LAUSR

The relative importance of environmental variables for Spartina alterniflora distribution was investigated across different spatial scales using maximum entropy modelling (MaxEnt), a species distribution modelling technique. The results showed that elevation was the most important predictor for species presence at each scale. Mean diurnal temperature range and isothermality were the second most important predictors at national and regional scales respectively. Soil drainage class, pH and organic carbon were important on the northern Chinese coast. The importance of climatic variable type was highest at global and national scales and declined as the scale decreased. The importance of soil variable type was lower at coarser scales, but varied greatly at finer scales. The relationships between environmental variables and species presence changed as the variables’ ranges changed across different scales. Climatic and soil variables were substantially affected by interactions among variables, which changed their relationships with species presence and relative importance. The modelled suitable area on the Chinese coast decreased from 54.16 to 12.64% limited by elevation from the global to national scale, and decreased to 8.04% limited by soil drainage, pH and organic carbon from the national to regional scale. The findings of the present study emphasise the importance of spatial scale for understanding relationships between environmental variables and the presence of S. alterniflora.