<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>3</ref-type><contributors></contributors><titles><title><style face="normal" font="default" size="100%">Adaptation and local validation in a Mediterranean environment of a process-level ecosystem model driven by remotely sensed inputs</style></title><secondary-title><style face="normal" font="default" size="100%">REMOTE SENSING `96: INTEGRATED APPLICATIONS FOR RISK ASSESSMENT AND DISASTER PREVENTION FOR THE MEDITERRANEAN</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1997</style></year></dates><publisher><style face="normal" font="default" size="100%">A A BALKEMA</style></publisher><pub-location><style face="normal" font="default" size="100%">PO BOX 1675, 3000 BR ROTTERDAM, NETHERLANDS</style></pub-location><pages><style face="normal" font="default" size="100%">299-303</style></pages><isbn><style face="normal" font="default" size="100%">90-5410-855-X</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">A process-level ecosystem model (FOREST-BGC) has been used to simulate the short-term variability of functional processes and the slower responding allocation of photosynthesis products to plant components maintenance or growth, and to decomposition. The model emphasises Leaf Area Index (LAI) as a key structural attribute with substantial control over ecosystem process rates. Model simulations (soil water balance, photosynthesis, net primary production,...) have been obtained for a 10 years period (1984-1993) and partially validated with ground measurements from an experimental test site located in Southern France (dominant species: holm oak). Further work include scaling up from local to regional level, using remote sensing inputs and ancillary data.</style></abstract></record></records></xml>