Abstract

Urbanization particularly promotes habitat fragmentation, which in turn strongly affects biodiversity patterns. A major driver of species loss in isolated habitat patches is dispersal limitation. The relative importance of dispersal ability of species, spatial habitat configuration and local environmental conditions for predicting species composition is still unclear though. Addressing urban abandoned railway areas as study areas, we analyzed the relative importance of environmental versus landscape predictors (e.g. proportions of sealed, built-up and ruderal areas) using variation partitioning methods. To add the perspective of individual species dispersal ability, we characterized the effect of species traits on explained variation in species occurrence with a regression tree. The difference in explained variation in the occurrence of individual species (ΔCfit) between a CCA with environmental predictors and environmental and landscape predictors together was analyzed. The results revealed that environmental predictors explained a slightly larger amount of variation than landscape predictors. Adding landscape predictors to the analysis with environmental predictors resulted in a sizeable increase in explained variation. The most important predictors in the CCA were photosynthetically active radiation, C/N-ratio in the soil and the proportion of ruderal habitats in the surroundings of the plots. The regression tree model showed higher ΔCfit values for species with a long-term persistent soil seed bank. The lowest ΔCfit values were found for species with a transient seed bank and long seeds. Linking dispersal-related traits to the predictability of species occurrence is a promising approach to reveal the interdependencies between environmental conditions, landscape configuration and species-specific dispersal abilities. Our results suggest that in fragmented urban habitats, a persistent seed bank is advantageous because it allows for stable populations once habitat patches have been colonized.

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