ISRIC's Fruitful Meeting21-Jan-2014

Alessandro Samuel RosaGuest Researcher

Working plan of visitJan-Dec2014

Origin

● Descendant of Italian and German immigrants● Born in a small town in Southern Brazil

– 15.000 inhabitants

● Raised in a small family farm– 15 hectares

● Lived many years in Southern Brazil● Last two years living near by Rio de Janeiro

Background - education

● Agro Technical School (2000 - 03)● Trainee – farm management, USA (2003 – 04)● Federal University of Santa Maria (2004 – 12)

– Bachelor's degree in Agronomy

– Secondary education teaching license - Agro Technical Schools

– Master's degree in Soil Science (DSM)

● Federal Rural University of Rio de Janeiro (2012 - 16)– PhD candidate – Agronomy-Soil Science (DSM)

Source: Dr. Ricardo DalmolinFederal University of Santa Maria

Background - experience

● Farming: annual and perennial crops, dairy cattle, pigs, chickens, and many others

● Ferralsol with high iron oxides content and kaolinite (1:1 phylossilicate)

Background - experience

● Educational activities– soil museum, website, newsletter

● Research activities (2004 - 14)– routine soil laboratory analysis

– mineralogy, FTIR and 13C NMR spectroscopy, soil quality indicators, soil fauna, constructed soils

– soil classification, soil and land use surveys

– DSM, GIS, remote sensing, geostatistics

Sandwich program (2014)

● Coordination for the Improvement of Higher Education Personnel (CAPES)

● Supervisors– Dr. Lúcia Anjos – Federal Rural University of Rio

de Janeiro

– Dr. Gustavo Vasques – Embrapa Soils

– Dr. Gerard Heuvelink – ISRIC (Why?)

● Main collaborator– Dr. Ricardo Dalmolin – Federal University of

Santa Maria

Activities during 2014

● PhD research project● GSIF project

– WOSIS and World Soil Profiles

– GSIF R-package

– documentation

● Universal Soil Classification System– Tropical Soils

PhD research project

● Evaluate the main sources of uncertainty in DSM under different database scenarios

1) How accurate are freely available environmental covariates? How much uncertainty reduction is achieved when more accurate environmental covariates are used?

2) How do calibration sample size and sampling design affect model composition and prediction accuracy? What is the trade-off between map accuracy and monetary cost?

PhD research project

3) How strongly correlated are environmental covariates? Is prediction accuracy improved when they are transformed to their principal components?

● 350 + 60 soil observations● topsoil● particle size distribution, ECEC, organic

carbon content● many environmental covariates● regression-kriging approach

Questions? Comments?

● Presentation will be available at http://pt.slideshare.net/alessandrosamuelrosa

● Images were obtained from Wikipedia, my personal archive, and from web profiles of cited researchers

● Contact:● E-mail: alessandro.rosa@wur.nl● Phone number: 0031 06 4435 9563