Scenarios of Future Climate and LandManagement Ef

Authors: Analia Carrera Jorge Ares Juan Labraga Stephanie Thurner Mónica Bertiller

Publish Date: 2007/09/06

Volume: 40, Issue: 6, Pages: 944-957

PDF Link

Abstract

We analyzed the possible effects of grazing management and future climate change on carbon C stocks in soils of northern Patagonian shrublands To this aim we coupled the outputs of three HadCM3 CSIRO Mk2 and CCSR/NIES global climate models to the CENTURY v53 model of terrestrial C balance The CENTURY model was initialized with longterm field data on local biome physiognomy seasonal phenologic trends and prevailing landmanagement systems and was validated with recent sequences of 1km Normalized Difference Vegetation Index MODISTerra images and soil C data In the tested scenarios the predicted climate changes would result in increased total C in soil organic matter SOMTC Maximum SOMTC under changed climate forcing would not differ significantly from that expected under baseline conditions 8 kg m−2 A decrease in grazing intensity would result in SOMTC increases of 11 to 12 even if climate changes did not occur Climate change would account for SOMTC increases of 5 to 6All satellite data were obtained through the Earth Observation System Data Gateway We are grateful to the IPCC Data Distribution Centre for the results from AOGC model runs This study was funded by Agencia Nacional de Promoción de Ciencia y Tecnología BID 1201/OCAR PICT0806027 and PICT0811131 A A Carrera was a fellow from Consejo Nacional de Investigaciones Científicas y Técnicas under the direction of M Bertiller and the codirection of J AresA simulation algorithm was used in this study to generate expected monthly precipitation and air temperature series at the Patagonian Monte during the current century under the assumption that no climate change would occur This represented a baseline condition for comparison of the various changes predicted by the AOGC models The algorithm uses EPRA meteorologic station data gathered during 1900 to 2003 to infer the characteristics of their Probability Distribution Functions PDFs Then the PDFs were convoluted to derive data realizations that mimic the observed time seriesWe used NOAAAVHRR 1km 10day composites of the area Kidwell 1995 obtained during the period April 1992 to April 1996 to estimate regional spatial fields of average air temperature T air The radiance values at Band 4 T 4 were rescaled with respect to the average values of 20 image pixels encircling the area of coverage of EPRA data corrected to °C and correlated to EPRA air temperature data Altitude correction was achieved based on reported regional temperature–altitude profiles Coronato 1992 and a 1km Digital Elevation Model EOS Data Gateway http//edcdaacusgsgov/gtopo30/gtopo30asp These resulted in a time series of 65 regional thermal images during 1992 to 1996 Time profiles of the image series were obtained at 73 gridcorner points covering the region and each profile was fitted to a sinusoidal trend wavelength 365 days Maximum max and minimum min fitted average amplitude and phase Av Am Ph respectively values of the sinusoidal trends were used to construct combined estimates of minimum minAv minAm minPh and maximum maxAv maxAm maxPh values of the regional thermal ranges of variation Similarly regional timeserial fields of precipitation P over the Patagonian Monte were calculated through a series of NOAAAVHRR images by applying the procedure described by Andersen 1996 This uses the zenithal instantaneous position of the AVHRR sensor Zenith Band and the recorded radiances at Bands 4 to 5 to generate images of the amount of atmospheric precipitable water P Water The procedure resulted in 65 regional P Water image 16day composite images during 1992 to 1996 These were rescaled to P values at ground level by calibration with 20 pixels surrounding the area of coverage of EPRA P ground data The imagebased P fields were then transformed to precipitationratio P r fields by dividing all pixel values by the average P at the 20 EPRAcalibrated pixels This produced P r maps describing the magnitude of regional anomalies of P with respect to simultaneous precipitation events at the EPRA site The ranges of P anomalies were further stochastically sampled to generate an estimate of the regional variability of precipitation events

Keywords: