HR: 0800h
AN: B51A-0048    [Abstracts]
TI: Mechanistic model for light-controlled leaf phenology in the Amazon rainforests
AU: * Kim, Y
EM: yjkim@oeb.harvard.edu
AF: Harvard University, Department of Organismic and Evolutionary Biology, Cambridge, MA 02138,
AU: Moorcroft, P R
EM: moorcrof@fas.harvard.edu
AF: Harvard University, Department of Organismic and Evolutionary Biology, Cambridge, MA 02138,
AU: Bras, R L
EM: rlbras@mit.edu
AF: Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, Cambridge, MA 02139,
AU: Medvigy, D
EM: dmm31@duke.edu
AF: Duke University, Department of Civil and Environmental Engineering, Durham, NC 27708,
AU: Hutyra, L R
EM: lrhutyra@u.washington.edu
AF: University of Washington, Urban Ecology Research Lab, Seattle, WA 98195,
AU: Pyle, E H
EM: pyle@fas.harvard.edu
AF: Harvard University, Department of Earth and Planetary Sciences, Cambridge, MA 02138,
AU: Wofsy, S C
EM: swofsy@deas.harvard.edu
AF: Harvard University, Department of Earth and Planetary Sciences, Cambridge, MA 02138,
AB: Satellite-based vegetation observations in the Amazon rainforest indicate a flush of leaves during the dry season when solar radiation is high. This light-controlled phenology is further confirmed with ground-based observations at the Tapajos National Forest (TNF; 2.86S, 54.96W, Para, Brazil) near km 67 of the Santarem-Cuiaba highway from 2001 to 2006. Observed leaf litterfall and canopy photosynthesis (Gross Primary Productivity: GPP) lags a few months past the seasonal variation of solar radiation. In well-watered rainforests, rich light leads to flush of new leaves, which have a high photosynthetic efficiency, consequently increasing GPP during the following months. In this study, we incorporate these mechanistic processes into the Ecosystem Demography model (ED) in order to capture the seasonality of leaf phenology and GPP, including the dry season flush of leaves. We use leaf litterfall rates, GPP and evapotranspiration measured at the TNF to constrain the model parameterizations. The initial model underestimates litterfall rates in both magnitude and seasonal fluctuation compared to the observed ones, and predicts seasonality of GPP opposite to the observed pattern, presenting peaks during the sunny dry season. The constrained model significantly improves the simulated litterfall rates and GPP against the observed ones. The model simulates litterfall rates quite accurately, and captures some of the seasonal dynamics of GPP. We also show that this modification in phenology, together with other changes in the model sensitivity to environmental conditions, improves the predicted seasonality of Net Ecosystem Exchange (NEE).
DE: 0315 Biosphere/atmosphere interactions (0426, 1610)
DE: 0428 Carbon cycling (4806)
DE: 1615 Biogeochemical cycles, processes, and modeling (0412, 0414, 0793, 4805, 4912)
DE: 1622 Earth system modeling (1225)
DE: 1813 Eco-hydrology
SC: Biogeosciences [B]
MN: 2007 Fall Meeting