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Aim: The main aims were to determine: (a) the relative contribution of species replacement and richness difference from components to overall taxonomic (TDβ) and functional (FDβ) beta diversity of spider communities; (b) the degree to which TDβ and FDβ components can be explained by the environmental or geographic predictors; (c) whether FDβ components were lower than expected given the underlying TDβ variation. Location: This study was carried out in 22 oak forest sites across the Iberian Peninsula. The area comprises two biogeographic regions, Eurosiberian (North) and Mediterranean (Centre and South). Methods: Spiders were sampled using a standardized protocol. A species x traits matrix was constructed. Total taxonomic (TDβtotal) and total functional (FDβtotal) beta diversity were calculated, by pairwise comparisons, and partitioned into their replacement (βrepl) and richness difference (βrich) components. Mantel tests were used to relate taxonomic and functional dissimilarity with environmental and geographic distances. A spatial eigenfunction model was constructed and the variation in TDβ and FDβ explained by environment and geographic predictors was quantified. Null models were used to test if FDβ was higher or lower than expected given TDβ. Results: βrepl was the dominant component contributing to 84.2% and 72.8% for TDβtotal and FDβtotal, respectively. TDβtotal and FDβtotal (and their replacement components) were higher between‐ than within‐biogeographic regions. TDβtotal and TDβrepl were positively correlated with environmental and geographic distances, even when controlling for a biogeographic effect, but their functional counterparts were only correlated with environmental distance. Variation partitioning showed that pure environmental and spatially structured environmental effects had a small contribution to beta diversity, except for TDβrich. The observed slopes of the regressions of FDβtotal and FDβrepl in relation to environmental distance were slower than the null model expectations. Main Conclusions: Spider assemblage variation was mainly determined by the replacement, and not the net loss, of species and traits. TDβ was influenced by niche filtering and dispersal limitation, whereas FDβ was mainly generated by niche filtering. A high level of functional convergence among spider communities, despite the high taxonomic divergence, revealed the signal of replacement of species performing similar functions across sites. [ABSTRACT FROM AUTHOR]

. 1. The Iberian Peninsula is one of the most relevant areas in terms of species richness, rarity and endemism in the Mediterranean Basin. Using spiders as a model, we studied the relative importance of environmental and non-environmental spatial variation along a gradient of mediterraneity on the western coast of the Iberian Peninsula. 2. We performed a spatially explicit analysis to evaluate the contribution of pure environmental and pure spatial effects and their shared influence on spider species richness by variation partitioning and principal coordinates of neighbour matrices (PCNM). We dissect the spatial variation of species richness into additive scale-specific models through PCNM analysis and estimate the relative importance of environmental variables for each model. 3. Variation partitioning revealed that 72.8% of species richness variation could be explained by the environmental (climate and dune stability) and spatial variables. Most of this variation (51.3%) corresponds to the environmental spatially structured component. 4. The influence of environmental variables was scale-dependent. At the broadest scales, the latitudinal-climatic gradient was the dominant factor that influenced spider species richness variation. At the finest scale, stability of the dune system was the most important component. 5. In conclusion, spider species richness patterns were determined mostly by spatially structured environmental variation. More importantly, this study shows that different environmental factors act at multiple scales. Hence, our results reinforce the importance of the incorporation of both local and broad-scale factors when examining species richness patterns. [ABSTRACT FROM AUTHOR]