Applying multiple generalized regression models, we studied spatial patterns in species richness for different taxonomic groups (amphibians, reptiles, grasshoppers, plants, mosses) within the German federal state Rhineland-Palatinate (RP). We aimed (1) to detect their centres of richness, (2) to rate the influence of climatic and land-use parameters on spatial patterns, and (3) to test whether patterns are congruent between taxonomic groups in RP. Centres of species richness differed between taxonomic groups and overall richness was the highest in the valleys of large rivers and in different areas of southern RP. Climatic parameters strongly correlated with richness in all taxa whereas land use was less significant. Spatial richness patterns of all groups were to a certain extent congruent but differed between group pairs. The number of grasshoppers strongly correlated with the number of plants and with overall species richness. An external validation corroborated the generality of our species richness models. 1. Introduction Europe has undergone a period of environmental change and loss of biodiversity over the last decades [1, 2]. A high level of biodiversity may help to preserve a range of options to adapt under changing environmental conditions such as climate and land-use change. Hence, studies of spatial patterns of species richness and its environmental determinants are required. Broad-scale patterns (i.e., global or continental extent and large grain size) in species richness are relatively well studied, and the determining mechanisms of patterns cover a wide range from energy and water availability [3–5] to historic climate and climate stability as predictors of present patterns [6, 7]. Distribution models are frequently applied to understand the relationship between spatial patterns in species occurrence and environmental variables, (e.g., [8–11]). While broad-scale species richness patterns are mainly determined by energy and water availability, (e.g., [3–5, 12–14]), regional patterns (except of few taxonomic groups, e.g., [15, 16]) were less frequently studied and underlying mechanisms are widely unknown. The strength of the impact of environmental variables on species distributions may differ with spatial extent and grain size [17–20] and a simple downscaling of the results found at broad spatial scales is not wise. The poor knowledge is particularly true for less studied taxonomic groups, for example, mosses, which encompass hundreds of species, but data availability on this group has only recently been improved at a national level (e.g.,
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