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Record W4323543751 · doi:10.21203/rs.3.rs-2635490/v1

Global patterns of thermal niche filling in ectotherms

2023· preprint· en· W4323543751 on OpenAlexafffund
Nikki A. Moore, Ignacio Morales‐Castilla, Anna L. Hargreaves, Miguel Á. Olalla‐Tárraga, Fabricio Villalobos, Piero Calosi, Susana Clusella‐Trullas, Juan G. Rubalcaba, Adam C. Algar, Brezo Martínez, Laura Juguera Rodríguez, Sarah Gravel, Joanne M. Bennett, Greta C. Vega, Carsten Rahbek, Miguel B. Araújo, Joey R. Bernhardt, Jennifer M. Sunday

Bibliographic record

VenueResearch Square · 2023
Typepreprint
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsUniversity of GuelphSimon Fraser UniversityLakehead UniversityUniversité du Québec à RimouskiMcGill University
FundersDeutsches Zentrum für integrative Biodiversitätsforschung Halle-Jena-LeipzigNatural Sciences and Engineering Research Council of CanadaUniversidad de AlcaláEuropean CommissionHorizon 2020 Framework ProgrammeDeutsche ForschungsgemeinschaftComunidad de Madrid
KeywordsEctothermNicheThermalEnvironmental scienceEcologyBiologyGeographyMeteorology

Abstract

fetched live from OpenAlex

Abstract Understanding how temperature determines the distribution of life is necessary to assess species’ sensitivities to contemporary climate change. Here we test the importance of temperature in limiting geographic ranges of ectotherms by comparing temperatures across occupied ranges to those species could potentially occupy based on their physiological thermal tolerances. Whereas marine and tropical terrestrial species occupy temperatures that closely match their thermal tolerances, high-latitude terrestrial species under-occupy warm temperatures and are absent from thermally tolerable areas towards the equator. This suggests that on land, temperature less often limits the equatorward range edge of temperate species, supporting the hypothesis that their historic expansion ‘out of the tropics’ was associated with tropical biotic exclusion. Our findings predict more direct responses to climate warming of marine ranges and cool range edges of terrestrial species.

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 score0.003
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
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.140
GPT teacher head0.399
Teacher spread0.259 · 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

Citations2
Published2023
Admission routes2
Has abstractyes

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