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Record W2944357061 · doi:10.1111/ele.13270

More salt, please: global patterns, responses and impacts of foliar sodium in grasslands

2019· letter· en· W2944357061 on OpenAlexaff
Elizabeth T. Borer, Eric M. Lind, Jennifer Firn, Eric W. Seabloom, T. Michael Anderson, Elisabeth S. Bakker, Lori Biederman, K. J. La Pierre, Andrew S. MacDougall, Joslin L. Moore, Anita C. Risch, M. Schütz, Carly Stevens

Bibliographic record

VenueEcology Letters · 2019
Typeletter
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsUniversity of Guelph
FundersNational Science Foundation
KeywordsHerbivoreNutrientHerbaceous plantSodiumAridBiologyEcologyAgronomyBotanyChemistry

Abstract

fetched live from OpenAlex

Sodium is unique among abundant elemental nutrients, because most plant species do not require it for growth or development, whereas animals physiologically require sodium. Foliar sodium influences consumption rates by animals and can structure herbivores across landscapes. We quantified foliar sodium in 201 locally abundant, herbaceous species representing 32 families and, at 26 sites on four continents, experimentally manipulated vertebrate herbivores and elemental nutrients to determine their effect on foliar sodium. Foliar sodium varied taxonomically and geographically, spanning five orders of magnitude. Site-level foliar sodium increased most strongly with site aridity and soil sodium; nutrient addition weakened the relationship between aridity and mean foliar sodium. Within sites, high sodium plants declined in abundance with fertilisation, whereas low sodium plants increased. Herbivory provided an explanation: herbivores selectively reduced high nutrient, high sodium plants. Thus, interactions among climate, nutrients and the resulting nutritional value for herbivores determine foliar sodium biogeography in herbaceous-dominated systems.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.297
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.006
GPT teacher head0.237
Teacher spread0.231 · 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

Citations52
Published2019
Admission routes1
Has abstractyes

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