Minimizing false‐negatives when predicting the potential distribution of an invasive species: a bioclimatic envelope for the red‐eared slider at global and regional scales

Abstract

Invasive species threaten biodiversity; hence, predicting where they may establish is vital for conservation. Our aim is to provide a robust predictive model for an invasive species suitable for managers acting at both global and regional scales. Specifically, we investigate one of the world's worst invasive species [the red-eared slider turtle (RES) Trachemys scripta elegans] and one of the world's biodiversity hotspots (New Zealand) as our representative systems. We used climate data and location records to define a bioclimatic envelope for the species. Multimodel inference was used to predict areas suitable for RES establishment, weighting in favour of models with low false-negative and high true-positive rates in predictive cross-validation tests. Our performance criterion was the partial area under the curve of a receiver operating characteristic plot where sensitivity exceeded 0.95. We generated both conservative (best-case scenario) and liberal (worst-case scenario) predictions, based on different levels of information about breeding potential. All predictions were expressed on a standard scale of suitability relative to existing known distribution. Globally, the best climate matches for RES outside of their native range in North America include south-east Asia, and parts of Europe, areas where RES have already established. The best available site in New Zealand is considered climatically more suitable than 16% of global sites where RES have bred successfully. While RES can survive in several areas throughout New Zealand, the potential to establish a self-sustaining (i.e. breeding) population appears restricted to the upper areas of the north island where the mean daily temperatures in the hottest month exceed 18 1C. The methods developed here were designed to reduce false-negative predictions as that represents a precautionary approach for species that pose a biosecurity risk. They could readily be adapted, however, to reduce false-positives when predicting areas suitable for translocation of rare and endangered species.

Online trade poses a threat to biosecurity in New Zealand

“…This species is a very popular pet worldwide, being 'mass-produced' in the USA for the international trade (Cadi et al 2004). In New Zealand it seems to be one of the most affordable and easily obtained exotic reptiles (Kikillus et al 2009). Isolated populations of the species have been found in the wild in New Zealand (Thomas and Hartnell 2000;Dykes 2007), and climatic models indicate that a number of northern areas are suitable for its establishment (Kikillus et al 2009).…”

“…In New Zealand it seems to be one of the most affordable and easily obtained exotic reptiles (Kikillus et al 2009). Isolated populations of the species have been found in the wild in New Zealand (Thomas and Hartnell 2000;Dykes 2007), and climatic models indicate that a number of northern areas are suitable for its establishment (Kikillus et al 2009). Some regional authorities now classify T. s. elegans as pests, and are advocating that research is carried out to determine whether they are likely to become invasive in New Zealand (Kikillus et al 2009).…”

“…Isolated populations of the species have been found in the wild in New Zealand (Thomas and Hartnell 2000;Dykes 2007), and climatic models indicate that a number of northern areas are suitable for its establishment (Kikillus et al 2009). Some regional authorities now classify T. s. elegans as pests, and are advocating that research is carried out to determine whether they are likely to become invasive in New Zealand (Kikillus et al 2009). In the meantime, unrestricted online trade means that it is likely that feral populations may become more widely established, and consequently affect native freshwater environments.…”

Uses and misuses of bioclimatic envelope modeling

“…Some are specific to the modeling technique used (e.g., Breiman 2001, Elith et al 2008, Phillips and Dudı´k 2008, while others are more general (e.g., Franklin 2009, Miller 2010. General guidelines include strategies for the selection of appropriate predictor variables in the models (e.g., Elith et al 2005, Heidy Kikillus et al 2010, Ashcroft et al 2011, the decision as to whether background or pseudo-absence data are warranted and how to select them (e.g., Phillips et al 2009, VanDerWal et al 2009a, Wisz and Guisan 2009), choice of methods to convert probabilities of occurrence or suitability scores into projections of species presence and absence on maps (e.g., Liu et al 2005, Freeman and Moisen 2008, Nenze´n and Arau´jo 2011, decisions regarding methodology for model evaluation (e.g., Hirzel et al 2006, Raes and ter Steege 2007, Peterson et al 2008a, and use of ensemble and consensus forecasting methodologies (e.g., Arau´jo et al 2005b, Diniz-Filho et al 2009, Marmion et al 2009, Garcia et al 2012. It is clear that decisions regarding the technical implementation of the models will affect their quality, a topic that has received extensive treatment and reviews elsewhere (Arau´jo and Guisan 2006, Heikkinen et al 2006, Latimer et al 2006, Austin 2007.…”

Distribution of the exotic Pond Slider (<em>Trachemys scripta</em>) in Ontario

“…although Pond Sliders can survive in many areas of the world, successful breeding is limited to a subset of these locations (Ficetola et al 2009), mainly in areas with a climate similar to or warmer than the native range of the Pond Slider in southeastern united States (e.g., Kikillus et al 2010). Sites with known breeding populations of Pond Sliders in italy had warmer summer and winter temperatures than sites where breeding was not occurring (Ficetola et al 2009).…”