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...

Morphological and DNA sequence data has been used to propose hypotheses of relationships within the Characiformes with minimal comparative discussion of causes underpinning the major intraordinal diversification patterns. We explore potential primary morphological factors controlling the early diversification process in some Neotropical characiforms as the first step to identifying factors contributing to the pronounced intraordinal morphological and species diversity. A phylogenetic reconstruction based on 16S rDNA (mitochondrial) and 18S rDNA (nuclear) genes provided the framework for the identification of the main morphological differences among the Acestrorhynchidae, Anostomidae, Characidae, Ctenoluciidae, Curimatidae, Cynodontidae, Gasteropelecidae, Prochilodontidae and Serrasalmidae. Results indicate an initial split into two major groupings: (i) species with long dorsal-fin bases relative to the size of other fins (Curimatidae, Prochilodontidae, Anostomidae, Serrasalmidae) which primarily inhabit lakes, swamps, and rivers (lineage I); and (ii) species with short dorsal-fin bases (Acestrorhynchidae, Gasteropelecidae, Characidae) which primarily inhabit creeks and streams (lineage II). The second diversification stage in lineage I involved substantial morphological diversification associated with trophic niche differences among the monophyletic families which range from detritivores to large item predators. Nonmonophyly of the Characidae complicated within lineage II analyzes but yielded groupings based on differences in pectoral and anal fin sizes correlated with life style differences.

Summary1. Data quality is one of the highest priorities for species distribution data warehouses, as well as one of the main concerns of data users. There is the need, however, for computational procedures with the facility to automatically or semi-automatically identify and correct errors and to seamlessly integrate expert knowledge and automated processes. 2. New version MODESTR 2.0 (http://www.ipez.es/ModestR) makes it easy to download occurrence records from the Global Biodiversity Information Facility (GBIF), to import shape files with species range maps such as those available at the website of the International Union for Conservation of Nature (IUCN), to import KML files, to import CSV files with records of the users, to import ESRI ASCII grid probability files generated by distribution modelling software and show the resulting records on a map. 3. MODESTR supports five different methods for cleaning the data: (i) data filtering when downloading records from GBIF, (ii) habitat data filtering, (iii) taxonomic disambiguation filtering, (iv) automatic spatial dispersion and environmental layer filters and (v) custom data filtering.