Abstract ID: 187

Mechanistic model for light-controlled leaf phenology - its implication for seasonality of water and carbon fluxes and deforestation in the Amazon rainforests

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. Existing land surface and biosphere models, however, predict such seasonal patterns of GPP and NEP (Net Ecosystem Production: NEP=GPP-R) wrongly or even oppositely. In this study, we therefore incorporate these mechanistic processes into the Ecosystem Demography model version 2 (ED2) in order to capture the seasonality of leaf phenology and fluxes of carbon and water. The model parameterizations, including new parameterization for the phenology model, are constrained with biometry and flux tower measurements at the TNF. Specifically the measured data include Net Ecosystem Productivity (NEP), evapotranspiration, leaf literfall and growth/mortality. A new light-controlled leaf-exchanging leaf phenology model allows the constrained ED2 model to capture seasonal variations of litterfall, which the initial ED2 model underestimates in both magnitude and seasonal fluctuation compared to the observed ones. For that reason, the new model captures seasonality of GPP, presenting peaks during the sunny dry season, which the initial model predicts oppositely to the observed pattern. This modification in phenology, together with changes in the sensitivity of heterotrophic respiration model to environmental conditions, improves the predicted seasonality of NEP. Furthermore, we use the ED2 model to predict the long-term ecological and hydrological impact of deforestations in the Amazon rainforests. Possible consequences of deforestations from 2000 through 2100 are evaluated using the socioeconomic scenarios of land use changes across the Brazil together with the IPCC climate change scenarios. Given the scenarios of deforestations and climate changes, it is of particular interests how the new leaf phenology model influences decadal trends of water and carbon fluxes as well as their seasonality.

Session:  Carbon - The role of seasonality in carbon and water balance.

Presentation Type:  Oral