Large-scale Degradation of the Tocantins-Araguaia River Basin.

The Tocantins-Araguaia Basin is one of the largest river systems in South America, located entirely within Brazilian territory. In the last decades, capital-concentrating activities such as agribusiness, mining, and hydropower promoted extensive changes in land cover, hydrology, and environmental conditions. These changes are jeopardizing the basin's biodiversity and ecosystem services. Threats are escalating as poor environmental policies continue to be formulated, such as environmentally unsustainable hydropower plants, large-scale agriculture for commodity production, and aquaculture with non-native fish. If the current model persists, it will deepen the environmental crisis in the basin, compromising broad conservation goals and social development in the long term. Better policies will require thought and planning to minimize growing threats and ensure the basin's sustainability for future generations.

Effects of connectivity and watercourse distance on temporal coherence patterns in a tropical reservoir.

Temporal coherence exists when environmental variables measured at different spatial locations vary synchronously over time. This is an important property to be analyzed because levels of coherence may indicate the role of regional and local processes in determining population and ecosystem dynamics. Also, studies on temporal coherence may guide the optimal allocation of sampling effort. We analyzed a dataset from a monitoring program undertaken at a tropical reservoir (Peixe Angical Reservoir, State of Tocantins, Brazil) to test three predictions. First, coherence should be a common pattern in the reservoir considering that sampling sites were distributed in a single water body and over a small spatial extent. Second, coherence was expected to decline with increasing watercourse distance and to increase with hydrological connectivity. Third, abiotic variables should exhibit higher coherence than biological variables. Twenty limnological variables were monitored at 14 sites and for 31 months. We found significant levels of coherence for all variables, supporting our first prediction. Watercourse distances, hydrological connectivity, or both were significant predictors of coherence for 17 environmental variables. In all these cases, the signs of the coefficients were in the direction predicted. Interestingly, for some environmental variables (color, turbidity, alkalinity, and total phosphorus), hydrological connectivity was even more important in predicting coherence than watercourse distance. The view that abiotic variables should exhibit higher coherence than biological variables was supported. Our analyses revealed that precipitation was an important factor inducing coherence of a key set of environmental variables, highlighting the role of regional processes in ecosystem dynamics.

Common and Rare Taxa of Planktonic Ciliates: Influence of Flood Events and Biogeographic Patterns in Neotropical Floodplains.

After much discussion about the cosmopolitan nature of microbes, the great issue nowadays is to identify at which spatial extent microorganisms may display biogeographic patterns and if temporal variation is important in altering those patterns. Here, planktonic ciliates were sampled from shallow lakes of four Neotropical floodplains, distributed over a spatial extent of ca. 3000 km, during high and low water periods, along with several abiotic and biotic variables potentially affecting the ciliate community. We found that common ciliate species were more associated with environmental gradients and rare species were more related to spatial variables; however, this pattern seemed to change depending on the temporal and spatial scales considered. Environmental gradients were more important in the high waters for both common and rare species. In low waters, common species continued to be mainly driven by environmental conditions, but rare species were more associated with the spatial component, suggesting dispersal limitation likely due to differences in dispersal ability and ecological tolerance of species. We also found that common and rare species were related to different environmental variables, suggesting different ecological niches. At the largest spatial extents, rare species showed clear biogeographic patterns.

The role of microorganisms in a planktonic food web of a floodplain lake.

Food webs include complex ecological interactions that define the flow of matter and energy, and are fundamental in understanding the functioning of an ecosystem. Temporal variations in the densities of communities belonging to the planktonic food web (i.e., microbial: bacteria, flagellate, and ciliate; and grazing: zooplankton and phytoplankton) were investigated, aiming to clarify the interactions between these organisms and the dynamics of the planktonic food web in a floodplain lake. We hypothesized that hydrological pulse determines the path of matter and energy flow through the planktonic food web of this floodplain lake. Data were collected monthly from March 2007 to February 2008 at three different sites in Guaraná Lake (Mato Grosso do Sul State, Brazil). The path analysis provided evidence that the dynamics of the planktonic food web was strongly influenced by the hydrological pulse. The high-water period favored interactions among the organisms of the microbial loop, rather than their relationships with zooplankton and phytoplankton. Therefore, in this period, the strong interaction among the organisms of the grazing food chain suggests that the microbial loop functions as a sink of matter and energy. In turn, in the low-water period, higher primary productivity appeared to favor different interactions between the components of the grazing food chain and microorganisms, which would function as a link to the higher trophic levels.

The best of both worlds: Phylogenetic eigenvector regression and mapping.

Eigenfunction analyses have been widely used to model patterns of autocorrelation in time, space and phylogeny. In a phylogenetic context, Diniz-Filho et al. (1998) proposed what they called Phylogenetic Eigenvector Regression (PVR), in which pairwise phylogenetic distances among species are submitted to a Principal Coordinate Analysis, and eigenvectors are then used as explanatory variables in regression, correlation or ANOVAs. More recently, a new approach called Phylogenetic Eigenvector Mapping (PEM) was proposed, with the main advantage of explicitly incorporating a model-based warping in phylogenetic distance in which an Ornstein-Uhlenbeck (O-U) process is fitted to data before eigenvector extraction. Here we compared PVR and PEM in respect to estimated phylogenetic signal, correlated evolution under alternative evolutionary models and phylogenetic imputation, using simulated data. Despite similarity between the two approaches, PEM has a slightly higher prediction ability and is more general than the original PVR. Even so, in a conceptual sense, PEM may provide a technique in the best of both worlds, combining the flexibility of data-driven and empirical eigenfunction analyses and the sounding insights provided by evolutionary models well known in comparative analyses.

Nutrient enrichment is related to two facets of beta diversity for stream invertebrates across the United States.

Beta diversity, the spatial or temporal variability of species composition, is a key concept in community ecology. However, our ability to predict the relative importance of the main drivers of beta diversity (e.g., environmental heterogeneity, dispersal limitation, and environmental productivity) remains limited. Using a comprehensive data set on stream invertebrate assemblages across the continental United States, we found a hump-shaped relationship between beta diversity and within-ecoregion nutrient concentrations. Within-ecoregion compositional dissimilarity matrices were mainly related to environmental distances in most of the 30 ecoregions analyzed, suggesting a stronger role for species-sorting than for spatial processes. The strength of these relationships varied considerably among ecoregions, but they were unrelated to within-ecoregion environmental heterogeneity or spatial extent. Instead, we detected a negative correlation between the strength of species sorting and nutrient concentrations. We suggest that eutrophication is a major mechanism disassembling invertebrate assemblages in streams at a continental scale.

A new eigenfunction spatial analysis describing population genetic structure.

Several methods of spatial analyses have been proposed to infer the relative importance of evolutionary processes on genetic population structure. Here we show how a new eigenfunction spatial analysis can be used to model spatial patterns in genetic data. Considering a sample of n local populations, the method starts by modeling the response variable (allele frequencies or phenotypic variation) against the eigenvectors sequentially extracted from a geographic distance matrix (n × n). The relationship between the coefficient of determination (R(2)) of the models and the cumulative eigenvalues, which we named the spatial signal-representation (SSR) curve, can be more efficient than Moran's I correlograms in describing different patterns. The SSR curve was also applied to simulated data (under distinct scenarios of population differentiation) and to analyze spatial patterns in alleles from microsatellite data for 25 local populations of Dipteryx alata, a tree species endemic to the Brazilian Cerrado. The SSR curves are consistent with previous phylogeographical patterns of the species, revealing combined effects of isolation-by-distance and range expansion. Our analyses demonstrate that the SSR curve is a useful exploratory tool for describing spatial patterns of genetic variability and for selecting spatial eigenvectors for models aiming to explain spatial responses to environmental variables and landscape features.

Mantel test in population genetics.

The comparison of genetic divergence or genetic distances, estimated by pairwise FST and related statistics, with geographical distances by Mantel test is one of the most popular approaches to evaluate spatial processes driving population structure. There have been, however, recent criticisms and discussions on the statistical performance of the Mantel test. Simultaneously, alternative frameworks for data analyses are being proposed. Here, we review the Mantel test and its variations, including Mantel correlograms and partial correlations and regressions. For illustrative purposes, we studied spatial genetic divergence among 25 populations of Dipteryx alata ("Baru"), a tree species endemic to the Cerrado, the Brazilian savannas, based on 8 microsatellite loci. We also applied alternative methods to analyze spatial patterns in this dataset, especially a multivariate generalization of Spatial Eigenfunction Analysis based on redundancy analysis. The different approaches resulted in similar estimates of the magnitude of spatial structure in the genetic data. Furthermore, the results were expected based on previous knowledge of the ecological and evolutionary processes underlying genetic variation in this species. Our review shows that a careful application and interpretation of Mantel tests, especially Mantel correlograms, can overcome some potential statistical problems and provide a simple and useful tool for multivariate analysis of spatial patterns of genetic divergence.

Dung removal increases under higher dung beetle functional diversity regardless of grazing intensification.

Dung removal by macrofauna such as dung beetles is an important process for nutrient cycling in pasturelands. Intensification of farming practices generally reduces species and functional diversity of terrestrial invertebrates, which may negatively affect ecosystem services. Here, we investigate the effects of cattle-grazing intensification on dung removal by dung beetles in field experiments replicated in 38 pastures around the world. Within each study site, we measured dung removal in pastures managed with low- and high-intensity regimes to assess between-regime differences in dung beetle diversity and dung removal, whilst also considering climate and regional variations. The impacts of intensification were heterogeneous, either diminishing or increasing dung beetle species richness, functional diversity, and dung removal rates. The effects of beetle diversity on dung removal were more variable across sites than within sites. Dung removal increased with species richness across sites, while functional diversity consistently enhanced dung removal within sites, independently of cattle grazing intensity or climate. Our findings indicate that, despite intensified cattle stocking rates, ecosystem services related to decomposition and nutrient cycling can be maintained when a functionally diverse dung beetle community inhabits the human-modified landscape.

Ice age climate, evolutionary constraints and diversity patterns of European dung beetles.

Current climate and Pleistocene climatic changes are both known to be associated with geographical patterns of diversity. We assess their associations with the European Scarabaeinae dung beetles, a group with high dispersal ability and well-known adaptations to warm environments. By assessing spatial stationarity in climate variability since the last glacial maximum (LGM), we find that current scarab richness is related to the location of their limits of thermal tolerance during the LGM. These limits mark a strong change in their current species richness-environment relationships. Furthermore, northern scarab assemblages are nested and composed of a phylogenetically clustered subset of large-range sized generalist species, whereas southern ones are diverse and variable in composition. Our results show that species responses to current climate are limited by the evolution of assemblages that occupied relatively climatically stable areas during the Pleistocene, and by post-glacial dispersal in those that were strongly affected by glaciations.