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Understanding how species are structured in space and time and how they are functionally related to environmental conditions is still a challenge in ecology. In this study, we assessed the predictive power of lake morphometry, physical and chemical conditions of the water, and zooplankton density in relation to phytoplankton taxonomic and functional diversity in Amazonian floodplain lakes during low- and high-water periods. We also examined to what extent taxonomic and functional indexes were coupled. Taxonomic diversity was evaluated by species richness and Shannon index, and functional diversity by functional richness (FRic) and community-weighted mean trait value (CWM). The relative importance of predictive factors was evaluated by model selection, multi-model inference and correlations. We found that phytoplankton taxonomic and functional diversity indexes were mostly related to the same factors within the low- and high-water periods. Total phosphorus was the main driving factor in the low water, while euphotic zone depth and zooplankton density were the main driving factors in the high water. Taxonomic and functional diversity indexes were weakly coupled in the low water, but strongly coupled in the high water. Our results highlight that phytoplankton taxonomic and functional diversity can differ between periods, but respond similarly to environmental driving factors.

Accelerated eutrophication reduces water quality and shifts plankton communities. However, its effects on the aquatic food web and ecosystem functions remain poorly understood. Within this context, functional ecology can provide valuable links relating community traits to ecosystem functioning. In this study, we assessed the effects of eutrophication and cyanobacteria blooms on zooplankton functional diversity in a tropical hypereutrophic lake. Phytoplankton and zooplankton communities and limnological characteristics of a tropical Brazilian Lake (Southeast, Brazil) were monitored monthly from April 2013 to October 2014. Lake eutrophication indicators were total phosphorus, total chlorophyll-a, and chlorophyll-a per group (blue, green, and brown). The variation of major phytoplankton taxonomic group biomass was calculated and used as a proxy for changes in phytoplankton composition. Zooplankton functional diversity was assessed through functional dispersion and the community-weighted mean trait value. Regressions were performed between the lake eutrophication indicators, the phytoplankton biomass variation, and zooplankton functional dispersion. Our results suggest that eutrophication and cyanobacterial dominance change the composition of zooplankton traits and reduce functional dispersion, leading to zooplankton niche overlap. These findings are important because they provide a meaningful view of phytoplankton-zooplankton trophic interactions and contribute to an improved understanding their functional effects on aquatic ecosystems.

Freshwater sediments are important sites of organic carbon (OC) burial and mineralization. Previous studies indicate that warming can increase rates of OC mineralization, implying more CO₂ release from sediments and, consequently, less OC burial, but temperatures typical of tropical ecosystems are poorly represented in the models of temperature and OC mineralization. We measured OC mineralization rates in 61 Brazilian tropical systems, including rivers, streams, lakes, coastal lagoons, and reservoirs from different regions (Pantanal, Amazonia, Atlantic Forest, and coastal areas). Oxygen consumption and dissolved inorganic carbon production in sediment core incubations were used for estimating OC mineralization rates. Multiple regression models were used to investigate the importance of temperature and other variables to predict OC mineralization. The average OC mineralization rate for all systems was 1223 ± 950 mg C m−2 d−1. Rates increased significantly with increasing temperature and varied across system types and regions. In addition, salinity, total nitrogen, and chlorophyll a were important factors controlling OC mineralization in tropical sediments. The pattern of increasing mineralization with temperature was remarkably consistent with theoretical and empirical expectations. The explanatory power of previous temperature vs. mineralization models is confirmed and enhanced by the addition of the tropical data that substantially extended the temperature range.

Artificial reservoirs likely accumulate more carbon than natural lakes due to their unusually high sedimentation rates. Nevertheless, the actual magnitude of carbon accumulating in reservoirs is poorly known due to a lack of whole-system studies of carbon burial. We determined the organic carbon (OC) burial rate and the total OC stock in the sediments of a tropical hydroelectric reservoir by combining a seismic survey with sediment core sampling. Our data suggest that no sediment accumulation occurs along the margins of the reservoir and that irregular bottom morphology leads to irregular sediment deposition. Such heterogeneous sedimentation resulted in high spatial variation in OC burial—from 0 to 209 g C m⁻² y⁻¹. Based on a regression between sediment accumulation and OC burial rates (R ² = 0.94), and on the mean reservoir sediment accumulation rate (0.51 cm y⁻¹, from the seismic survey), the whole-reservoir OC burial rate was estimated at 42.2 g C m⁻² y⁻¹. This rate was equivalent to 70% of the reported carbon emissions from the reservoir surface to the atmosphere and corresponded to a total sediment OC accumulation of 0.62 Tg C since the reservoir was created. The approach we propose here allows an inexpensive and integrative assessment of OC burial in reservoirs by taking into account the high degree of spatial variability and based on a single assessment. Because burial can be assessed shortly after the survey, the approach combining a seismic survey and coring could, if applied on a larger scale, contribute to a more complete estimate of carbon stocks in freshwater systems in a relatively short period of time.

Single nucleotide polymorphisms (SNPs) located in transcript sequences showing allele-specific expression (ASE SNPs) were previously identified in the Longissimus thoracis muscle of a Nelore ( Bos indicus ) population consisting of 190 steers. Given that the allele-specific expression pattern may result from cis -regulatory SNPs, called allele-specific expression quantitative trait loci (aseQTLs), in this study, we searched for aseQTLs in a window of 1 Mb upstream and downstream from each ASE SNP. After this initial analysis, aiming to investigate variants with a potential regulatory role, we further screened our aseQTL data for sequence similarity with transcription factor binding sites and microRNA (miRNA) binding sites. These aseQTLs were overlapped with methylation data from reduced representation bisulfite sequencing (RRBS) obtained from 12 animals of the same population. We identified 1134 aseQTLs associated with 126 different ASE SNPs. For 215 aseQTLs, one allele potentially affected the affinity of a muscle-expressed transcription factor to its binding site. 162 aseQTLs were predicted to affect 149 miRNA binding sites, from which 114 miRNAs were expressed in muscle. Also, 16 aseQTLs were methylated in our population. Integration of aseQTL with GWAS data revealed enrichment for traits such as meat tenderness, ribeye area, and intramuscular fat . To our knowledge, this is the first report of aseQTLs identification in bovine muscle. Our findings indicate that various cis -regulatory and epigenetic mechanisms can affect multiple variants to modulate the allelic expression. Some of the potential regulatory variants described here were associated with the expression pattern of genes related to interesting phenotypes for livestock. Thus, these variants might be useful for the comprehension of the genetic control of these phenotypes.

The spiking of neuronal populations in motor cortex provides accurate information about movement parameters. Here we show that hand movement target and velocity can be inferred from multiple local field potentials (LFPs) in single trials approximately as efficiently as from multiple single-unit activity (SUA) recorded from the same electrodes. Our results indicate that LFPs can be used as an additional signal for decoding brain activity, particularly for new neuroprosthetic applications.

Differences between the expression of the two alleles of a gene are known as allele-specific expression (ASE), a common event in the transcriptome of mammals. Despite ASE being a source of phenotypic variation, its occurrence and effects on genetic prediction of economically relevant traits are still unexplored in bovines. Furthermore, as ASE events are likely driven by cis-regulatory mutations, scanning them throughout the bovine genome represents a significant step to elucidate the mechanisms underlying gene expression regulation. To address this question in a Bos indicus population, we built the ASE profile of the skeletal muscle tissue of 190 Nelore steers, using RNA sequencing data and SNPs genotypes from the Illumina BovineHD BeadChip (770 K bp). After quality control, 820 SNPs showed at least one sample with ASE. These SNPs were widespread among all autosomal chromosomes, being 32.01% found in 3′UTR and 31.41% in coding regions. We observed a considerable variation of ASE profile among individuals, which highlighted the need for biological replicates in ASE studies. Functional analysis revealed that ASE genes play critical biological functions in the development and maintenance of muscle tissue. Additionally, some of these genes were previously reported as associated with beef production and quality traits in livestock, thus indicating a possible source of bias on genomic predictions for these traits.

Wood density is a critical control on tree biomass, so poor understanding of its spatial variation can lead to large and systematic errors in forest biomass estimates and carbon maps. The need to understand how and why wood density varies is especially critical in tropical America where forests have exceptional species diversity and spatial turnover in composition. As tree identity and forest composition are challenging to estimate remotely, ground surveys are essential to know the wood density of trees, whether measured directly or inferred from their identity. Here, we assemble an extensive dataset of variation in wood density across the most forested and tree-diverse continent, examine how it relates to spatial and environmental variables, and use these relationships to predict spatial variation in wood density over tropical and sub-tropical South America. Our analysis refines previously identified eastwest Amazon gradients in wood density, improves them by revealing fine-scale variation, and extends predictions into Andean, dry, and Atlantic forests. The results halve biomass prediction errors compared to a naïve scenario with no knowledge of spatial variation in wood density. Our findings will help improve remote sensing-based estimates of aboveground biomass carbon stocks across tropical South America.Understanding spatial and temporal variation in forest biomass carbon stocks is critical for numerous applications and research questions, including national carbon stock inventories [e.g. ref. 1], assessments of forest responses and recovery from disturbance 2-4 , and investigation of climate feedbacks [e.g. ref. 5]. However, quantifying the distribution of aboveground live carbon stocks across the tropical forest biome remains challenging. Despite decades of fieldwork 6 and investment in satellite and airborne remote sensing to measure canopy structure with Lidar or vegetation volume through radar scattering 1,7 , there is still considerable uncertainty about the amount and distribution of aboveground carbon in tropical forests. Indeed, marked differences among recent global maps of biomass carbon 8-10 reflect the challenge of large-scale calibration and validation across tropical forests.The challenge partly arises because remote-sensing approaches, which allow large-scale and spatially continuous measurements, cannot provide all the information available from ground-based surveys. Wood density is a fundamental determinant of tree biomass 11-13 , and estimating it requires skilled botanical surveys to identify trees.Airborne and satellite remote-sensing methods provide measurements that allow estimates of tree height or volume, but not their identity or wood density 14 . While some inferences about taxonomic composition can be made from hyperspectral imagery [e.g. refs. 15, 16], this remains limited compared to what can be obtained by a ground-based botanical survey. Lack of wood density information can lead to marked discrepancies between remote sensed and ground-based estimates of aboveground biomass 17 , including spatial biases in aboveground biomass estimates of around 30% even within a single country 18 .Future improvements in remote-sensing-based forest biomass maps therefore require improved knowledge of spatial variation in tree wood density. The need to tackle this huge challenge is especially important in South America. Not only are tropical rain forests here the most extensive in the world, but they also include many of the most productive and carbon-rich forests on Earth 19,20 and large carbon sinks and fluxes [e.g. 21-23 ]. The nature of the challenge is also most profound in South America, as ~40% of Earth's 73,000 tree species are found in forests here 24 . Amazonia alone is home to at least 15,000 25 , and beyond

Hydroelectric reservoirs bury significant amounts of organic carbon (OC) in their sediments. Many reservoirs are characterized by high sedimentation rates, low oxygen concentrations in bottom water and a high share of terrestrially derived OC, and all of these factors have been linked to a high efficiency of OC burial. However, investigations of OC burial efficiency (OCBE, i.e., the ratio between buried and deposited OC) in reservoirs are limited to a few studies, none of which include spatially resolved analyses. In this study we determined the spatial variation in OCBE in a large subtropical reservoir and related it to sediment characteristics. Our results show that the sediment accumulation rate explains up to 92 % of the spatial variability in OCBE, outweighing the effect of other variables, such as OC source and oxygen exposure time. OCBE at the pelagic sites varied from 48 to 86 % (mean 67 %) and decreased towards the dam. At the margins, OCBE was lower (9–17 %) due to the low sediment accumulation in shallow areas. Our data show that the variability in OCBE both along the rivers–dam and the margin–pelagic axes must be considered in whole-reservoir assessments. Combining these results with a spatially resolved assessment of sediment accumulation and OC burial in the studied reservoir, we estimated a spatially resolved mean OC burial efficiency of 57 %. Being the first assessment of OCBE with such a high spatial resolution in a reservoir, these results suggest that reservoirs may bury OC more efficiently than natural lakes.