Ranking the risk of CO2 emissions from seagrass soil carbon stocks under global change threats

Seagrass meadows are natural carbon storage hotspots at risk from global change threats, and their loss can result in the remineralization of soil carbon stocks and CO2 emissions fueling climate change. Here we used expert elicitation and empirical evidence to assess the risk of CO2 emissions from seagrass soils caused by multiple human-induced, biological and climate change threats. Judgments from 41 experts were synthesized into a seagrass CO2 emission risk score based on vulnerability factors (i.e., spatial scale, frequency, magnitude, resistance and recovery) to seagrass soil organic carbon stocks. Experts perceived that climate change threats (e.g., gradual ocean warming and increased storminess) have the highest risk for CO2 emissions at global spatial scales, while direct threats (i.e., dredging and building of a marina or jetty) have the largest CO2 emission risks at local spatial scales. A review of existing peer-reviewed literature showed a scarcity of studies assessing CO2 emissions following seagrass disturbance, but the limited empirical evidence partly confirmed the opinion of experts. The literature review indicated that direct and long-term disturbances have the greatest negative impact on soil carbon stocks per unit area, highlighting that immediate management actions after disturbances to recover the seagrass canopy can significantly reduce soil CO2 emissions. We conclude that further empirical evidence assessing global change threats on the seagrass carbon sink capacity is required to aid broader uptake of seagrass into blue carbon policy frameworks. The preliminary findings from this study can be used to estimate the potential risk of CO2 emissions from seagrass habitats under threat and guide nature-based solutions for climate change mitigation

Evidence from in vivo 31-phosphorus magnetic resonance spectroscopy phosphodiesters that exhaled ethane is a biomarker of cerebral n-3 polyunsaturated fatty acid peroxidation in humans

<p>Abstract</p> <p>Background</p> <p>This study tested the hypothesis that exhaled ethane is a biomarker of cerebral <it>n</it>-3 polyunsaturated fatty acid peroxidation in humans. Ethane is released specifically following peroxidation of <it>n</it>-3 polyunsaturated fatty acids. We reasoned that the cerebral source of ethane would be the docosahexaenoic acid component of membrane phospholipids. Breakdown of the latter also releases phosphorylated polar head groups, giving rise to glycerophosphorylcholine and glycerophosphorylethanolamine, which can be measured from the 31-phosphorus neurospectroscopy phosphodiester peak. Schizophrenia patients were chosen because of evidence of increased free radical-mediated damage and cerebral lipid peroxidation in this disorder.</p> <p>Methods</p> <p>Samples of alveolar air were obtained from eight patients and ethane was analyzed and quantified by gas chromatography and mass spectrometry (<it>m</it>/<it>z </it>= 30). Cerebral 31-phosphorus spectra were obtained from the same patients at a magnetic field strength of 1.5 T using an image-selected <it>in vivo </it>spectroscopy sequence (TR = 10 s; 64 signal averages localized on a 70 × 70 × 70 mm³voxel). The quantification of the 31-phosphorus signals using prior knowledge was carried out in the temporal domain after truncating the first 1.92 ms of the signal to remove the broad component present in the 31-phosphorus spectra.</p> <p>Results</p> <p>The ethane and phosphodiester levels, expressed as a percentage of the total 31-phosphorus signal, were positively and significantly correlated (<it>r</it>_{<it>s </it>}= 0.714, <it>p </it>< 0.05).</p> <p>Conclusion</p> <p>Our results support the hypothesis that the measurement of exhaled ethane levels indexes cerebral <it>n</it>-3 lipid peroxidation. From a practical viewpoint, if human cerebral <it>n</it>-3 polyunsaturated fatty acid catabolism can be measured by ethane in expired breath, this would be more convenient than determining the area of the 31-phosphorus neurospectroscopy phosphodiester peak.</p

Integrated assessment—how does it help unpack water access by marginalized farmers?

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Water is critical to the lives and livelihoods of rural communities in developing countries; however, access to water can be inequitable within communities. This paper uses a generalized integrated assessment approach to explore the determinants of water access by marginalized farmers in two villages in coastal Bangladesh, before and after the setup of local water institutions. The study was part of a broader project aimed at promoting socially inclusive agricultural intensification. An integrative framework was developed in this study to capture and link the diverse range of factors that influence the distribution of water, including the often-overlooked role of social dynamics and governance arrangements. While interventions around improving water resource infrastructure can be critical for freshwater availability, the case studies show that a breakdown of asymmetric power structures may also be needed for water access to all individuals, especially marginalized groups. Establishing a community-based water institution on its own does not necessarily address power issues in a community. It is imperative that the agency and capacities of the marginalized members are developed and that the institutional arrangements foster an enabling environment for marginalized members to influence decision making. Integrated assessment allowed the case studies to be explored from multiple perspectives so as to gain a greater understanding of the barriers and levers to obtaining equitable outcomes from water interventions

A framework for characterising and evaluating the effectiveness of environmental modelling

Environmental modelling is transitioning from the traditional paradigm that focuses on the model and its quantitative performance to a more holistic paradigm that recognises successful model-based outcomes are closely tied to undertaking modelling as a social process, not just as a technical procedure. This paper redefines evaluation as a multi-dimensional and multi-perspective concept, and proposes a more complete framework for identifying and measuring the effectiveness of modelling that serves the new paradigm. Under this framework, evaluation considers a broader set of success criteria, and emphasises the importance of contextual factors in determining the relevance and outcome of the criteria. These evaluation criteria are grouped into eight categories: project efficiency, model accessibility, credibility, saliency, legitimacy, satisfaction, application, and impact. Evaluation should be part of an iterative and adaptive process that attempts to improve model-based outcomes and foster pathways to better futures

Eight grand challenges in socio-environmental systems modeling

Modeling is essential to characterize and explore complex societal and environmental issues in systematic and collaborative ways. Socio-environmental systems (SES) modeling integrates knowledge and perspectives into conceptual and computational tools that explicitly recognize how human decisions affect the environment. Depending on the modeling purpose, many SES modelers also realize that involvement of stakeholders and experts is fundamental to support social learning and decision-making processes for achieving improved environmental and social outcomes. The contribution of this paper lies in identifying and formulating grand challenges that need to be overcome to accelerate the development and adaptation of SES modeling. Eight challenges are delineated: bridging epistemologies across disciplines; multi-dimensional uncertainty assessment and management; scales and scaling issues; combining qualitative and quantitative methods and data; furthering the adoption and impacts of SES modeling on policy; capturing structural changes; representing human dimensions in SES; and leveraging new data types and sources. These challenges limit our ability to effectively use SES modeling to provide the knowledge and information essential for supporting decision making. Whereas some of these challenges are not unique to SES modeling and may be pervasive in other scientific fields, they still act as barriers as well as research opportunities for the SES modeling community. For each challenge, we outline basic steps that can be taken to surmount the underpinning barriers. Thus, the paper identifies priority research areas in SES modeling, chiefly related to progressing modeling products, processes and practices

Effective modeling for integrated water resource management: a guide to contextual practices by phases and steps and future opportunities

The effectiveness of Integrated Water Resource Management (IWRM) modeling hinges on the quality of practices employed through the process, starting from early problem definition all the way through to using the model in a way that serves its intended purpose. The adoption and implementation of effective modeling practices need to be guided by a practical understanding of the variety of decisions that modelers make, and the information considered in making these choices. There is still limited documented knowledge on the modeling workflow, and the role of contextual factors in determining this workflow and which practices to employ. This paper attempts to contribute to this knowledge gap by providing systematic guidance of the modeling practices through the phases (Planning, Development, Application, and Perpetuation) and steps that comprise the modeling process, positing questions that should be addressed. Practice-focused guidance helps explain the detailed process of conducting IWRM modeling, including the role of contextual factors in shaping practices. We draw on findings from literature and the authors’ collective experience to articulate what and how contextual factors play out in employing those practices. In order to accelerate our learning about how to improve IWRM modeling, the paper concludes with five key areas for future practice-related research: knowledge sharing, overcoming data limitations, informed stakeholder involvement, social equity and uncertainty management. © 2019 Elsevier Lt

Genetic association study of QT interval highlights role for calcium signaling pathways in myocardial repolarization.

The QT interval, an electrocardiographic measure reflecting myocardial repolarization, is a heritable trait. QT prolongation is a risk factor for ventricular arrhythmias and sudden cardiac death (SCD) and could indicate the presence of the potentially lethal mendelian long-QT syndrome (LQTS). Using a genome-wide association and replication study in up to 100,000 individuals, we identified 35 common variant loci associated with QT interval that collectively explain ∼8-10% of QT-interval variation and highlight the importance of calcium regulation in myocardial repolarization. Rare variant analysis of 6 new QT interval-associated loci in 298 unrelated probands with LQTS identified coding variants not found in controls but of uncertain causality and therefore requiring validation. Several newly identified loci encode proteins that physically interact with other recognized repolarization proteins. Our integration of common variant association, expression and orthogonal protein-protein interaction screens provides new insights into cardiac electrophysiology and identifies new candidate genes for ventricular arrhythmias, LQTS and SCD