Historic emissions from deforestation and forest degradation in Mato Grosso, Brazil: 1) source data uncertainties

Morton, Douglas C.; Sales, Márcio; Souza, Carlos M.; Griscom, Bronson W.

doi:10.1186/1750-0680-6-18

Cited by 23 publications

(19 citation statements)

References 66 publications

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“…Forest carbon stock estimates have high variability. For example, investigations in Mato Grosso, Brazil, found a variability of more than two-fold in stock estimates (Morton et al, 2011). A review of studies estimating indirect LUC (iLUCs) associated with biofuel production found a large variation in estimates of forest carbon stocks among studies, contributing to the uncertainty in iLUC accounting (DG; Energy, 2010).…”

Section: Deforestationmentioning

confidence: 99%

“…The size of the deforested area is another source of uncertainty. Brazil is considered to have one of the best monitoring programmes for deforestation, yet a 20% uncertainty in annual deforestation rate was found in the Mato Grosso study (Morton et al, 2011). Increased knowledge of LU after deforestation is vital as carbon losses for cropland are potentially higher than for pasture, perennial plantation or secondary forests (Morton et al, 2006).…”

Section: Deforestationmentioning

confidence: 99%

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An LCA researcher's wish list – data and emission models needed to improve LCA studies of animal production

Cederberg

Henriksson

Berglund

2013

Animal

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The last decade has seen an increase in environmental systems analysis of livestock production, resulting in a significant number of studies with a holistic approach often based on life-cycle assessment (LCA) methodology. The growing public interest in global warming has added to this development; guidelines for carbon footprint (CF) accounting have been developed, including for greenhouse gas (GHG) accounting of animal products. Here we give an overview of methods for estimating GHG emissions, with emphasis on nitrous oxide, methane and carbon from land use change, presently used in LCA/CF studies of animal products. We discuss where methods and data availability for GHGs and nitrogen (N) compounds most urgently need to be improved in order to produce more accurate environmental assessments of livestock production. We conclude that the top priority is to improve models for N fluxes and emissions from soils and to implement soil carbon change models in LCA/CF studies of animal products. We also point at the need for more farm data and studies measuring emissions from soils, manure and livestock in developing countries.

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Section: Deforestationmentioning

confidence: 99%

Section: Deforestationmentioning

confidence: 99%

An LCA researcher's wish list – data and emission models needed to improve LCA studies of animal production

Cederberg

Henriksson

Berglund

2013

Animal

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“…Time series of annual data on deforestation and understorey fires are, therefore, necessary to characterize the spatial and temporal relationships between forest conversion and understorey fires in standing forests. The nature of these relationships can inform efforts to Reduce Emissions from Deforestation and Forest Degradation plus enhance forest carbon stocks (REDDþ) [22,23], including whether understorey fires are an independent source of carbon emissions or a regional driver of deforestation.…”

Section: Introductionmentioning

confidence: 99%

Understorey fire frequency and the fate of burned forests in southern Amazonia

Morton

Page

DeFries

et al. 2013

Phil. Trans. R. Soc. B

194

220

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Recent drought events underscore the vulnerability of Amazon forests to understorey fires. The long-term impact of fires on biodiversity and forest carbon stocks depends on the frequency of fire damages and deforestation rates of burned forests. Here, we characterized the spatial and temporal dynamics of understorey fires (1999–2010) and deforestation (2001–2010) in southern Amazonia using new satellite-based estimates of annual fire activity (greater than 50 ha) and deforestation (greater than 10 ha). Understorey forest fires burned more than 85 500 km 2 between 1999 and 2010 (2.8% of all forests). Forests that burned more than once accounted for 16 per cent of all understorey fires. Repeated fire activity was concentrated in Mato Grosso and eastern Pará, whereas single fires were widespread across the arc of deforestation. Routine fire activity in Mato Grosso coincided with annual periods of low night-time relative humidity, suggesting a strong climate control on both single and repeated fires. Understorey fires occurred in regions with active deforestation, yet the interannual variability of fire and deforestation were uncorrelated, and only 2.6 per cent of forests that burned between 1999 and 2008 were deforested for agricultural use by 2010. Evidence from the past decade suggests that future projections of frontier landscapes in Amazonia should separately consider economic drivers to project future deforestation and climate to project fire risk.

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“…For instance, intense drought episodes may compromise the consistency of the RRB comparison, between observed AGB and simulated total biomass, due to changes in carbon allocation patterns in vegetation (Doughty et al 2015). However, the AGB product in Liu et al (2015) also embodies significant uncertainties, that are partly related to the spatial extrapolation method (Mitchard et al 2014) based on Saatchi et al (2011). Moreover, this AGB dataset may be of limited use for evaluating impacts of climate extremes on tropical forests, in view of the possible underestimation of inter-annual variations of biomass by VOD signals, in comparison with other satellite indicators of vegetation (Liu et al 2011).…”

Section: The Rrb Concept Its Interpretation and Caveatsmentioning

confidence: 99%

Evaluating changes of biomass in global vegetation models: the role of turnover fluctuations and ENSO events

Cantú

Frieler

Reyer

et al. 2018

Environ. Res. Lett.

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This paper evaluates the ability of eight global vegetation models to reproduce recent trends and inter-annual variability of biomass in natural terrestrial ecosystems. For the purpose of this evaluation, the simulated trajectories of biomass are expressed in terms of the relative rate of change in biomass (RRB), defined as the deviation of the actual rate of biomass turnover from its equilibrium counterpart. Cumulative changes in RRB explain long-term changes in biomass pools. RRB simulated by the global vegetation models is compared with its observational equivalent, derived from vegetation optical depth reconstructions of above-ground biomass (AGB) over the period 1993-2010. According to the RRB analysis, the rate of global biomass growth described by the ensemble of simulations substantially exceeds the observation. The observed fluctuations of global RRB are significantly correlated with El Niño Southern Oscillation events (ENSO), but only some of the simulations reproduce this correlation. However, the ENSO sensitivity of RRB in the tropics is not significant in the observation, while it is in some of the simulations. This mismatch points to an important limitation of the observed AGB reconstruction to capture biomass variations in tropical forests. Important discrepancies in RRB were also identified at the regional scale, in the tropical forests of Amazonia and Central Africa, as well as in the boreal forests of north-western America, western and central Siberia. In each of these regions, the RRBs derived from the simulations were analyzed in connection with underlying differences in net primary productivity and biomass turnover rate -as a basis for exploring in how far differences in simulated changes in biomass are attributed to the response of the carbon uptake to CO 2 increments, as well as to the model representation of factors affecting the rates of mortality and turnover of foliage and roots. Overall, our findings stress the usefulness of using RRB to evaluate complex vegetation models and highlight the importance of conducting further evaluations of both the actual rate of biomass turnover and its equilibrium counterpart, with special focus on their background values and sources of variation. In turn, this task would require the availability of more accurate multi-year observational data of biomass and net primary productivity for natural ecosystems, as well as detailed and updated information on land-cover classification.

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Historic emissions from deforestation and forest degradation in Mato Grosso, Brazil: 1) source data uncertainties

Cited by 23 publications

References 66 publications

An LCA researcher's wish list – data and emission models needed to improve LCA studies of animal production

An LCA researcher's wish list – data and emission models needed to improve LCA studies of animal production

Understorey fire frequency and the fate of burned forests in southern Amazonia

Evaluating changes of biomass in global vegetation models: the role of turnover fluctuations and ENSO events

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