New Zealand

“…although the approach is different in each study they show results broadly similar to ours: New Zealand is too cold for A. gracilipes (Lester 2005), marginal for S. invicta in northern New Zealand (Morrison et al 2004;Lester 2005;Sutherst & Maywald 2005), and suitable for L. humile, particularly in the North island (Harris 2002;Hartley & Lester 2003;Hartley et al 2006). a soilbased temperature model predicted several southerly locations suitable for L. humile that were considered too cold when based on air temperature (Hartley & Lester 2003).…”

“…However, where temperature and rainfall parameters are near their lower limits for a species, the chances of successful establishment are probably lowered. in the case of L. humile, interactions between temperature and rainfall suggest that temperature optima increase as precipitation increases (Hartley et al 2006).…”

Predicting tree distributions in an East African biodiversity hotspot: model selection, data bias and envelope uncertainty

“…However, if models are lacking, either in fit or stability, we think it prudent to investigate other selection options as a matter of course, in which case the computation of a model average would be trivial. Other kinds of multimodel have also produced favourable results (Anderson et al, 2000;Johnson and Omland, 2004;Hartley et al, 2006;Dormann et al, 2008), and appear to be generally superior to best-model approaches for predictive purposes.…”

Climate change impoverishes and homogenizes ants’ community structure: a long term study

“…The majority of publications on the effect of climate change on ants, either in geographical or in local ecological scales, deal with the distribution and spread of invasive ant species (Chen 2008, Espadaler and Gómez 2003, RouraPascual et al 2004, Hartley et al 2006, Sutherst and Maywald 2005, Ward 2007, Bertelsmeier et al 2016. As no occurrence of invasive ant species has been documented from the studied habitat in question, I am not discussing the results of the present paper in the light of those studies, although local density increase of Plagiolepis taurica, which is a thermophilous and drought tolerant species, is similar to the expansion of invasive ant species on larger scales.…”