Chorological information concerning 182 taxa of monocotyledons endemic to the Iberian Peninsula and Balearic Islands was compiled and related to the 100×100 km, 50×50 km and 10×10 km UTM grids. Distributions were analysed using multivariate methods (two‐way indicator species analysis and detrended correspondence analysis) for each scale. Comparison of results allows recognition of several floristic elements and sectors (i.e. Balearic, Murcian‐Almerian, south western) common to all three scales, whereas other regions are assigned to different sectors depending on the grid size considered. As a consequence of the increase in detail, characteristics such as number of sectors, the outline of boundaries and continuity or fragmentation of the areas also change. These factors are discussed.

This article delineates the compositional regions present in the Iberian-Balearic fern flora and compares these regions to previously proposed biogeographic units. It also assesses the extent to which environmental variables could explain the regions and the fern species richness gradients found within them. A combination of 40 previously published and new maps were used to compile the distribution of 123 pteridophytes on a 50 9 50 km UTM grid. Cluster analysis of the resulting 257 squares was used to classify 10 regions based on fern species assemblages. Discriminant function analysis identified the environmental variables that best explained these fern composition regions. Using generalized linear models; the number of species in each square was regressed against topography, climate, geology, environmental diversity, land use and spatial variables within each region. Two main latitudinal pteridophyte zones can be recognized in the Iberian Peninsula. These two zones are longitudinally subdivided into two sub zones. The 10 regions established significantly differ both in species richness and influential environmental variables. Climatic variables discriminate the most among regions, followed by topography, heterogeneity and geology. Pteridophyte richness varies, with richer areas being located along the coast and the main mountain ranges and the poorest areas being in the central plateaus and some north eastern and south western river basins. Species richness variation in Iberia is positively correlated with altitude range, precipitation, maximum altitude and area with siliceous soils. It is negatively correlated with the total annual days of sun, however. The fact that species richness is explained by different variables within each of the 10 regions indicates that the specific factors determining the spatial distribution of species richness vary from region to region. Some coastal regions are poorly explained by the model, and display a negative correlation with the selected causal factors. This finding suggests that persistent historic effects might play a local role in determining species assemblages in these regions.

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The Global Strategy for Plant Conservation (GSPC) seeks to assess the conservation status of the world vascular plants by 2020, and to guarantee that at least 75% threatened taxa are conserved in situ. A comprehensive evaluation of IUCN categories for 7269 Spanish vascular plants (GSPC Target 2), using distribution data and environmental niche models, is presented. A gap analysis to assess the percentage of threatened plants effectively conserved in situ (considering national parks, plant micro-reserves and recovery or conservation plans) was also conducted (Target 7). The result is that only 44.4% threatened species are subject to an adequate in situ protection. An appropriate management of additional natural protected areas towards the conservation of threatened plants would make Spain meet this threshold, but severe deficiencies should be corrected. The methodology presented here is proposed as a tool to assess the degree of achievement of GSPC targets. This procedure can be quickly implemented and allows an easy evaluation of the progress, as well as the pending tasks in a given period of time.

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Aim We analysed the distributional pattern of the vascular flora of the Iberian Peninsula and Balearic archipelago using cluster and parsimony methods to delineate a biogeographical scheme for south‐western Europe and to compare the results with previous regionalizations. Additionally, we aim to identify areas of endemism. Location South‐western Europe (Iberian Peninsula and the Balearic Islands). Methods Pattern analysis of a chorological dataset, consisting of the occurrences of 3041 vascular plant species in each of the 50 km × 50 km UTM cells of a grid covering Iberia and the Balearic Islands, was based on cluster analysis (unweighted pair‐group method using arithmetic averages; UPGMA) and parsimony analysis of endemicity (PAE). The Jaccard similarity index was used in the UPGMA, and the set of most parsimonious trees from the PAE were summarized in a 75% majority consensus tree. Results The UPGMA dendrogram delineated two main branches in the study region: (1) an eastern area of six sectors including the Balearic Islands plus those regions of Iberia with basic substrates, and (2) a western area with three sectors comprising the regions with acidic soils. The majority rule consensus tree of 53 most parsimonious trees from PAE showed eight main clades similarly separating eastern Iberia plus the Balearic Islands with their basic substrates, from western Iberia with its acidic and basic substrates; in addition the PAE tree showed some previously undetected chorological patterns. Main conclusions The use of large and inclusive datasets allows for the recognition of different spatial patterns from those obtained using a limited number of endemic or indicator species. The analyses support some floristic regions previously recognized for Iberia, but not the classic Eurosiberian–Mediterranean division, and some transition territories. Our recognition of 19 areas of endemism consisting of two or more cells and 60 consisting of one cell in south‐western Europe is new.

Figure 8 along with its legends were incorrectly published with errors in the original publication.This erratum corrects Figure 8 and its legend accordingly.The online version of the original article can be found under

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