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1. Identity statement
Reference TypeJournal Article
Sitemtc-m21b.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP3W34P/3L9LQL2
Repositorysid.inpe.br/mtc-m21b/2016/03.03.17.42   (restricted access)
Last Update2016:03.03.17.49.01 (UTC) simone
Metadata Repositorysid.inpe.br/mtc-m21b/2016/03.03.17.42.40
Metadata Last Update2018:06.04.02.40.37 (UTC) administrator
DOI10.1111/gcb.13087
ISSN1354-1013
Labelself-archiving-INPE-MCTI-GOV-BR
Citation KeyBustamanteRAAAAABBCCFFFKMMMOPPSTV:2016:ToInMo
TitleToward an integrated monitoring framework to assess the effects of tropical forest degradation and recovery on carbon stocks and biodiversity
Year2016
MonthJan.
Access Date2024, May 18
Type of Workjournal article
Secondary TypePRE PI
Number of Files1
Size358 KiB
2. Context
Author 1 Bustamante, Mercedes M. C.
 2 Roitman, Iris
 3 Aide, T. Mitchell
 4 Alencar, Ane
 5 Anderson, Liana O.
 6 Aragão, Luiz Eduardo Oliveira e Cruz de
 7 Asner, Gregory P.
 8 Barlow, Jos
 9 Berenguer, Erika
10 Chambers, Jeffrey
11 Costa, Marcos H.
12 Fanin, Thierry
13 Ferreira, Laerte G.
14 Ferreira, Joice
15 Keller, Michael
16 Magnusson, William E.
17 Morales-Barquero, Lucia
18 Morton, Douglas
19 Ometto, Jean Pierre Henry Balbaud
20 Palace, Michael
21 Peres, Carlos A .
22 Silverio, Divino
23 Trumbore, Susan
24 Vieira, Ima C. G.
Group 1
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 6 DSR-OBT-INPE-MCTI-GOV-BR
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19 CST-CST-INPE-MCTI-GOV-BR
Affiliation 1 Universidade de Brasília (UNB)
 2 Universidade de Brasília (UNB)
 3 Universidad Puerto Rico
 4 Amazon Environm Res Inst IPAM
 5 Natl Ctr Monitoring & Early Warning Nat Disasters
 6 Instituto Nacional de Pesquisas Espaciais (INPE)
 7 Carnegie Inst Sci
 8 University of Lancaster
 9 University of Lancaster
10 Univ Calif Berkeley
11 Universidade Federal de Vicosa
12 Vrije Univ Amsterdam
13 Universidade Federal de Goias
14 Embrapa Amazonia Oriental
15 US Forest Serv
16 Instituto Nacional de Pesquisas da Amazonia (INPA)
17 Bangor University
18 NASA
19 Instituto Nacional de Pesquisas Espaciais (INPE)
20 UNH, Inst Study Earth Oceans & Space
21 Univ E Anglia
22 Universidade de Brasília (UNB)
23 Max Planck Inst Biogeochem
24 Museu Paraense Emilio Goeldi
Author e-Mail Address 1
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 6 luiz.aragao@inpe.br
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19 jean.ometto@inpe.br
JournalGlobal Change Biology
Volume22
Number1
Pages92-109
Secondary MarkA1_MEDICINA_I A1_INTERDISCIPLINAR A1_GEOGRAFIA A1_GEOCIÊNCIAS A1_ENGENHARIAS_III A1_CIÊNCIAS_BIOLÓGICAS_I A1_CIÊNCIAS_AMBIENTAIS A1_CIÊNCIAS_AGRÁRIAS_I A1_BIODIVERSIDADE A2_PLANEJAMENTO_URBANO_E_REGIONAL_/_DEMOGRAFIA A2_ASTRONOMIA_/_FÍSICA B1_EDUCAÇÃO C_ENGENHARIAS_II
History (UTC)2016-03-03 17:42:40 :: simone -> administrator ::
2016-06-04 05:08:16 :: administrator -> simone :: 2016
2016-06-20 12:39:43 :: simone -> administrator :: 2016
2018-06-04 02:40:37 :: administrator -> simone :: 2016
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
Keywordscarbon emissions
ecosystem modeling
field inventories
forest dynamics
remote sensing
AbstractTropical forests harbor a significant portion of global biodiversity and are a critical component of the climate system. Reducing deforestation and forest degradation contributes to global climate-change mitigation efforts, yet emissions and removals from forest dynamics are still poorly quantified. We reviewed the main challenges to estimate changes in carbon stocks and biodiversity due to degradation and recovery of tropical forests, focusing on three main areas: (1) the combination of field surveys and remote sensing; (2) evaluation of biodiversity and carbon values under a unified strategy; and (3) research efforts needed to understand and quantify forest degradation and recovery. The improvement of models and estimates of changes of forest carbon can foster process-oriented monitoring of forest dynamics, including different variables and using spatially explicit algorithms that account for regional and local differences, such as variation in climate, soil, nutrient content, topography, biodiversity, disturbance history, recovery pathways, and socioeconomic factors. Generating the data for these models requires affordable large-scale remote-sensing tools associated with a robust network of field plots that can generate spatially explicit information on a range of variables through time. By combining ecosystem models, multiscale remote sensing, and networks of field plots, we will be able to evaluate forest degradation and recovery and their interactions with biodiversity and carbon cycling. Improving monitoring strategies will allow a better understanding of the role of forest dynamics in climate-change mitigation, adaptation, and carbon cycle feedbacks, thereby reducing uncertainties in models of the key processes in the carbon cycle, including their impacts on biodiversity, which are fundamental to support forest governance policies, such as Reducing Emissions from Deforestation and Forest Degradation.
AreaSRE
Arrangement 1urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDSR > Toward an integrated...
Arrangement 2urlib.net > BDMCI > Fonds > Produção anterior à 2021 > COCST > Toward an integrated...
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source Directory Contentthere are no files
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4. Conditions of access and use
Languageen
Target Filebustamante_toward.pdf
User Groupsimone
Reader Groupadministrator
simone
Visibilityshown
Archiving Policydenypublisher denyfinaldraft
Read Permissiondeny from all and allow from 150.163
Update Permissionnot transferred
5. Allied materials
Mirror Repositoryurlib.net/www/2011/03.29.20.55
Next Higher Units8JMKD3MGPCW/3ER446E
8JMKD3MGPCW/3F3T29H
Citing Item Listsid.inpe.br/bibdigital/2013/10.19.20.40 1
sid.inpe.br/bibdigital/2013/09.13.21.11 1
DisseminationWEBSCI; PORTALCAPES; SCOPUS.
Host Collectionsid.inpe.br/mtc-m21b/2013/09.26.14.25.20
6. Notes
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