Estimating the spatial pattern of soil respiration in Tibetan alpine grasslands using Landsat TM images and MODIS data

Monitoring soil respiration (R-s) at regional scales using images from operational satellites remains a challenge because of the problem in scaling local R-s to the regional scales. In this study, we estimated the spatial distribution of R-s in the Tibetan alpine grasslands as a product of vegetation index (VI). Three kinds of vegetation indices (VIs), that is, normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and modified soil adjusted vegetation index (MSAVI), derived from Landsat Thematic Mapper (TM) and Moderate-resolution Imaging Spectroradiometer (MODIS) surface reflectance product were selected to test our method. Different statistical models were used to analyze the relationships among the three VIs and R-s. The results showed that, based on the remote sensing data from either MODIS or Landsat TM, exponential function was the optimal fit function for describing the relationships among VIs and R-s during the peak growing season of alpine grasslands. Additionally, NDVI consistently showed higher explanation capacity for the spatial variation in R-s than EVI and MSAVI. Thus, we used the exponential function of TM-based NDVI as the R-s predictor model. Since it is difficult to achieve full spatial coverage of the entire study area with Landsat TM images only, we used the MODIS 8-day composite images to obtain the spatial extrapolation of plot-level R-s after converting the NDVI_MODIS into its corresponding NDVI_TM. The performance of the R-s predictor model was validated by comparing it with the field measured R-s using an independent dataset. The TM-calibrated MODIS-estimated R-s was within an accuracy of field measured R-s with R-2 of 0.78 and root mean square error of 1.45 gC m(-2) d(-1). At the peak growing season of alpine grasslands, R-s was generally much higher in the southeastern part of the Tibetan Plateau and gradually decreased toward the northwestern part. Satellite remote sensing demonstrated the potential for the large scale mapping of R-s in this study. (C) 2012 Elsevier Ltd. All rights reserved.

[1]  R. Betts,et al.  Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model , 2000, Nature.

[2]  T. Niu,et al.  The characteristics of climate change over the Tibetan Plateau in the last 40 years and the detection of climatic jumps , 2004 .

[3]  Shaohong Wu,et al.  Vegetation distribution on Tibetan Plateau under climate change scenario , 2011 .

[4]  Yuhong He,et al.  Estimation of leaf CO2 exchange rates using a SPOT image , 2011 .

[5]  B. Hansen.  Monitoring natural vegetation in Southern Greenland using NOAA AVHRR and field measurements , 1991 .

[6]  C. Schadt,et al.  Labile soil carbon inputs mediate the soil microbial community composition and plant residue decomposition rates. , 2010, The New phytologist.

[7]  Jianwu Tang,et al.  Tree photosynthesis modulates soil respiration on a diurnal time scale , 2005 .

[8]  J. Moncrieff,et al.  Soil CO2 efflux and its spatial variation in a Florida slash pine plantation , 1998, Plant and Soil.

[9]  R. M. Hoffer,et al.  Biomass estimation on grazed and ungrazed rangelands using spectral indices , 1998 .

[10]  Wei Zhang,et al.  The relationship between NDVI and precipitation on the Tibetan Plateau , 2007 .

[11]  Shaopeng Wang,et al.  Soil Respiration in Tibetan Alpine Grasslands: Belowground Biomass and Soil Moisture, but Not Soil Temperature, Best Explain the Large-Scale Patterns , 2012, PloS one.

[12]  A. Huete,et al.  Normalization of multidirectional red and NIR reflectances with the SAVI , 1992 .

[13]  Andrew K. Skidmore,et al.  Integration of multi-sensor data to assess grassland dynamics in a Yellow River sub-watershed , 2012 .

[14]  Zhao Jin,et al.  Seasonal patterns of soil respiration in three types of communities along grass-desert shrub transition in Inner Mongolia, China , 2009 .

[15]  E. Schulze,et al.  Response of mycorrhizal, rhizosphere and soil basal respiration to temperature and photosynthesis in a barley field , 2007 .

[16]  Meixue Yang,et al.  Comparison analysis of the summer monsoon precipitation between northern and southern slopes of Tanggula Mountains, Qinghai–Xizang (Tibetan) Plateau: a case study in summer 1998 , 2007 .

[17]  J. A. Schell,et al.  Monitoring the Vernal Advancement and Retrogradation (Green Wave Effect) of Natural Vegetation. [Great Plains Corridor] , 1973 .

[18]  Steven W. Running,et al.  Applying Improved Estimates of MODIS Productivity to Characterize Grassland Vegetation Dynamics , 2006 .

[19]  A. Huete,et al.  A Modified Soil Adjusted Vegetation Index , 1994 .

[20]  José A. Sobrino,et al.  Accelerated Changes of Environmental Conditions on the Tibetan Plateau Caused by Climate Change , 2011 .

[21]  Jingyun Fang,et al.  Aboveground biomass in Tibetan grasslands , 2009 .

[22]  Qinxue Wang,et al.  Estimation of soil respiration in a paddy ecosystem in the subtropical region of China , 2007 .

[23]  C. Malmström,et al.  The effects of phenology on indirect measures of aboveground biomass in annual grasses , 2009 .

[24]  A. Huete.  A soil-adjusted vegetation index (SAVI) , 1988 .

[25]  Ole Wendroth,et al.  Assessment of Pasture Biomass with the Normalized Difference Vegetation Index from Active Ground-Based Sensors , 2008 .

[26]  J. Balogh,et al.  Dependence of soil respiration on soil moisture, clay content, soil organic matter, and CO2 uptake in dry grasslands , 2011 .

[27]  Andreas Buerkert,et al.  Quantification of aboveground rangeland productivity and anthropogenic degradation on the Arabian Peninsula using Landsat imagery and field inventory data , 2011 .

[28]  Moon-Soo Park,et al.  Estimation of soil respiration using automated chamber systems in an oak (Quercus mongolica) forest at the Nam-San site in Seoul, Korea. , 2012, The Science of the total environment.

[29]  W. Post,et al.  Modeling soil respiration and variations in source components using a multi-factor global climate change experiment , 2011 .

[30]  Jin Chen,et al.  Estimating aboveground biomass of grassland having a high canopy cover: an exploratory analysis of in situ hyperspectral data , 2009 .

[31]  Chaoyang Wu,et al.  Modeling net primary production of a fast-growing forest using a light use efficiency model , 2010 .

[32]  W. Schlesinger,et al.  The global carbon dioxide flux in soil respiration and its relationship to vegetation and climate , 1992 .

[33]  José M. Paruelo,et al.  REGIONAL PATTERNS OF NORMALIZED DIFFERENCE VEGETATION INDEX IN NORTH AMERICAN SHRUBLANDS AND GRASSLANDS , 1995 .

[34]  E. Pendall,et al.  Elevated CO2 stimulates soil respiration in a FACE wheat field , 2001 .

[35]  J. Qi,et al.  Remote Sensing for Grassland Management in the Arid Southwest , 2006 .

[36]  Jeffrey A. Andrews,et al.  Soil respiration and the global carbon cycle , 2000 .

[37]  Yang Yang,et al.  Biotic and abiotic factors controlling the spatial and temporal variation of soil respiration in an agricultural ecosystem , 2007 .

[38]  R. Jackson,et al.  Spectral response of a plant canopy with different soil backgrounds , 1985 .

[39]  Dingwen Zhou,et al.  Interannual variability of the normalized difference vegetation index on the Tibetan Plateau and its relationship with climate change , 2007 .

[40]  N. Bader,et al.  Rhizosphere priming effect of Populus fremontii obscures the temperature sensitivity of soil organic carbon respiration , 2007 .

[41]  J. Qi,et al.  A comparative analysis of broadband and narrowband derived vegetation indices in predicting LAI and CCD of a cotton canopy , 2007 .

[42]  B. Wylie,et al.  Satellite mapping of surface biophysical parameters at the biome scale over the North American grasslands a case study , 2002 .

[43]  F. Chapin,et al.  Predominance of ecophysiological controls on soil CO2 flux in a Minnesota grassland , 1999, Plant and Soil.

[44]  D. O. Hall,et al.  The global carbon sink: a grassland perspective , 1998 .

[45]  Limin Yang,et al.  COMPLETION OF THE 1990S NATIONAL LAND COVER DATA SET FOR THE CONTERMINOUS UNITED STATES FROM LANDSAT THEMATIC MAPPER DATA AND ANCILLARY DATA SOURCES , 2001 .

[46]  N. Buchmann,et al.  Large-scale forest girdling shows that current photosynthesis drives soil respiration , 2001, Nature.

[47]  J. Mustard,et al.  Cross-scalar satellite phenology from ground, Landsat, and MODIS data , 2007 .

[48]  S. Trumbore.  Carbon respired by terrestrial ecosystems – recent progress and challenges , 2006 .

[49]  Y. Nouvellon,et al.  Soil carbon balance in a tropical grassland: Estimation of soil respiration and its partitioning using a semi-empirical model , 2012 .

[50]  Yaoming Ma,et al.  Assessment of vegetation dynamics and their response to variations in precipitation and temperature in the Tibetan Plateau , 2010 .

[51]  Yanfen Wang,et al.  Effect of water stress on ecosystem photosynthesis and respiration of a Leymus chinensis steppe in Inner Mongolia , 2006 .

[52]  T. Yao,et al.  Review of climate and cryospheric change in the Tibetan Plateau , 2010 .

[53]  A. Huete,et al.  Overview of the radiometric and biophysical performance of the MODIS vegetation indices , 2002 .

[54]  Christopher B. Field,et al.  Diverse responses of phenology to global changes in a grassland ecosystem , 2006, Proceedings of the National Academy of Sciences.

[55]  Y. Kuzyakov,et al.  Root and rhizomicrobial respiration: A review of approaches to estimate respiration by autotrophic and heterotrophic organisms in soil , 2005 .