The modulating effect of CO2 on the circulatory response to hypoxia in chronically instrumented conscious dogs was examined over a wide range of arterial partial pressure of O2 [PaO2 (from 80 to 25 Torr)] during a 41-min rebreathing period at three CO2 levels: hypocapnia (from PaCO2 of 32 to 18 Torr), eucapnia (32 Torr), and mild hypercapnia (40 Torr). Eucapnic and hypercapnic hypoxic responses were also measured after sinoaortic denervation (SAD) to assess the arterial chemoreceptor and baroreceptor reflex contributions. Elevating PaCO2 attenuated the tachycardia during hypoxia and produced progressively greater systemic, renal, and splanchnic vasoconstriction before but not after SAD. Vagal block converted the rises in renal and splanchnic flows observed during hypocapnic hypoxia to declines. The increase in left ventricular dP/dtmax was not affected by varying PaCO2 either before or after SAD. Coronary flow increased an additional onefold during hypoxia when PaCO2 was elevated both before and after SAD, but the tension-time indices did not differ significantly. These results indicate that: a) cardiopulmonary vagal afferents effectively counteract chemoreflex-induced vasoconstriction during hypocapnic hypoxia; b) chemoreflex vasoconstriction predominates in the renal and splanchnic beds when PaCO2 is elevated; c) the sinoaortic reflexes restrain the heart rate, but not the contractility response to hypoxia when PaCO2 is increased; and d) the augmented coronary vasodilation produced by CO2 is probably mediated by local CO2-hypoxic interactions.

Abstract. The Ice, Cloud and Land Elevation Satellite-II (ICESat-2) mission has been selected by NASA as a Decadal Survey mission, to be launched in 2016. Mission objectives are to measure land ice elevation, sea ice freeboard/ thickness and changes in these variables and to collect measurements over vegetation that will facilitate determination of canopy height, with an accuracy that will allow prediction of future environmental changes and estimation of sea-level rise. The importance of the ICESat-2 project in estimation of biomass and carbon levels has increased substantially, following the recent cancellation of all other planned NASA missions with vegetation-surveying lidars.Two innovative components will characterize the ICESat-2 lidar: (1) Collection of elevation data by a multi-beam system and (2) application of micropulse lidar (photon counting) technology. A micropulse photon-counting altimeter yields clouds of discrete points, which result from returns of individual photons, and hence new data analysis techniques are required for elevation determination and association of returned points to reflectors of interest including canopy and ground in forested areas.The objective of this paper is to derive and validate an algorithm that allows detection of ground under dense canopy and identification of ground and canopy levels in simulated ICESat-2-type data. Data are based on airborne observations with a SigmaSpace micropulse lidar and vary with respect to signal strength, noise levels, photon sampling options and other properties. A mathematical algorithm is developed, using spatial statistical and discrete mathematical concepts, including radial basis functions, density measures, geometrical anisotropy, eigenvectors and geostatistical classification parameters and hyperparameters. Validation shows that the algorithm works very well and that ground and canopy elevation, and hence canopy height, can be expected to be observable with a high accuracy during the ICESat-2 mission. A result relevant for instrument design is that even the two weaker beam classes considered can be expected to yield useful results for vegetation measurements (93.01-99.57% correctly selected points for a beam with expected return of 0.93 mean signals per shot (msp9) and 72.85% -98.68% for 0.48 msp (msp4)). Resampling options affect 1 https://ntrs.nasa.gov/search.jsp?R=20120012964 2019-06-20T00:45:47+00:00Z results more than noise levels. The algorithm derived here is generally applicable for analysis of micropulse lidar altimeter data collected over forested areas as well as other surfaces, including land ice, sea ice and land surfaces. (1) IntroductionDetermination of vegetation height of the Earth's forests is an essential requirement in estimation of global and regional biomass and carbon levels. Because of the scale of the problem and the inaccessibility of many of the Earth's forested areas, this is best achieved from satellite. NASA's Ice, Cloud and Land Elevation Satellite (ICESat) mission (2003)(2004)(2005)(2006)(2007)(2008)...

The Bering Glacier–Bagley Icefield system in Alaska is currently surging (2011). Large-scale elevation changes and small-scale elevation-change characteristics are investigated to understand surge progression, especially mass transport from the pre-surge reservoir area to the receiving area and propagation of the kinematic surge wave as manifested in heavy crevassing characteristic of rapid, brittle deformation. This analysis is based on airborne laser altimeter data collected over Bering Glacier in September 2011. Results include the following: (1) Maximal crevasse depth is 60 m, reached in a rift that separates two deformation domains, indicative of two different flow regimes. Otherwise surge crevasse depth reaches 20–30 m. (2) Characteristic parameters of structural provinces are derived by application of geostatistical classification. Parameters include significance and spacing of crevasses, surface roughness and crevasse-edge curvature (indicative of crevasse age). A classification based on these parameters serves to objectively discriminate structural provinces, indicative of surge progression down-glacier and up-glacier. (3) Elevation changes from 2011 and 2010 altimetry show 40–70 m surface lowering in the reservoir area in lower central Bering Glacier and 20–40m thickening near the front in Tashalich arm. Combining elevation changes with results of crevasse profilometry and pattern analysis, the rapid progression of the surge can be mathematically–physically reconstructed.

Microdochium patch is an important turfgrass disease in cool‐humid regions and is caused by the pathogen Microdochium nivale (Fries) Samuels & Hallett. Control of the pathogen is necessary to provide acceptable putting‐green‐quality turf, and fungicide applications are the predominant method of control. Increasing pesticide restrictions have generated interest in alternative management techniques of Microdochium patch. This research evaluated the effects of three nitrogen and five iron sulfate rates on Microdochium patch development on a trafficked, sand‐based, annual bluegrass (Poa annua L.) putting green in Corvallis, OR for over 2 yr in the absence of fungicides. Data included turf quality, area under disease progress curve, and soil test results of saturated paste extract pH, cation extractable sulfate, and DTPA‐sorbitol extractable iron. This research provided evidence that low rates of urea (4.88 kg N ha−1) applied every 2 wk did not lead to an increase in Microdochium patch severity and that iron sulfate applications decreased Microdochium patch on annual bluegrass putting greens. Despite the disease suppression observed, no treatment received a turf‐quality rating considered acceptable. Low turf‐quality ratings where disease development was low were attributed to turfgrass thinning or blackening of the shoots resulting from iron sulfate applications. Soil tests provided evidence that the highest iron sulfate level used in this study (97.65 kg ha−1) applied every 2 wk would likely lead to a lower soil pH and an increase in soil sulfate levels.