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Determining the Optimal Sowing Density for a Mixture of Native Plants Used to Revegetate Degraded Ecosystems

2006· article· en· W1964503792 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueRestoration Ecology · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicRangeland and Wildlife Management
Canadian institutionsRoyal British Columbia MuseumPositive Living NorthUniversity of Northern British ColumbiaUniversity of Victoria
Fundersnot available
KeywordsSeedingSowingRevegetationAgronomyFertilizerPerennial plantBiologyGrowing seasonHerbaceous plantFestucaEnvironmental scienceEcological successionBotanyPoaceae

Abstract

fetched live from OpenAlex

Abstract No standardized, objective methodology exists for optimizing seeding rates when establishing herbaceous plant cover for pastures, hay fields, ecological restoration, or other revegetation activities. Seeding densities, fertilizer use, season of seeding, and the interaction of these treatments were tested using native plants on degraded sites in northern British Columbia, Canada. A mixture of 20% Achillea millefolium , 20% Carex aenea , 20% Elymus glaucus , 20% Festuca occidentalis , 16% Geum macrophyllum , and 4% Lupinus polyphyllus seed was applied at 0, 375, 750, 1,500, 3,000, and 6,000 pure live seed (PLS) per m 2 in 2.5 × 2.5–m rototilled test plots, established in the fall and spring, with and without fertilizer. There was no significant difference in plant cover of sown species between fall seeding and spring seeding, and few treatment interactions were identified in the first 2 years after sowing. There was no significant difference in cover between seed densities of 3,000 and 6,000 PLS/m 2 in the first year, nor among 1,500, 3,000, and 6,000 PLS/m 2 treatments in the second year. Seed densities as low as 375 PLS/m 2 produced year 2 plant cover equivalent to that observed at 3,000 PLS/m 2 in year 1. Plots sown to seed densities less than or equal to 750 PLS/m 2 generally exhibited an increase (infilling) in plant density from year 1 to year 2, whereas plots sown to seed densities greater than or equal to 1,500 PLS/m 2 generally exhibited a decrease (density‐dependent mortality) in plant density. These results imply a most efficient sowing density between 750 and 1,500 PLS/m 2 (corresponding to 190–301 established plants . m −2 after two growing seasons). It is suggested that net changes in plant populations observed over a range of sowing densities are a robust and objective means of determining optimal sowing densities for the establishment of herbaceous perennials.

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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 score0.030
Threshold uncertainty score0.242

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 head0.017
GPT teacher head0.241
Teacher spread0.224 · 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