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Record W2097483865 · doi:10.2980/17-4-3372

The phosphorus legacy of former agricultural land use can affect the production of germinable seeds in forest herbs

2010· article· en· W2097483865 on OpenAlexvenueno aff
Lander Baeten, Margot Vanhellemont, Pieter De Frenne, Martin Hermy, Kris Verheyen

Bibliographic record

VenueEcoscience · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGerminationBiologyAgricultureAgricultural landAgroforestryAgronomyEcology

Abstract

fetched live from OpenAlex

Land-use history can have large effects on the different life stages and demography of forest plant species. Here we studied how the legacies of former land use in post-agricultural forests, and increased phosphorus (P) availability in particular, may alter the germinability and seed quantity in populations of the forest herbs Primula elatior and Geum urbanum. We collected seeds in experimental populations of P. elatior and G. urbanum established in post-agricultural and ancient forest stands 10 y ago and determined the number of seeds per fruit and germination percentage. The effect of P availability on the production of germinable seeds was tested in a pot experiment with 3 P levels. Former land use had an impact on the mean germination percentage: seed germinability tended to be higher in post-agricultural compared to ancient forest sites. For G. urbanum, the number of seeds per fruit was also higher in post-agricultural forest. Whereas P availability had no effect on G. urbanum seed quantity and germinability, the germination percentage of P. elatior seeds increased significantly with P supply. Whereas previous studies showed that former agricultural land use can have detrimental effects on particular life stages of forest herbs (e.g., reduced juvenile or adult survival), the production of germinable seeds might rather benefit from it. The environmental legacies of former land use thus affect the various life stages of a plant differently, which results in complex effects of land-use history on the demography of forest plants.

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 score0.090
Threshold uncertainty score0.926

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 studies0.0000.001
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 head0.006
GPT teacher head0.214
Teacher spread0.207 · 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

Citations12
Published2010
Admission routes1
Has abstractyes

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