Complex species distribution models of Goldcrests and Firecrests densities in Poland: are remote sensing-based predictors sufficient?

摘要: Species distribution models should identify ecological requirements of species and predict their spatial density. However, data from remote sensing sources are often used alone as predictors in modelling distributions. Such will only produce accurate if features that distinguishable by a good match to the environmental traits delineate habitat requirements. Both Goldcrest Regulus regulus Firecrest ignicapilla respond complex habitats not described simple data. We tested usefulness predictor for two according 970 study plots sized 1 × 1 km. Predictors were aggregated using PCAs related Hayne estimator density GAMs. The based on both detailed proved be better than model and/or forest structure reached highest areas with high share old spruce-dominated forests substantial fir, avoiding pine, it preferred low number tree species. In turn, favoured forests, dominated spruce beech, an admixture single fir larch trees, preferring suggest free sources, but also more containing thorough information inventory derived ground measurements.