Amazon Integrated Carbon Analysis / AMAZONICA

Lead Research Organisation: University of Leeds
Department Name: Sch of Geography


Amazonian tropical forests cover the largest forested area globally, constitute the largest reservoir of above-ground organic carbon and are exceptionally species rich. They are under strong human pressure through logging, forest to pasture conversion and exploitation of natural resources. They face a warming climate and a changing atmospheric environment. These factors have the potential to affect significantly the global atmospheric greenhouse gas burden (CO2, CH4), chemistry and climate. A central diagnostic of the state and changes of the land surface is its net carbon balance but currently we do not even know the sign of this balance. Although estimates of fluxes associated with known contributing processes such as deforestation exist, along with evidence for responses of undisturbed rainforests to a changing environment and substantial inter-annual fluctuations, different estimates vary widely. Thus it is very difficult to determine the overall significance of these independent estimates. The uncertainty of the greenhouse gas balances have also made it difficult to assess the realism of future model simulation predictions of the Amazon, some of them predicting alarming fates for the rainforests. Ultimately, the most stringent constraint on surface fluxes of a compound is its accumulation / depletion in overlying air. A major large-scale constraint on the net balance of the Amazon that would resolve the discrepancy in the various carbon flux estimates is therefore an accurate characterization of the 3D carbon cycle related tropospheric greenhouse gas concentration fields above the entire basin. Spatio-temporal concentration patterns can further be translated into surface flux fields using inverse modelling of atmospheric transport. By incorporating the large amount of existing on-ground data on ecosystem functioning from LBA, the RAINFOR network, and the ongoing TROBIT NERC project / and targeted measurements where knowledge gaps remain - into a coupled land-surface land-ecosystem model, we will develop a properly data-grounded model representation of the system. Further, the model will be tested by comparing its predictions with observed atmospheric concentration patterns. In turn this will permit defensible projections of the future of Amazonian vegetation. Human activity climate interactions and the land river link will also for the first time be included in these simulations. Therefore, we propose a project of 5 year duration based on the following five pillars: 1. To obtain large-scale budgets of greenhouse gases top-down, based on atmospheric concentration data and inverse atmospheric transport modelling. 2. To estimate fluxes associated with individual processes bottom-up, based on existing and new remote sensing information (deforestation and fires), tree-by-tree censuses in undisturbed forests, and river carbon measurements. 3. To use existing, and, where missing, targeted new, on-ground measurements of ecosystem functioning and climate response, in order to constrain land ecosystem and river carbon model representation, which will then be combined in an integrated land carbon cycle model. 4. To couple a fully integrated land carbon cycle model (from 3) into a regional climate model and use it (i) to predict current concentrations, and (ii) to calculate the systems response to a changing climate and human population, given a representative range of scenarios. 5. In a final synthesis step we will analyse and combine top-down (1) and bottom-up estimates (2&3) to develop multiple constraint and mutually consistent carbon fluxes over the four-year measurement period. We expect to obtain much better quantification of a major but currently poorly constrained component of the global carbon cycle, based on a new understanding of the underlying processes and their large-scale effect. The project will also provide much improved predictions of the response of the Amazon to future climate change.

Related Projects

Project Reference Relationship Related To Start End Award Value
NE/F005873/1 01/03/2008 31/12/2012 £197,654
NE/F005873/2 Transfer NE/F005873/1 01/01/2013 30/06/2014 £170,254
Description Many excellent results as can be seen from resulting publications, several in top journals.

First large-scale greenhouse gas budgets of the Amazon basin - a key region for global climate, biodiversity, global carbon cycle based on greenhouse gas concentration observations across the basin. We found substantial sensitivity of the carbon balance to drier than usual conditions in a generally warming world. These are the first quantitative indications of the sensitivity of the Amazon humid forests to an increasingly variable and hotter climate.

These results are in agreement with on-the ground continuous ecosystem monitoring data from the same project.

We have also for the fist time been able to estimate CH4 emissions from the basin. We can show - based on seasonality - that these emissions are primarily from the seasonally varying inundated area (up to 25% of the basin). We can furthermore quantify how large the Amazon wetland CH4 emissions are.
Exploitation Route The most important records are greenhouse gas concentration data for the Amazon. Those data which we have published are publically available and there seems to be substantial demand - e.g. from the remote sensing community attempting to estimate total atmospheric air column greenhouse gas composition.
Sectors Agriculture, Food and Drink,Education,Environment

Description Please see entries to AMAZONICA output listed above.
First Year Of Impact 2009
Impact Types Societal

Description Amazon greenhouse gas measurement network 
Organisation National Institute for Space Research Brazil
Country Brazil 
Sector Public 
PI Contribution PDRA staying at University of Leeds for one year (bolsa ciencia sem fronteiras) (Dr. Luana Basso) Several publications about status and changes of the Amazon forests via analysis of lower-troposphere greenhouse gas measurements and atmospheric transport modelling Have been staying at INPE or several months per year as part of a stipend (Bolsa Ciencia sem fronteiras) guest professorship - the bolsa included research money A proposal to CNPQ for sustaining and expanding the Amazon greenhouse gas monitoring network - which will be resubmitted shortly. It would fund new measurements techniques (COS, d13CO2) as well as support to continue existing measurement sites.
Collaborator Contribution The high precision gas analytics laboratory at INPE led by Luciana Gatti analysis flask air for greenhouse gases and trace substances which permit conclusions the source type of greenhouse gas emissions.
Impact Many publications including sofar one publication in Nature (Gatti et al. 2014).
Start Year 2008