An SMP Soft Classification Algorithm for Remote Sensing

This work introduces a symmetric multiprocessing (SMP) version of the continuous iterative guided spectral class rejection (CIGSCR) algorithm, a semiautomated classification algorithm for remote sensing (multispectral) images. The algorithm uses soft data clusters to produce a soft classification containing inherently more information than a comparable hard classification at an increased computational cost. Previous work suggests that similar algorithms achieve good parallel scalability, motivating the parallel algorithm development work here. Experimental results of applying parallel CIGSCR to an image with approximately 10^8 pixels and six bands demonstrate superlinear speedup. A soft two class classification is generated in just over four minutes using 32 processors

Temperature Changes in the United States

Temperature is among the most important climatic elements used in decision-making. For example, builders and insurers use temperature data for planning and risk management while energy companies and regulators use temperature data to predict demand and set utility rates. Temperature is also a key indicator of climate change: recent increases are apparent over the land, ocean, and troposphere, and substantial changes are expected for this century. This chapter summarizes the major observed and projected changes in near-surface air temperature over the United States, emphasizing new data sets and model projections since the Third National Climate Assessment (NCA3). Changes are depicted using a spectrum of observations, including surface weather stations, moored ocean buoys, polar-orbiting satellites, and temperature-sensitive proxies. Projections are based on global models and downscaled products from CMIP5 (Coupled Model Intercomparison Project Phase 5) using a suite of Representative Concentration Pathways (RCPs; see Ch. 4: Projections for more on RCPs and future scenarios)

Social stress-enhanced severity of Citrobacter rodentium-induced colitis is CCL2-dependent and attenuated by probiotic Lactobacillus reuteri

Psychological stressors are known to affect colonic diseases but the mechanisms by which this occurs, and whether probiotics can prevent stressor effects, are not understood. Because inflammatory monocytes that traffic into the colon can exacerbate colitis, we tested whether CCL2, a chemokine involved in monocyte recruitment, was necessary for stressor-induced exacerbation of infectious colitis. Mice were exposed to a social disruption stressor that entails repeated social defeat. During stressor exposure, mice were orally challenged with Citrobacter rodentium to induce a colonic inflammatory response. Exposure to the stressor during challenge resulted in significantly higher colonic pathogen levels, translocation to the spleen, increases in colonic macrophages, and increases in inflammatory cytokines and chemokines. The stressor-enhanced severity of C. rodentium-induced colitis was not evident in CCL2[superscript −/−] mice, indicating the effects of the stressor are CCL2-dependent. In addition, we tested whether probiotic intervention could attenuate stressor-enhanced infectious colitis by reducing monocyte/macrophage accumulation. Treating mice with probiotic Lactobacillus reuteri reduced CCL2 mRNA levels in the colon and attenuated stressor-enhanced infectious colitis. These data demonstrate that probiotic L. reuteri can prevent the exacerbating effects of stressor exposure on pathogen-induced colitis, and suggest that one mechanism by which this occurs is through downregulation of the chemokine CCL2.National Cancer Institute (U.S.) (Grants AT006552-01A1, P30-CA016058, and T32-DE014320

Chapter 15: Potential Surprises: Compound Extremes and Tipping Elements

The Earth system is made up of many components that interact in complex ways across a broad range of temporal and spatial scales. As a result of these interactions the behavior of the system cannot be predicted by looking at individual components in isolation. Negative feedbacks, or self-stabilizing cycles, within and between components of the Earth system can dampen changes (Ch. 2: Physical Drivers of Climate Change). However, their stabilizing effects render such feedbacks of less concern from a risk perspective than positive feedbacks, or self-reinforcing cycles. Positive feedbacks magnify both natural and anthropogenic changes. Some Earth system components, such as arctic sea ice and the polar ice sheets, may exhibit thresholds beyond which these self-reinforcing cycles can drive the component, or the entire system, into a radically different state. Although the probabilities of these state shifts may be difficult to assess, their consequences could be high, potentially exceeding anything anticipated by climate model projections for the coming century

Post-landslide soil and vegetation recovery in a dry, montane system is slow and patchy

Landslides are common disturbances in forests around the world, and a major threat to human life and property. Landslides are likely to become more common in many areas as storms intensify. Forest vegetation can improve hillslope stability via long, deep rooting across and through failure planes. In the U.S. Rocky Mountains, landslides are infrequent but widespread when they do occur. They are also extremely understudied, with little known about the basic vegetation recovery processes and rates of establishment which restabilize hills. This study presents the first evaluation of post-landslide vegetation recovery on forested landslides in the southern Rocky Mountains. Six years after a major landslide event, the surveyed sites have very little regeneration in initiation zones, even when controlling for soil coverage. Soils are shallower and less nitrogen rich in initiation zones as well. Rooting depth was similar between functional groups regardless of position on the slide, but deep-rooting trees are much less common in initiation zones. A lack of post-disturbance tree regeneration in these lower elevation, warm/dry settings, common across a variety of disturbance types, suggests that complete tree restabilization of these hillslopes is likely to be a slow or non-existent, especially as the climate warms. Replacement by grasses would protect against shallow instabilities but not the deeper mass movement events which threaten life and property

Daily snow depth measurements from 195 stations in the United States

This document describes a database containing daily measurements of snow depth at 195 National Weather Service (NWS) first-order climatological stations in the United States. The data have been assembled and made available by the National Climatic Data Center (NCDC) in Asheville, North Carolina. The 195 stations encompass 388 unique sampling locations in 48 of the 50 states; no observations from Delaware or Hawaii are included in the database. Station selection criteria emphasized the quality and length of station records while seeking to provide a network with good geographic coverage. Snow depth at the 388 locations was measured once per day on ground open to the sky. The daily snow depth is the total depth of the snow on the ground at measurement time. The time period covered by the database is 1893--1992; however, not all station records encompass the complete period. While a station record ideally should contain daily data for at least the seven winter months (January through April and October through December), not all stations have complete records. Each logical record in the snow depth database contains one station`s daily data values for a period of one month, including data source, measurement, and quality flags

Local climate determines vulnerability to camouflage mismatch in snowshoe hares

AimPhenological mismatches, when life‐events become mistimed with optimal environmental conditions, have become increasingly common under climate change. Population‐level susceptibility to mismatches depends on how phenology and phenotypic plasticity vary across a species’ distributional range. Here, we quantify the environmental drivers of colour moult phenology, phenotypic plasticity, and the extent of phenological mismatch in seasonal camouflage to assess vulnerability to mismatch in a common North American mammal.LocationNorth America.Time period2010–2017.Major taxa studiedSnowshoe hare (Lepus americanus).MethodsWe used > 5,500 by‐catch photographs of snowshoe hares from 448 remote camera trap sites at three independent study areas. To quantify moult phenology and phenotypic plasticity, we used multinomial logistic regression models that incorporated geospatial and high‐resolution climate data. We estimated occurrence of camouflage mismatch between hares’ coat colour and the presence and absence of snow over 7 years of monitoring.ResultsSpatial and temporal variation in moult phenology depended on local climate conditions more so than on latitude. First, hares in colder, snowier areas moulted earlier in the fall and later in the spring. Next, hares exhibited phenotypic plasticity in moult phenology in response to annual variation in temperature and snow duration, especially in the spring. Finally, the occurrence of camouflage mismatch varied in space and time; white hares on dark, snowless background occurred primarily during low‐snow years in regions characterized by shallow, short‐lasting snowpack.Main conclusionsLong‐term climate and annual variation in snow and temperature determine coat colour moult phenology in snowshoe hares. In most areas, climate change leads to shorter snow seasons, but the occurrence of camouflage mismatch varies across the species’ range. Our results underscore the population‐specific susceptibility to climate change‐induced stressors and the necessity to understand this variation to prioritize the populations most vulnerable under global environmental change.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154444/1/geb13049.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154444/2/geb13049_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154444/3/geb13049-sup-0001-Supinfo.pd

3D Molecular Cytology of Hop (Humulus lupulus) Meiotic Chromosomes Reveals Non-disomic Pairing and Segregation, Aneuploidy, and Genomic Structural Variation

Hop (Humulus lupulus L.) is an important crop worldwide, known as the main flavoring ingredient in beer. The diversifying brewing industry demands variation in flavors, superior process properties, and sustainable agronomics, which are the focus of advanced molecular breeding efforts in hops. Hop breeders have been limited in their ability to create strains with desirable traits, however, because of the unusual and unpredictable inheritance patterns and associated non-Mendelian genetic marker segregation. Cytogenetic analysis of meiotic chromosome behavior has also revealed conspicuous and prevalent occurrences of multiple, atypical, non-disomic chromosome complexes, including those involving autosomes in late prophase. To explore the role of meiosis in segregation distortion, we undertook 3D cytogenetic analysis of hop pollen mother cells stained with DAPI and FISH. We used telomere FISH to demonstrate that hop exhibits a normal telomere clustering bouquet. We also identified and characterized a new sub-terminal 180 bp satellite DNA tandem repeat family called HSR0, located proximal to telomeres. Highly variable 5S rDNA FISH patterns within and between plants, together with the detection of anaphase chromosome bridges, reflect extensive departures from normal disomic signal composition and distribution. Subsequent FACS analysis revealed variable DNA content in a cultivated pedigree. Together, these findings implicate multiple phenomena, including aneuploidy, segmental aneuploidy, or chromosome rearrangements, as contributing factors to segregation distortion in hop

Our Globally Changing Climate

Since the Third U.S. National Climate Assessment (NCA3) was published in May 2014, new observations along multiple lines of evidence have strengthened the conclusion that Earth's climate is changing at a pace and in a pattern not explainable by natural influences. While this report focuses especially on observed and projected future changes for the United States, it is important to understand those changes in the global context (this chapter). The world has warmed over the last 150 years, especially over the last six decades, and that warming has triggered many other changes to Earth's climate. Evidence for a changing climate abounds, from the top of the atmosphere to the depths of the oceans. Thousands of studies conducted by tens of thousands of scientists around the world have documented changes in surface, atmospheric, and oceanic temperatures; melting glaciers; disappearing snow cover; shrinking sea ice; rising sea level; and an increase in atmospheric water vapor. Rainfall patterns and storms are changing, and the occurrence of droughts is shifting

Seasonality, intensity, and duration of rainfall extremes change in a warmer climate

Precipitation extremes are expected to intensify under climate change with consequent impacts in flooding and ecosystem functioning. Here we use station data and high‐resolution simulations from the WRF convection permitting climate model (∼4 km, 1 h) over the US to assess future changes in hourly precipitation extremes. It is demonstrated that hourly precipitation extremes and storm depths are expected to intensify under climate change and what is now a 20‐year rainfall will become a 7‐year rainfall on average for ∼ 75% of gridpoints over the US. This intensification is mostly expressed as an increase in rainfall tail heaviness. Statistically significant changes in the seasonality and duration of rainfall extremes are also exhibited over ∼ 95% of the domain. Our results suggest more non‐linear future precipitation extremes with shorter spell duration that are distributed more uniformly throughout the year