In one paragraphSynthesis in Science advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
2 · The registryThe trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
3 · Its place in the literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
41 authors.
Viola HeinrichSection 1.4 Remote Sensing and Geoinformatics, GFZ Helmholtz Centre for Geosciences, Potsdam, Germany.ORCID 0000-0003-0501-0032 Amelia HolcombDepartment of Computer Science and Technology, University of Cambridge, Cambridge, UK.ORCID 0000-0001-5081-7201 Simon BesnardSection 1.4 Remote Sensing and Geoinformatics, GFZ Helmholtz Centre for Geosciences, Potsdam, Germany.ORCID 0000-0002-1137-103X Daniela Requena SuarezSection 1.4 Remote Sensing and Geoinformatics, GFZ Helmholtz Centre for Geosciences, Potsdam, Germany.ORCID 0000-0002-3081-6882 Robin ChazdonForest Research Institute, University of the Sunshine Coast, Sunshine Coast, Queensland, Australia.ORCID 0000-0002-7349-5687 Flavia Souza MendesPlanet Labs Germany GmbH, Berlin, Germany.
Celso H L Silva-JuniorInstituto de Pesquisa Ambiental da Amazônia (IPAM), Brasília 70863-520, Brazil.ORCID 0000-0002-1052-5551 Bienvenu H K AmaniUniversité Nangui Abrogoua, Unité de Formation et de Recherches en Sciences de la Nature, Laboratoire d'Écologie et du Développement Durable (LEDD), 02 BP 801 Abidjan 02, Côte d'Ivoire.ORCID 0000-0003-1610-1212 Jean-Francois BastinTeaching and Research Center (TERRA), Gembloux Agro-Bio Tech-Université de Liège, 5030 Gembloux, Belgium.ORCID 0000-0003-2602-7247 Timothée Besisa NgubaTeaching and Research Center (TERRA), Gembloux Agro-Bio Tech-Université de Liège, 5030 Gembloux, Belgium.ORCID 0000-0002-4808-0543 Na ChenDepartment of Civil and Environmental Engineering, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA.
Huiying ChenDepartment of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing 100084, China.
Philippe CiaisLaboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, 91191 Gif-sur-Yvette, France.ORCID 0000-0001-8560-4943 Xu DouDepartment of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing 100084, China.
Quan DuanDepartment of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing 100084, China.
Xueyuan GaoDepartment of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA.ORCID 0000-0003-2997-2332 Jo HouseSchool of Geographical Sciences, University of Bristol, Bristol, UK.
David M LapolaCentro de Pesquisas Meteorológicas e Climáticas Aplicadas à Agricultura - CEPAGRI, Universidade Estadual de Campinas - UNICAMP, Campinas 13086-883, Brazil.ORCID 0000-0002-2654-7835 Zekai MengDepartment of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing 100084, China.ORCID 0009-0007-1137-7996 Gert-Jan NabuursWageningen Environmental Research, Wageningen University and Research, Wageningen, Netherlands.ORCID 0000-0002-9761-074X Johannes ReicheLaboratory of Geo-Information Science and Remote Sensing, Wageningen University and Research, Wageningen, Netherlands.ORCID 0000-0002-4327-4349 Anne-Juul WelsinkLaboratory of Geo-Information Science and Remote Sensing, Wageningen University and Research, Wageningen, Netherlands.ORCID 0000-0002-0034-4220 Chao WuDepartment of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing 100084, China.ORCID 0000-0003-3233-856X Yidi XuLaboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, 91191 Gif-sur-Yvette, France.ORCID 0000-0003-1528-4256 Jinqi ZhaoDepartment of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing 100084, China.ORCID 0009-0003-1193-8846 Martin HeroldSection 1.4 Remote Sensing and Geoinformatics, GFZ Helmholtz Centre for Geosciences, Potsdam, Germany.ORCID 0000-0003-0246-6886 Funding
No grant is acknowledged in the PubMed record.
6 · The paper itselfAbstract
Aboveground carbon (AGC) fluxes from deforestation and subsequent regrowth in tropical moist forest (TMF) are increasingly well characterized, but carbon losses and gains following partial disturbance are uncertain. We synthesized 146 studies quantifying postdisturbance AGC changes relative to undisturbed forests across TMF. Immediate AGC losses (mean ± 1 SD; 2.5 ± 2.3 years after disturbance) following partial anthropogenic disturbances were greatest for forest fires (49 ± 26%), selective logging (34 ± 20%), and edge effects (31 ± 19%). Higher-frequency and -intensity disturbances significantly increased carbon loss. After 20 years of regeneration, AGC stock was higher in recovering degraded forests (41 to 117%) compared to secondary regrowth forests after complete deforestation (1 to 74%), indicating greater regeneration potential when forest structure is preserved. Our compiled database and associated meta-analysis improve accuracy and completeness for carbon inventory reporting and modeling. Substantial AGC losses and gains from distinct degradation and recovery processes are now better characterized, serving as an evidence base for policies to halt degradation and foster recovery for climate mitigation.
Indexed as
CarbonConservation of Natural ResourcesForestsTropical ClimateEcosystemTreesCarbon
Identifiers
PMID42397928
PMCPMC13330863
What OpenQuestion holds
Textmetadata
LicenceCC BY
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