269 research outputs found
Spatiotemporal Analysis of Soil Quality Degradation and Emissions in the State of Iowa (USA)
The concept of soil quality (SQ) is defined as the soil\u27s capacity to function, which is commonly assessed at the field scale. Soil quality is composed of inherent (soil suitability) and dynamic (soil health, SH) SQ, which can also be analyzed using geospatial tools as a SQ continuum (SQC). This study proposes an innovative spatiotemporal analysis of SQ degradation and emissions from land developments using the state of Iowa (IA) in the United States of America (USA) as a case study. The SQ degradation was linked to anthropogenic soil (SD) and land degradation (LD) in the state. More than 88% of land in IA experienced anthropogenic LD primarily due to agriculture (93%). All six soil orders were subject to various degrees of anthropogenic LD: Entisols (75%), Inceptisols (94%), Histosols (59%), Alfisols (79%), Mollisols (93%), and Vertisols (98%). Soil and LD have primarily increased between 2001 and 2016. In addition to agricultural LD, there was also SD/LD caused by an increase in developments often through urbanization. All land developments in IA can be linked to damages to SQ, with 8385.9 km2 of developed area, causing midpoint total soil carbon (TSC) losses of 1.7 × 1011 kg of C and an associated midpoint of social cost of carbon dioxide emissions (SC-CO2) of 1.3B in SC-CO2. New developments are often located near urban areas, for example, near the capital city of Des Moines, and other cities (Sioux City, Dubuque). Results of this study reveal several different kinds of SQ damage from developments: loss of potential for future C sequestration in soils, soil C loss, and “realized” soil C social costs (SC-CO2). The state of IA has very limited potential land (2.0% of the total state area) for nature-based solutions (NBS) to compensate for SD and LD. The results of this study can be used to support pending soil health-related legislation in IA and monitoring towards achieving the Sustainable Development Goals (SDGs) developed by the United Nations (UN) by providing a landscape-level perspective on LD to focus field-level initiatives to reduce soil loss and improve SQ. Future technological innovations will provide higher spatial and temporal remote sensing data that can be fused with field-level direct sensing to track SH and SQ changes
Quantifying Damages to Soil Health and Emissions from Land Development in the State of Illinois (USA)
The concept of soil health is increasingly being used as an indicator for sustainable soil management and even includes legislative actions. Current applications of soil health often lack geospatial and monetary analyses of damages (e.g., land development), which can degrade soil health through loss of carbon (C) and productive soils. This study aims to evaluate the damages to soil health (e.g., soil C, the primary soil health indicator) attributed to land developments within the state of Illinois (IL) in the United States of America (USA). All land developments in IL can be associated with damages to soil health, with 13,361.0 km2 developed, resulting in midpoint losses of 2.5 × 1011 of total soil carbon (TSC) and a midpoint social cost of carbon dioxide emissions (SC-CO2) of 2.7B in SC-CO2. New developments occurred adjacent to current urban areas near the capital cities of Springfield, Chicago, and St. Louis (the border city between the states of Missouri and IL). Results of this study reveal several types of damage to soil health from developments: soil C loss, associated “realized” soil C social costs (SC-CO2), and loss of soil C sequestration potential from developments. The innovation of this study has several aspects. Geospatial analysis of land cover combined with corresponding soil types can identify changes in the soil health continuum at the landscape level. Because soil C is a primary soil health indicator, land conversions caused by developments reduce soil health and the availability of productive soils for agriculture, forestry, and C sequestration. Current IL soil health legislation can benefit from this landscape level data on soil C loss with GHG emissions and associated SC-CO2 costs by providing insight into the soil health continuum and its dynamics. These techniques and data can also be used to expand IL’s GHG emissions reduction efforts from being solely focused on the energy sector to include soil-based emissions from developments. Current soil health legislation does not recognize that soil’s health is harmed by disturbance from land developments and that this disturbance results in GHG emissions. Soil health programs could be broadened to encourage less disturbance of soil types that release high levels of GHG and set binding targets based on losses in the soil health continuum
Climate Change Planning: Soil Carbon Regulating Ecosystem Services and Land Cover Change Analysis to Inform Disclosures for the State of Rhode Island, USA
The state of Rhode Island (RI) has established its greenhouse gas (GHG) emissions reduction goals, which require rapidly acquired and updatable science-based data to make these goals enforceable and effective. The combination of remote sensing and soil information data can estimate the past and model future GHG emissions because of conversion of “low disturbance” land covers (e.g., evergreen forest, hay/pasture) to “high disturbance” land covers (e.g., low-, medium-, and high-intensity developed land). These modeled future emissions can be used as a predevelopment potential GHG emissions information disclosure. This study demonstrates the rapid assessment of the value of regulating ecosystems services (ES) from soil organic carbon (SOC), soil inorganic carbon (SIC), and total soil carbon (TSC) stocks, based on the concept of the avoided social cost of carbon dioxide (CO2) emissions for RI by soil order and county using remote sensing and information from the State Soil Geographic (STATSGO) and Soil Survey Geographic Database (SSURGO) databases. Classified land cover data for 2001 and 2016 were downloaded from the Multi-Resolution Land Characteristics Consortium (MRLC) website. Obtained results provide accurate and quantitative spatio-temporal information about likely GHG emissions and show their patterns which are often associated with existing urban developments. These remote sensing tools could be used by the state of RI to both understand the nature of land cover change and likely GHG emissions from soil and to institute mandatory or voluntary predevelopment assessments and potential GHG emissions disclosures as a part of a climate mitigation policy
Association of Left Ventricular Hypertrophy With Incident Hypertension: The Multi-Ethnic Study of Atherosclerosis
Increased left ventricular (LV) mass and changes in LV geometry may precede hypertension onset. The authors examined the associations of LV mass and geometry, assessed by cardiac magnetic resonance imaging, with hypertension incidence in 2,567 normotensive participants enrolled in 2000–2002 in the Multi-Ethnic Study of Atherosclerosis, an ethnically diverse, population-based, US study. Over a median follow-up of 4.8 years, 745 (29%) participants developed hypertension. In a fully adjusted model including baseline blood pressure, the relative risks of incident hypertension from the lowest to highest LV mass quartile were 1.00 (referent), 1.13 (95% confidence interval (CI): 0.89, 1.43), 1.28 (95% CI: 1.00, 1.63), and 1.78 (95% CI: 1.38, 2.30) (P < 0.001 for linear trend). Higher levels of LV concentric geometry, defined by higher LV mass to end-diastolic volume quartiles, were associated with higher risk of incident hypertension in a fully adjusted model (P = 0.044 for linear trend). In a final model containing both quartiles of LV mass and LV mass/volume along with all covariates including baseline blood pressure, higher LV mass quartiles were associated with incident hypertension (P < 0.001 for linear trend), whereas higher LV mass/volume quartiles were not (P = 0.643 for linear trend). In this multiethnic cohort, alterations in LV mass preceded hypertension onset among normotensive individuals
Competing biosecurity and risk rationalities in the Chittagong poultry commodity chain, Bangladesh
This paper anthropologically explores how key actors in the Chittagong live bird trading network perceive biosecurity and risk in relation to avian influenza between production sites, market maker scenes and outlets. They pay attention to the past and the present, rather than the future, downplaying the need for strict risk management, as outbreaks have not been reported frequently for a number of years. This is analysed as ‘temporalities of risk perception regarding biosecurity’, through Black Swan theory, the idea that unexpected events with major effects are often inappropriately rationalized (Taleb in The Black Swan. The impact of the highly improbable, Random House, New York, 2007). This incorporates a sociocultural perspective on risk, emphasizing the contexts in which risk is understood, lived, embodied and experienced. Their risk calculation is explained in terms of social consent, practical intelligibility and convergence of constraints and motivation. The pragmatic and practical orientation towards risk stands in contrast to how risk is calculated in the avian influenza preparedness paradigm. It is argued that disease risk on the ground has become a normalized part of everyday business, as implied in Black Swan theory. Risk which is calculated retrospectively is unlikely to encourage investment in biosecurity and, thereby, points to the danger of unpredictable outlier events
Drug-gene interactions of antihypertensive medications and risk of incident cardiovascular disease: a pharmacogenomics study from the CHARGE consortium
Background
Hypertension is a major risk factor for a spectrum of cardiovascular diseases (CVD), including myocardial infarction, sudden death, and stroke. In the US, over 65 million people have high blood pressure and a large proportion of these individuals are prescribed antihypertensive medications. Although large long-term clinical trials conducted in the last several decades have identified a number of effective antihypertensive treatments that reduce the risk of future clinical complications, responses to therapy and protection from cardiovascular events vary among individuals.
Methods
Using a genome-wide association study among 21,267 participants with pharmaceutically treated hypertension, we explored the hypothesis that genetic variants might influence or modify the effectiveness of common antihypertensive therapies on the risk of major cardiovascular outcomes. The classes of drug treatments included angiotensin-converting enzyme inhibitors, beta-blockers, calcium channel blockers, and diuretics. In the setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, each study performed array-based genome-wide genotyping, imputed to HapMap Phase II reference panels, and used additive genetic models in proportional hazards or logistic regression models to evaluate drug-gene interactions for each of four therapeutic drug classes. We used meta-analysis to combine study-specific interaction estimates for approximately 2 million single nucleotide polymorphisms (SNPs) in a discovery analysis among 15,375 European Ancestry participants (3,527 CVD cases) with targeted follow-up in a case-only study of 1,751 European Ancestry GenHAT participants as well as among 4,141 African-Americans (1,267 CVD cases).
Results
Although drug-SNP interactions were biologically plausible, exposures and outcomes were well measured, and power was sufficient to detect modest interactions, we did not identify any statistically significant interactions from the four antihypertensive therapy meta-analyses (Pinteraction > 5.0×10−8). Similarly, findings were null for meta-analyses restricted to 66 SNPs with significant main effects on coronary artery disease or blood pressure from large published genome-wide association studies (Pinteraction ≥ 0.01). Our results suggest that there are no major pharmacogenetic influences of common SNPs on the relationship between blood pressure medications and the risk of incident CVD
Greater temperature sensitivity of plant phenology at colder sites: implications for convergence across northern latitudes
Warmer temperatures are accelerating the phenology of organisms around the world. Temperature sensitivity of phenology might be greater in colder, higher latitude sites than in warmer regions, in part because small changes in temperature constitute greater relative changes in thermal balance at colder sites. To test this hypothesis, we examined up to 20 years of phenology data for 47 tundra plant species at 18 high-latitude sites along a climatic gradient. Across all species, the timing of leaf emergence and flowering was more sensitive to a given increase in summer temperature at colder than warmer high-latitude locations. A similar pattern was seen over time for the flowering phenology of a widespread species, Cassiope tetragona. These are among the first results highlighting differential phenological responses of plants across a climatic gradient and suggest the possibility of convergence in flowering times and therefore an increase in gene flow across latitudes as the climate warms
Dynamics and nucleation of dislocations in crystals
Hydrogen-poor superluminous supernovae (SLSNe-I) have been predominantly
found in low-metallicity, star-forming dwarf galaxies. Here we identify
Gaia17biu/SN 2017egm as an SLSN-I occurring in a "normal" spiral galaxy (NGC
3191) in terms of stellar mass (several times 10^10 M_sun) and metallicity
(roughly Solar). At redshift z=0.031, Gaia17biu is also the lowest redshift
SLSN-I to date, and the absence of a larger population of SLSNe-I in dwarf
galaxies of similar redshift suggests that metallicity is likely less important
to the production of SLSNe-I than previously believed. With the smallest
distance and highest apparent brightness for an SLSN-I, we are able to study
Gaia17biu in unprecedented detail. Its pre-peak near-ultraviolet to optical
color is similar to that of Gaia16apd and among the bluest observed for an
SLSN-I while its peak luminosity (M_g = -21 mag) is substantially lower than
Gaia16apd. Thanks to the high signal-to-noise ratios of our spectra, we
identify several new spectroscopic features that may help to probe the
properties of these enigmatic explosions. We detect polarization at the ~0.5%
level that is not strongly dependent on wavelength, suggesting a modest, global
departure from spherical symmetry. In addition, we put the tightest upper limit
yet on the radio luminosity of an SLSN-I with <5.4x10^26 erg/s/Hz (at 10 GHz),
which is almost a factor of 40 better than previous upper limits and one of the
few measured at an early stage in the evolution of an SLSN-I. This limit
largely rules out an association of this SLSNe-I with known populations of
gamma-ray burst (GRB) like central engines.Comment: Accepted for publication in ApJ. Ancillary ASCII tables added:
TRL.txt -- blackbody temperature, radius and luminosity; uvw2uvm2uvw1uvu.txt
-- UV photometry; BgVri.txt -- optical photometry; zJHK.txt -- NIR photometr
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