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Record W2135762822 · doi:10.1890/14-2333.1

The importance of plant genotype and contemporary evolution for terrestrial ecosystem processes

2015· article· en· W2135762822 on OpenAlexaff
Connor R. Fitzpatrick, Anurag A. Agrawal, Nathan Basiliko, Amy P. Hastings, Marney E. Isaac, Michael D. Preston, Marc T. J. Johnson

Bibliographic record

VenueEcology · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsThe Scarborough HospitalLaurentian UniversityUniversity of Toronto
Fundersnot available
KeywordsEcosystemBiologyEcologyHerbivoreSeedlingBiomass (ecology)Evolutionary ecologyTerrestrial ecosystemPlant evolutionAdaptation (eye)AgronomyHost (biology)

Abstract

fetched live from OpenAlex

Plant genetic variation and evolutionary dynamics are predicted to impact ecosystem processes but these effects are poorly understood. Here we test the hypothesis that plant genotype and contemporary evolution influence the flux of energy and nutrients through soil, which then feedback to affect seedling performance in subsequent generations. We conducted a multiyear field evolution experiment using the native biennial plant Oenothera biennis. This experiment was coupled with experimental assays to address our hypothesis and quantify the relative importance of evolutionary and ecological factors on multiple ecosystem processes. Plant genotype, contemporary evolution, spatial variation, and herbivory affected ecosystem processes (e.g., leaf decay, soil respiration, seedling performance, N cycling), but their relative importance varied between specific ecosystem variables. Insect herbivory and evolution also contributed to a feedback that affected seedling biomass of O. biennis in the next generation. Our results show that heritable variation among plant genotypes can be an important factor affecting local ecosystem processes, and while effects of contemporary evolution were detectable and sometimes strong, they were often contingent on other ecological, factors.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.966

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)0.0000.000

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 head0.023
GPT teacher head0.241
Teacher spread0.218 · 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.

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

Citations20
Published2015
Admission routes1
Has abstractyes

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