Submitted to: Environmental Management
Publication Type: Peer reviewed journal
Publication Acceptance Date: 8/17/2003
Publication Date: 3/4/2004
Citation: Wylie, B.K., Gilmanov, T.G., Johnson, D.A., Saliendra, N.Z., Akshalov, K., Tieszen, L.L., Reed, B.C., Laca, E. 2004. Remote sensing and geographic information system in rangelands of northern kazakhstan: quantification and mapping of seasonal co2 fluxes from bowen ratio-energy balance measurements. Environmental Management 33:S482-S491. Interpretive Summary: Because rangelands cover more than 40% of the earth's land surface, they could potentially be important for storing large amounts of carbon. Towers with a variety of instruments mounted on them were used to measure carbon dioxide exchange at a representative steppe rangeland area in northern Kazakhstan. Because these measurements represent values at specific sites, remote sensing and Geographical Information System (GIS) technologies must be used to estimate carbon dioxide exchange at regional levels. We developed mathematical models that were used to map carbon dioxide exchange during 10-day periods for steppe rangelands in Kazakhstan. Estimates from these models agreed well with actual data for 2000. These procedures will be useful for scaling up carbon dioxide exchange to regional levels in other rangeland ecosystems.
Technical Abstract: 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 fluxes measurements to regional levels. We obtained Bowen ratio-energy balance (BREB) flux tower measurements during the growing seasons of 1998-2000 above a steppe grassland 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 (R2 = 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). Five-fold 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-1 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.