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Record W1973835720 · doi:10.1111/jvs.12058

Plant community assembly in semi‐natural grasslands and ex‐arable fields: a trait‐based approach

2013· article· en· W1973835720 on OpenAlexfundno aff
Bryndís Marteinsdóttir, Ove Eriksson

Bibliographic record

VenueJournal of Vegetation Science · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsnot available
FundersVetenskapsrådetMcGill University
KeywordsGrasslandArable landSpecies richnessAbundance (ecology)EcologyPlant communitySpecific leaf areaBiologyRelative species abundanceAgronomySpecies diversityTraitBotany

Abstract

fetched live from OpenAlex

Abstract Question The assembly of plants into communities is one of the central topics in plant community ecology. The objective of this study was to investigate how plant functional trait diversity and environmental factors influence community assembly in two different grassland communities, and if variation in these factors could explain the difference in species assembly between these communities. Location Six grazed ex‐arable fields and eight semi‐natural grasslands in southeast S weden. Methods We estimated species abundance and measured soil attributes at each site. For each species within each site we measured specific leaf area ( SLA ), leaf dry matter content ( LDMC ) and seed mass. We analysed the data both for abundance‐weighted species values and species occurrence. Results Trait gradient analysis indicated random distribution of species among sites, while CCA analysis indicated that both soil phosphorus and moisture were related to species assembly at a site. Correlations and fourth‐corner analysis also revealed a relationship between measured species traits and soil phosphorus and moisture. There was a lower average seed mass and higher SLA of species in ex‐arable fields compared to species in semi‐natural grasslands. Conclusions Even though trait gradient analysis indicated that plant community assembly in the studied grasslands was random, other results implied that species occurrence and abundance was influenced both by environmental factors and species traits. Higher species richness in semi‐natural grasslands was associated with more large‐seeded species found there compared to ex‐arable fields, indicating that large‐seeded species establish in grasslands later than small‐seeded 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 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)0.001
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 score0.064
Threshold uncertainty score0.238

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.017
GPT teacher head0.251
Teacher spread0.234 · 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

Citations25
Published2013
Admission routes1
Has abstractyes

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