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Record W4296797773 · doi:10.1126/science.abo3856

Termite sensitivity to temperature affects global wood decay rates

2022· article· en· W4296797773 on OpenAlexafffund
Amy E. Zanne, Habacuc Flores‐Moreno, Jeff R. Powell, William K. Cornwell, James W. Dalling, Amy T. Austin, Aimée T. Classen, Paul Eggleton, K. Okada, Catherine L. Parr, E. Carol Adair, Stephen Adu‐Bredu, Md Azharul Alam, Carolina Alvarez-Garzón, Deborah M. G. Apgaua, Roxana Aragón, Marcelo Ardón, Stefan K. Arndt, Louise A. Ashton, Nicholas A. Barber, Jacques Beauchêne, Matty P. Berg, Jason Beringer, Matthias M. Boer, José Antonio Bonet, Katherine Bunney, Tynan Burkhardt, Dulcinéia de Carvalho, Dennis Castillo‐Figueroa, Lucas A. Cernusak, Alexander W. Cheesman, Tainá Mamede Cirne-Silva, James Cleverly, Johannes H. C. Cornelissen, Timothy J. Curran, André M. D’Angioli, Caroline Dallstream, Nico Eisenhauer, Fidèle Evouna Ondo, Alex Fajardo, Romina Fernández, Astrid Ferrer, Marco Aurélio Leite Fontes, Mark L. Galatowitsch, Grizelle González, Felix Gottschall, Peter Grace, Elena Granda, Hannah M. Griffiths, Mariana Guerra Lara, Motohiro Hasegawa, Mariet M. Hefting, Nina Hinko‐Najera, Lindsay B. Hutley, Jennifer Jones, Anja Kahl, Mirko Karan, Joost A. Keuskamp, Tim Lardner, Michael J. Liddell, Craig Macfarlane, Cate Macinnis‐Ng, Ravi Fernandes Mariano, Marcela Méndez, Wayne S. Meyer, Akira Mori, Aloysio Souza de Moura, Matthew Northwood, Romà Ogaya, Rafael S. Oliveira, Alberto Orgiazzi, Juliana Pardo, Guille Peguero, Josep Peñuelas, Luis I. Pérez, Juan M. Posada, Cecilia M. Prada, Tomáš Přívětivý, Suzanne M. Prober, Jonathan Prunier, Gabriel W. Quansah, Víctor Resco de Dios, Ronny Richter, Mark P. Robertson, Lucas Fernandes Rocha, Megan A. Rúa, Carolina Sarmiento, Richard Silberstein, Mateus Silva, Flávia Freire de Siqueira, Matthew G. Stillwagon, Jacqui Stol, Melanie K. Taylor, François P. Teste, David Y. P. Tng, David Tucker, Manfred Türke, Michael D. Ulyshen, Oscar J. Valverde‐Barrantes, Eduardo van den Berg, Richard S. P. van Logtestijn, G. F. Veen, Jason G. Vogel, Tim Wardlaw, Georg Wiehl, Christian Wirth, Michaela J. Woods, Paul‐Camilo Zalamea

Bibliographic record

VenueScience · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInsect and Arachnid Ecology and Behavior
Canadian institutionsUniversité de MontréalMcGill University
FundersDivision of Environmental BiologyJoint Research CentreU.S. Forest ServiceCollege of Engineering, Michigan State UniversityAgencia Nacional de Investigación y DesarrolloDeutsches Zentrum für integrative Biodiversitätsforschung Halle-Jena-LeipzigUniversitat Autònoma de BarcelonaUniversitat de LleidaUniversidad del RosarioUniversität LeipzigUniversidad Nacional de TucumánCentre de Coopération Internationale en Recherche Agronomique pour le DéveloppementUniversidad de AlcaláUniversité de MontréalForeign, Commonwealth and Development OfficeCentre National de la Recherche ScientifiqueSouthwest University of Science and TechnologyUniversity of Hong KongMcGill UniversityConselho Nacional de Desenvolvimento Científico e TecnológicoGeorge Washington UniversityConsejo Nacional de Investigaciones Científicas y TécnicasUniversiteit UtrechtAustralian Academy of ScienceUniversidade Estadual de CampinasRijksuniversiteit GroningenCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorInternational Institute of Tropical ForestryEuropean CommissionFundação de Amparo à Pesquisa do Estado de São PauloNorth Carolina State UniversityCharles Darwin UniversityKoninklijke Nederlandse Akademie van WetenschappenFundação de Amparo à Pesquisa do Estado de Minas GeraisEdith Cowan UniversityInstitut National de la Recherche AgronomiqueJames Cook UniversityUniversity of MelbourneUniversity of TokyoEnvironmental Restoration and Conservation AgencyAgence Nationale de la RechercheAgroParisTechUniversity of TasmaniaAgencia Nacional de Promoción Científica y TecnológicaCommonwealth Scientific and Industrial Research OrganisationUniversidad de TalcaNederlands Instituut voor EcologieUniversidad Nacional de San LuisDepartamento Administrativo de Ciencia, Tecnología e Innovación (COLCIENCIAS)Deutsche ForschungsgemeinschaftSight Research UKSouthwest UniversityCentres de Recerca de CatalunyaMichigan State UniversityUniversity of DaytonFundación Ramón ArecesFlorida International UniversityDirectorate for Biological SciencesUniversity of South FloridaUniversidade Federal de LavrasQueensland University of TechnologyNatural Environment Research CouncilCollege of Science and Engineering, University of MinnesotaU.S. Department of AgricultureNorthern Illinois UniversityNational Science Foundation
KeywordsDecomposerSubtropicsEnvironmental scienceTropicsTropical climateClimate changePrecipitationCarbon fibersEcosystemHumid subtropical climateTropical forestAtmospheric sciencesGlobal warmingEcologyBiologyGeographyGeologyMaterials scienceMeteorology

Abstract

fetched live from OpenAlex

Deadwood is a large global carbon store with its store size partially determined by biotic decay. Microbial wood decay rates are known to respond to changing temperature and precipitation. Termites are also important decomposers in the tropics but are less well studied. An understanding of their climate sensitivities is needed to estimate climate change effects on wood carbon pools. Using data from 133 sites spanning six continents, we found that termite wood discovery and consumption were highly sensitive to temperature (with decay increasing >6.8 times per 10°C increase in temperature)-even more so than microbes. Termite decay effects were greatest in tropical seasonal forests, tropical savannas, and subtropical deserts. With tropicalization (i.e., warming shifts to tropical climates), termite wood decay will likely increase as termites access more of Earth's surface.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.268
Teacher spread0.262 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations146
Published2022
Admission routes2
Has abstractyes

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