Geology topics

D.L. Phillips

Publications and source records attributed to D.L. Phillips.

3 recordsLinked to original sources

USGS2006

Effects of elevated CO2 on fine root dynamics in a Mojave Desert community: A FACE study

Fine roots (??? 1mm diameter) are critical in plant water and nutrient absorption, and it is important to understand how rising atmospheric CO2 will affect them as part of terrestrial ecosystem responses to global change. This study's objective was to determine effects of elevated CO2 on production, mortality, and standing crops of fine root length over 2 years in a free-air CO2 enrichment (FACE) facility in the Mojave Desert of southern Nevada, USA. Three replicate 25m diameter FACE rings were maintained at ambient (??? 370 ??mol mol-1) and elevated CO2 (??? 550 ??mol mol-1) atmospheric concentrations. Twenty-eight minirhizotron tubes were placed in each ring to sample three microsite locations: evergreen Larrea shrubs, drought-deciduous Ambrosia shrubs, and along systematic community transects (primarily in shrub interspaces which account for ??? 85% of the area). Seasonal dynamics were similar for ambient and elevated CO2: fine root production peaked in April-June, with peak standing crop occurring about 1 month later, and peak mortality occurring during the hot summer months, with higher values for all three measures in a wet year compared with a dry year. Fine root standing crop, production, and mortality were not significantly different between treatments except standing crop along community transects, where fine root length was significantly lower in elevated CO2. Fine root turnover (annual cumulative mortality/mean standing crop) ranged from 2.33 to 3.17 year-1, and was not significantly different among CO2 treatments, except for community transect tubes where it was significantly lower for elevated CO2. There were no differences in fine root responses to CO2 between evergreen (Larrea) and drought-deciduous (Ambrosia) shrubs. Combined with observations of increased leaf-level water-use efficiency and lack of soil moisture differences, these results suggest that under elevated CO2 conditions, reduced root systems (compared with ambient CO2) appear sufficient to provide resources for modest aboveground production increases across the community, but in more fertile shrub microsites, fine root systems of comparable size with those in ambient CO2 were required to support the greater aboveground production increases. For community transects, development of the difference in fine root standing crops occurred primarily through lower stimulation of fine root production in the elevated CO2 treatment during periods of high water availability. ?? 2005 Blackwell Publishing Ltd.

Global Change Biology↗

USGS2003

Use of sulfur and nitrogen stable isotopes to determine the importance of whitebark pine nuts to Yellowstone grizzly bears

Whitebark pine ( Pinus albicaulis ) is a masting species that produces relatively large, fat- and protein-rich nuts that are consumed by grizzly bears ( Ursus arctos horribilis ). Trees produce abundant nut crops in some years and poor crops in other years. Grizzly bear survival in the Greater Yellowstone Ecosystem is strongly linked to variation in pine-nut availability. Because whitebark pine trees are infected with blister rust ( Cronartium ribicola ), an exotic fungus that has killed the species throughout much of its range in the northern Rocky Mountains, we used stable isotopes to quantify the importance of this food resource to Yellowstone grizzly bears while healthy populations of the trees still exist. Whitebark pine nuts have a sulfur-isotope signature (9.2 ± 1.3 (mean ± 1 SD)) that is distinctly different from those of all other grizzly bear foods (ranging from 1.9 ± 1.7 for all other plants to 3.1 ± 2.6 for ungulates). Feeding trials with captive grizzly bears were used to develop relationships between dietary sulfur-, carbon-, and nitrogen-isotope signatures and those of bear plasma. The sulfur and nitrogen relationships were used to estimate the importance of pine nuts to free-ranging grizzly bears from blood and hair samples collected between 1994 and 2001. During years of poor pine-nut availability, 72% of the bears made minimal use of pine nuts. During years of abundant cone availability, 8 ± 10% of the bears made minimal use of pine nuts, while 67 ± 19% derived over 51% of their assimilated sulfur and nitrogen (i.e., protein) from pine nuts. Pine nuts and meat are two critically important food resources for Yellowstone grizzly bears.

Wyoming↗

USGS1996

Spatial uncertainty analysis: Propagation of interpolation errors in spatially distributed models

In simulation modelling, it is desirable to quantify model uncertainties and provide not only point estimates for output variables but confidence intervals as well. Spatially distributed physical and ecological process models are becoming widely used, with runs being made over a grid of points that represent the landscape. This requires input values at each grid point, which often have to be interpolated from irregularly scattered measurement sites, e.g., weather stations. Interpolation introduces spatially varying errors which propagate through the model We extended established uncertainty analysis methods to a spatial domain for quantifying spatial patterns of input variable interpolation errors and how they propagate through a model to affect the uncertainty of the model output. We applied this to a model of potential evapotranspiration (PET) as a demonstration. We modelled PET for three time periods in 1990 as a function of temperature, humidity, and wind on a 10-km grid across the U.S. portion of the Columbia River Basin. Temperature, humidity, and wind speed were interpolated using kriging from 700- 1000 supporting data points. Kriging standard deviations (SD) were used to quantify the spatially varying interpolation uncertainties. For each of 5693 grid points, 100 Monte Carlo simulations were done, using the kriged values of temperature, humidity, and wind, plus random error terms determined by the kriging SDs and the correlations of interpolation errors among the three variables. For the spring season example, kriging SDs averaged 2.6??C for temperature, 8.7% for relative humidity, and 0.38 m s-1 for wind. The resultant PET estimates had coefficients of variation (CVs) ranging from 14% to 27% for the 10-km grid cells. Maps of PET means and CVs showed the spatial patterns of PET with a measure of its uncertainty due to interpolation of the input variables. This methodology should be applicable to a variety of spatially distributed models using interpolated inputs.

Ecological Modelling↗