An invasive species' relationship with environmental variables changes across multiple spatial scales.
To further our understanding of invasive species' novel distributions, knowledge of invasive species' relationships with environmental variables at multiple spatial scales is paramount. Here, we investigate which environmental variables and which spatial scales best explain the invasive mute swan's (Cygnus olor) distribution in southern Ontario (Canada). Specifically we model mute swan distribution changes according to ecologically-relevant spatial scales: average territory size radius, 140 m; median dispersal distance of cygnets, 3,000 m; and average activity distance of males, 8,000 m. For individual spatial scales, global models using variables measured at each particular scale result in the highest Akaike weights, AUC, and Cohen's Kappa values. Yet composite models (models combining variables measured at different scales) elicit the best models, as determined by higher Akaike weights and high AUC and Cohen's Kappa values. Overall, percent water, waterbody perimeter density, temperature, precipitation, and road density are positively correlated with mute swan distribution, while percent forest and elevation are negatively correlated at all scales of analysis. Only percent water and annual precipitation are more influential in determining mute swan distribution at the 3,000 and 8,000 m zone scales than the territory scale. While most species distribution models are performed at a single scale, the results of our study suggest that composite models reflecting a species' ecological needs provide models of better fit with similar, if not better, predictive accuracy. When analyzing species distributions, we also recommend that ecologists consider the scale of the underlying landscape processes and the effect that this may have on their modelling outcomes.