The consumption of ice-derived resources is associated with higher mercury contamination in an Arctic seabird.

Sea ice plays a fundamental role in Arctic marine environments, by driving primary productivity and sustaining ice-associated ecosystems. Simultaneously, sea ice influences the contamination of Arctic marine organisms, by modifying contaminant cycles or their bioavailability. Changes in sea ice conditions could therefore profoundly impact the functioning of Arctic marine food webs and their contamination. Top predators such as seabirds, which are subject to bioaccumulation and biomagnification of contaminants, are particularly exposed. In this context, the present study aims to investigate the influence of sea ice and of the use of ice-derived resources on the contamination of seabirds by mercury (Hg). To this end, eggs of thick-billed murres (Brünnich's guillemots, Uria lomvia; n = 60) were collected on Prince Leopold Island (Canadian High Arctic) during four years of varying ice conditions (2010-2013). Trophic tracers (i.e., Highly Branched Isoprenoids, HBIs - an indicator of the use of ice-derived resources; carbon and nitrogen stable isotopes - indicators of foraging habitats and trophic status), as well as total Hg concentrations were quantified. Results showed that feeding on ice-derived resources (as indicated by HBI concentrations) was positively correlated to sea ice cover, and both positively influenced Hg concentrations in murre eggs. However, when testing for the best predictor with model selection, sea ice concentration only drove Hg contamination in murres. This work provides new insights into the role of sea ice and ice-derived resources in the contamination by Hg of Arctic wildlife. Further research is now needed to better understand the relationship between sea ice and Hg contamination in Arctic biota and its underlying mechanisms, but also to identify Hg sources in rapidly changing environmental conditions in the Arctic.

Cytoarchitectonic Maps of the Human Metathalamus in 3D Space.

The human metathalamus plays an important role in processing visual and auditory information. Understanding its layers and subdivisions is important to gain insights in its function as a subcortical relay station and involvement in various pathologies. Yet, detailed histological references of the microanatomy in 3D space are still missing. We therefore aim at providing cytoarchitectonic maps of the medial geniculate body (MGB) and its subdivisions in the BigBrain - a high-resolution 3D-reconstructed histological model of the human brain, as well as probabilistic cytoarchitectonic maps of the MGB and lateral geniculate body (LGB). Therefore, histological sections of ten postmortem brains were studied. Three MGB subdivisions (MGBv, MGBd, MGBm) were identified on every 5th BigBrain section, and a deep-learning based tool was applied to map them on every remaining section. The maps were 3D-reconstructed to show the shape and extent of the MGB and its subdivisions with cellular precision. The LGB and MGB were additionally identified in nine other postmortem brains. Probabilistic cytoarchitectonic maps in the MNI "Colin27" and MNI ICBM152 reference spaces were computed which reveal an overall low interindividual variability in topography and extent. The probabilistic maps were included into the Julich-Brain atlas, and are freely available. They can be linked to other 3D data of human brain organization and serve as an anatomical reference for diagnostic, prognostic and therapeutic neuroimaging studies of healthy brains and patients. Furthermore, the high-resolution MGB BigBrain maps provide a basis for data integration, brain modeling and simulation to bridge the larger scale involvement of thalamocortical and local subcortical circuits.

S-Convnet: A Shallow Convolutional Neural Network Architecture for Neuromuscular Activity Recognition Using Instantaneous High-Density Surface EMG Images.

The recent progress in recognizing low-resolution instantaneous high-density surface electromyography (HD-sEMG) images opens up new avenues for the development of more fluid and natural muscle-computer interfaces. However, the existing approaches employed a very large deep convolutional neural network (ConvNet) architecture and complex training schemes for HD-sEMG image recognition, which requires learning of >5.63 million(M) training parameters only during fine-tuning and pre-trained on a very large-scale labeled HD-sEMG training dataset, as a result, it makes high-end resource-bounded and computationally expensive. To overcome this problem, we propose S-ConvNet models, a simple yet efficient framework for learning instantaneous HD-sEMG images from scratch using random-initialization. Without using any pre-trained models, our proposed S-ConvNet demonstrate very competitive recognition accuracy to the more complex state of the art, while reducing learning parameters to only ≈ 2M and using ≈ 12 × smaller dataset. The experimental results proved that the proposed S-ConvNet is highly effective for learning discriminative features for instantaneous HD-sEMG image recognition, especially in the data and high-end resource-constrained scenarios.

Linking fisheries to land use: How anthropogenic inputs from the watershed shape fish habitat quality.

Aquatic ecosystems are increasingly threatened by anthropogenic stressors, both at local and larger scales. For instance, runoff from intensively cultivated areas leads to higher nutrient and sediment concentrations deteriorating water quality, which potentially trigger trophic state changes. Unfortunately, we have a poor understanding of the complex relationships linking water quality degradation and different ecosystem components. Here we analyze the long-term cascading effects of several anthropogenic stressors on both submerged aquatic vegetation (SAV) and the key traits of an exploited yellow perch (Perca flavescens, YP) population from the watershed of Lake Saint-Pierre - the largest fluvial lake of the St. Lawrence River (Québec, Canada). Lake Saint-Pierre drains one of the most impacted watersheds in Eastern Canada and had sustained a YP fishery (worth up to 10 M$ CAN/year) until the population collapsed in the mid-1990s. SAV abundance has declined since the 1980s, partially overlapping with the YP collapse. Within a structural equation modeling framework, we tested the links between changes in both SAV abundance and the YP fishery with abiotic stressors acting at both local and larger scales. Our results show that both SAV and YP declines are causally associated with anthropogenic nutrient and sediment loadings from the watershed. The decline of YP landings is also explained by a reduction in SAV abundance and YP juvenile growth, mainly caused by a sharp decrease in water transparency over the last decades. These results suggest a causal association between environmental degradation due to nutrients and sediments and different components of the trophic aquatic network. Such an integrative approach is crucial for the development of management strategies that consider cultivated lands and aquatic systems as a continuum rather than separate compartments. SAV restoration is thus a critical feature contributing to water depuration and promoting the recovery of fish populations threatened by habitat degradation.

Arctic seabirds and shrinking sea ice: egg analyses reveal the importance of ice-derived resources.

In the Arctic, sea-ice plays a central role in the functioning of marine food webs and its rapid shrinking has large effects on the biota. It is thus crucial to assess the importance of sea-ice and ice-derived resources to Arctic marine species. Here, we used a multi-biomarker approach combining Highly Branched Isoprenoids (HBIs) with δ13C and δ15N to evaluate how much Arctic seabirds rely on sea-ice derived resources during the pre-laying period, and if changes in sea-ice extent and duration affect their investment in reproduction. Eggs of thick-billed murres (Uria lomvia) and northern fulmars (Fulmarus glacialis) were collected in the Canadian Arctic during four years of highly contrasting ice conditions, and analysed for HBIs, isotopic (carbon and nitrogen) and energetic composition. Murres heavily relied on ice-associated prey, and sea-ice was beneficial for this species which produced larger and more energy-dense eggs during icier years. In contrast, fulmars did not exhibit any clear association with sympagic communities and were not impacted by changes in sea ice. Murres, like other species more constrained in their response to sea-ice variations, therefore appear more sensitive to changes and may become the losers of future climate shifts in the Arctic, unlike more resilient species such as fulmars.

Global distribution of dissolved organic matter along the aquatic continuum: Across rivers, lakes and oceans.

Based on an extensive literature survey containing more than 12,000 paired measurements of dissolved organic carbon (DOC) concentrations and absorption of chromophoric dissolved organic matter (CDOM) distributed over four continents and seven oceans, we described the global distribution and transformation of dissolved organic matter (DOM) along the aquatic continuum across rivers and lakes to oceans. A strong log-linear relationship (R2=0.92) between DOC concentration and CDOM absorption at 350nm was observed at a global scale, but was found to be ecosystem-dependent at local and regional scales. Our results reveal that as DOM is transported towards the oceans, the robustness of the observed relation decreases rapidly (R2 from 0.94 to 0.44) indicating a gradual decoupling between DOC and CDOM. This likely reflects the decreased connectivity between the landscape and DOM along the aquatic continuum. To support this hypothesis, we used the DOC-specific UV absorbance (SUVA) to characterize the reactivity of the DOM pool which decreased from 4.9 to 1.7m2 × gC-1 along the aquatic continuum. Across the continuum, a piecewise linear regression showed that the observed decrease of SUVA occurred more rapidly in freshwater ecosystems compared to marine water ecosystems, suggesting that the different degradation processes act preferentially on CDOM rather than carbon content. The observed change in the DOM characteristics along the aquatic continuum also suggests that the terrestrial DOM pool is gradually becoming less reactive, which has profound consequences on cycling of organic carbon in aquatic ecosystems.

Testing the influence of environmental heterogeneity on fish species richness in two biogeographic provinces.

Environmental homogenization in coastal ecosystems impacted by human activities may be an important factor explaining the observed decline in fish species richness. We used fish community data (>200 species) from extensive surveys conducted in two biogeographic provinces (extent >1,000 km) in North America to quantify the relationship between fish species richness and local (grain <10 km(2)) environmental heterogeneity. Our analyses are based on samples collected at nearly 800 stations over a period of five years. We demonstrate that fish species richness in coastal ecosystems is associated locally with the spatial heterogeneity of environmental variables but not with their magnitude. The observed effect of heterogeneity on species richness was substantially greater than that generated by simulations from a random placement model of community assembly, indicating that the observed relationship is unlikely to arise from veil or sampling effects. Our results suggest that restoring or actively protecting areas of high habitat heterogeneity may be of great importance for slowing current trends of decreasing biodiversity in coastal ecosystems.

Googling trends in conservation biology.

Web-crawling approaches, that is, automated programs data mining the internet to obtain information about a particular process, have recently been proposed for monitoring early signs of ecosystem degradation or for establishing crop calendars. However, lack of a clear conceptual and methodological framework has prevented the development of such approaches within the field of conservation biology. Our objective was to illustrate how Google Trends, a freely accessible web-crawling engine, can be used to track changes in timing of biological processes, spatial distribution of invasive species, and level of public awareness about key conservation issues. Google Trends returns the number of internet searches that were made for a keyword in a given region of the world over a defined period. Using data retrieved online for 13 countries, we exemplify how Google Trends can be used to study the timing of biological processes, such as the seasonal recurrence of pollen release or mosquito outbreaks across a latitudinal gradient. We mapped the spatial extent of results from Google Trends for 5 invasive species in the United States and found geographic patterns in invasions that are consistent with their coarse-grained distribution at state levels. From 2004 through 2012, Google Trends showed that the level of public interest and awareness about conservation issues related to ecosystem services, biodiversity, and climate change increased, decreased, and followed both trends, respectively. Finally, to further the development of research approaches at the interface of conservation biology, collective knowledge, and environmental management, we developed an algorithm that allows the rapid retrieval of Google Trends data.

Colorful niches of phytoplankton shaped by the spatial connectivity in a large river ecosystem: a riverscape perspective.

Large rivers represent a significant component of inland waters and are considered sentinels and integrators of terrestrial and atmospheric processes. They represent hotspots for the transport and processing of organic and inorganic material from the surrounding landscape, which ultimately impacts the bio-optical properties and food webs of the rivers. In large rivers, hydraulic connectivity operates as a major forcing variable to structure the functioning of the riverscape, and--despite increasing interest in large-river studies--riverscape structural properties, such as the underwater spectral regime, and their impact on autotrophic ecological processes remain poorly studied. Here we used the St. Lawrence River to identify the mechanisms structuring the underwater spectral environment and their consequences on pico- and nanophytoplankton communities, which are good biological tracers of environmental changes. Our results, obtained from a 450 km sampling transect, demonstrate that tributaries exert a profound impact on the receiving river's photosynthetic potential. This occurs mainly through injection of chromophoric dissolved organic matter (CDOM) and non-algal material (tripton). CDOM and tripton in the water column selectively absorbed wavelengths in a gradient from blue to red, and the resulting underwater light climate was in turn a strong driver of the phytoplankton community structure (prokaryote/eukaryote relative and absolute abundances) at scales of many kilometers from the tributary confluence. Our results conclusively demonstrate the proximal impact of watershed properties on underwater spectral composition in a highly dynamic river environment characterized by unique structuring properties such as high directional connectivity, numerous sources and forms of carbon, and a rapidly varying hydrodynamic regime. We surmise that the underwater spectral composition represents a key integrating and structural property of large, heterogeneous river ecosystems and a promising tool to study autotrophic functional properties. It confirms the usefulness of using the riverscape approach to study large-river ecosystems and initiate comparison along latitudinal gradients.

Spatial connectivity in a large river system: resolving the sources and fate of dissolved organic matter.

Large rivers are generally heterogeneous and productive systems that receive important inputs of dissolved organic matter (DOM) from terrestrial and in situ sources. Thus, they are likely to play a significant role in the biogeochemical cycling of the DOM flowing to the oceans. The asymmetric spatial gradient driven by directional flow and environmental heterogeneity contributes to the fate of DOM flowing downstream. Yet, the relative effects of spatial connectivity and environmental heterogeneity on DOM dynamics are poorly understood. For example, since environmental variables show spatial heterogeneity, the variation explained by environmental and spatial variables may be redundant. We used the St. Lawrence River (SLR) as a representative large river to resolve the unique influences of environmental heterogeneity and spatial connectivity on DOM dynamics. We used three-dimensional fluorescence matrices combined with parallel factor analysis (PARAFAC) to characterize the DOM pool in the SLR. Seven fluorophores were modeled, of which two were identified to be of terrestrial origin and three from algal exudates. We measured a set of environmental variables that are known to drive the fate of DOM in aquatic systems. Additionally, we used asymmetric eigenvector map (AEM) modeling to take spatial connectivity into account. The combination of spatial and environmental models explained 85% of the DOM variation. We show that spatial connectivity is an important driver of DOM dynamics, as a large fraction of environmental heterogeneity was attributable to the asymmetric spatial gradient. Along the longitudinal axis, we noted a rapid increase in dissolved organic carbon (DOC), mostly controlled by terrestrial input of DOM originating from the tributaries. Variance partitioning demonstrated that freshly produced protein-like DOM was found to be the preferential substrate for heterotrophic bacteria undergoing rapid proliferation, while humic-like DOM was more correlated to the diffuse attenuation coefficient of UVA radiation.

Layered surface fluid simulation for surgical training.

We present a novel approach to fluid simulation over complex dynamic geometry designed for the specific context of virtual surgery simulation. The method combines a surface-based fluid simulation model with a multi-layer depth peeling representation to allow realistic yet efficient simulation of bleeding on complex surfaces undergoing geometry and topology modifications. Our implementation allows for fast fluid propagation and accumulation over the entire scene, and runs on the GPU at a constant low cost that is independent of the amount of blood in the scene. The proposed bleeding simulation is integrated in a complete simulator for brain tumor resection, where trainees have to manage blood aspiration and tissue/vessel cauterization while they perform virtual surgery tasks.

Visualizing and analyzing the Mona Lisa.

Size and scale issues present a complexity problem in visualizing detailed 3D models built from sensor data. A model of Leonardo da Vinci's Mona Lisa, with its thin pictorial layer, illustrates the need for intuitive real-time processing tools that are seamlessly integrated with a multiresolution visualization environment.

Using VR to improve the performance of low-earth orbit space robot operations.

The operations of current robotics systems in low-earth orbit could benefit from the use of virtual reality (VR) systems to improve their performance. This paper presents an example of the type of contribution such a system could provide to assist the space robot operators in their operations, by using the increased situational awareness and the ease of use associated with VR systems.