@Article{AguiarONLAVSASVC:2012:INFrAp,
author = "Aguiar, Ana Paula Dutra and Ometto, Jean P. and Nobre, Carlos and
Lapola, David M. and Almeida, Claudio and Vieira, Ima C. and
Soares, Jo{\~a}o Vianei and Alvala, Regina and Saatchi, Sassan
and Valeriano, Dalton and Castilla-Rubio, Juan C.",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de
Pesquisas Espaciais (INPE)} and Laborat{\'o}rio de Ci{\^e}ncia
do Sistema Terrestre (LabTerra), Department of Ecology,
Universidade Estadual Paulista (UNESP), Av. 24A, 1515, 13506-900,
Rio Claro, SP, Brazil and Amazon Regional Center (CRA), Brazilian
Institute for Space Research (INPE), Parque de Ci{\^e}ncia e
Tecnologia do Guam{\'a}, Bel{\'e}m, PA, Brazil and Museu
Paraense Emilio Goeldi (MPEG), Av. Magalh{\~a}es Barata 376 -
S{\~a}o Braz, CEP: 66040-170, Bel{\'e}m, PA, Brazil and
{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)} and JET Propulsion
Laboratory, NASA, 4800 Oak Grove Drive, Pasadena, CA 91109, USA
and {Instituto Nacional de Pesquisas Espaciais (INPE)} and
Planetary Skin Institute, Silicon Valley, CA, USA",
title = "Modeling the spatial and temporal heterogeneity of
deforestation-driven carbon emissions: the INPE-EM framework
applied to the Brazilian Amazon",
journal = "Global Change Biology",
year = "2012",
volume = "18",
number = "11",
pages = "3346–3366",
month = "Nov.",
keywords = "Amazonia, carbon emissions, deforestation, LUCC , REDD , secondary
forests.",
abstract = "We present a generic spatially explicit modeling framework to
estimate carbon emissions from deforestation (INPE-EM). The
framework incorporates the temporal dynamics related to the
deforestation process and accounts for the biophysical and
socioeconomic heterogeneity of the region under study. We build an
emission model for the Brazilian Amazon combining annual maps of
new clearings, four maps of biomass and a set of alternative
parameters based on the recent literature. The most important
results are: (a) Using different biomass maps leads to large
differences in estimates of emission; for the entire region of the
Brazilian Amazon in the last decade, emission estimates of primary
forest deforestation range from 0.21 to 0.26 PgCyr\−1. (b)
Secondary vegetation growth presents a small impact on emission
balance because of the short duration of secondary vegetation. In
average, the balance is only 5% smaller than the primary forest
deforestation emissions. (c) Deforestation rates decreased
significantly in the Brazilian Amazon in recent years, from 27
Mkm2 in 2004 to 7 Mkm2 in 2010. INPE-EM process-based estimates
reflect this decrease even though the agricultural frontier is
moving to areas of higher biomass. The decrease is slower than a
non-process instantaneous model would estimate as it considers
residual emissions (slash, wood products and secondary
vegetation). The average balance, considering all biomass,
decreases from 0.28 in 2004 to 0.15 PgCyr\−1 in 2009; the
non-process model estimates a decrease from 0.33 to 0.10
PgCyr\−1. We conclude that the INPE-EM is a powerful tool
for representing deforestation-driven carbon emissions. Biomass
estimates are still the largest source of uncertainty in the
effective use of this type of model for informing mechanisms such
as REDD+. The results also indicate that efforts to reduce
emissions should focus not only on controlling primary forest
deforestation but also on creating incentives for the restoration
of secondary forests.",
doi = "10.1111/j.1365-2486.2012.02782.x",
url = "http://dx.doi.org/10.1111/j.1365-2486.2012.02782.x",
issn = "1354-1013",
language = "en",
urlaccessdate = "27 abr. 2024"
}