Geology Reports⌕ Search

Geology topics

D.S. Ojima

Publications and source records attributed to D.S. Ojima.

6 recordsLinked to original sources
USGS2006

Vegetation greenness impacts on maximum and minimum temperatures in northeast Colorado

The impact of vegetation on the microclimate has not been adequately considered in the analysis of temperature forecasting and modelling. To fill part of this gap, the following study was undertaken. A daily 850–700 mb layer mean temperature, computed from the National Center for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR) reanalysis, and satellite-derived greenness values, as defined by NDVI (Normalised Difference Vegetation Index), were correlated with surface maximum and minimum temperatures at six sites in northeast Colorado for the years 1989–98. The NDVI values, representing landscape greenness, act as a proxy for latent heat partitioning via transpiration. These sites encompass a wide array of environments, from irrigated-urban to short-grass prairie. The explained variance (r 2 value) of surface maximum and minimum temperature by only the 850–700 mb layer mean temperature was subtracted from the corresponding explained variance by the 850–700 mb layer mean temperature and NDVI values. The subtraction shows that by including NDVI values in the analysis, the r 2 values, and thus the degree of explanation of the surface temperatures, increase by a mean of 6% for the maxima and 8% for the minima over the period March–October. At most sites, there is a seasonal dependence in the explained variance of the maximum temperatures because of the seasonal cycle of plant growth and senescence. Between individual sites, the highest increase in explained variance occurred at the site with the least amount of anthropogenic influence. This work suggests the vegetation state needs to be included as a factor in surface temperature forecasting, numerical modeling, and climate change assessments.

Meteorological Applications↗
USGS2004

Changes in plant functional groups, litter quality, and soil carbon and nitrogen mineralization with sheep grazing in an Inner Mongolian Grassland

This study reports on changes in plant functional group composition, litter quality, and soil C and N mineralization dynamics from a 9-year sheep grazing study in Inner Mongolia. Addressed are these questions: 1) How does increasing grazing intensity affect plant community composition? 2) How does increasing grazing intensity alter soil C and N mineralization dynamics? 3) Do changes in soil C and N mineralization dynamics relate to changes in plant community composition via inputs of the quality or quantity of litter? Grazing plots were set up near the Inner Mongolia Grassland Ecosystem Research Station (IMGERS) with 5 grazing intensities: 1.3, 2.7, 4.0, 5.3, and 6.7 sheep ha −1 ·yr −1 . Plant cover was lower with increasing grazing intensity, which was primarily due to a dramatic decline in grasses, Carex duriuscula , and Artemisia frigida . Changes in litter mass and percentage organic C resulted in lower total C in the litter layer at 4.0 and 5.3 sheep ha −1 ·yr −1 compared with 2.7 sheep ha −1 ·yr −1 . Total litter N was lower at 5.3 sheep ha −1 ·yr −1 compared with 2.7 sheep ha −1 ·yr −1 . Litter C:N ratios, an index of litter quality, were significantly lower at 4.0 sheep ha −1 ·yr −1 relative to 1.3 and 5.3 sheep ha −1 ·yr −1 . Cumulative C mineralized after 16 days decreased with increasing grazing intensity. In contrast, net N mineralization ( NH 4 NO − 3 ) after a 12-day incubation increased with increasing grazing intensity. Changes in C and N mineralization resulted in a narrowing of CO 2 -C:net N min ratios with increasing grazing intensity. Grazing explained 31% of the variability in the ratio of CO 2 -C:net N min . The ratio of CO 2 -C:net N min was positively correlated with litter mass. Furthermore, there was a positive correlation between litter mass and A. frigida cover. Results suggest that as grazing intensity increases, microbes become more C limited resulting in decreased microbial growth and demand for N.

Journal of Range Management↗
USGS2004

VEMAP Phase 2 bioclimatic database. I. Gridded historical (20th century) climate for modeling ecosystem dynamics across the conterminous USA

Analysis and simulation of biospheric responses to historical forcing require surface climate data that capture those aspects of climate that control ecological processes, including key spatial gradients and modes of temporal variability. We developed a multivariate, gridded historical climate dataset for the conterminous USA as a common input database for the Vegetation/Ecosystem Modeling and Analysis Project (VEMAP), a biogeochemical and dynamic vegetation model intercomparison. The dataset covers the period 1895—1993 on a 0.5° latitude/longitude grid. Climate is represented at both monthly and daily timesteps. Variables are: precipitation, mininimum and maximum temperature, total incident solar radiation, daylight-period irradiance, vapor pressure, and daylight-period relative humidity. The dataset was derived from US Historical Climate Network (HCN), cooperative network, and snowpack telemetry (SNOTEL) monthly precipitation and mean minimum and maximum temperature station data. We employed techniques that rely on geostatistical and physical relationships to create the temporally and spatially complete dataset. We developed a local kriging prediction model to infill discontinuous and limited-length station records based on spatial autocorrelation structure of climate anomalies. A spatial interpolation model (PRISM) that accounts for physiographic controls was used to grid the infilled monthly station data. We implemented a stochastic weather generator (modified WGEN) to disaggregate the gridded monthly series to dailies. Radiation and humidity variables were estimated from the dailies using a physically-based empirical surface climate model (MTCLIM3). Derived datasets include a 100 yr model spin-up climate and a historical Palmer Drought Severity Index (PDSI) dataset. The VEMAP dataset exhibits statistically significant trends in temperature, precipitation, solar radiation, vapor pressure, and PDSI for US National Assessment regions. The historical climate and companion datasets are available online at data archive centers.

Climate Research↗
USGS2002

Using simple environmental variables to estimate below-ground productivity in grasslands

In many temperate and annual grasslands, above-ground net primary productivity (NPP) can be estimated by measuring peak above-ground biomass. Estimates of below-ground net primary productivity and, consequently, total net primary productivity, are more difficult. We addressed one of the three main objectives of the Global Primary Productivity Data Initiative for grassland systems to develop simple models or algorithms to estimate missing components of total system NPP. Any estimate of below-ground NPP (BNPP) requires an accounting of total root biomass, the percentage of living biomass and annual turnover of live roots. We derived a relationship using above-ground peak biomass and mean annual temperature as predictors of below-ground biomass (r2 = 0.54; P = 0.01). The percentage of live material was 0.6, based on published values. We used three different functions to describe root turnover: constant, a direct function of above-ground biomass, or as a positive exponential relationship with mean annual temperature. We tested the various models against a large database of global grassland NPP and the constant turnover and direct function models were approximately equally descriptive (r2 = 0.31 and 0.37), while the exponential function had a stronger correlation with the measured values (r2 = 0.40) and had a better fit than the other two models at the productive end of the BNPP gradient. When applied to extensive data we assembled from two grassland sites with reliable estimates of total NPP, the direct function was most effective, especially at lower productivity sites. We provide some caveats for its use in systems that lie at the extremes of the grassland gradient and stress that there are large uncertainties associated with measured and modelled estimates of BNPP.

Global Ecology and Biogeography↗
USGS1999

Dynamic replacement and loss of soil carbon on eroding cropland

Links between erosion/sedimentation history and soil carbon cycling were examined in a highly erosive setting in Mississippi loess soils. We sampled soils on (relatively) undisturbed and cropped hillslopes and measured C, N, 14 C, and CO 2 flux to characterize carbon storage and dynamics and to parameterize Century and spreadsheet 14 C models for different erosion and tillage histories. For this site, where 100 years of intensive cotton cropping were followed by fertilization and contour plowing, there was an initial and dramatic decline in soil carbon content from 1870 to 1950, followed by a dramatic increase in soil carbon. Soil erosion amplifies C loss and recovery: About 100% of the original, prehistoric soil carbon was likely lost over 127 years of intensive land use, but about 30% of that carbon was replaced after 1950. The eroded cropland was therefore a local sink for CO 2 since the 1950s. However, a net CO 2 sink requires a full accounting of eroded carbon, which in turn requires that decomposition rates in lower slopes or wetlands be reduced to about 20% of the upland value. As a result, erosion may induce unaccounted sinks or sources of CO 2 , depending on the fate of eroded carbon and its protection from decomposition. For erosion rates typical of the United States, the sink terms may be large enough (1 Gt yr −1 , back‐of‐the‐envelope) to warrant a careful accounting of site management, cropping, and fertilization histories, as well as burial rates, for a more meaningful global assessment.

Global Biogeochemical Cycles↗