1. LBA Fluxtower Sites: Vastly Diverse Samples of Amazonian Terrain LBA Fluxtower Sites: Vastly Diverse Samples of Amazonian Terrain Antonio Donato Nobre Celso Randow Camilo Daleles Renno Luz Adriana Cuartas Alessandro Carioca de Araujo Scott Saleska LBA Fluxtower Synthesis Group GEOMA Environmental Physics Group INPA Instituto Nacional de Pesquisas da Amazonia INPE Instituto Nacional de Pesquisas Espaciais University of Arizona USA VUA Free Universtity of Amsterdam Holland

2. Topography has strong influence on soils and ecosystems terrainsoil vegetation

3. HAND, a new quantitative terrain approach Hydrology ASU catchment (LBA) –hillslope hydrology, –ground water, –stream flow, –vegetation-water relations (Tomasella et al 2007, Hodnet et al 2007a, Hodnet et al 2007b, Waterloo et al 2006, Cuartas et al 2007) Terrain analysis (GEOMA) –Digital elevation model (SRTM) –Terrain descriptor (Rennó et al 2008) –Field validation and testing –Terrain vs Hydrology

4. Questions and Assumptions Tower significant footprint usually does not exceed 10 km –Therefore, terrain around the towers within a circle with 10 km radius can be hypothetically associated with flux-data Remote sensing data require broader and representative validations –testing representativeness of the assumed tower footprint (10 km), we choose an encompassing circle of 50 km radius for comparisons

5. São Gabriel da Cachoeira SRTM 50 km 10 km

6. Flood land Mask By Novo, Mellack et al SRTM São Gabriel

7. 4% Flooded 42% Waterlogged 36% Ecotone 8% Slope 10% Plateau HAND map São Gabriel

8. Manaus K34 & C14 SRTM

9. Flood land Mask By Novo, Mellack et al SRTM Manaus K34

10. 10% Flooded 20% Waterlogged 20% Ecotone 31% Slope 19% Plateau HAND map Manaus K34

11. Caxiuana SRTM

12. Flood land Mask By Novo, Mellack et al SRTM Caxiuana

13. 36% Flooded 30% Waterlogged 20% Ecotone 2% Slope 12% Plateau HAND map Caxiuana

14. Santarem km 67 SRTM

15. SRTM Santarem km 67 Flood land Mask By Novo, Mellack et al

16. 20% Flooded 6% Waterlogged 6% Ecotone 27% Slope 41% Plateau HAND map Santarem km 67

17. Ji-parana

18. Flood land Mask By Novo, Mellack et al SRTM Ji-parana

19. 2% Flooded 32% Waterlogged 25% Ecotone 24% Slope 17% Plateau HAND map Ji-parana

20. Sinop SRTM

21. Flood land Mask By Novo, Mellack et al SRTM Sinop

22. 4% Flooded 21% Waterlogged 21% Ecotono 8% Slope 47% Plateau HAND map Sinop

23. K34 Sinop Caxiuana Nobre et al Terrain classes, 50 km / 10 km ratios Representativeness of Flux-sites for RS

24. Comparing sites Hydrology –New spatially accurate data, vital to feed models Vegetation –Powerful predictor of community distribution –Potential proxy for biomass Topography –Metric for topographic roughness –Coupled terrain/footprint analysis

25. Large Circle(20000.000m)Small Circle(5000.0000m) Total Área :146293pixelsTotal Área :9141pixels Background:3,11%Background:1,78% class[0-5]:17,29%class[0-5]:14,64% class]5.3-15]:22,28%class]5.3-15]:15,24% class>15(slope>7.6%):23,28%class>15(slope>7.6%):29,64% class>15(slope<=7.6%):34,04%class>15(slope<=7.6%):38,7% Statistics for Manaus C14 Coupled terrain/footprint analysis

26. Footprints C14 Manaus Wet unstable Wet stable Topography Cross Section vs flux contribution with distance Each footprint isoline encloses a zone of probability for flux signal source

27. Dry unstable Dry stable Footprints C14 Manaus

28. Manaus K34 Caxiuana Ji-parana Santarem km 67 Santarem km 83 Sao Gabriel (dry unstable) Sinop Manaus C14 Site Footprint Comparison WET UNSTABLE

29. Manaus K34 Manaus C14 Santarem K 67 S Gabriel Caxiuana Sinop Tower Site HAND map Comparison

30. Footprint C14 Manaus Wet unstable Wet stable Terrain Class Distribution by Footprint Probability Class

31. Dry unstable Dry stable

32. Manaus K34 Caxiuana Ji-parana Santarem km 67 Santarem km 83 Sao Gabriel (dry unstable) Sinop Manaus C14 WET UNSTABLE SITE Comparison

33. % accumulated contribution WET UNSTABLE WET STABLE DRY UNSTABLE DRY STABLE Up to 5km63,5139,5064,6736,80 Up to 20km92,3986,7993,6686,56

34. Footprint conclusions Fluxtower Footprint analysis allows matching of dynamic fluxsource data with terrain composition Most fluxtower sites sample terrains close by (less than 1 km radius), skewing the weight of their measurements to such terrains. Much more detailed footprint significance analysis can yield a potentially good indication of how to interpret terrain/ecosystem contribution to flux data