Abstract

Aim Habitat loss and degradation is one of the main threats to biodiversity worldwide. Ecological modelling community has been increasingly incorporating habitat changes in the species distribution models (SDMs). However, the effect that the uncertainty arising from the standard procedures of land-use/land-cover (LULC) mapping can have on SDMs has been overlooked. Remote sensing offers a great source of information to assess the habitat changes at different spatiotemporal scales. However, despite the great variety of satellite imagery preprocessing and supervised classification procedures currently available, their effects on SDMs remain largely unknown. Location Baixa Limia-Serra do Xures Natural Park, NW Spain. Methods We developed SDMs for 27 bird species with 4 modelling algorithms using 12 sets of the LULC predictors derived from the combination of 3 image preprocessing levels and 4 supervised classification algorithms. Results The preprocessing level, classification method and modelling algorithm had a significant impact on the SDM performance and on the spatial and temporal predictions, with the considerable variation between species. Even if the effects of satellite image processing and classification procedures on the performance and transferability of SDMs were lower than that of the modelling algorithms themselves, the spatial and temporal predictions of SDMs were overall strongly affected by these LULC mapping procedures, sometimes overriding the effect of modelling algorithms. Main conclusions We argue that the uncertainty arising from the standard LULC mapping procedures when predicting species distribution dynamics should receive the same level of attention as the variability due to the different types of climate simulations and models often used in the ecological research. We also highlight the need to report accuracy of the satellite-based LULC maps for each LULC class since some of these classes can be of key importance for certain types of the ecological applications.