Geology topics

T.G. Gilmanov

Publications and source records attributed to T.G. Gilmanov.

4 recordsLinked to original sources

USGS2011

Using normalized difference vegetation index to estimate carbon fluxes from small rotationally grazed pastures

Satellite-based normalized difference vegetation index (NDVI) data have been extensively used for estimating gross primary productivity (GPP) and yield of grazing lands throughout the world. However, the usefulness of satellite-based images for monitoring rotationally-grazed pastures in the northeastern United States might be limited because paddock size is often smaller than the resolution limits of the satellite image. This research compared NDVI data from satellites with data obtained using a ground-based system capable of fine-scale (submeter) NDVI measurements. Gross primary productivity was measured by eddy covariance on two pastures in central Pennsylvania from 2003 to 2008. Weekly 250-m resolution satellite NDVI estimates were also obtained for each pasture from the moderate resolution imaging spectroradiometer (MODIS) sensor. Ground-based NDVI data were periodically collected in 2006, 2007, and 2008 from one of the two pastures. Multiple-regression and regression-tree estimates of GPP, based primarily on MODIS 7-d NDVI and on-site measurements of photosynthetically active radiation (PAR), were generally able to predict growing-season GPP to within an average of 3% of measured values. The exception was drought years when estimated and measured GPP differed from each other by 11 to 13%. Ground-based measurements improved the ability of vegetation indices to capture short-term grazing management effects on GPP. However, the eMODIS product appeared to be adequate for regional GPP estimates where total growing-season GPP across a wide area would be of greater interest than short-term management-induced changes in GPP at individual sites.

Pennsylvania↗

USGS2007

Adaptive data-driven models for estimating carbon fluxes in the Northern Great Plains

Rangeland carbon fluxes are highly variable in both space and time. Given the expansive areas of rangelands, how rangelands respond to climatic variation, management, and soil potential is important to understanding carbon dynamics. Rangeland carbon fluxes associated with Net Ecosystem Exchange (NEE) were measured from multiple year data sets at five flux tower locations in the Northern Great Plains. These flux tower measurements were combined with 1-km2 spatial data sets of Photosynthetically Active Radiation (PAR), Normalized Difference Vegetation Index (NDVI), temperature, precipitation, seasonal NDVI metrics, and soil characteristics. Flux tower measurements were used to train and select variables for a rule-based piece-wise regression model. The accuracy and stability of the model were assessed through random cross-validation and cross-validation by site and year. Estimates of NEE were produced for each 10-day period during each growing season from 1998 to 2001. Growing season carbon flux estimates were combined with winter flux estimates to derive and map annual estimates of NEE. The rule-based piece-wise regression model is a dynamic, adaptive model that captures the relationships of the spatial data to NEE as conditions evolve throughout the growing season. The carbon dynamics in the Northern Great Plains proved to be in near equilibrium, serving as a small carbon sink in 1999 and as a small carbon source in 1998, 2000, and 2001. Patterns of carbon sinks and sources are very complex, with the carbon dynamics tilting toward sources in the drier west and toward sinks in the east and near the mountains in the extreme west. Significant local variability exists, which initial investigations suggest are likely related to local climate variability, soil properties, and management.

Remote Sensing of Environment↗

USGS2006

Long-term dynamics of production, respiration, and net CO 2 exchange in two sagebrush-steppe ecosystems

We present a synthesis of long-term measurements of CO 2 exchange in 2 US Intermountain West sagebrush-steppe ecosystems. The locations near Burns, Oregon (1995–2001), and Dubois, Idaho (1996–2001), are part of the AgriFlux Network of the Agricultural Research Service, United States Department of Agriculture. Measurements of net ecosystem CO 2 exchange ( F c ) during the growing season were continuously recorded at flux towers using the Bowen ratio-energy balance technique. Data were partitioned into gross primary productivity ( P g ) and ecosystem respiration ( R e ) using the light-response function method. Wintertime fluxes were measured during 1999/2000 and 2000/2001 and used to model fluxes in other winters. Comparison of daytime respiration derived from light-response analysis with nighttime tower measurements showed close correlation, with daytime respiration being on the average higher than nighttime respiration. Maxima of P g and R e at Burns were both 20 g CO 2 ·m −2 ·d −1 in 1998. Maxima of P g and R e at Dubois were 37 and 35 g CO 2 ·m −2 ·d −1 , respectively, in 1997. Mean annual gross primary production at Burns was 1 111 (range 475–1 715) g CO 2 ·m −2 ·y −1 or about 30% lower than that at Dubois (1 602, range 963–2 162 g CO 2 ·m −2 ·y −1 ). Across the years, both ecosystems were net sinks for atmospheric CO 2 with a mean net ecosystem CO 2 exchange of 82 g CO 2 ·m −2 ·y −1 at Burns and 253 g CO 2 ·m −2 ·y −1 at Dubois, but on a yearly basis either site could be a C sink or source, mostly depending on precipitation timing and amount. Total annual precipitation is not a good predictor of carbon sequestration across sites. Our results suggest that F c should be partitioned into P g and R e components to allow prediction of seasonal and yearly dynamics of CO 2 fluxes.

Rangeland Ecology and Management↗

USGS2004

Intra-seasonal mapping of CO 2 flux in rangelands of northern Kazakhstan at one-kilometer resolution

Algorithms that establish relationships between variables obtained through remote sensing and geographic information system (GIS) technologies are needed to allow the scaling up of site-specific CO2 flux measurements to regional levels. We obtained Bowen ratio-energy balance (BREB) flux tower measurements during the growing seasons of 1998-2000 above a grassland steppe in Kazakhstan. These BREB data were analyzed using ecosystem light-curve equations to quantify 10-day CO2 fluxes associated with gross primary production (GPP) and total respiration (R). Remotely sensed, temporally smoothed normalized difference vegetation index (NDVIsm) and environmental variables were used to develop multiple regression models for the mapping of 10-day CO2 fluxes for the Kazakh steppe. Ten-day GPP was estimated (R 2 = 0.72) by day of year (DOY) and NDVIsm, and 10-day R was estimated (R2 = 0.48) with the estimated GPP and estimated 10-day photosynthetically active radiation (PAR). Regression tree analysis estimated 10-day PAR from latitude, NDVIsm, DOY, and precipitation (R2 = 0.81). Fivefold cross-validation indicated that these algorithms were reasonably robust. GPP, R, and resulting net ecosystem exchange (NEE) were mapped for the Kazakh steppe grassland every 10 days and summed to produce regional growing season estimates of GPP, R, and NEE. Estimates of 10-day NEE agreed well with BREB observations in 2000, showing a slight underestimation in the late summer. Growing season (May to October) mean NEE for Kazakh steppe grasslands was 1.27 Mg C/ha in 2000. Winter flux data were collected during the winter of 2001-2002 and are being analyzed to close the annual carbon budget for the Kazakh steppe. ?? 2004 Springer-Verlag New York, LLC.

Environmental Management↗