Scale Impacts in Net Ecosystem Productivity Estimations

Net ecosystem production (NEP) estimations play a key role in the terrestrial carbon cycle assessment, both at regional and global scales studies. The emergence of remote sensing greatly improved NEP estimation methods and analysis domain. Yet, spatial and temporal resolution of sensors and remote sensing products often imply adjustments to NEP calculation methods. The Carnegie Ames Stanford Approach (CASA) terrestrial biogeochemical model (Potter et al., 1993; Friedlingstein et al., 1999) simulates plant and soil processes allowing the estimation of NEP through the difference between net primary productivity and soil respiration. CASA inputs include climatic data: precipitation, temperature and solar radiation; soil texture; vegetation type and percentage cover; as well as leaf area index (LAI), fraction of photosynthetically active radiation absorbed by vegetation (FPAR) and normalized difference vegetation index (NDVI). With a research interest in regional vegetation dynamics in the Iberian Peninsula (IP), estimations of NEP were compared with local measurements over a Quercus ilex and Quercus suber with perennial grassland ecosystem, representing a region characteristic land cover. The CASA calibration process aimed the tuning of efficiency scalars directly related to net primary productivity and soil respiration calculations, maximum light use efficiency (å*) and temperature effect on soil fluxes (Q10). To this end local weather station data was used as climatic inputs, with remotely sensed LAI, FPAR and NDVI products from MODIS sensor. In a first approach the NEP calculations were performed at a finer spatial and temporal resolution of 1 km and 8 days, respectively, for the periods of 2002 and 2003 (years of available NEP measurements). A confident correlation is found, although local extremes tend to differ and affect the annual balance concordance between estimations and measurements of NEP. Consequently, calibrated å* and Q10 values were used at coarser temporal and spatial resolutions, whose varying correlation results will be presented, as well as results for the scalars calibration at different temporal and spatial scales. Accordingly, NEP modeling results for the IP are presented, as well as an analysis of the impact of temperature and precipitation fields in the dynamic trends of vegetation spatial patterns and intra-annual behavior.