13 research outputs found

    LIGHT-bgcArgo-1.0: using synthetic float capabilities in E3SMv2 to assess spatiotemporal variability in ocean physics and biogeochemistry

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    Since their advent over 2 decades ago, autonomous Argo floats have revolutionized the field of oceanography, and, more recently, the addition of biogeochemical and biological sensors to these floats has greatly improved our understanding of carbon, nutrient, and oxygen cycling in the ocean. While Argo floats offer unprecedented horizontal, vertical, and temporal coverage of the global ocean, uncertainties remain about whether Argo sampling frequency and density capture the true spatiotemporal variability in physical, biogeochemical, and biological properties. As the true distributions of, e.g., temperature or oxygen are unknown, these uncertainties remain difficult to address with Argo floats alone. Numerical models with synthetic observing systems offer one potential avenue to address these uncertainties. Here, we implement synthetic biogeochemical Argo floats into the Energy Exascale Earth System Model version 2 (E3SMv2), which build on the Lagrangian In Situ Global High-Performance Particle Tracking (LIGHT) module in E3SMv2 (E3SMv2-LIGHT-bgcArgo-1.0). Since the synthetic floats sample the model fields at model run time, the end user defines the sampling protocol ahead of any model simulation, including the number and distribution of synthetic floats to be deployed, their sampling frequency, and the prognostic or diagnostic model fields to be sampled. Using a 6-year proof-of-concept simulation, we illustrate the utility of the synthetic floats in different case studies. In particular, we quantify the impact of (i) sampling density on the float-derived detection of deep-ocean change in temperature or oxygen and on float-derived estimates of phytoplankton phenology, (ii) sampling frequency and sea-ice cover on float trajectory lengths and hence float-derived estimates of current velocities, and (iii) short-term variability in ecosystem stressors on estimates of their seasonal variability

    An inclusive Research and Education Community (iREC) model to facilitate undergraduate science education reform

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    Funding: This work was supported by Howard Hughes Medical Institute grants to DIH is GT12052 and MJG is GT15338.Over the last two decades, there have been numerous initiatives to improve undergraduate student outcomes in STEM. One model for scalable reform is the inclusive Research Education Community (iREC). In an iREC, STEM faculty from colleges and universities across the nation are supported to adopt and sustainably implement course-based research – a form of science pedagogy that enhances student learning and persistence in science. In this study, we used pathway modeling to develop a qualitative description that explicates the HHMI Science Education Alliance (SEA) iREC as a model for facilitating the successful adoption and continued advancement of new curricular content and pedagogy. In particular, outcomes that faculty realize through their participation in the SEA iREC were identified, organized by time, and functionally linked. The resulting pathway model was then revised and refined based on several rounds of feedback from over 100 faculty members in the SEA iREC who participated in the study. Our results show that in an iREC, STEM faculty organized as a long-standing community of practice leverage one another, outside expertise, and data to adopt, implement, and iteratively advance their pedagogy. The opportunity to collaborate in this manner and, additionally, to be recognized for pedagogical contributions sustainably engages STEM faculty in the advancement of their pedagogy. Here, we present a detailed pathway model of SEA that, together with underpinning features of an iREC identified in this study, offers a framework to facilitate transformations in undergraduate science education.Peer reviewe

    Models of classroom assessment for course-based research experiences

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    Course-based research pedagogy involves positioning students as contributors to authentic research projects as part of an engaging educational experience that promotes their learning and persistence in science. To develop a model for assessing and grading students engaged in this type of learning experience, the assessment aims and practices of a community of experienced course-based research instructors were collected and analyzed. This approach defines four aims of course-based research assessment—(1) Assessing Laboratory Work and Scientific Thinking; (2) Evaluating Mastery of Concepts, Quantitative Thinking and Skills; (3) Appraising Forms of Scientific Communication; and (4) Metacognition of Learning—along with a set of practices for each aim. These aims and practices of assessment were then integrated with previously developed models of course-based research instruction to reveal an assessment program in which instructors provide extensive feedback to support productive student engagement in research while grading those aspects of research that are necessary for the student to succeed. Assessment conducted in this way delicately balances the need to facilitate students’ ongoing research with the requirement of a final grade without undercutting the important aims of a CRE education

    More than heavy rain turning into fast-flowing water – a landscape perspective on the 2021 Eifel floods

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    Rapidly evolving floods are rare but powerful drivers of landscape reorganisation that have severe and long-lasting impacts on both the functions of a landscape’s subsystems and the affected society. The July 2021 flood that particularly hit several river catchments of the Eifel region in western Germany and Belgium was a drastic example. While media and scientists highlighted the meteorological and hydrological aspects of this flood, it was not just the rising water levels in the main valleys that posed a hazard, caused damage, and drove environmental reorganisation. Instead, the concurrent coupling of landscape elements and the wood, sediment, and debris carried by the fast-flowing water made this flood so devastating and difficult to predict. Because more intense floods are able to interact with more landscape components, they at times reveal rare non-linear feedbacks, which may be hidden during smaller events due to their high thresholds of initiation. Here, we briefly review the boundary conditions of the 14–15 July 2021 flood and discuss the emerging features that made this event different from previous floods. We identify hillslope processes, aspects of debris mobilisation, the legacy of sustained human land use, and emerging process connections and feedbacks as critical non-hydrological dimensions of the flood. With this landscape scale perspective, we develop requirements for improved future event anticipation, mitigation, and fundamental system understanding

    Coccolithophore Growth and Calcification in an Acidified Ocean: Insights From Community Earth System Model Simulations

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    Anthropogenic CO2 emissions are inundating the upper ocean, acidifying the water, and altering the habitat for marine phytoplankton. These changes are thought to be particularly influential for calcifying phytoplankton, namely, coccolithophores. Coccolithophores are widespread and account for a substantial portion of open ocean calcification; changes in their abundance, distribution, or level of calcification could have far‐reaching ecological and biogeochemical impacts. Here, we isolate the effects of increasing CO2 on coccolithophores using an explicit coccolithophore phytoplankton functional type parameterization in the Community Earth System Model. Coccolithophore growth and calcification are sensitive to changing aqueous CO2. While holding circulation constant, we demonstrate that increasing CO2 concentrations cause coccolithophores in most areas to decrease calcium carbonate production relative to growth. However, several oceanic regions show large increases in calcification, such the North Atlantic, Western Pacific, and parts of the Southern Ocean, due to an alleviation of carbon limitation for coccolithophore growth. Global annual calcification is 6% higher under present‐day CO2 levels relative to preindustrial CO2 (1.5 compared to 1.4 Pg C/year). However, under 900 ÎŒatm CO2, global annual calcification is 11% lower than under preindustrial CO2 levels (1.2 Pg C/year). Large portions of the ocean show greatly decreased coccolithophore calcification relative to growth, resulting in significant regional carbon export and air‐sea CO2 exchange feedbacks. Our study implies that coccolithophores become more abundant but less calcified as CO2 increases with a tipping point in global calcification (changing from increasing to decreasing calcification relative to preindustrial) at approximately ∌600 ÎŒatm CO2.ISSN:1942-246

    NFkappaB selectivity of estrogen receptor ligands revealed by comparative crystallographic analyses

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    Our understanding of how steroid hormones regulate physiological functions has been significantly advanced by structural biology approaches. However, progress has been hampered by misfolding of the ligand binding domains in heterologous expression systems and by conformational flexibility that interferes with crystallization. Here, we show that protein folding problems that are common to steroid hormone receptors are circumvented by mutations that stabilize well-characterized conformations of the receptor. We use this approach to present the structure of an apo steroid receptor that reveals a ligand-accessible channel allowing soaking of preformed crystals. Furthermore, crystallization of different pharmacological classes of compounds allowed us to define the structural basis of NFkappaB-selective signaling through the estrogen receptor, thus revealing a unique conformation of the receptor that allows selective suppression of inflammatory gene expression. The ability to crystallize many receptor-ligand complexes with distinct pharmacophores allows one to define structural features of signaling specificity that would not be apparent in a single structure.Kendall W Nettles, John B Bruning, German Gil, Jason Nowak, Sanjay K Sharma, Johnnie B Hahm, Kristen Kulp, Richard B Hochberg, Haibing Zhou, John A Katzenellenbogen, Benita S Katzenellenbogen, Younchang Kim, Andrzej Joachimiak & Geoffrey L Green
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