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Record W2052119654 · doi:10.1139/b04-143

Soil seed bank composition over desert microhabitats: patterns and plausible mechanisms

2004· article· en· W2052119654 on OpenAlexvenueno aff
Luis Marone, Víctor R. Cueto, Fernando A. Milesi, Javier López de Casenave

Bibliographic record

VenueCanadian Journal of Botany · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsnot available
FundersUniversidad de Buenos AiresConsejo Nacional de Investigaciones Científicas y TécnicasJohn Simon Guggenheim Memorial Foundation
KeywordsSoil seed bankSeed dispersalShrublandForbSeed predationBiological dispersalBiologyProsopisLarreaSeed dispersal syndromeHabitatCanopyAgronomyDiaspore (botany)Deserts and xeric shrublandsGerminationEcologyShrubPopulationGrassland

Abstract

fetched live from OpenAlex

We assessed soil seed bank composition and size over several microhabitats of two habitats of the central Monte Desert of Argentina (open Prosopis woodland and Larrea shrubland) to analyse differences among them. Seed densities were similar to those already reported for other deserts, but we found consistent differences in seed composition among microhabitats. Whereas grass seeds (e.g., Aristida, Pappophorum, Neobouteloua, Trichloris, Digitaria) prevailed in natural depressions of open areas, forb seeds (e.g., Phacelia, Lappula, Descurainia, Plantago, Chenopodium) were more abundant under trees. The comparison of seed production during primary dispersal (i.e., seed rain) with seed density on the ground at the end of dispersal indicated that most forb seeds entered the habitat through the micro habitats located beneath the canopy of trees and tall shrubs, and remained there after redistribution. Most grass seeds, by contrast, entered it through bare-soil and under-grass microhabitats, and reached more even distributions after secondary dispersal, especially because of dramatic losses in bare soil. Patterns of plant recruitment and seed dynamics in specific microhabitats were better understood when differences of soil seed bank composition, but not of total seed density, were taken into account.Key words: Monte Desert, seed dispersal, seed predation, seed production, seeds.

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 score0.272
Threshold uncertainty score0.736

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 head0.005
GPT teacher head0.193
Teacher spread0.188 · 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

Citations60
Published2004
Admission routes1
Has abstractyes

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