Inclusion of explicit measures of geodiversity improve biodiversity models in a boreal landscape

摘要: Measures of geodiversity may provide a potentially useful surrogate for biodiversity patterns in insufficiently surveyed areas. However, their reliability modelling the spatial variation species richness is inadequately understood. We investigated whether explanatory and predictive power models can be improved by considering explicit measures (variability earth surface materials, forms processes) addition to climate topography variables. Vascular plant was modelled two study areas Northern Europe, Finland at resolution 500 or 1000 m, as function three (geological, geomorphological hydrological diversity) variables, six Variation partitioning used identify independent shared contributions geodiversity, variable groups explaining richness. Generalized additive were explore ability different variables predicting within between In both areas, inclusion power, robustness models. conclusion, appear promising surrogates biodiversity, which reflect important abiotic resource factors, thus an equally, even more reliable basis transferring new than based on