Comprehensive and Agricultural Greenhouse Gas Emissions Inventories for Nebraska and the Midwest as Baselines for Climate Change Mitigation

Climate change is the paramount challenge of today for a sustainable future. Mitigation of greenhouse gas (GHG) emissions is necessary to reduce the associated risks and impacts on society. Using the EPA’s SIT and literature review, comprehensive GHG-emissions inventories were developed for the state of Nebraska over 25 years (1990-2015) and agricultural GHG emissions inventories were developed for the Midwest U.S for one year (2016). Nebraska’s net emissions increased from 56.2 million metric tons of carbon dioxide equivalent (MMtCO2e) in 1990 to 87.4 MMtCO2e in 2016. Agriculture was found to be the sector with the most emissions (36 MMtCO2e), primarily from beef cattle, followed by electricity generation (21 MMtCO2e), primarily from coal. Total emissions in Nebraska were found to be 47.4 MtCO2e per capita in 2015, compared to 20.6 in the U.S. due to concentrated agricultural emissions and low population. Total agricultural GHG emissions per state in the Midwest in 2016 were found to range from 10.3 MMtCO2e (Michigan) to 41.0 MMtCO2e (Iowa), with an average of 23.3 MMtCO2e. In 2016, Wisconsin was the least efficient state (0.86 MtCO2e/kg product) and Illinois was the most efficient (0.34 MtCO2e/kg product) in terms of emissions per product, which aligned with these states having the highest (71.5%) and lowest (21%) percentage of livestock out of total agriculture. Agricultural emissions per capita ranged from 1.0 MtCO2e (MI) to 26.2 MtCO2e (SD), driven by cattle and state population. A review of literature was also conducted to explore the interactions between climate change and the insurance industry. Climatic events accounted for 91% of $1.05 trillion in insured costs for global catastrophic events from 1980 to 2016. Insurance feedbacks in response to disaster events caused by climate change include changes in 1) premiums and insurance policies, 2) non-coverage, and 3) policy making and litigation. Alongside a suite of strategies, including government policies, insurance feedbacks could be used to facilitate and manage climate change mitigation. Advisors: Adam Liska and Michael Haye

Adaptation to Climate Change via Insurance and Financial Incentives

Catastrophic climatic events have accounted for 72% of global insurance claims and totaled ~$1 trillion from 1980 to 2012. Costs are driven by socio-economic developments and an increased frequency and severity of climatic disasters in which climate change may have been a contributing factor. Climate change is projected to become a more prominent driver of these changes in the decades ahead. Government policies to reduce systemic risk have been the predominant approach for multi-level mitigation and adaptation to climate change. The analysis presented here shows how forceful and effective market-based approaches for adaptation and mitigation to climate change already operate via the insurance industry. Feedbacks from insurance to society include these primary changes: 1) premiums and insurance policies, 2) non-coverage, and 3) policy making and litigation (Chapter 1). Through these mechanisms, the insurance industry actively manages climate change adaptations and creates incentives to lessen impacts on industry and society. For mitigation of climate change, renewable energy-based energy production has become more of a priority for utilities in recent years (Chapter2). However, renewable energy is competitively disadvantaged compared to fossil-fuel based systems due to high investment costs, the intermittent nature of renewables, and a lack of pricing for externalities (Chapter 2). A model is used for calculating the total cost of a renewable utility and the cost of energy for that utility. Three scenarios were modeled (a null scenario with no incentive, an existing incentive in Nebraska, and a federal incentive that until recently was available to renewable utilities) to show the effects of incentives on the cost of production to the utility and the costs to the incentive providers. In Nebraska, the incentive was found to provide some relief to the utility compared to the null scenario and the federal incentive provided significantly more relief to the utility. Costs for the incentive investor with the federal incentive were significantly higher than with the Nebraska incentive, compared to the null scenario. To develop renewable-energy production and mitigate climate change impacts, incentives enable market entry where externalities for fossil fuels are not adequately priced. Adaptation to climate change requires thorough understanding of how the impacts affect society (Chapter 1) and how society might mitigate and adapt to the impacts of climate change (Chapter 2). Advisors: Adam J. Liska & Michael J. Haye

Adaptation to Climate Change via Insurance and Financial Incentives

Catastrophic climatic events have accounted for 72% of global insurance claims and totaled ~$1 trillion from 1980 to 2012. Costs are driven by socio-economic developments and an increased frequency and severity of climatic disasters in which climate change may have been a contributing factor. Climate change is projected to become a more prominent driver of these changes in the decades ahead. Government policies to reduce systemic risk have been the predominant approach for multi-level mitigation and adaptation to climate change. The analysis presented here shows how forceful and effective market-based approaches for adaptation and mitigation to climate change already operate via the insurance industry. Feedbacks from insurance to society include these primary changes: 1) premiums and insurance policies, 2) non-coverage, and 3) policy making and litigation (Chapter 1). Through these mechanisms, the insurance industry actively manages climate change adaptations and creates incentives to lessen impacts on industry and society. For mitigation of climate change, renewable energy-based energy production has become more of a priority for utilities in recent years (Chapter2). However, renewable energy is competitively disadvantaged compared to fossil-fuel based systems due to high investment costs, the intermittent nature of renewables, and a lack of pricing for externalities (Chapter 2). A model is used for calculating the total cost of a renewable utility and the cost of energy for that utility. Three scenarios were modeled (a null scenario with no incentive, an existing incentive in Nebraska, and a federal incentive that until recently was available to renewable utilities) to show the effects of incentives on the cost of production to the utility and the costs to the incentive providers. In Nebraska, the incentive was found to provide some relief to the utility compared to the null scenario and the federal incentive provided significantly more relief to the utility. Costs for the incentive investor with the federal incentive were significantly higher than with the Nebraska incentive, compared to the null scenario. To develop renewable-energy production and mitigate climate change impacts, incentives enable market entry where externalities for fossil fuels are not adequately priced. Adaptation to climate change requires thorough understanding of how the impacts affect society (Chapter 1) and how society might mitigate and adapt to the impacts of climate change (Chapter 2). Advisors: Adam J. Liska & Michael J. Haye

A Greenhouse Gas Emissions Inventory for Nebraska: Livestock and Coal Loom Large

Mitigation of climate change requires the systematic identification and cataloging of emissions sources at city, state, and national levels. In this study, an inventory of annual greenhouse gas emissions from the state of Nebraska was created based on industry data, and emissions inventories were completed each year from 1990 to 2016. Nebraska’s net emissions were found to increase from 56.2 million metric tons of carbon dioxide equivalents (MMtCO2e) in 1990 to 87.4 MMtCO2e in 2016. Agriculture was found to be the sector with the most emissions (36 MMtCO2e) followed by electricity generation (21 MMtCO2e). In 2016, emissions from beef cattle made up 55% of agricultural emissions and 23.7% of net state emissions; if all beef were substituted with pork, net state emissions could be reduced by 17.9%. Coal for electricity had the largest increase in emissions from 1990 to 2016 (7.4 MMtCO2e) and made up 23.7% of the state’s net emissions in 2016. Net emissions per capita in Nebraska were found to be 46.2 metric tons CO2e per capita (MtCO2e) in 2015, which is more than double US average emissions at 18.4 MtCO2e, though potentially similar to those of other agricultural states when emissions from agriculture are included in state inventories

Climate Change and Market-Based Insurance Feedbacks

Climatic events have accounted for 91% of $1.05 trillion in insured costs for global catastrophic events from 1980 to 2016. Costs are driven by socio-economic development and increased frequency and severity of climatic disasters driven by climate change. Government policies to reduce systemic risk (e.g., cap-and-trade, carbon tax) have been a predominant approach for mitigation and adaptation. Alternatively, market-based incentives for climate change adaptation and mitigation already operate via the insurance industry to lessen impacts on society. Insurance feedbacks include changes in 1) premiums and insurance policies, 2) non-coverage, and 3) policy making and litigation. Alongside government policies, insurance feedbacks could be used to facilitate climate change adaptation and mitigation to a significant degree. Ultimately, a negotiated distribution of climate-related costs between the public and private insurance is needed

The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the extended Baryon Oscillation Spectroscopic Survey and from the second phase of the Apache Point Observatory Galactic Evolution Experiment

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since July 2014. This paper describes the second data release from this phase, and the fourteenth from SDSS overall (making this, Data Release Fourteen or DR14). This release makes public data taken by SDSS-IV in its first two years of operation (July 2014-2016). Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey (eBOSS); the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data driven machine learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS website (www.sdss.org) has been updated for this release, and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020, and will be followed by SDSS-V.Comment: SDSS-IV collaboration alphabetical author data release paper. DR14 happened on 31st July 2017. 19 pages, 5 figures. Accepted by ApJS on 28th Nov 2017 (this is the "post-print" and "post-proofs" version; minor corrections only from v1, and most of errors found in proofs corrected

Neuropathology in Mouse Models of Mucopolysaccharidosis Type I, IIIA and IIIB

Mucopolysaccharide diseases (MPS) are caused by deficiency of glycosaminoglycan (GAG) degrading enzymes, leading to GAG accumulation. Neurodegenerative MPS diseases exhibit cognitive decline, behavioural problems and shortened lifespan. We have characterised neuropathological changes in mouse models of MPSI, IIIA and IIIB to provide a better understanding of these events

Ancient Lowland Maya neighborhoods: Average Nearest Neighbor analysis and kernel density models, environments, and urban scale

Many humans live in large, complex political centers, composed of multi-scalar communities including neighborhoods and districts. Both today and in the past, neighborhoods form a fundamental part of cities and are defined by their spatial, architectural, and material elements. Neighborhoods existed in ancient centers of various scales, and multiple methods have been employed to identify ancient neighborhoods in archaeological contexts. However, the use of different methods for neighborhood identification within the same spatiotemporal setting results in challenges for comparisons within and between ancient societies. Here, we focus on using a single method—combining Average Nearest Neighbor (ANN) and Kernel Density (KD) analyses of household groups—to identify potential neighborhoods based on clusters of households at 23 ancient centers across the Maya Lowlands. While a one-size-fits all model does not work for neighborhood identification everywhere, the ANN/KD method provides quantifiable data on the clustering of ancient households, which can be linked to environmental zones and urban scale. We found that centers in river valleys exhibited greater household clustering compared to centers in upland and escarpment environments. Settlement patterns on flat plains were more dispersed, with little discrete spatial clustering of households. Furthermore, we categorized the ancient Maya centers into discrete urban scales, finding that larger centers had greater variation in household spacing compared to medium-sized and smaller centers. Many larger political centers possess heterogeneity in household clustering between their civic-ceremonial cores, immediate hinterlands, and far peripheries. Smaller centers exhibit greater household clustering compared to larger ones. This paper quantitatively assesses household clustering among nearly two dozen centers across the Maya Lowlands, linking environment and urban scale to settlement patterns. The findings are applicable to ancient societies and modern cities alike; understanding how humans form multi-scalar social groupings, such as neighborhoods, is fundamental to human experience and social organization

Development and Notch Signaling Requirements of the Zebrafish Choroid Plexus

The choroid plexus (CP) is an epithelial and vascular structure in the ventricular system of the brain that is a critical part of the blood-brain barrier. The CP has two primary functions, 1) to produce and regulate components of the cerebral spinal fluid, and 2) to inhibit entry into the brain of exogenous substances. Despite its importance in neurobiology, little is known about how this structure forms.Here we show that the transposon-mediated enhancer trap zebrafish line Et(Mn16) expresses green fluorescent protein within a population of cells that migrate toward the midline and coalesce to form the definitive CP. We further demonstrate the development of the integral vascular network of the definitive CP. Utilizing pharmacologic pan-notch inhibition and specific morpholino-mediated knockdown, we demonstrate a requirement for Notch signaling in choroid plexus development. We identify three Notch signaling pathway members as mediating this effect, notch1b, deltaA, and deltaD.This work is the first to identify the zebrafish choroid plexus and to characterize its epithelial and vasculature integration. This study, in the context of other comparative anatomical studies, strongly indicates a conserved mechanism for development of the CP. Finally, we characterize a requirement for Notch signaling in the developing CP. This establishes the zebrafish CP as an important new system for the determination of key signaling pathways in the formation of this essential component of the vertebrate brain