ALBERT

Description: We present a simple chemical definition to demark the edge of the mesospheric polar vortices. Because this vortex definition does not rely on the wind field it is useful in the mesosphere where wind observations are sparse and reanalysis winds are unreliable. The chemical definition is also insensitive to double jets that complicate vortex identification in the mesosphere. The algorithm is based on horizontal gradients of carbon monoxide (CO) and mirrors the widely used vortex edge definition in the stratosphere based on potential vorticity (PV) gradients. Here, the approach is used to identify the Arctic vortex in the mesosphere during a 10-year (2004–2014) record of Microwave Limb Sounder data. Vortex size and shape comparisons are made where the CO and PV methods overlap in the upper stratosphere. A case study is presented during the NH 2008–2009 winter that demonstrates the fidelity of the CO gradient method on individual days and emphasizes the impact of double jets on methods to identify the polar vortex. We recommend transitioning from a PV or stream function-based vortex definition in the stratosphere to using a CO gradient definition above 0.1 hPa (~60 km). The CO gradient method identifies a coherent region of high CO at 80 km that is confined to mid-to-high latitudes 99.8% of the time during Arctic winter. Taking advantage of the CO gradient method to identify the polar vortex adds ~20 km of reliable vortex information (from 60–80 km) in a region of the atmosphere where reanalyses are most suspect.

Description: Genome-wide association studies have implicated PLEXIN D1 (PLXND1) in body fat distribution and type 2 diabetes. However, a role for PLXND1 in regional adiposity and insulin resistance is unknown. Here we use in vivo imaging and genetic analysis in zebrafish to show that Plxnd1 regulates body fat distribution and insulin...

Description: Predicting the effects of aquaculture development for coastal ecosystems remains challenging, particularly for data-limited systems, and tools that account for complex ecological interactions are needed to support ecosystem approaches to aquaculture. Here, we used qualitative network models (QNMs) to examine the potential community effects of increasing bivalve aquaculture in South Puget Sound, a large estuarine system in Washington, United States. QNMs are formalized conceptual models that require only a qualitative understanding of how variables composing a system interact (that is, the sign of interactions: +, –, and 0) and are therefore well-suited to data-limited systems. Specifically, we examined community-wide responses to scenarios in which bivalve cultivation effort increased for three different bivalve species (Manila clam Venerupis philippinarum , Pacific oyster Crassostrea gigas , and geoduck Panopea generosa ). Further, we evaluated community-wide responses to the removal of benthic bivalve predators, a future increase in nutrient loadings, and combinations of these scenarios acting simultaneously. The scenarios enabled identification of potential trade-offs between increased aquaculture and shifts in the abundance of community members and assessment of the possible effects of different management actions. We also analysed the QNM to identify key interactions that influence the sign outcome of community responses to press perturbations, highlighting potential points for management intervention and linkages deserving of more focused quantitative study. QNMs are mathematically robust and highly flexible, but remain underutilized. We suggest that they may serve as valuable tools for supporting ecosystem approaches to aquaculture.

Description: Motivation: Expression quantitative trait loci (eQTL) studies have discovered thousands of genetic variants that regulate gene expression, enabling a better understanding of the functional role of non-coding sequences. However, eQTL studies are costly, requiring large sample sizes and genome-wide genotyping of each sample. In contrast, analysis of allele-specific expression (ASE) is becoming a popular approach to detect the effect of genetic variation on gene expression, even within a single individual. This is typically achieved by counting the number of RNA-seq reads matching each allele at heterozygous sites and testing the null hypothesis of a 1:1 allelic ratio. In principle, when genotype information is not readily available, it could be inferred from the RNA-seq reads directly. However, there are currently no existing methods that jointly infer genotypes and conduct ASE inference, while considering uncertainty in the genotype calls. Results: We present QuASAR, quantitative allele-specific analysis of reads, a novel statistical learning method for jointly detecting heterozygous genotypes and inferring ASE. The proposed ASE inference step takes into consideration the uncertainty in the genotype calls, while including parameters that model base-call errors in sequencing and allelic over-dispersion. We validated our method with experimental data for which high-quality genotypes are available. Results for an additional dataset with multiple replicates at different sequencing depths demonstrate that QuASAR is a powerful tool for ASE analysis when genotypes are not available. Availability and implementation: http://github.com/piquelab/QuASAR . Contact: fluca@wayne.edu or rpique@wayne.edu Supplementary information: Supplementary Material is available at Bioinformatics online.

Description: Expansion of the shellfish aquaculture industry has the potential to affect the structure and dynamics of coastal estuarine foodwebs. To better understand foodweb trade-offs, we incorporated both trophic and non-trophic interactions (e.g. habitat facilitation and predator refuge) into a foodweb model of central Puget Sound to predict the effects of an increase in geoduck ( Panopea generosa ) aquaculture. At a basin scale, the foodweb can support at least 120% increased geoduck aquaculture, above current production levels (landings of 10 546 kg in 2012), with only minor changes in individual species' biomass and/or metrics of ecosystem resilience. The non-trophic effects of increased geoduck aquaculture, related to the influence of anti-predator structure, had a stronger influence on the foodweb than the trophic role of cultured geoducks as filter-feeders and prey to other species. Increased geoduck culture caused substantial increases in biomass densities of surfperch, nearshore demersal fish, and small crabs, and decreases in seabirds, flatfish, and certain invertebrates (e.g. predatory gastropods and small crustaceans). This study identifies species that should be a priority for additional empirical research and monitoring related to bivalve aquaculture interactions, including demersal fish, small crustaceans, and seabirds. It also provides insights into the benefits and challenges of incorporating habitat-related data into a foodweb model. Understanding these relationships can inform management decisions by clarifying trade-offs in ecosystem functions and services in Puget Sound and facilitates estimation of direct and cumulative effects of bivalve aquaculture at a foodweb scale.

Description: Coastal upwelling regimes are some of the most productive ecosystems in the ocean but are also among the most vulnerable to ocean acidification (OA) due to naturally high background concentrations of CO 2 . Yet our ability to predict how these ecosystems will respond to additional CO 2 resulting from anthropogenic emissions is poor. To help address this uncertainty, researchers perform manipulative experiments where biological responses are evaluated across different CO 2 partial pressure ( p CO 2 ) levels. In upwelling systems, however, contemporary carbonate chemistry variability remains only partly characterized and patterns of co-variation with other biologically important variables such as temperature and oxygen are just beginning to be explored in the context of OA experimental design. If co-variation among variables is prevalent, researchers risk performing OA experiments with control conditions that are not experienced by the focal species, potentially diminishing the ecological relevance of the experiment. Here, we synthesized a large carbonate chemistry dataset that consists of carbonate chemistry, temperature, and oxygen measurements from multiple moorings and ship-based sampling campaigns from the California Current Ecosystem (CCE), and includes fjord and tidal estuaries and open coastal waters. We evaluated patterns of p CO 2 variability and highlight important co-variation between p CO 2 , temperature, and oxygen. We subsequently compared environmental p CO 2 –temperature measurements with conditions maintained in OA experiments that used organisms from the CCE. By drawing such comparisons, researchers can gain insight into the ecological relevance of previously published OA experiments, but also identify species or life history stages that may already be influenced by contemporary carbonate chemistry conditions. We illustrate the implications co-variation among environmental variables can have for the interpretation of OA experimental results and suggest an approach for designing experiments with p CO 2 levels that better reflect OA hypotheses while simultaneously recognizing natural co-variation with other biologically relevant variables.

Description: Author(s): S. P. Harvey, C. G. L. Bøttcher, L. A. Orona, S. D. Bartlett, A. C. Doherty, and A. Yacoby Fast, high-fidelity single and two-qubit gates are essential to building a viable quantum information processor, but achieving both in the same system has proved challenging for spin qubits. We propose and analyze an approach to perform a long-distance two-qubit controlled phase (CPHASE) gate betwee... [Phys. Rev. B 97, 235409] Published Thu Jun 07, 2018