Consensual predictions of potential distributional areas for invasive species: a case study of Argentine ants in the Iberian Peninsula

Abstract

International audienceInvasive species are known to influence the structure and function of invaded ecological communities, and preventive measures appear to be the most efficient means of controlling these effects. However, management of biological invasions requires use of adequate tools to understand and predict invasion patterns in recently introduced areas. The present study: (1) estimates the potential geographic distribution and ecological requirements of the Argentine ant (Linepithema humile Mayr), one of the most conspicuous invasive species throughout the world, in the Iberian Peninsula using ecological niche modeling, and (2) provides new insights into the process of selection of consensual areas among predictions from several modeling methodologies. Ecological niche models were developed using 5 modeling techniques: generalized linear models (GLM), generalized additive models (GAM), generalized boosted models (GBM), Genetic Algorithm for Rule-Set Prediction (GARP), and Maximum Entropy (Maxent). Models for the eastern and western portions of the Iberian Peninsula were built using subsets of occurrence and environmental data to investigate the potential for ecological niche differences between the invading populations. Our results indicate geographic differences between predictions of different approaches, and the utility of ensemble predictions in identifying areas of uncertainty regarding the species' invasive potential. More generally, our models predict coastal areas and major river corridors as highly suitable for Argentine ants, and indicate that western and eastern Iberian Peninsula populations occupy similar environmental conditions

The limits to prediction in ecological systems

“…Instead, invasion biology has largely been an ad hoc, retrospective analysis of why certain species have become invasive when introduced into new habitats (e.g., Rosecchi et al 2001, Roura-Pascual et al 2009). We suggest that the prediction of species invasions and community invasibility has proven to be such an intractable problem because it is computationally irreducible for reasons similar to those outlined above for climate change.…”

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

“…It also enabled us to identify which climatic variables were most effective in defining a climatic envelope for the species that could be transferred across space. Furthermore, when there is some uncertainty regarding the correct model, predictions based on multimodel inference are generally regarded as more robust than those derived from a single model defined a priori (Roura-Pascual et al, 2009).…”

Development and Comparison of Species Distribution Models for Forest Inventories

“…Results showed that new methods, such as maximum entropy (MaxEnt), have greater predictive power than other methods, such as logistic regression (both adjusted generalized linear models, GLM, and adjusted generalized additive models, GAM). Subsequent studies have also obtained better predictive capacity for MaxEnt than for logistic regression [7][8][9][10][11].…”