In this post Johanna Bradie discusses her recent paper with Brian Leung ‘Estimating non-indigenous species establishment and their impact on biodiversity, using the Relative Suitability Richness model‘
Invasive species are one of the leading causes of biodiversity loss and established invaders are nearly impossible to eradicate. Conservation efforts should therefore focus on preventing the establishment of invasive species. Managers need to be able to predict which species will establish and what type of impact they will have in order to prioritize management efforts and make sure limited conservation dollars are spent in the most cost-effective way.
Currently, species distribution models (SDMs) are used to predict whether a species will establish in a new region, but these models do not take into account how native species in the community will affect the likelihood an invader will establish. Further, SDMs do not allow managers to anticipate the impact an invader will have on a community.
Logically, the biotic community in receiving environments affects the likelihood that an invader will establish, and in turn, the native community can be affected by an established invader. Estimating biotic interactions would provide insight into the potential consequences of invasion and provide information about the value of management options to inhibit establishment and control impacts. Yet, our ability to estimate the consequences of these biotic interactions have been limited, especially given incomplete data.
In our recent study we developed new methods that allow managers to incorporate any available community data to predict whether a potential invader will establish and predict how it will impact native species if it establishes. Our method, termed the Relative Suitability Richness (RSR) model, estimates the biotic components of biological invasions. We show that by using relative environmental suitability, constrained by species richness, it is possible to incorporate biotic information to make predictions for invader occurrence and use these predictions to estimate biodiversity impacts. The RSR model was evaluated over a range of conditions, including different levels of competition between species. Results indicate that even though SDMs based solely on abiotic factors can perform very well, the inclusion of even partial community data can improve predictions. Thus, the RSR model can not only help managers predict where a species will establish, but can also provide information of invader impact which was not possible using an SDM approach.
Managers typically face limited time, information and resources, and need to prioritize their efforts. They should do so using the best available data, incorporating information on both biotic and abiotic environmental conditions, and considering not just probability of non-indigenous species occurrence, but also severity of their impact. The RSR model has great potential in management applications to identify sites where an invader is likely to be found and to quantify the impact of invaders on native biodiversity.