Prediction of hydro-physical attributes from different soil quality indexes

• Grant number: 11/20911-2
• Support Opportunities: Scholarships abroad - Research Internship - Master's degree
• Start date: April 01, 2012
• End date: September 30, 2012
• Field of knowledge: Agronomical Sciences - Agronomy - Soil Science
• Principal Investigator: Miguel Cooper
• Grantee: Thalita Campos Oliveira
• Supervisor: Daniel Giménez
• Host Institution: Escola Superior de Agricultura Luiz de Queiroz (ESALQ). Universidade de São Paulo (USP). Piracicaba , SP, Brazil
• Institution abroad: Rutgers The State University of New Jersey, New Brunswick, United States
• Associated to the scholarship: 11/05453-8 - Prediction of water-physical attributes from different levels of soil quality, BP.MS

Abstract

Originally the Atlantic Forest formed a continuous area covering more than 1.000.000 km2 of Brazilian territory. Nowadays this biome suffers with constant degradation and only 8% of this cover remains, mostly like secondary forest fragments.This study was located in a permanent plot located inside the Caetetus Ecological Station, which has one of the most significant remnants of semi deciduous forest of São Paulo. Aspects of soil and vegetation were fully studied in this fragment. This project is part of the thematic project "Diversidade, dinâmica e conservação em florestas do Estado de São Paulo: 40 ha de parcelas permanentes (Programa de Pesquisas em Caracterização, Conservação e Uso Sustentável da Biodiversidade do Estado de São Paulo, BIOTA-FAPESP)".Using a database of hydro-physical attributes of the soils from the Caetetus Ecological Station, this project has the purpose of obtaining quantitative parameters of soil structure, allowing a better prediction of soil physical attributes using models that include pedotransfer functions and soil quality indexes. Reference values of the pedotransfer functions and soil indexes are expected to be obtained from soils that have not suffered degradation and antropic activities.Entropy Indexes and the Kullback-Leiber distance (DKL) will be used to obtain the pore distribution and multifractal models will be used to determine the pore space. (AU)