44 research outputs found
Variations in sediment sources and yields in the Finger Lakes and Catskills regions of New York
The proportional contributions of stream bank and surface sources to fine sediment loads in watersheds in New York State were quantified with uncertainty analysis. Eroding streamside glacial drift, including glaciolacustrine deposits, were examined to help explain variations in the proportional contributions made by bank erosion. Sediment sources were quantified by comparing concentrations of the bomb-derived radionuclide 137Cs in fluvial sediment with sediment from potential source areas such as agricultural soils, forest soils and stream banks.
To compare sediment sources in streams containing abundant deposits of fine-grained glacial drift with watersheds that lacked moderate or extensive streamside deposits, samples were taken from 15 watersheds in the region. The mean contribution of bank erosion to sediment loads in the six streams with glaciolacustrine deposits was 60% (range 46?76%). The proportional contribution of bank erosion was also important in one stream lacking glaciolacustrine deposits (57%) but was less important in the remainder, with contributions ranging from 0 to 46%. Data from this study on the varying contributions of bank erosion and data from past studies of sediment yield in 15 watersheds of New York State suggest that eroding streamside glacial
deposits dominate sediment yield in many watersheds. In other watersheds, past impacts to streams, such as channelization, have also resulted in high levels of bank erosion
Distinct serum metabolomics profiles associated with malignant progression in the KrasG12Dmouse model of pancreatic ductal adenocarcinoma
Genetic Drivers of Heterogeneity in Type 2 Diabetes Pathophysiology
Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P \u3c 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care
Genetic drivers of heterogeneity in type 2 diabetes pathophysiology
Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.</p
Variability in soil redistribution in the northern Chihuahuan Desert based on 137Cesium measurements
A hypothesis for understanding the stability of northern Chihuahuan Desert landscapes is that the distribution of soil resources changes from spatially homogeneous in arid grasslands to spatially heterogeneous in invading shrublands. Since radioactive fallout 137Cesium (137Cs) was deposited uniformly across the landscape during the 1950s and 1960s and was quickly adsorbed to soil particles, any redistribution of 137Cs across the landscape would be due to soil redistribution or instability at either plant-interspaces or on a landscape scale. The concentration of 137Cs in soils collected from different vegetation communities (black grama grass, tarbush, tobosa grass, and mesquite) at the USDA-ARS Jornada Experimental Range in the Northern Chihuahuan Desert in New Mexico was determined. At the black grama grass and tobosa grass sites, 137Cs was uniformly distributed at the plant interspace scale. At the mesquite sites, 137Cs was concentrated in the dune area under mesquite shrubs with little to no 137 Cs in the interdune areas. 137Cs data support the hypothesis that significant soil redistribution has occurred at dune sites created by invading mesquite. In the arid grassland-shrub sites with black grama grass, tobosa grass, and tarbush the 137Cs data support the hypothesis of spatially homogeneous distribution of soil resources. High concentrations of 137Cs in the biological soil crusts (0-5 mm) at the tarbush sites indicate that biological soil crusts can contribute tn the stability of these sites
Potential for Semiarid Community Type Differentiation Via Exploitation of the Directional Signal: Tests with AVHRR Data
Community-level vegetation type differentiation is regarded as an important application of remote sensing in monitoring the health of semiarid environments and yet it has proved difficult to discriminate more than two or three community types with confidence when using coarse spatial resolution data from off-nadir scanning sensors such as the AVHRR, even when multi-temporal datasets are used. Attempts to relate vegetation phenology to community type using AVHRR data have produced mixed results and large classification errors have been attributed to subpixel scale topographic and soil background variations, lack of in-flight calibration, inaccurate reflectance retrieval and poor registration. While these are important factors, anisotropy in surface reflectance as a result of the bidirectional reflectance distribution function (BRDF) also causes severe perturbations in the signal and yet this is rarely accounted for adequately. Recent years have seen a wider acknowledgement of this fundamental aspect of optical remote sensing, although it is usually approached as a problem. The extent of the improvement in community type differentiation may be considerable when a BRDF model is used to separate isotropic and anisotropic components. Here this potential is tested using data from the AVHRR over semi-arid regions
Improved Semi-Arid Community Type Differentiation with the NOAA AVHRR Via Exploitation of the Directional Signal
Mapping semi-arid vegetation types at the community level is extremely difficult for optical sensors with large ground footprints such as the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR). Attempts to usc solar wavelength AVHRR data in community type differentiation have often resulted in unacceptable classification errors which are usually attributed to noise from topographic and soil background variations, inaccurate reflectance retrieval and poor registration. One source of variation which is rarely accounted for adequately is the directional signal resulting from the combined effects of the surface bidirectional reflectance distribution function (BRDF) and the variation of viewing and illumination geometry as a function of scan angle, season, latitude and orbital overpass time. In this study, a linear semiempirical kernel-driven (LiSK) BRDF model is used to examine the utility of the directional signal in community and cover type differentiation over discontinuous but statistically homogeneous semi-arid canopies in Inner Mongolia Autonomous Region (IMAR), China, and New Mexico (NM), USA. This research shows that the directional signal resulting from the physical structure of the canopy-soil complex can be retrieved to provide information which is highly complementary to that obtained in the spectral domain
Simulation of Grassland-Shrubland Transition Zone Landscape Images At 650 Nm using a Simple BRDF Model
The objective of this study was to assess the capability of a simple bidirectional reflectance distribution function (BRDF) model to simulate angular 650 nm (red wavelength) images of shrubland landscapes when driven by a small number of spatially-varying structural parameters (mean shrub density and width, together with derived mean canopy height and overall brightness), together with two static parameters (spectral reflectance of leaves and a parametric soil/understory BRDF). It was hypothesized that this simple parameterization will lead to important errors in reconstruction of directional (off-nadir) images, as acquired by a tilting multispectral digital camera at six different viewing directions and three different solar zenith angles in the principal plane. The results show that great care is needed in parameterizing the BRDF in this way and that variations in the brightness of the understory - here represented by grasses, forbs, subshrubs, biotic crusts and bare soil - has an important effect on modeled estimates of bidirectional reflectance in the red wavelengths