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From small streams to the sea: a multi-scale synthesis of Carbon and Hydrological dynamics across the Amazon landscape. J. E. Richey, R. Victoria.

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Presentation on theme: "From small streams to the sea: a multi-scale synthesis of Carbon and Hydrological dynamics across the Amazon landscape. J. E. Richey, R. Victoria."— Presentation transcript:

1 From small streams to the sea: a multi-scale synthesis of Carbon and Hydrological dynamics across the Amazon landscape. J. E. Richey, R. Victoria

2 Relevancy to LBA  Background support important  Very good summary of past achievements  Deals with relevant topics of LBA agenda: carbon & hydrologic dynamics and supported with high quality modeling tools.  Overall objective: find the sequence of processes to define the role of fluvial systems in the C cycle in the Amazon: from small to large scales.

3 South American counter-parts  Emphasis is given to Brazilian and US students both in field and modeling purposes.  No chances are given to other South American students nor to other Amazon countries students.

4 Training and education plan  Full partnership between USA and Bazil, UW & CENA, other Amazonian Institutions.  PIs come from two leading universities in field and modeling activities and long research experience.  No specific mention is done to other South American institutions / partners.

5 Training and education plan  It shows an strong training (workshops) and education plan, but it lacks identifying specific number of events.  AREAS: data synthesis, modeling, analytic environmental chemistry.  Strong statement on the importance of “water” within the Amazon but no efforts are given by high education institutions.

6 LBA Data Policy  Clear descriptions of data management according to LBA policies. It refers to 4 tasks:  1. Project management: direction and coordination.  2. Data management: data quality control, need to meet LBA-DIS metadata standards  3. System management: adequate connectivity between team members, data collections and LBA-DIS.  4. Product management: track completeness of data collection.


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