CD-09 Group Augmented Abstract


A Modeling Synthesis of the Impacts of Tropical Forest Conversion on Carbon Fluxes and Storage, and on Nutrient Dynamics in Amaz˘nia.


Edward B. Rastetter -- The Ecosystems Center, Marine Biological Laboratory (MBL)
Yosio Edemir Shimabokuro -- Instituto Nacional de Pesquisas Espaciais (INPE) 

Objectives

Our objectives are to quantify and improve our understanding of the changes in C storage, C exchange, and nutrient dynamics in response to human-induced environmental change in Amaz˘nia. We will address these goals using models of canopy gas-exchange and ecosystem biogeochemistry. These models will allow us to use existing information and information collected during the intensive field studies to generate regional extrapolations, thus creating linkages in LBA between the specific point studies and the remotely sensed data.

We will use a hierarchy of models to scale in space from point to region and in time from hours to decades.

  1. At the finest scale we will employ a process-based multi-layer canopy, soil-plant-atmosphere model (SPA) that predicts hourly gross photosynthesis and transpiration. This model is parameterized with fine-scale measurements of canopy structure and meteorology, and can be tested against independently collected tower eddy covariance flux measurements. We will also develop a transect version of the model to generate predictions of gas exchange along an aircraft flight path. The transect runs will necessarily be parameterized with less detailed data, and will allow us to investigate the effects of any simplifying assumptions on model efficacy.
  2. At the next coarser scale, we will use a simpler, aggregated model of daily whole-canopy carbon ę fixation and transpiration. This model is derived wholly from the process-based model, capturing its aggregated behavior, while operating with daily input and at significantly higher computing speeds. This aggregated model serves two purposes. Firstly, it can be employed within a gridded GIS database, so that we can derive regional estimates of C and energy fluxes under specified land-use and climate change scenarios. Secondly, it can be inserted into our ecosystem biogeochemistry model as a validated photosynthesis/transpiration component.
  3. The third model, of ecosystem biogeochemistry (MBL-GEM), will be used to examine the coupling between nutrient dynamics and longer-term C storage and exchange. Our primary goal will be to test whether we can predict the long-term responses of biomass and soil organic matter to land-use change using chronosequence data for validation. This model will also be coupled with a GIS-database model to generate regional extrapolations. In this instance our predictions of regionally varying biomass and leaf area can be tested against remotely sensed data as a further test.

The proposed work will represent a significant step toward an understanding of Amaz˘nia for three important reasons. Firstly, by identifying key functional differences in canopy gas exchange characteristics our soil-plant-atmosphere model will help to develop effective inter-site comparisons. Secondly, our models represent a logistically effective means for generating linkages among components of LBA, particularly in terms of linking the point measurements of towers with remotely-sensed regional data-sets. Our aggregation protocols will help to generate coarser-scaled predictions, with more modest data requirements, better suited for extrapolation. Thirdly, we will integrate the understanding derived from tower-based flux measurements into our ecosystem biogeochemical models. Understanding the linkages between C and nutrient cycles is crucial for developing long-term predictions of the response of biomass and soil organic matter to land-use and climate change.

We hope to work closely with those teams making eddy flux measurements, both from towers and aircraft. We are also interested in collaborating with groups developing regional data sets of land-cover, vegetation type and climate variables. We are searching for a Brazilian or South American collaborator to work with us on model parameterization, validation, analysis, and extrapolation.