Species distribution models based on occurrence data (SDM) are used to derive broad‐scale estimates of relative abundance, but a triangular relationship between predicted suitability for species occurrence and abundance is commonly observed—that is, a low suitability would correspond to low abundances, whereas a high suitability would correspond to either low or high abundances. To properly understand the factors behind this triangular relationship, we assessed: (1) the capacity of SDM to explain variations in population abundance, and (2) the effect of population growth in the dynamics on the triangular relationship by comparing its variation in two sampling periods in the case of a species that is increasing in numbers.
Data on roe deer (Capreolus capreolus) relative abundance were obtained for 441 localities, of which 145 were surveyed twice (2006–2007 and 2011–2013). Species distribution was modelled using the favourability function. The relationship between favourability values for species occurrence and abundances were explored using quantile regressions.
The number of roe deer is increasing on a regional scale. The results from the earlier survey showed a weaker relationship than those obtained from the survey carried out later. Growth rates were significantly related to the residuals of the quantile regression fitted to the earlier survey (the higher the residual difference between observed and expected abundances, the higher the population growth rates).
Our results support the use of the residuals of the quantile regression as a proxy of the population growth rate. They also partly support the interpretation of the upper limit of abundance delimited by the regression as the environmental carrying capacity. Overall, the results are of general interest when using SDM to predict the population abundance of expanding species, such as alien species and/or in changing environments.