MétaCan
Menu
Back to cohort
Record W3138930504 · doi:10.1139/as-2020-0020

Developing common protocols to measure tundra herbivory across spatial scales

2021· article· en· W3138930504 on OpenAlexafffundvenue
Isabel C. Barrio, Dorothée Ehrich, Eeva M. Soininen, Virve Ravolainen, C. Guillermo Bueno, Olivier Gilg, Amanda M. Koltz, James D. M. Speed, David S. Hik, Martin Alfons Mörsdorf, Juha M. Alatalo, Anders Angerbjörn, Joël Bêty, Loı̈c Bollache, Noémie Boulanger‐Lapointe, Glen S. Brown, Isabell Eischeid, Marie‐Andrée Giroux, Tomáš Hájek, Brage Bremset Hansen, Stijn P. Hofhuis, Jean‐François Lamarre, Johannes Lang, Christopher J. Latty, Nicolas Lecomte, Petr Macek, Laura McKinnon, Isla H. Myers‐Smith, Åshild Ønvik Pedersen, Janet S. Prevéy, James D. Roth, Sarah T. Saalfeld, Niels Martin Schmidt, Paul A. Smith, Aleksandr Sokolov, Natalia Sokolova, Claire D. Stolz, R.S.A. van Bemmelen, Øystein Varpe, Paul Woodard, Ingibjörg S. Jónsdóttir

Bibliographic record

VenueArctic Science · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsEnvironment and Climate Change CanadaDefence Research and Development CanadaUniversité de MonctonMinistry of Natural Resources and ForestryYork UniversityUniversity of British ColumbiaCenter for Northern StudiesUniversité du Québec à RimouskiUniversity of ManitobaSimon Fraser University
FundersEuropean Regional Development FundNatural Environment Research CouncilQatar PetroleumNorges ForskningsrådInstitut Polaire Français Paul Emile VictorInternational Arctic Science CommitteeCarl Tryggers Stiftelse för Vetenskaplig ForskningUniversité de MonctonEesti TeadusagentuurSight Research UKGovernment of NunavutHáskóli ÍslandsCentre National de la Recherche ScientifiquePolar Knowledge Canada
KeywordsTundraMeasure (data warehouse)HerbivoreEcologyGeographyComputer scienceBiologyData miningEcosystem

Abstract

fetched live from OpenAlex

Understanding and predicting large-scale ecological responses to global environmental change requires comparative studies across geographic scales with coordinated efforts and standardized methodologies. We designed, applied, and assessed standardized protocols to measure tundra herbivory at three spatial scales: plot, site (habitat), and study area (landscape). The plot- and site-level protocols were tested in the field during summers 2014–2015 at 11 sites, nine of them consisting of warming experimental plots included in the International Tundra Experiment (ITEX). The study area protocols were assessed during 2014–2018 at 24 study areas across the Arctic. Our protocols provide comparable and easy to implement methods for assessing the intensity of invertebrate herbivory within ITEX plots and for characterizing vertebrate herbivore communities at larger spatial scales. We discuss methodological constraints and make recommendations for how these protocols can be used and how sampling effort can be optimized to obtain comparable estimates of herbivory, both at ITEX sites and at large landscape scales. The application of these protocols across the tundra biome will allow characterizing and comparing herbivore communities across tundra sites and at ecologically relevant spatial scales, providing an important step towards a better understanding of tundra ecosystem responses to large-scale environmental change.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.130
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.109
GPT teacher head0.343
Teacher spread0.234 · 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 teacher head, not a consensus.

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

Citations9
Published2021
Admission routes3
Has abstractyes

Explore more

Same venueArctic ScienceSame topicClimate change and permafrostFrench-language works237,207