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RAINFOR Red Amazonica de Inventarios Forestales Rede Amazonica de Inventarios Florestais

Funding EU Framework V Max Planck Institute for Biogeochemistry The Royal Society. RAINFOR Red Amazonica de Inventarios Forestales Rede Amazonica de Inventarios Florestais The Amazon Forest Inventory Network http://www.geog.leeds.ac.uk/projects/rainfor.

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RAINFOR Red Amazonica de Inventarios Forestales Rede Amazonica de Inventarios Florestais

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  1. Funding EU Framework V Max Planck Institute for Biogeochemistry The Royal Society RAINFOR Red Amazonica de Inventarios Forestales Rede Amazonica de Inventarios Florestais The Amazon Forest Inventory Network http://www.geog.leeds.ac.uk/projects/rainfor Malhi et al, 2002, Journal of Vegetation Science An international network to monitor the structure, composition and dynamics of Amazonian forests (RAINFOR)

  2. RAINFOR Field Activities 2001-2004 GUYANA 2004 ST ELIE LA SABANITA 2004 NOURAGUES SAN CARLOS 2004 BRAGANCA 2002 JATUN SACHA 2002 JARI 2003 YASUNI 2002 TAPAJOS 2003 MOCAMBO 2003 MANAUS 2002 CAXIUANA 2002 IQUITOS 2001 MARABA ACRE 2003 CARAJAS SINOP 2002 JARU TAMBOPATA 2002 NOEL KEMPFF 2001 ANDES TRANSECT 2003

  3. ABOVE-GROUND WOOD PRODUCTIVITY Measurements from multiple censuses of 104 sites, standardised to take account of wood density and census interval. Malhi et al, The above-ground coarse wood productivity of 104 Neotropical forest plots, Global Change Biology, in press

  4. Malhi et al, The above-ground coarse wood productivity of 104 Neotropical forest plots, Global Change Biology, in press

  5. Malhi et al, The above-ground coarse wood productivity of 104 Neotropical forest plots, Global Change Biology, in press

  6. Spatial Interpolation: Kriging Total AGWP = 1.69 Pg C yr-1 D. Wood, MSc Thesis

  7. Spatial Interpolation: Cochrane soils map allocation Total AGWP = 1.86 Pg C yr-1 D. Wood, MSc Thesis

  8. WOOD DENSITY AND FOREST STRUCTURE Slow-growing forests have higher mean wood densities Baker et al, Wood density determines spatial patterns In biomass in Amazonian forests, Global Change Biology, in press

  9. WOOD DENSITY AND STEM DISTRIBUTION FACTOR

  10. ABOVE-GROUND LIVE WOOD BIOMASS

  11. 207 sites used in extrapolation

  12. BASAL AREA CORRELATES WITH LENGTH OF DRY SEASON

  13. ABOVE GROUND LIVE WOODY BIOMASS Estimated total aboveground live biomass of Amazonian forests = 91-95 Pg C (Area mean = 315-335 t dry weight ha-1)

  14. Above Ground Woody Biomass Carbon Derived from NASA_CASA Model Early 1990s 0 5,000 10,000 18,000 g C m-2

  15. LIVE WOOD BIOMASS TURNOVER TIMES

  16. CHANGE IN BIOMASS OVER TIME

  17. The old-growth forests appear to be increasing in biomass, at a rate related to soil fertility

  18. CHANGES IN FOREST DYNAMICS

  19. Acceleration in both growth and mortality and increase in stem number. Lewis et al Phil. Trans. Royal Society In press

  20. The most parsimonious explanation may be that an external driver (CO2, light?) is accelerating forest growth, which in turn is accelerating tree death Net C sink Accelerated tree growth Lagging accelerated tree death Lewis et al, in press

  21. Live biomass carbon sink extrapolated from RAINFOR plots

  22. Estimated Mean Change in Above-Ground Live Biomass In Old-Growth Forests: = 0.55-0.85 t C ha-1 year-1 = 0.3-0.5 Pg C yr-1 Does not include: dead wood, belowground biomass or soil carbon

  23. Conclusions This is substantial variability in forest carbon dynamics and other properties across Amazonia – extrapolation from a few sites should be done with caution. In particular, the Manaus-Santarem-Belem axis contains some of the least dynamic forests in all Amazonia. Current models of productivity and biomass of Amazonia miss critical processes (e.g. variability in allocation to wood, variability in wood residence time) that determine pan-Amazon patterns. It should be straightforward to start incorporating these processes into existing models. Soils may be more important than climate in determining the current carbon dynamics and carbon balance of Amazonia. Long term and spatially extensive plot observations provide vital insight into how forest dynamics and forest ecology are responding to atmospheric change. Creating and supporting a standardised observation network now could provide immense payback in the near future.

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