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AimTo determine whether the method used to build distributional maps from raw data influences the representation of two principal macroecological patterns: the latitudinal gradient in species richness and the latitudinal variation in range sizes (Rapoport's rule).Location World-wide. MethodsAll available distribution data from the Global Biodiversity Information Facility (GBIF) for those fish species that are members of orders of fishes with only marine representatives in each order were extracted and cleaned so as to compare four different procedures: point-to-grid (GBIF maps), range maps applying an α-shape [GBIF-extent of occurrence (EOO) maps], the MaxEnt method of species distribution modelling (GBIF-MaxEnt maps) and the MaxEnt method but restricted to the area delimited by the α-shape (GBIF-MaxEnt-restricted maps). ResultsThe location of hotspots and the latitudinal gradient in species richness or range sizes are relatively similar in the four procedures. GBIF-EOO maps and most GBIF-MaxEnt-maps provide overestimations of species richness when compared with those present in a priori well-surveyed cells. GBIF-EOO maps seem to provide more reasonable world macroecological patterns. MaxEnt can erroneously predict the presence of species in environmentally similar cells of another hemisphere or in other regions that lie outside the range of the species. Limiting this overpredictive capacity, as in the case of GBIF-MaxEnt-restricted maps, seems to mimic the frequency of observations derived from a simple point-to-grid procedure, with the utility of this procedure consequently being limited. Main conclusionsIn studies of macroecological patterns at a global scale, the simple α-shape method seems to be a more parsimonious option for extrapolating species distributions from primary data than are distribution models performed indiscriminately and automatically with MaxEnt. GBIF data may be used in macroecological patterns if original data are cleaned, autocorrelation is corrected and species richness figures do not constitute obvious underestimations. Efforts therefore should focus on improving the number and quality of records that can serve as the source of primary data in macroecological studies.

Aim To examine the pattern and cumulative curve of descriptions of freshwater fishes world-wide, the geographical biases in the available information on that fauna, the relationship between species richness and geographical rarity of such fishes, as well as to assess the relative contributions of different environmental factors on these variables. Location Global.Methods MODESTR was used to summarize the geographical distribution of freshwater fish species using information available from data-based geographical records. The first-order jackknife richness estimator was used to estimate the completeness of such data in all terrestrial 1-degree cells world-wide. An a-shape procedure was used to build range maps capable of providing relatively accurate species richness and geographical rarity values for each grid cell. We also examined the explanatory capacity of a high number of environmental variables using multiple regressions and Support Vector Machine. ResultsCumulative species description curves show that a high number of species of freshwater fishes remain to be discovered. Completeness values indicate that only 199 one-degree grid cells, mainly located in eastern North America and Europe, could be considered as having relatively accurate inventories. Range maps provide species richness values that are positively and significantly related to those resulting from the first-order jackknife richness estimator. The relationship between species richness and geographical rarity is triangular, so that these species-rich cells are those with a higher proportion of distributionally rare species. Species richness is predicted by climatic and/or productivity variables but geographical rarity is not.Main conclusions In general, species-rich tropical areas harbour a higher number of narrowly distributed species although comparatively species-poor subtropical cells may also contain narrowly distributed species. Historical factors may help to explain the faunistic composition of these latter areas; a supposition also supported by the low predictive capacity of climatic and productivity variables on geographical rarity values.

Th e ModestR package consists of three applications: MapMaker, DataManager and MRFinder. MapMaker facilitates making range maps by drawing the areas, by importing existing data or using the Global Biodiversity Information Facility portal. It can discriminate between diff erent habitats, thereby making data cleaning tasks easier. DataManager allows the management of taxonomically structured databases for range maps. MRFinder supports querying ModestR databases to fi nd the species present in specifi c areas. Possible applications include the compilation and management of species distribution databases, cleaning data and computing aggregated data to perform subsequent analyses in other packages thanks to emphasized interoperability.ModestR package has been developed with the primary aim of providing the scientifi c community with an easy-to-use but powerful tool for managing species distribution data. It is designed to be simple and intuitive even for users not familiar with general-purpose Geographical Information Systems tools (GIS) that are broadly used for species distribution mapping. ModestR supports databases structured on hierarchical taxonomy. It provides features to easily clean, manage, analyse and summarise large species distribution datasets. It off ers high interoperability with the other software tools widely used for pre-post processing data related to distributions, such as spreadsheets, GIS software, and SDM software. Particular attention, however, has been paid to facilitate data exchange with R statistical environment (R Development Core Team) and subsequently with packages widely used in distribution analysis, such as SDMtools (VanDerWal et al. 2012) or dismo (Hijmans et al. 2012). Moreover, a new interface is being developed, which is specifi cally designed to link the output of ModestR with R environment. Data exchange, however, is also possible with other stand-alone applications such as SAM spatial analysis software (Rangel et al. 2010) and SDM software such as Maxent (Phillips et al. 2006). ModestR software designTh e ModestR package consists of three applications: MapMaker, DataManager and MRFinder. MapMaker allows users to easily draw range maps by means of an intuitive interface. A map made with MapMaker will be stored in a ModestR database linked to taxonomic data. Th is database can be created and managed with DataManager, which also allows maps to be processed, and information to be aggregated and exported for subsequent analysis using other packages. MRFinder allows querying a ModestR database to retrieve the species that are present in a specifi c area, and subsequently calculate and export aggregated data from those species.To be useful to the broadest range of users, it was decided to prioritise the ease of use and the innovative and useful features in ModestR, together with the data interoperability with existing tools that already provide many other capabilities that diff erent users may need. Th e following sections provide further details about each of the applications in Mo...

Abstract:We herein present FactorsR, an RWizard application which provides tools for the identification of the most likely causal factors significantly correlated with species richness, and for depicting on a map the species richness predicted by a Support Vector Machine (SVM) model. As a demonstration of FactorsR, we used an assessment using a database incorporating all species of terrestrial carnivores, a total of 249 species, distributed across 12 families. The model performed with SVM explained 91.9% of the variance observed in the species richness of terrestrial carnivores. Species richness was higher in areas with both higher vegetation index and patch index, i.e., containing higher numbers of species whose range distribution is less fragmented. Lower species richness than expected was observed in Chile, Madagascar, Sumatra, Taiwan, and Sulawesi. OPEN ACCESSDiversity 2015, 7 386