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Record W2981612066 · doi:10.1126/science.aax4851

Global distribution of earthworm diversity

2019· article· en· W2981612066 on OpenAlexafffund
Helen R. P. Phillips, Carlos A. Guerra, Marie Luise Carolina Bartz, María J.I. Briones, George Gardner Brown, Thomas W. Crowther, Olga Ferlian, Konstantin B. Gongalsky, Johan van den Hoogen, Julia Krebs, Alberto Orgiazzi, Devin Routh, Benjamin Schwarz, Elizabeth M. Bach, Joanne M. Bennett, Ulrich Brose, Thibaud Decaëns, Birgitta König‐Ries, Michel Loreau, Jérôme Mathieu, Christian Mulder, Wim H. van der Putten, Kelly S. Ramirez, Matthias C. Rillig, David Russell, Michiel Rutgers, Madhav P. Thakur, Franciska T. de Vries, Diana H. Wall, David A. Wardle, Miwa Arai, Fredrick O. Ayuke, Geoff Baker, Robin Beauséjour, José Camilo Bedano, Klaus Birkhofer, Éric Blanchart, Bernd Blossey, Thomas Bolger, Robert L. Bradley, Mac A. Callaham, Yvan Capowiez, Mark E. Caulfield, Amy Choi, Felicity Crotty, Jasmine M. Crumsey, Andrea Dávalos, Darío J. Díaz Cosín, Anahí Domínguez, Andrés Duhour, N.J.M. van Eekeren, Christoph Emmerling, Liliana Falco, Rosa Fernández, Steven J. Fonte, Carlos Fragoso, André L.C. Franco, Martine Fugère, Abegail Fusilero, Shaieste Gholami, Michael J. Gundale, Mónica Gutiérrez, Davorka K. Hackenberger, Luis M. Hernández, Takuo Hishi, Andrew R. Holdsworth, Martin Holmstrup, Kristine N. Hopfensperger, Esperanza Huerta Lwanga, Veikko Huhta, Tunsisa T. Hurisso, Basil V. Iannone, M. Iordache, Monika Joschko, Nobuhiro Kaneko, Radoslava Kanianska, Aidan M. Keith, Courtland Kelly, Maria Kernecker, Jonatan Klaminder, Armand W. Koné, Yahya Kooch, Sanna Kukkonen, H. Lalthanzara, Daniel R. Lammel, Iurii M. Lebedev, Yiqing Li, Juan B. Jesús Lidón, Noa Kekuewa Lincoln, Scott R. Loss, Raphaël Marichal, Radim Matula, Jan Hendrik Moos, Gerardo Moreno, Alejandro Morón‐Ríos, Bart Muys, Johan Neirynck, Lindsey Norgrove, Marta Novo, Visa Nuutinen, Victoria Nuzzo, Johan Pansu, Shishir Paudel, Guenola Pérès, Lorenzo Pérez‐Camacho, Raúl Piñeiro, Jean‐François Ponge, Muhammad Imtiaz Rashid, Salvador Rebollo, Javier Rodeiro Iglesias, Miguel Á. Rodrı́guez, Alexander M. Roth, Guillaume Xavier Rousseau, Anna Rożen, Ehsan Sayad, Loes van Schaik, Bryant C. Scharenbroch, Michael Schirrmann, Olaf Schmidt, Boris Schröder, Julia Seeber, Maxim Shashkov, Jaswinder Singh, Sandy M. Smith, Michael Steinwandter, José Antonio Talavera, Dolores Trigo, Jiro Tsukamoto, Anne W. de Valença, Steven J. Vanek, Iñigo Virto, Adrian Wackett, Matthew Warren, Nathaniel H. Wehr, Joann K. Whalen, Michael Wironen, Volkmar Wolters, И. В. Зенкова, Weixin Zhang, Erin K. Cameron, Nico Eisenhauer

Bibliographic record

VenueScience · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInvertebrate Taxonomy and Ecology
Canadian institutionsMcGill UniversityUniversity of TorontoSaint Mary's UniversityUniversité de Sherbrooke
FundersUniversidad Complutense de MadridRussian Foundation for Basic ResearchStrategic Environmental Research and Development ProgramUniversity of Illinois at ChicagoUniversity of Illinois at Urbana-ChampaignLandwirtschaftliche RentenbankUniversität InnsbruckHigher Education Commision, PakistanEuropean Agricultural Fund for Rural DevelopmentTarbiat Modares UniversityUniversity of Hawai'i at MānoaNature ConservancyNatural Environment Research CouncilUniversidad Nacional de LujánRoyal Canadian Geographical SocietyUniversity of TorontoAgentúra na Podporu Výskumu a VývojaInternational Atomic Energy AgencyScience Foundation IrelandDeutsches Zentrum für integrative Biodiversitätsforschung Halle-Jena-LeipzigFundação de Amparo à Pesquisa e ao Desenvolvimento Científico e Tecnológico do MaranhãoJapan Society for the Promotion of ScienceDirectorate for Biological SciencesConselho Nacional de Desenvolvimento Científico e TecnológicoMinistry of Education, Culture, Sports, Science and TechnologyNatural Sciences and Engineering Research Council of CanadaAustrian Science FundConsejo Nacional de Investigaciones Científicas y TécnicasRussian Academy of SciencesOklahoma Agricultural Experiment StationEuropean CommissionFundação de Amparo à Pesquisa do Estado de São PauloCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorU.S. NavyConsejo Nacional de Ciencia y TecnologíaAgence Nationale de la RechercheUniversity of Hawai'iDeutsche ForschungsgemeinschaftFondo para la Investigación Científica y TecnológicaWageningen University and ResearchU.S. Department of DefenseMinisterio de Ciencia, Innovación y UniversidadesScience and Engineering Research BoardNational Science FoundationGrains Research and Development CorporationDePaul UniversityMcKnight FoundationInstituto Nacional de Investigación y Tecnología Agraria y Alimentaria
KeywordsEarthwormAbundance (ecology)EcologySpecies richnessBiomass (ecology)HabitatEcosystemTropicsTerrestrial ecosystemDiversity (politics)Species diversityBiologyGeography

Abstract

fetched live from OpenAlex

Soil organisms, including earthworms, are a key component of terrestrial ecosystems. However, little is known about their diversity, their distribution, and the threats affecting them. We compiled a global dataset of sampled earthworm communities from 6928 sites in 57 countries as a basis for predicting patterns in earthworm diversity, abundance, and biomass. We found that local species richness and abundance typically peaked at higher latitudes, displaying patterns opposite to those observed in aboveground organisms. However, high species dissimilarity across tropical locations may cause diversity across the entirety of the tropics to be higher than elsewhere. Climate variables were found to be more important in shaping earthworm communities than soil properties or habitat cover. These findings suggest that climate change may have serious implications for earthworm communities and for the functions they provide.

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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.188
Teacher spread0.175 · 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

Citations480
Published2019
Admission routes2
Has abstractyes

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