MétaCan
Menu
Back to cohort
Record W2616111333 · doi:10.1126/science.aaj1631

Higher predation risk for insect prey at low latitudes and elevations

2017· article· en· W2616111333 on OpenAlexaff
Tomas Roslin, Bess Hardwick, Vojtêch Novotný, William K. Petry, Nigel R. Andrew, Ashley Asmus, Isabel C. Barrio, Yves Basset, Andrea Larissa Boesing, Timothy C. Bonebrake, Erin K. Cameron, Wesley Dáttilo, David A. Donoso, Pavel Drozd, Claudia L. Gray, David S. Hik, Sarah J. Hill, Tapani Hopkins, Shuyin Huang, Benita C. Laird‐Hopkins, Liisa Laukkanen, Owen T. Lewis, Sol Milne, Isaiah Mwesige, Akihiro Nakamura, Colleen S. Nell, Elizabeth Nichols, Alena Prokurat, Kateřina Sam, Niels Martin Schmidt, Alison Slade, Victor Slade, Alžběta Suchanková, Tiit Teder, Saskya van Nouhuys, Vigdis Vandvik, Anita Weissflog, Vital Zhukovich, Eleanor M. Slade

Bibliographic record

VenueScience · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsUniversity of Alberta
FundersNatural Environment Research CouncilAcademy of FinlandNorges ForskningsrådGrantová Agentura České RepublikySuomen KulttuurirahastoOskar Öflunds StiftelseEuropean Science FoundationNational Science FoundationHaridus- ja TeadusministeeriumSight Research UKFundação de Amparo à Pesquisa do Estado de São PauloJohns Hopkins University
KeywordsPredationInsectLatitudeBiologyEcologyZoologyGeographyGeodesy

Abstract

fetched live from OpenAlex

Biotic interactions underlie ecosystem structure and function, but predicting interaction outcomes is difficult. We tested the hypothesis that biotic interaction strength increases toward the equator, using a global experiment with model caterpillars to measure predation risk. Across an 11,660-kilometer latitudinal gradient spanning six continents, we found increasing predation toward the equator, with a parallel pattern of increasing predation toward lower elevations. Patterns across both latitude and elevation were driven by arthropod predators, with no systematic trend in attack rates by birds or mammals. These matching gradients at global and regional scales suggest consistent drivers of biotic interaction strength, a finding that needs to be integrated into general theories of herbivory, community organization, and life-history evolution.

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 score0.002
Threshold uncertainty score0.007

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)0.0020.000

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 head0.048
GPT teacher head0.289
Teacher spread0.240 · 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

Citations522
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueScienceSame topicSpecies Distribution and Climate ChangeFrench-language works237,207