João Carlos Nabout

A coupled phylogeographical and species distribution modelling approach recovers the demographical history of a Neotropical seasonally dry forest tree species

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.

A review of techniques for spatial modeling in geographical, conservation and landscape genetics

Most evolutionary processes occur in a spatial context and several spatial analysis techniques have been employed in an exploratory context. However, the existence of autocorrelation can also perturb significance tests when data is analyzed using standard correlation and regression techniques on modeling genetic data as a function of explanatory variables. In this case, more complex models incorporating the effects of autocorrelation must be used. Here we review those models and compared their relative performances in a simple simulation, in which spatial patterns in allele frequencies were generated by a balance between random variation within populations and spatially-structured gene flow. Notwithstanding the somewhat idiosyncratic behavior of the techniques evaluated, it is clear that spatial autocorrelation affects Type I errors and that standard linear regression does not provide minimum variance estimators. Due to its flexibility, we stress that principal coordinate of neighbor matrices (PCNM) and related eigenvector mapping techniques seem to be the best approaches to spatial regression. In general, we hope that our review of commonly used spatial regression techniques in biology and ecology may aid population geneticists towards providing better explanations for population structures dealing with more complex regression problems throughout geographic space.

Ensemble forecasting shifts in climatically suitable areas for Tropidacris cristata (Orthoptera: Acridoidea: Romaleidae)

Abstract.  1. The effects of climate change on species’ ranges have been usually inferred using niche‐based models creating bioclimatic envelopes that are projected into geographical space. Here, we apply an ensemble forecasting approach for niche models in the Neotropical grasshopper Tropidacris cristata (Acridoidea: Romaleidae). A novel protocol was used to partition and map the variation in modelled ranges due to niche models, Atmosphere‐Ocean Global Circulation Models (AOGCM), and emission scenarios.

Weak evidence for determinants of citation frequency in ecological articles

Citation frequency has been considered a biased surrogate of publication merit. However, previous studies on this subject were based on small sample sizes and were entirely based on null-hypothesis significance testing. Here we evaluated the relative effects of different predictors on citation frequency of ecological articles using an information theory framework designed to evaluate multiple competing hypotheses. Supposed predictors of citation frequency (e.g., number of authors, length of articles) accounted for a low fraction of the total variation. We argue that biases concerning citation are minor in ecology and further studies that attempt to quantify the scientific relevance of an article, aiming to make further relationships with citation, are needed to advance our understanding of why an article is cited.

A straightforward conceptual approach for evaluating spatial conservation priorities under climate change

Despite wide evidence of a quickly changing world, systematic conservation planning analyses are usually static assuming that the biodiversity being preserved in sites do not change through time. Here we generated a comprehensive ensemble forecasting experiment for 444 amphibian species inhabiting the Atlantic Forest Biodiversity Hotspot. Models were based on four methods for modeling ecological niches, and three future climate simulations. Combinations of these models were used to estimate species occurrences. We used species occurrences to optimize the current and future representation of amphibians with different conservation targets based on their geographic range size. We compared spatial priority outcomes (variance of site selection frequency scores) under dynamic conditions, using a bi-dimensional plot in which the relative importance of each site in achieving conservation targets was assessed both for current time and to 2050. Projections for 2050 show that species richness pattern will remain approximately constant, whereas high turnover rates are forecasted. Selection frequency of several locations varied widely, with recurrent sites located at the north and southeast of the biome. As for 2050, spatial priorities concentrate in the northern part of the biome. Thirty-three sites have high priority for conservation as they play an important role now and will still stand as priority locations in 2050. We present a conceptual model for dynamic spatial conservation prioritization that helps to identify priority sites under climate change. We also call attention to sites in which risk of investment is high, and to those that may become interesting options in the future.

How many species of Cyanobacteria are there? Using a discovery curve to predict the species number

Although the number of biodiversity studies is increasing, the total number of species in different taxonomic groups remains uncertain. Estimates of the number of described species of Cyanobacteria range from 2,000 to 8,000. However, no studies have used discovery curves to estimate this number. The aim of this study was to understand the status of cyanobacterial biodiversity on a global scale and to estimate the number of still-unknown species, using a discovery curve. The species and year of descriptions of Cyanobacteria were obtained from the CyanoDB database. The cumulative number of species per year was adjusted using three asymptotic models (Logistic, Gompertz, and Extreme Value). These nonlinear models were compared through the Akaike information criterion. There are currently 2,698 described species of Cyanobacteria, and the best model (Gompertz) estimated that this group must contain 6,280 species. These three models proved to be quite idiosyncratic (Extreme value: 3,166 species and Logistic: 3,769 species), and therefore the choice of model is fundamental in studies using a discovery curve. Many Cyanobacteria species remain to be described, demonstrating the importance of increasing investment in research on the biodiversity of Cyanobacteria, in particular in understudied geographic regions.

Phytoplankton diversity (alpha, beta, and gamma) from the Araguaia River tropical floodplain lakes (central Brazil)

Alpha, beta and gamma are three components of species diversity. Knowing these attributes in floodplain lake phytoplankton communities is vital when selecting conservation areas. Species diversity is commonly used with other taxonomic groups, but rarely with phytoplankton. We compared the number of phytoplankton species (alpha diversity) from 21 Middle Araguaia River floodplain lakes in the 2000 and 2001 rainy and dry seasons. From these samples we estimated complete survey species richness (gamma diversity), quantified differences in species composition between lakes (beta diversity) and assessed the influence of abiotic variables on beta diversity. We recorded a total of 577 taxa. The Sjack1 estimator indicated that 62.31% of taxa were sampled in the 2000 rainy and 67.65% dry seasons, and 68.36% in the 2001 rainy and 73.5% dry seasons. In almost all seasons, alpha diversity negatively correlated with latitude. Beta diversity (β-1) was higher in high water periods, especially in 2000. This may have been caused by isolated heavy rainfall, which would have increased environmental heterogeneity and raised beta diversity. DCA showed differences in phytoplankton composition between rainy and dry seasons in 2000 and 2001, reflecting the influence of flood pulses on phytoplankton composition. The Mantel test indicated spatial distribution patterns where geographically more distant lakes had less-similar phytoplankton communities.

Planning for optimal conservation of geographical genetic variability within species

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.

Niche modelling and landscape genetics of Caryocar brasiliense ("Pequi" tree: Caryocaraceae) in Brazilian Cerrado: an integrative approach for evaluating central-peripheral population patterns.

Complex and integrative approaches may be necessary to understand the abundant-centre model and the patterns in genetic diversity that may be explained by this model. Here we developed an integrated framework to study spatial patterns in genetic diversity within local populations, coupling genetic data, niche modelling and landscape genetics, and applied this framework to evaluate population structure of Caryocar brasiliense, an endemic tree from the Brazilian Cerrado. We showed different geographical patterns for genetic diversity, allelic richness and inbreeding levels, estimated using microsatellite data for ten local populations. Ecological suitability was estimating by combining five niche modelling techniques. Genetic diversity tend to follow a central-periphery model and is associated with ecological variables. On the other hand, inbreeding levels may be alternatively explained by isolation processes and habitat fragmentation more related to intense recent human occupation in the southern border of the biome, or by deeper historical patterns in the origin of the populations. Although still suffering from some of the problems of central-periphery analysis (small number of local populations), our analyses show how these patterns can be better investigated and offering a better understanding of the processes structuring genetic diversity within species’ geographic ranges.

Trends in the scientific literature on phytoplankton

The use of scientometric techniques can assist in evaluating the importance of a subject, author or article, and also emphasize the trends and contributions of a discipline, scientist or research group, institution or country regarding world-wide scientific and technological advances. We applied scientometric analysis to papers in the Thomson ISI database, in order to understand temporal trends in phytoplankton research. From the years 1991 through 2005, the number of articles on this topic increased. We found 19,681 articles containing the word “phytoplankton” in the title, keyword and/or abstract. Principal components analysis (PCA) was used to summarize changes in the focus of papers published from 1991 to 2005. The keywords gradually changed, in the earliest years indicating descriptive study, whereas in recent years (2000 and after), the keywords became more diversified and related to aspects of technology, genetics, evolution and public health.