Biomphalaria snails are instrumental in transmission of the human blood fluke Schistosoma mansoni. With the World Health Organization's goal to eliminate schistosomiasis as a global health problem by 2025, there is now renewed emphasis on snail control. Here, we characterize the genome of Biomphalaria glabrata, a lophotrochozoan protostome, and provide timely and important information on snail biology. We describe aspects of phero-perception, stress responses, immune function and regulation of gene expression that support the persistence of B. glabrata in the field and may define this species as a suitable snail host for S. mansoni. We identify several potential targets for developing novel control measures aimed at reducing snail-mediated transmission of schistosomiasis.

Aim Species distribution modelling (SDM) has increasingly been used to predict palaeodistributions at regional and global scales in order to understand the response of vegetation to climate change and to estimate palaeodistributions for the testing of biogeographical hypotheses. However, there are many sources of uncertainty in SDM that may restrict the ability of models to hindcast palaeodistributions and provide a basis for hypothesis testing in molecular phylogenetics and phylogeographical studies.Location Seasonally dry forests (SDFs) in South America. MethodsWe addressed the problem of using palaeodistribution modelling for SDFs based on the projection of their current distribution into past environments (21 ka) using 11 methods for SDMs and five coupled atmosphere-ocean global circulation models (AOGCMs) for 16 species. ResultsWe observed considerable uncertainty in the hindcasts, with the most important effects for AOGCM (median 12.2%), species (median 15.6%) and their interaction (median 13.6%). The effects of AOGCMs were stronger in the Amazon region, whereas the species effect occurred primarily in the dry areas of central Brazil. The log-linear model detected significant effects of the three sources of variation and their interaction on the classification of each map in supporting alternative hypotheses. An expansion scenario combining the Pleistocene arc and Amazonian expansion, and Pennington's Amazonian expansion alone, were the most frequently supported palaeodistribution scenarios.Main conclusions As a basis for evaluating a given hypothesis, hindcast distributions must be used in direct association with other evidence, such as molecular variation and the fossil record. We propose an alternative framework concerning hypothesis testing that couples SDM and phylogeographical work, in which palaeoclimatic distributions and other sources of information, such as the pollen fossil record and coalescence modelling, must be weighted equally.

We investigated here the demographical history of Tabebuia impetiginosa (Bignoniaceae) to understand the dynamics of the disjunct geographical distribution of South American seasonally dry forests (SDFs), based on coupling an ensemble approach encompassing hindcasting species distribution modelling and statistical phylogeographical analysis. We sampled 17 populations (280 individuals) in central Brazil and analysed the polymorphisms at chloroplast (trnS-trnG, psbA-trnH, and ycf6-trnC intergenic spacers) and nuclear (ITS nrDNA) genomes. Phylogenetic analyses based on median-joining network showed no haplotype sharing among population but strong evidence of incomplete lineage sorting. Coalescent analyses showed historical constant populations size, negligible gene flow among populations, and an ancient time to most recent common ancestor dated from ~4.7 ± 1.1 Myr BP. Most divergences dated from the Lower Pleistocene, and no signal of important population size reduction was found in coalescent tree and tests of demographical expansion. Demographical scenarios were built based on past geographical range dynamic models, using two a priori biogeographical hypotheses ('Pleistocene Arc' and 'Amazonian SDF expansion') and on two additional hypotheses suggested by the palaeodistribution modelling built with several algorithms for distribution modelling and palaeoclimatic data. The simulation of these demographical scenarios showed that the pattern of diversity found so far for T. impetiginosa is in consonance with a palaeodistribution expansion during the last glacial maximum (LGM, 21 kyr BP), strongly suggesting that the current disjunct distribution of T. impetiginosa in SDFs may represent a climatic relict of a once more wide distribution.

Abstract.-Studies in biogeography and macroecology have been increasing massively since climate and biodiversity databases became easily accessible. Climate simulations for past, present, and future have enabled macroecologists and biogeographers to combine data on species' occurrences with detailed information on climatic conditions through time to predict biological responses across large spatial and temporal scales. Here we present and describe ecoClimate, a free and open data repository developed to serve useful climate data to macroecologists and biogeographers. ecoClimate arose from the need for climate layers with which to build ecological niche models and test macroecological and biogeographic hypotheses in the past, present, and future. ecoClimate offers a suite of processed, multi-temporal climate data sets from the most recent multi-model ensembles developed by the Coupled Modeling Intercomparison Projects (CMIP5) and Paleoclimate Modeling Intercomparison Projects (PMIP3) across past, present, and future time frames, at global extents and 0.5° spatial resolution, in convenient formats for analysis and manipulation. A priority of ecoClimate is consistency across these diverse data, but retaining information on uncertainties among model predictions. The ecoClimate research group intends to maintain the web repository updated continuously as new model outputs become available, as well as software that makes our workflows broadly accessible.

Systematic Conservation Planning (SCP) involves a series of steps that should be accomplished to determine the most cost-effective way to invest in conservation action. Although SCP has been usually applied at the species level (or hierarchically higher), it is possible to use alleles from molecular analyses at the population level as basic units for analyses. Here we demonstrate how SCP procedures can be used to establish optimum strategies for in situ and ex situ conservation of a single species, using Dipteryx alata (a Fabaceae tree species widely distributed and endemics to Brazilian Cerrado) as a case study. Data for the analyses consisted in 52 alleles from eight microsatellite loci coded for a total of 644 individual trees sampled in 25 local populations throughout species' geographic range. We found optimal solutions in which seven local populations are the smallest set of local populations of D. alata that should be conserved to represent the known genetic diversity. Combining these several solutions allowed estimating the relative importance of the local populations for conserving all known alleles, taking into account the current land-use patterns in the region. A germplasm collection for this species already exists, so we also used SCP approach to identify the smallest number of populations that should be further collected in the field to complement the existing collection, showing that only four local populations should be sampled for optimizing the species ex situ representation. The initial application of the SCP methods to genetic data showed here can be a useful starting point for methodological and conceptual improvements and may be a first important step towards a comprehensive and balanced quantitative definition of conservation goals, shedding light to new possibilities for in situ and ex situ designs within species.

Most species data display spatial autocorrelation that can affect ecological niche models (ENMs) accuracy-statistics, affecting its ability to infer geographic distributions. Here we evaluate whether the spatial autocorrelation underlying species data affects accuracy-statistics and map the uncertainties due to spatial autocorrelation effects on species range predictions under past and future climate models. As an example, ENMs were fitted to Qualea grandiflora (Vochysiaceae), a widely distributed plant from Brazilian Cerrado. We corrected for spatial autocorrelation in ENMs by selecting sampling sites equidistant in geographical (GEO) and environmental (ENV) spaces. Distributions were modelled using 13 ENMs evaluated by two accuracy-statistics (TSS and AUC), which were compared with uncorrected ENMs. Null models and the similarity statistics I were used to evaluate the effects of spatial autocorrelation. Moreover, we applied a hierarchical ANOVA to partition and map the uncertainties from the time (across last glacial maximum, pre-insustrial, and 2080 time periods) and methodological components (ENMs and autocorrelation corrections). The GEO and ENV models had the highest accuracy-statistics values, although only the ENV model had values higher than expected by chance alone for most of the 13 ENMs. Uncertainties from time component were higher in the core region of the Brazilian Cerrado where Q. grandiflora occurs, whereas methodological components presented higher uncertainties in the extreme northern and southern regions of South America (i.e. outside of Brazilian Cerrado). Our findings show that accounting for autocorrelation in environmental space is more efficient than doing so in geographical space. Methodological uncertainties were concentrated in outside the core region of Q. grandiflora's habitat. Conversely, uncertainty due to time component in the Brazilian Cerrado reveals that ENMs were able to capture climate change effects on Q. grandiflora distributions.

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Here we studied the demographical history of Caryocar brasiliense (Caryocaraceae), by coupling ecological niche modeling (ENM) and statistical phylogeography. Analyses were based on the polymorphism of 147 individuals sampled in 12 populations for the chloroplast genome. C. brasiliense presented low genetic diversity but high population genetic differentiation, which is not correlated with geographical distances among localities. The most ancient lineage divergence from southern and western Cerrado boundaries occurred around ~3.3 ± 2.3 Myr BP. The simulation of demographic scenarios showed that the diversity pattern found so far for C. brasiliense is most likely due to a range retraction during the last glacial maximum (LGM, 21 kyr BP), leading to multiple refugia. The paleodistribution models and coalescent analyses strongly suggest that the current distribution of C. brasiliense is wider than during the dry periods of the Quaternary.