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Record W3160692687 · doi:10.1139/as-2020-0041

The tundra phenology database: more than two decades of tundra phenology responses to climate change

2021· article· en· W3160692687 on OpenAlexafffundvenue
Janet S. Prevéy, Sarah C. Elmendorf, Anne D. Bjorkman, Juha M. Alatalo, Isabel W. Ashton, Jakob J. Assmann, Robert G. Björk, Mats P. Björkman, Nicoletta Cannone, Michele Carbognani, Chelsea Chisholm, Karin Clark, Courtney G. Collins, Elisabeth J. Cooper, Bo Elberling, Esther R. Frei, Gregory R.H. Henry, Robert D. Hollister, Toke T. Høye, Ingibjörg S. Jónsdóttir, Jeffrey T. Kerby, Kari Klanderud, Christopher W. Kopp, Esther Lévesque, Marguerite Mauritz, Ulf Molau, Isla H. Myers‐Smith, Susan M. Natali, Steven F. Oberbauer, Zoe A. Panchen, Alessandro Petraglia, Eric Post, Christian Rixen, Heidi Rodenhizer, Sabine B. Rumpf, Niels Martin Schmidt, Ted Schuur, Philipp Semenchuk, Jane G. Smith, Katharine N. Suding, Ørjan Totland, Tiffany G. Troxler, Henrik Wahren, J. M. Welker, Sonja Wipf, Yue Yang

Bibliographic record

VenueArctic Science · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsUniversité du Québec à Trois-RivièresUniversity of British ColumbiaInstitute for Circumpolar Health Research
FundersBiological and Environmental ResearchNatural Resources CanadaNorges ForskningsrådNatural Environment Research CouncilSwiss Federal Institute for Forest, Snow and Landscape ResearchDanmarks GrundforskningsfondMiljøstyrelsenEuropean CommissionEidgenössische Anstalt für Wasserversorgung Abwasserreinigung und GewässerschutzAarhus Universitets ForskningsfondSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Research FoundationAarhus UniversitetArcticNetU.S. Department of EnergyDeutsche ForschungsgemeinschaftSight Research UKNatural Sciences and Engineering Research Council of CanadaW. Garfield Weston FoundationPolar Knowledge CanadaVillum FondenNational Geographic SocietyDanmarks Frie ForskningsfondNational Science Foundation
KeywordsTundraPhenologyClimate changeEnvironmental scienceGeographyPhysical geographyClimatologyEcologyEcosystemBiologyGeology

Abstract

fetched live from OpenAlex

Observations of changes in phenology have provided some of the strongest signals of the effects of climate change on terrestrial ecosystems. The International Tundra Experiment (ITEX), initiated in the early 1990s, established a common protocol to measure plant phenology in tundra study areas across the globe. Today, this valuable collection of phenology measurements depicts the responses of plants at the colder extremes of our planet to experimental and ambient changes in temperature over the past decades. The database contains 150 434 phenology observations of 278 plant species taken at 28 study areas for periods of 1–26 years. Here we describe the full data set to increase the visibility and use of these data in global analyses and to invite phenology data contributions from underrepresented tundra locations. Portions of this tundra phenology database have been used in three recent syntheses, some data sets are expanded, others are from entirely new study areas, and the entirety of these data are now available at the Polar Data Catalogue ( https://doi.org/10.21963/13215 ).

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.043
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.015
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.005

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 head0.086
GPT teacher head0.328
Teacher spread0.242 · 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 designNot applicable
Domainnot available
GenreDataset

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

Citations15
Published2021
Admission routes3
Has abstractyes

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