Iceberg properties and distributions in three Greenlandic fjords using satellite imagery

Icebergs calved from tidewater glaciers represent about one third to one half of the freshwater flux from the Greenland ice sheet to the surrounding ocean. Using multiple satellite datasets, we quantify the first fjord-wide distributions of iceberg sizes and characteristics for three fjords with distinct hydrography and geometry: Sermilik Fjord, Rink Isbræ Fjord and Kangerlussuup Sermia Fjord. We estimate average total iceberg volumes in summer in the three fjords to be 6.4 ± 1.5, 1.7 ± 0.40 and 0.16 ± 0.09 km3, respectively. Iceberg properties are influenced by glacier calving style and grounding line depth, with variations in size distribution represented by exponents of power law distributions that are −1.95 ± 0.06, −1.87 ± 0.05 and −1.62 ± 0.04, respectively. The underwater surface area of icebergs exceeds the subsurface area of glacial termini by at least one order of magnitude in all three fjords, underscoring the need to include iceberg melt in fjord freshwater budgets. Indeed, in Sermilik Fjord, we calculate summertime freshwater flux from iceberg melt of 620 m3 s−1 (±140 m3 s−1), similar in magnitude to subglacial discharge. The method developed here can be extended across Greenland to assess relationships between glacier calving, iceberg discharge and freshwater production.NNX12AP50G55223

Data-Driven Decision Support Tool Co-Development with a Primary Health Care Practice Based Learning Network

Background: The Alliance for Healthier Communities is a learning health system that supports Community Health Centres (CHCs) across Ontario, Canada to provide team-based primary health care to people who otherwise experience barriers to care. This case study describes the ongoing process and lessons learned from the first Alliance for Healthier Communities’ Practice Based Learning Network (PBLN) data-driven decision support tool co-development project. Methods: We employ an iterative approach to problem identification and methods development for the decision support tool, moving between discussion sessions and case studies with CHC electronic health record (EHR) data. We summarize our work to date in terms of six stages: population-level descriptive-exploratory study, PBLN team engagement, decision support tool problem selection, sandbox case study 1: individual-level risk predictions, sandbox case study 2: population-level planning predictions, project recap and next steps decision. Results: The population-level study provided an initial point of engagement to consider how clients are (not) represented in EHR data and to inform problem selection and methodological decisions thereafter. We identified three meaningful types of decision support, with initial target application areas: risk prediction/screening, triaging specialized program referrals, and identifying care access needs. Based on feasibility and expected impact, we started with the goal to support earlier identification of mental health decline after diabetes diagnosis. As discussions deepened around clinical use cases associated with example prediction task set ups, the target problem evolved towards supporting the upstream task of organizational planning and advocacy for adequate mental health care service capacity to meet incoming needs. Conclusions: This case study contributes towards a tool to support diabetes and mental health care, as well as lays groundwork for future CHC decision support tool initiatives. We share lessons learned and reflections from our process that other primary health care organizations may use to inform their own co-development initiatives

Successful conservation of global waterbird populations depends on effective governance

Understanding global patterns of biodiversity change is crucial for conservation research, policies and practices. However, for most ecosystems, the lack of systematically collected data at a global level limits our understanding of biodiversity changes and their local-scale drivers. Here we address this challenge by focusing on wetlands, which are among the most biodiverse and productive of any environments and which provide essential ecosystem services, but are also amongst the most seriously threatened ecosystems. Using birds as an indicator taxon of wetland biodiversity, we model time-series abundance data for 461 waterbird species at 25,769 survey sites across the globe. We show that the strongest predictor of changes in waterbird abundance, and of conservation efforts having beneficial effects, is the effective governance of a country. In areas in which governance is on average less effective, such as western and central Asia, sub-Saharan Africa and South America, waterbird declines are particularly pronounced; a higher protected area coverage of wetland environments facilitates waterbird increases, but only in countries with more effective governance. Our findings highlight that sociopolitical instability can lead to biodiversity loss and undermine the benefit of existing conservation efforts, such as the expansion of protected area coverage. Furthermore, data deficiencies in areas with less effective governance could lead to underestimations of the extent of the current biodiversity crisis.</p

The C4 Clustering Algorithm: Clusters of Galaxies in the Sloan Digital Sky Survey

We present the "C4 Cluster Catalog", a new sample of 748 clusters of galaxies identified in the spectroscopic sample of the Second Data Release (DR2) of the Sloan Digital Sky Survey (SDSS). The C4 cluster--finding algorithm identifies clusters as overdensities in a seven-dimensional position and color space, thus minimizing projection effects which plagued previous optical clusters selection. The present C4 catalog covers ~2600 square degrees of sky with groups containing 10 members to massive clusters having over 200 cluster members with redshifts. We provide cluster properties like sky location, mean redshift, galaxy membership, summed r--band optical luminosity (L_r), velocity dispersion, and measures of substructure. We use new mock galaxy catalogs to investigate the sensitivity to the various algorithm parameters, as well as to quantify purity and completeness. These mock catalogs indicate that the C4 catalog is ~90% complete and 95% pure above M_200 = 1x10^14 solar masses and within 0.03 <=z <= 0.12. The C4 algorithm finds 98% of X-ray identified clusters and 90% of Abell clusters within 0.03 <= z <= 0.12. We show that the L_r of a cluster is a more robust estimator of the halo mass (M_200) than the line-of-sight velocity dispersion or the richness of the cluster. L_r. The final SDSS data will provide ~2500 C4 clusters and will represent one of the largest and most homogeneous samples of local clusters.Comment: 32 pages of figures and text accepted in AJ. Electronic version with additional tables, links, and figures is available at http://www.ctio.noao.edu/~chrism/c

Moving from frugivory to seed dispersal: incorporating the functional outcomes of interactions in plant-frugivore networks

1. There is growing interest in understanding the functional outcomes of species interactions in ecological networks. For many mutualistic networks, including pollination and seed dispersal networks, interactions are generally sampled by recording animal foraging visits to plants. However, these visits may not reflect actual pollination or seed dispersal events, despite these typically being the ecological processes of interest. 2. Frugivorous animals can act as seed dispersers, by swallowing entire fruits and dispersing their seeds, or as pulp peckers or seed predators, by pecking fruits to consume pieces of pulp or seeds. These processes have opposing consequences for plant reproductive success. Therefore, equating visitation with seed dispersal could lead to biased inferences about the ecology, evolution and conservation of seed dispersal mutualisms. 3. Here we use natural history information on the functional outcomes of pairwise bird-plant interactions to examine changes in the structure of seven European plant-frugivore visitation networks after non-mutualistic interactions (pulp-pecking and seed predation) have been removed. Following existing knowledge of the contrasting structures of mutualistic and antagonistic networks, we hypothesised a number of changes following interaction removal, such as increased nestedness and lower specialisation. 4. Non-mutualistic interactions with pulp peckers and seed predators occurred in all seven networks, accounting for 21–48% of all interactions and 6–24% of total interaction frequency. When non-mutualistic interactions were removed, there were significant increases in network-level metrics such as connectance and nestedness, while robustness decreased. These changes were generally small, homogenous and driven by decreases in network size. Conversely, changes in species-level metrics were more variable and sometimes large, with significant decreases in plant degree, interaction frequency, specialisation and resilience to animal extinctions, and significant increases in frugivore species strength. 5. Visitation data can overestimate the actual frequency of seed dispersal services in plant-frugivore networks. We show here that incorporating natural history information on the functions of species interactions can bring us closer to understanding the processes and functions operating in ecological communities. Our categorical approach lays the foundation for future work quantifying functional interaction outcomes along a mutualism–antagonism continuum, as documented in other frugivore faunas.B.I.S. was supported by the Natural Environment Research Council as part of the Cambridge Earth System Science NERC DTP (NE/L002507/1). J.P.G.‐V. was funded by an Individual Fellowship from the Marie Sklodowska‐Curie Actions (H2020‐MSCA‐IF‐2014‐656572: MobileLinks). D.G. was funded by a grant from the Spanish MinECo (CGL2017‐82847‐P). W.J.S. is funded by Arcadia. N.F. thanks the administration of the Białowieża National Park, the forestry administrations of Białowieża, Hajnówka and Browsk and Polish authorities (Ministry of Environment, GDOS and RDOS) for the permissions to work in Białowieża Forest. J.A. was supported by the German Federal Foundation for Environment (DBU) and by the German Academic Exchange Service in the framework of a post‐doctorate fellowship grant (DAAD, No 91568794). L.V.D. was supported by the Natural Environment Research Council (grants NE/K015419/1 and NE/N014472/1)

A Family of microRNAs Encoded by Myosin Genes Governs Myosin Expression and Muscle Performance

SummaryMyosin is the primary regulator of muscle strength and contractility. Here we show that three myosin genes, Myh6, Myh7, and Myh7b, encode related intronic microRNAs (miRNAs), which, in turn, control muscle myosin content, myofiber identity, and muscle performance. Within the adult heart, the Myh6 gene, encoding a fast myosin, coexpresses miR-208a, which regulates the expression of two slow myosins and their intronic miRNAs, Myh7/miR-208b and Myh7b/miR-499, respectively. miR-208b and miR-499 play redundant roles in the specification of muscle fiber identity by activating slow and repressing fast myofiber gene programs. The actions of these miRNAs are mediated in part by a collection of transcriptional repressors of slow myofiber genes. These findings reveal that myosin genes not only encode the major contractile proteins of muscle, but act more broadly to influence muscle function by encoding a network of intronic miRNAs that control muscle gene expression and performance

Obesity-induced insulin resistance in human skeletal muscle is characterised by defective activation of p42/p44 MAP kinase

Insulin resistance (IR), an impaired cellular, tissue and whole body response to insulin, is a major pathophysiological defect of type 2 diabetes mellitus. Although IR is closely associated with obesity, the identity of the molecular defect(s) underlying obesity-induced IR in skeletal muscle remains controversial; reduced post-receptor signalling of the insulin receptor substrate 1 (IRS1) adaptor protein and downstream effectors such as protein kinase B (PKB) have previously been implicated. We examined expression and/or activation of a number of components of the insulin-signalling cascade in skeletal muscle of 22 healthy young men (with body mass index (BMI) range, 20–37 kg/m2). Whole body insulin sensitivity (M value) and body composition was determined by the hyperinsulinaemic (40 mU. min−1.m−2.), euglycaemic clamp and by dual energy X-ray absorptiometry (DEXA) respectively. Skeletal muscle (vastus lateralis) biopsies were taken before and after one hour of hyperinsulinaemia and the muscle insulin signalling proteins examined by western blot and immunoprecipitation assay. There was a strong inverse relationship between M-value and BMI. The most striking abnormality was significantly reduced insulin-induced activation of p42/44 MAP kinase, measured by specific assay, in the volunteers with poor insulin sensitivity. However, there was no relationship between individuals' BMI or M-value and protein expression/phosphorylation of IRS1, PKB, or p42/44 MAP kinase protein, under basal or hyperinsulinaemic conditions. In the few individuals with poor insulin sensitivity but preserved p42/44 MAP kinase activation, other signalling defects were evident. These findings implicate defective p42/44 MAP kinase signalling as a potential contributor to obesity-related IR in a non-diabetic population, although clearly multiple signalling defects underlie obesity associated IR

Domain ontology for digital marketplaces

Recently the sharing economy has emerged as a viable alternative to fulfilling a variety of consumer needs. As there is no consensus on the definition of ‘sharing economy’ we use the term ‘marketplace’ to refer more specifically to Internet/software-based sharing economy platforms connecting two different market segments. In the field of sharing economy and marketplaces we found a research gap concerning the (socio)technological aspects and the development of marketplaces. A marketplace ontology can help to have a clear account of marketplace concepts which will facilitate communication, consensus and alignment. In this paper we design this marketplace ontology in four steps. First the selection of UFO as foundation and UFO-S as core ontology. Second the search for a set of minimal conditions and properties common for marketplaces and the derivation into competency questions. Third, use the competency questions to identify fragmented sub-ontology pieces called Domain-Related Ontology Patterns (DROPs) and apply them informally by extending UFO-S concepts to design a marketplace domain ontology. This marketplace domain ontology is represented in OntoUML. The last step is the validation of the OntoUML model using expert knowledge