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.

Interspecific synchrony is related to body-length similarity in a fish community under prolonged drought conditions.

Interspecific synchrony and trait-based differences between species are likely to be related to each other. Therefore, we investigated interspecific synchrony patterns in a fish community under prolonged drought conditions, using a trait-based approach. We hypothesized that trait-similarity would predict interspecific synchrony among fish populations. We also expected that a general synchronous pattern for the whole community would be high during a severe drought context, indicating low stability. The study was conducted in a semi-arid reservoir between 2010 and 2017, which encompassed a five-year period of severe drought. We considered species differences in body length, gonadosomatic index, relative condition factor, and trophic level and found that interspecific synchrony was negatively related to species differences in body length. This result can be related to species requirements in terms of habitats and food resources. We also found a significant level of community-wide synchrony, with important implications for community stability during periods of prolonged drought. In conclusion, our results indicated a strong effect of environmental filtering in fish population dynamics over time. We highlight the importance of a trait-based approach to shed light on understanding ecological processes driving population dynamics.

Lakes in the era of global change: moving beyond single-lake thinking in maintaining biodiversity and ecosystem services.

The Anthropocene presents formidable threats to freshwater ecosystems. Lakes are especially vulnerable and important at the same time. They cover only a small area worldwide but harbour high levels of biodiversity and contribute disproportionately to ecosystem services. Lakes differ with respect to their general type (e.g. land-locked, drainage, floodplain and large lakes) and position in the landscape (e.g. highland versus lowland lakes), which contribute to the dynamics of these systems. Lakes should be generally viewed as 'meta-systems', whereby biodiversity is strongly affected by species dispersal, and ecosystem dynamics are contributed by the flow of matter and substances among locations in a broader waterscape context. Lake connectivity in the waterscape and position in the landscape determine the degree to which a lake is prone to invasion by non-native species and accumulation of harmful substances. Highly connected lakes low in the landscape accumulate nutrients and pollutants originating from ecosystems higher in the landscape. The monitoring and restoration of lake biodiversity and ecosystem services should consider the fact that a high degree of dynamism is present at local, regional and global scales. However, local and regional monitoring may be plagued by the unpredictability of ecological phenomena, hindering adaptive management of lakes. Although monitoring data are increasingly becoming available to study responses of lakes to global change, we still lack suitable integration of models for entire waterscapes. Research across disciplinary boundaries is needed to address the challenges that lakes face in the Anthropocene because they may play an increasingly important role in harbouring unique aquatic biota as well as providing ecosystem goods and services in the future.

Can information from citizen science data be used to predict biodiversity in stormwater ponds?

Citizen science data (CSD) have the potential to be a powerful scientific approach to assess, monitor and predict biodiversity. Here, we ask whether CSD could be used to predict biodiversity of recently constructed man-made habitats. Biodiversity data on adult dragonfly abundance from all kinds of aquatic habitats collected by citizen scientists (volunteers) were retrieved from the Swedish Species Observation System and were compared with dragonfly abundance in man-made stormwater ponds. The abundance data of dragonflies in the stormwater ponds were collected with a scientific, standardized design. Our results showed that the citizen science datasets differed significantly from datasets collected scientifically in stormwater ponds. Hence, we could not predict biodiversity in stormwater ponds from the data collected by citizen scientists. Using CSD from past versus recent years or from small versus large areas surrounding the stormwater ponds did not change the outcome of our tests. However, we found that biodiversity patterns obtained with CSD were similar to those from stormwater ponds when we restricted our analyses to rare species. We also found a higher beta diversity for the CSD compared to the stormwater dataset. Our results suggest that if CSD are to be used for estimating or predicting biodiversity, we need to develop methods that take into account or correct for the under-reporting of common species in CSD.

Meta-analyzing the likely cross-species responses to climate change.

Ecological Niche Models (ENMs) have different performances in predicting potential geographic distributions. Here we meta-analyzed the likely effects of climate change on the potential geographic distribution of 1,205 bird species from the Neotropical region, modeled using eight ENMs and three Atmosphere-Ocean General Circulation Models (AOGCM). We considered the variability in ENMs performance to estimate a weighted mean difference between potential geographic distributions for baseline and future climates. On average, potential future ranges were projected to be from 25.7% to 44.5% smaller than current potential ranges across species. However, we found that 0.2% to 18.3% of the total variance in range shifts occurred "within species" (i.e., owing to the use of different modeling techniques and climate models) and 81.7% to 99.8% remained between species (i.e., it could be explained by ecological correlates). Using meta-analytical techniques akin to regression, we also showed that potential range shifts are barely predicted by bird biological traits. We demonstrated that one can combine and reduce species-specific effects with high uncertainty in ENMs and also explore potential causes of climate change effect on species using meta-analytical tools. We also highlight that the search for powerful correlates of climate change-induced range shifts can be a promising line of investigation.

Effects of land use and spatial processes in water and surface sediment of tropical reservoirs at local and regional scales.

The effects of land use and connectivity on the characteristics of aquatic ecosystems are thought to be scale-dependent. This study aimed to evaluate the relationships between land use and reservoir characteristics at two spatial scales, after controlling for spatial processes. Water and surface sediment samples were collected from 31 sites (7 reservoirs) in the Paiva Castro and Piracicaba River basins (Cantareira System, São Paulo State, Brazil), during austral summer and winter. The dataset included 15 water quality variables and 6 surface sediment variables. Land use variables (natural areas, pasture, agriculture and urban areas) were obtained at two spatial scales (buffer and watershed) in each reservoir. Spatial variables were calculated using Moran's Eigenvectors Maps and Asymmetric Eigenvector Maps. The strengths of the relationships between land use and sediment variables were stronger than those between land use and water quality variables. The strengths of some of the relationships were scale-dependent. Finally, spatial processes, mostly hydrological connectivity, play an important role in water-sediment quality and should be considered in landscape management programs.

Macroevolutionary dynamics in environmental space and the latitudinal diversity gradient in New World birds.

Correlations between species richness and climate suggest non-random occupation of environmental space and niche evolution through time. However, the evolutionary mechanisms involved remain unresolved. Here, we partition the occupation of environmental space into intra- and inter-clade components to differentiate a model based on pure conservation of ancestral niches with higher diversification rates in the tropics, and an adaptive radiation model based on shifts in adaptive peaks at the family level allowing occupation of temperate regions. We examined these mechanisms using within- and among-family skewness components based on centroids of 3560 New World bird species across four environmental variables. We found that the accumulation of species in the tropics is a result of both processes. The components of adaptive radiation have family level skewness of species' distributions strongly structured in space, but not phylogenetically, according to the integrated analyses of spatial filters and phylogenetic eigenvectors. Moreover, stronger radiation components were found for energy variables, which are often used to argue for direct climatic effects on diversity. Thus, the correspondence between diversity and climate may be due to the conservation of ancestral tropical niches coupled with repeated broad shifts in adaptive peaks during birds' evolutionary history more than by higher diversification rates driven by more energy in the tropics.

A global evaluation of metabolic theory as an explanation for terrestrial species richness gradients.

We compiled 46 broadscale data sets of species richness for a wide range of terrestrial plant, invertebrate, and ectothermic vertebrate groups in all parts of the world to test the ability of metabolic theory to account for observed diversity gradients. The theory makes two related predictions: (1) In-transformed richness is linearly associated with a linear, inverse transformation of annual temperature, and (2) the slope of the relationship is near -0.65. Of the 46 data sets, 14 had no significant relationship; of the remaining 32, nine were linear, meeting prediction 1. Model I (ordinary least squares, OLS) and model II (reduced major axis, RMA) regressions then tested the linear slopes against prediction 2. In the 23 data sets having nonlinear relationships between richness and temperature, split-line regression divided the data into linear components, and regressions were done on each component to test prediction 2 for subsets of the data. Of the 46 data sets analyzed in their entirety using OLS regression, one was consistent with metabolic theory (meeting both predictions), and one was possibly consistent. Using RMA regression, no data sets were consistent. Of 67 analyses of prediction 2 using OLS regression on all linear data sets and subsets, two were consistent with the prediction, and four were possibly consistent. Using RMA regression, one was consistent (albeit weakly), and four were possibly consistent. We also found that the relationship between richness and temperature is both taxonomically and geographically conditional, and there is no evidence for a universal response of diversity to temperature. Meta-analyses confirmed significant heterogeneity in slopes among data sets, and the combined slopes across studies were significantly lower than the range of slopes predicted by metabolic theory based on both OLS and RMA regressions. We conclude that metabolic theory, as currently formulated, is a poor predictor of observed diversity gradients in most terrestrial systems.

Main predictors of periphyton species richness depend on adherence strategy and cell size.

Periphytic algae are important components of aquatic ecosystems. However, the factors driving periphyton species richness variation remain largely unexplored. Here, we used data from a subtropical floodplain (Upper Paraná River floodplain, Brazil) to quantify the influence of environmental variables (total suspended matter, temperature, conductivity, nutrient concentrations, hydrology, phytoplankton biomass, phytoplankton species richness, aquatic macrophyte species richness and zooplankton density) on overall periphytic algal species richness and on the richness of different algal groups defined by morphological traits (cell size and adherence strategy). We expected that the coefficients of determination of the models estimated for different trait-based groups would be higher than the model coefficient of determination of the entire algal community. We also expected that the relative importance of explanatory variables in predicting species richness would differ among algal groups. The coefficient of determination for the model used to predict overall periphytic algal species richness was higher than the ones obtained for models used to predict the species richness of the different groups. Thus, our first prediction was not supported. Species richness of aquatic macrophytes was the main predictor of periphyton species richness of the entire community and a significant predictor of the species richness of small mobile, large mobile and small-loosely attached algae. Abiotic variables, phytoplankton species richness, chlorophyll-a concentration, and hydrology were also significant predictors, depending on the group. These results suggest that habitat heterogeneity (as proxied by aquatic macrophytes richness) is important for maintaining periphyton species richness in floodplain environments. However, other factors played a role, suggesting that the analysis of species richness of different trait-based groups unveils relationships that were not detectable when the entire community was analysed together.

Predicting temporal variation in zooplankton beta diversity is challenging.

Beta diversity, the spatial variation in species composition, has been related to different explanatory variables, including environmental heterogeneity, productivity and connectivity. Using a long-term time series of zooplankton data collected over 62 months in a tropical reservoir (Ribeirão das Lajes Reservoir, Rio de Janeiro State, Brazil), we tested whether beta diversity (as measured across six sites distributed along the main axis of the reservoir) was correlated with environmental heterogeneity (spatial environmental variation in a given month), chlorophyll-a concentration (a surrogate for productivity) and water level. We did not found evidence for the role of these predictors, suggesting the need to reevaluate predictions or at least to search for better surrogates of the processes that hypothetically control beta diversity variation. However, beta diversity declined over time, which is consistent with the process of biotic homogenization, a worldwide cause of concern.