1. Old paradigms grow up: tree species composition, forest productivity and biomass across Amazonia Tim Baker Max Planck Institüt für Biogeochemie, Jena, Germany and Earth and Biosphere Institute, School of Geography, University of Leeds, UK

2. RAINFOR FOREST INVENTORIES (BOTANICAL AND STRUCTURAL) AIM To establish if Amazonian forests vary across regional scales or are changing over time, in structure, biomass, composition, and dynamics. Focus on previously established sample plots

3. NOEL KEMPFF 2001 TAMBOPATA 2002 YASUNI 2002 IQUITOS 2001 MANAUS 2002 CAXIUANA 2002 BRAGANCA 2002 TAPAJOS 2003 JATUN SACHA 2002 RAINFOR Field Activities 2001-2004 ACRE 2003 SINOP 2002 SAN CARLOS 2004 JARI 2003 MOCAMBO 2003 EL DORADO 2004 ANDES TRANSECT 2003 RIO GRANDE 2004 AMACAYACU 2004 ALTA FLORESTA 2002

4. Jon Lloyd 1, Oliver Phillips 2, Yadvinder Malhi 3, Samuel Almeida 4, Luzmila Arroyo 5, Jerome Chave 18, Anthony DiFiore 6, Terry Erwin 16, Rafael Herrera 1, Niro Higuchi 17, Tim Killeen 7, Susan Laurance 8, William Laurance 8, Simon Lewis 2, Abel Monteagudo 9, David Neill 10, Sandra Patiño 1,11, Nigel Pitman 12, Michael Schwarz 1, Natalino Silva 13,14, Rodolfo V. Martinez 15. 1. Max Planck Institüt für Biogeochemie, Jena, Germany 2. University of Leeds, UK. 3. University of Edinburgh, UK. 4. Museu Paraense Emilio Goeldi, Belém, Brazil. 5. Museo Noel Kempff Mercado, Santa Cruz, Bolivia. 6. New York University, USA. 7.Conservation International, Washington DC, USA. 8. Smithsonian Tropical Research Institute, Balboa, Panama. 9. Universidad Nacional San Antonio Abad del Cusco, Peru. 10. Missouri Botanical Garden, Quito, Ecuador. 11. Alexander von Humboldt Biological Research Institute, Bogota, Colombia. 12. Duke University, Durham, USA. 13. CIFOR, Tapajos, Brazil. 14. EMBRAPA Amazonia Oriental, Belém, Brazil. 15. Proyecto Flora del Perú, Oxapampa, Perú. 16. Smithsonian Institution, Washington DC, USA. 17. INPA, Manaus, Brazil. 18. CNRS, Toulouse, France.

5. Site locations Other plot sites BLUE - < 1 month with less than 100 mm rainfall RED - > 5 months with less than 100 mm rainfall All plots are in ‘old- growth’ forest, and are typically 1 ha. Data sources: Forest cover - FAO (2001); Climate - UEA Climatic Research Unit global observational climate dataset, 1960-1998. 277 +/- 6 Mg DW ha -1 341 +/- 9 Mg DW ha -1 246 +/- 10 Mg DW ha -1 Baker et al. (2004) Wood density determines spatial patterns in Amazonian forest biomass. Global Change Biology. Key results: stand biomass

6. Malhi et al. (2004) The above-ground coarse wood productivity of 104 Neotropical forest plots, Global Change Biology. Key results: rates of wood production

7. Is spatial variation in species composition important for understanding variation in ecosystem structure and function? How should variation in species composition be incorporated into models of carbon cycling?

8. Outline 1.Regional variation in the abundance of different types of tree in Amazonian forests 2.Variation in growth rates between functional groups 3.Implications for regional patterns of biomass and wood production

9. Regional variation in the abundance of different types of tree in Amazonian forests

10. Defining different types of tree Turner (2001) Light demand Max. size Shade tolerant Small stature species Light demanding Large stature species Shade tolerant Large stature species Light demanding Small stature species

11. Defining different types of tree Light demand Max. size

12. Maximum size obtained from floras: estimates of maximum height >1500 species Generic or family level means used for stems with no species level trait data or lacking full species determination Light demand quantified using published wood density data low wood density related to high light demand 583 species (Chave et al. in prep >2000 species) Defining different types of tree

13. Species-level variation in wood density and max height Subcanopy 0-20 m; canopy 21-30 m; emergent 31+ m. Low ( 0.7 g cm -3 ) wood density classes HighMedLow Emer. Can. Subcan

14. Emergent High Subcanopy Canopy MediumLow Maximum height Wood density p>0.01 % abundance of all stems RED - C & E Amazon BLUE - W Amazon 59 plots; 43,631 trees

15. Emergent High Subcanopy Canopy MediumLow Maximum height Wood density % abundance of all stems C & E Amazonia W Amazonia

16. Why? In Western Amazon…. higher rates of extrinsic disturbance ? higher soil fertility ?

17. Variation in growth rates between functional groups

18. Emergent High Subcanopy Canopy MediumLow Maximum height Wood density Growth rate High growth rate Low growth rate

19. 341 species with >20 individuals (21,159 trees) Most recent census interval of approx. 6 years Diameter increment Relative diameter increment Biomass increment Relative biomass increment Biomass calculated using a tree-by-tree allometric equation with a correction factor to account for variation in wood specific gravity Calculating growth rates

20. Emergent High Subcanopy Canopy MediumLow Maximum height Wood density Diameter increment / cm yr -1

21. Emergent High Subcanopy Canopy MediumLow Maximum height Wood density Relative diameter increment / % yr -1

22. Emergent High Subcanopy Canopy MediumLow Maximum height Wood density Biomass increment / kg DW yr -1

23. Emergent High Subcanopy Canopy MediumLow Maximum height Wood density Relative biomass increment / % yr -1

24. Emergent High Subcanopy Canopy MediumLow Maximum height Wood density Summary Diameter increment Rel. dbh increment Rel. biomass increment Biomass increment

25. Implications for regional patterns of biomass and wood production

26. Can variation in species composition explain variation in forest biomass and wood productivity?

27. Stand-level biomass/wood production estimated using the abundance and mean biomass/biomass increment for each functional group For each plot, across functional groups…  ( Abundance x mean biomass or mean productivity) Compared with stand-level values calculated using tree by tree data Estimating stand biomass and productivity from functional composition

28. Significance for stand-level patterns: wood production

29. Significance for stand-level patterns: biomass

30. Conclusions 1. Larger statured, high wood density species favoured in C & E Amazonia; smaller statured, low wood density species favoured in W Amazonia 2.Low wood density species have higher rates of diameter growth, but similar rates of absolute biomass increment compared to high wood density species 3.Variation in forest functional composition can explain a substantial proportion of variation in stand biomass across Amazonia