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Record W4392866980 · doi:10.1002/ecs2.4785

Geographic gradients in a functional trait: Drivers of body size and size diversity of ground invertebrate communities

2024· article· en· W4392866980 on OpenAlexafffund
Michael Kaspari, Katie E. Marshall, Michael D. Weiser, Cameron D. Siler, Miranda K. Theriot, Kirsten M. de Beurs

Bibliographic record

VenueEcosphere · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaNational Science Foundation
KeywordsInvertebrateEcologyTraitDiversity (politics)Functional diversityBergmann's ruleBiologyGeographyComputer science

Abstract

fetched live from OpenAlex

Abstract Body size is a key functional trait governing how an animal community transforms resources and conditions into performance, abundance, and fitness. Here we use the National Ecological Observatory Network of pitfall traps to explore how an ecosystem's plant productivity, temperature, and growing season length accounts for the range of body size across 99 ground invertebrate communities. The 19‐fold continental variation in mean body size failed to covary with latitude, while common ordinal subtaxa grew smaller (e.g., myriapods) to larger (e.g., acari) from Puerto Rico to Alaska. Communities with a larger mean size arose when winters were longer and gross primary productivity was high. The diversity of body sizes in a community (measured as the CV) varied ninefold and decreased with latitude ( r 2 = 0.24) consistently across common orders. Size‐diverse communities were less likely in ecosystems with long winters (suggesting constraints on the time to build, r 2 = 0.34) and those with high invertebrate activity (and hence trap catch, r 2 = 0.12). Body size distributions thus appeared to arise from conflicting combinations of constraint (i.e., the ability to build large bodies) and performance (utility of large size in surviving long winters). As warming promotes growing season length, populations of larger, rarer individuals may benefit.

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)0.000
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 score0.028
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

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

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 head0.009
GPT teacher head0.195
Teacher spread0.186 · 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

Citations1
Published2024
Admission routes2
Has abstractyes

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