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Binocular rivalry is a phenomenon in which perception spontaneously shifts between two different images that are dichoptically presented to the viewer. By elucidating the cortical networks responsible for these stochastic fluctuations in perception, we can potentially learn much about the neural correlates of visual awareness. We obtained concurrent EEG-fMRI data for a group of 20 healthy human subjects during the continuous presentation of dichoptic visual stimuli. The two eyes’ images were tagged with different temporal frequencies so that eye specific steady-state visual evoked potential (SSVEP) signals could be extracted from the EEG data for direct comparison with changes in fMRI BOLD activity associated with binocular rivalry. We additionally included a smooth replay condition that emulated the perceptual transitions experienced during binocular rivalry as a control stimulus. We evaluated a novel SSVEP-informed fMRI analysis in this study in order to delineate the temporal dynamics of rivalry-related BOLD activity from both an electrophysiological and behavioral perspective. In this manner, we assessed BOLD activity during rivalry that was directly correlated with peaks and crosses of the two rivaling, frequency-tagged SSVEP signals, for comparison with BOLD activity associated with subject reported perceptual transitions. Our findings point to a critical role of a right lateralized fronto-parietal network in the processing of bistable stimuli, given that BOLD activity in the right superior/inferior parietal lobules was significantly elevated throughout binocular rivalry and in particular during perceptual transitions, compared with the replay condition. Based on the SSVEP-informed analysis, rivalry was further associated with significantly enhanced BOLD suppression in the posterior mid-cingulate cortex during perceptual transitions, compared with SSVEP crosses. Overall, this work points to a careful interplay between early visual areas, the right posterior parietal cortex and the mid-cingulate cortex in mediating the spontaneous perceptual changes associated with binocular rivalry and has significant implications for future multimodal imaging studies of perception and awareness.
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Montane environments around the globe are biodiversity ‘hotspots’ and important reservoirs of genetic diversity. Montane species are also typically more vulnerable to environmental change than their low-elevation counterparts due to restricted ranges and dispersal limitations. Here we focus on two abundant congeneric mayflies (Baetis bicaudatus and B. tricaudatus) from montane streams over an elevation gradient spanning 1400 m. Using single-nucleotide polymorphism genotypes, we measured population diversity and vulnerability in these two species by: (i) describing genetic diversity and population structure across elevation gradients to identify mechanisms underlying diversification; (ii) performing spatially explicit landscape analyses to identify environmental drivers of differentiation; and (iii) identifying outlier loci hypothesized to underlie adaptive divergence. Differences in the extent of population structure in these species were evident depending upon their position along the elevation gradient. Heterozygosity, effective population sizes and gene flow all declined with increasing elevation, resulting in substantial population structure in the higher elevation species (B. bicaudatus). At lower elevations, populations of both species are more genetically similar, indicating ongoing gene flow. Isolation by distance was detected at lower elevations only, whereas landscape barriers better predicted genetic distance at higher elevations. At higher elevations, dispersal was restricted due to landscape effects, resulting in greater population isolation. Our results demonstrate differentiation over small spatial scales along an elevation gradient, and highlight the importance of preserving genetic diversity in more isolated high-elevation populations.
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Background: The endoplasmic reticulum enzyme glucose-6-phosphatase catalyzes the common terminal reaction in the gluconeogenic/glycogenolytic pathways and plays a central role in glucose homeostasis. In most mammals, different G6PC subunits are encoded by three paralogous genes (G6PC, G6PC2, and G6PC3). Mutations in G6PC and G6PC3 are responsible for human mendelian diseases, whereas variants in G6PC2 are associated with fasting glucose (FG) levels. Results: We analyzed the evolutionary history of G6Pase genes. Results indicated that the three paralogs originated during early vertebrate evolution and that negative selection was the major force shaping diversity at these genes in mammals. Nonetheless, site-wise estimation of evolutionary rates at corresponding sites revealed weak correlations, suggesting that mammalian G6Pases have evolved different structural features over time. We also detected pervasive positive selection at mammalian G6PC2. Most selected residues localize in the C-terminal protein region, where several human variants associated with FG levels also map. This region was re-sequenced in ~560 subjects from Saudi Arabia, 185 of whom suffering from type 2 diabetes (T2D). The frequency of rare missense and nonsense variants was not significantly different in T2D and controls. Association analysis with two common missense variants (V219L and S342C) revealed a weak but significant association for both SNPs when analyses were conditioned on rs560887, previously identified in a GWAS for FG. Two haplotypes were significantly associated with T2D with an opposite effect direction. Conclusions: We detected pervasive positive selection at mammalian G6PC2 genes and we suggest that distinct haplotypes at the G6PC2 locus modulate susceptibility to T2D.
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Modeling of species distributions has undergone a shift from relying on equilibrium assumptions to recognizing transient system dynamics explicitly. This shift has necessitated more complex modeling techniques, but the performance of these dynamic models has not yet been assessed for systems where unobservable states exist. Our work is motivated by the impacts of the emerging infectious disease chytridiomycosis, a disease of amphibians that associated with declines of many species worldwide. Using this host-pathogen system as a general example, we first illustrate how misleading inferences can result from failing to incorporate pathogen dynamics into the modeling process, especially when the pathogen is difficult or impossible to survey in the absence of a host species. We found that traditional modeling techniques can underestimate the effect of a pathogen on host species occurrence and dynamics when the pathogen can only be detected in the host, and pathogen information is treated as a covariate. We propose a dynamic multistate modeling approach that is flexible enough to account for the detection structures that may be present in complex multistate systems, especially when the sampling design is limited by a species’ natural history or sampling technology. When multistate occupancy models are used and an unobservable state is present, parameter estimation can be influenced by model complexity, data sparseness, and the underlying dynamics of the system. We show that, even with large sample sizes, many models incorporating seasonal variation in vital rates may not generate reasonable estimates, indicating parameter redundancy. We found that certain types of missing data can greatly hinder inference, and we make study design recommendations to avoid these issues. Additionally, we advocate the use of time-varying covariates to explain temporal trends in the data, and the development of sampling techniques that match the biology of the system to eliminate unobservable states when possible.
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Effective predictive and management approaches for species occurring in a metapopulation structure require good understanding of inter-population connectivity. In this study we ask whether population genetic structure of marine species with fragmented distributions can be predicted by stepping-stone oceanographic transport and habitat continuity, using as model an ecosystem-structuring brown alga, Cystoseira amentacea var. stricta. To answer this question, we analyzed the genetic structure and estimated the connectivity of populations along discontinuous rocky habitat patches in southern Italy, using microsatellite markers at multiple scales. In addition, we modelled the effect of rocky habitat continuity and ocean circulation on gene flow by simulating Lagrangian particle dispersal based on ocean surface currents allowing multigenerational stepping-stone dynamics. Populations were highly differentiated, at scales from few meters up to 1000s of kilometers. The best possible model fit to explain the genetic results combined current direction, rocky habitat extension and distance along the coast among rocky sites. We conclude that a combination of variables suitable habitat and oceanographic transport is a useful predictor of genetic structure. This relationship provides insight into the mechanisms of dispersal and the role of life history traits. Our results highlight the importance of spatially explicit modeling of stepping stone dynamics and oceanographic directional transport coupled with habitat suitability, to better describe and predict marine population structure and differentiation. This study also suggests the appropriate spatial scales for the conservation, restoration and management of species that are increasingly affected by habitat modifications.
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Defining subpopulations using genetics has traditionally used data from microsatellite markers to investigate population structure; however, single-nucleotide polymorphisms (SNPs) have emerged as a tool for detection of fine-scale structure. In Hudson Bay, Canada, three polar bear (Ursus maritimus) subpopulations (Foxe Basin (FB), Southern Hudson Bay (SH), and Western Hudson Bay (WH)) have been delineated based on mark–recapture studies, radiotelemetry and satellite telemetry, return of marked animals in the subsistence harvest, and population genetics using microsatellites. We used SNPs to detect fine-scale population structure in polar bears from the Hudson Bay region and compared our results to the current designations using 414 individuals genotyped at 2,603 SNPs. Analyses based on discriminant analysis of principal components (DAPC) and STRUCTURE support the presence of four genetic clusters: (i) Western—including individuals sampled in WH, SH (excluding Akimiski Island in James Bay), and southern FB (south of Southampton Island); (ii) Northern—individuals sampled in northern FB (Baffin Island) and Davis Strait (DS) (Labrador coast); (iii) Southeast—individuals from SH (Akimiski Island in James Bay); and (iv) Northeast—individuals from DS (Baffin Island). Population structure differed from microsatellite studies and current management designations demonstrating the value of using SNPs for fine-scale population delineation in polar bears.
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Aim: We compared the power of different nuclear markers to investigate genetic structure of southern Balkan wild boar. We distinguished between historic events, such as isolation in different refugia during glacial periods, from recent demographic processes, such as naturally occurring expansions. Location: Southern Balkans/Greece. Methods: We sampled 555 wild boars from 20 different locations in southern Balkans/Greece. All individuals were analysed with 10 microsatellites and a subgroup of 91 with 49,508 single nucleotide polymorphisms (SNPs). Patterns of genetic structure and demographic processes were assessed with Bayesian clustering, linkage disequilibrium and past effective population size estimation analysis. Results: Both microsatellite and SNP data analyses detected genetic structure caused by historic events and support the existence of three groups in the studied area. A hybrid zone between two of the groups was also detected. We also showed that genome-wide SNP data analysis can identify recent events in bottlenecked populations. Main conclusions: We inferred the three groups diverged ~50,000–10,000 yr bp when populations contracted to different refugia. Our findings strengthened the evidence that the southern Balkan area was a glacial refugium including further local smaller refugia. Genome-wide genotyping inferred a recent population expansion that can mimic a ‘refugium within refugium’ scenario. It seems that microsatellite data tend to overestimate genetic structure when genetic drift happens in bottlenecked populations over a short distance. Therefore, genome-wide SNPs are more powerful at inferring phylogeography in natural populations, resolving inconsistencies from mitochondrial and microsatellite data sets.
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Sauropodomorpha represents an important group of Mesozoic megaherbivores, and includes the largest terrestrial animals ever known. It was the first dinosaur group to become abundant and widespread, and its members formed a significant component of terrestrial ecosystems from the Late Triassic until the end of the Cretaceous. Both of these factors have been explained by their adoption of herbivory, but understanding the evolution of sauropodomorph feeding has been hampered by the scarcity of biomechanical studies. To address this, the jaw adductor musculature of the basal sauropodomorph Plateosaurus and the sauropod Camarasaurus have been reconstructed. These reconstructions provide boundary conditions for finite element models to assess differences in structural performance between the two taxa. Results demonstrate that Camarasaurus was capable of much greater bite forces than Plateosaurus, due to greater relative adductor muscle mass and shape changes to the mandible. The skull and mandible of Camarasaurus are also ‘stronger’ under static biting. The Plateosaurus mandible appears to compromise structural efficiency and force transmission in order to maintain relatively high jaw closure speed. This supports suggestions of facultative omnivory in basal sauropodomorph taxa. The expanded mandibular symphysis and ‘lateral plates’ of sauropods each lead to greater overall craniomandibular robustness, and may have been especially important in accommodating forces related to asymmetric loading. The functional roles of these characters, and observed general shape changes in increasing skull robustness, are consistent with hypotheses linking bulk-herbivory with the origin of Sauropoda and the evolution of gigantism.
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Remote sensing is increasingly needed to meet the critical demand for estimates of forest structure and composition at landscape to continental scales. Hyperspectral images can detect tree canopy properties, including species identity, leaf chemistry and disease. Tree growth rates are related to these measurable canopy properties but whether growth can be directly predicted from hyperspectral data remains unknown. We used a single hyperspectral image and LiDAR-derived elevation to predict growth rates for twenty tropical tree species planted in experimental plots. We asked whether a consistent relationship between spectral data and growth rates exists across all species and which spectral regions, associated with different canopy chemical and structural properties, are important for predicting growth rates. We found that a linear combination of narrowband indices and elevation is correlated with standardized growth rates across all twenty tree species (R2=53.70%). Although wavelengths from the entire visible-to-shortwave infrared spectrum were involved in our analysis, results point to relatively greater importance of visible and near-infrared regions for relating canopy reflectance to tree growth data. Overall, we demonstrate the potential for hyperspectral data to quantify tree demography over a much larger area than possible with field-based methods in forest inventory plots.
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Modes and mechanisms of speciation are best studied in young species pairs. In older taxa, it is increasingly difficult to distinguish what happened during speciation from what happened after speciation. Lake Victoria cichlids in the genus Pundamilia encompass a complex of young species and polymorphic populations. One Pundamilia species pair, P. pundamilia and P. nyererei, is particularly well suited to study speciation because sympatric population pairs occur with different levels of phenotypic differentiation and reproductive isolation at different rocky islands within the lake. Genetic distances between allopatric island populations of the same nominal species often exceed those between the sympatric species. It thus remained unresolved whether speciation into P. nyererei and P. pundamilia occurred once, followed by geographical range expansion and interspecific gene flow in local sympatry, or if the species pair arose repeatedly by parallel speciation. Here, we use genomic data and demographic modelling to test these alternative evolutionary scenarios. We demonstrate that gene flow plays a strong role in shaping the observed patterns of genetic similarity, including both gene flow between sympatric species and gene flow between allopatric populations, as well as recent and early gene flow. The best supported model for the origin of P. pundamilia and P. nyererei population pairs at two different islands is one where speciation happened twice, whereby the second speciation event follows shortly after introgression from an allopatric P. nyererei population that arose earlier. Our findings support the hypothesis that very similar species may arise repeatedly, potentially facilitated by introgressed genetic variation.
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