Amazon Integrated Carbon Analysis / AMAZONICA

Lead Research Organisation: University of Oxford
Department Name: Environmental Change Institute SoGE


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.


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Description We calculated the magnitude of the Amazon carbon source during the drought of 2010. This has led to two papers in Nature.
Exploitation Route Similar approaches can be applied to other tropical continents
Sectors Environment

Title Development of a Point-based Method for Map Validation and Confidence Interval Estimation 
Description Forest fires and their associated emissions are a key component for the efficient implementation of the Reducing Emissions from Deforestation and Forest Degradation (REDD+) policy. The most suitable method for quantifying large scale fire-associated impacts is by mapping burned areas using remote sensing data. However, to provide robust quantification of the impacts of fire and support coherent policy decisions, these thematic maps must have their accuracy quantitatively assessed. The aim of this research is to present a point-based validation method developed for quantifying the accuracy of burned area thematic maps and test this method in a study case in the Amazon. The method is general; it can be applied to any thematic map consisting of two land cover classes. A stratified random sampling scheme is used to ensure that each class is represented adequately. The confidence intervals for the user's accuracies and for both overall accuracy and area error are calculated using the Wilson Score method and Jeffrey Perks interval, respectively. Such interval methods are novel in the context of map accuracy assessment. Despite the complexity of calculation of the confidence intervals, their use is recommended. A spreadsheet to calculate point and interval estimates is provided for users 
Type Of Material Physiological assessment or outcome measure 
Year Produced 2015 
Provided To Others? Yes  
Impact A Master thesis used the method for mapping and quantifying uncertanties in burned area estimation. The MSc abstract follows: With the incentive for the occupation of the Brazilian Amazon in end of the 60s, forest areas suffered from anthropic interferences. Between 1988 and 2004 there was an intensification of the deforestation within the Legal Amazon. Based on the panorama of deforestation and on the growing international concern about greenhouse gas emissions, Brazil launched the Plan for Prevention and Control of Deforestation in the Legal Amazon (PPCDAm) with the objective of reducing deforestation rates. This plan was focused on a list of priority municipalities, which was based on deforestation rates, for greater control and inspection. Since then, the reducing greenhouse gas emissions policies in Brazil have been focusing on efforts to reduce deforestation rates, leaving the contributions from other emission sources, such as forest degradation by fires and logging implicit. The objective of this study was to estimate a carbon dioxide emission from three processes (deforestation, fire and degradation) for the 2008-2012 period in the municipalities within the Legal Amazon to generate a new metric to indicate priority municipalities. Thirty-one municipalities within the Amazon region were highlighted. Six municipalities have a greater contribution to the deforestation, 21 due to fires, and 4 due to degradation. Between 2008 and 2012 a total of 3.88 Gt CO2 was emitted from deforestation, burning and fires and degradation in the Amazon. From these values, 45.5% were driven by the fires of 2010. This result shows that in years of extreme droughts, fires emit more CO2 than the deforestation and should be also considered when defining priority areas for policies to reduce greenhouse gas emissions.