Predicting range expansion of invasive species: pitfalls and best practices for obtaining biologically realistic projections

Species Distribution Models (SDM) for seven invasive plant species in North America. Species distribution models (SDMs) are widely used to forecast potential range expansion of invasive species. However, invasive species occurrence datasets often have spatial biases that may violate key SDM assumptions. We examined alternative methods of spatial bias correction and multiple methods for model evaluation for seven invasive plant species. Species SDMs include Common Tansy (Tanacetum vulgare), Wild Parsnip (Pastinaca sativa), Leafy Spurge (Euphorbia virgata), Common Teasel (Dipsacus fullonum), Brown Knapweed (Centaurea jacea), Black Swallowwort (Vincetoxicum nigrum), and Dalmatian Toadflax (Linaria dalmatica). 

Methods
We employed bias-correction measures for both occurrence sampling (1km occurrence points and 20km occurrence points) and background sampling (GKD 0, GKD1, and GKD 3) inputs in a factorial design for Maxent SDMs resulting in six potential models for each of the seven species.