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Record W2968502596 · doi:10.1002/rra.3505

Pulses of seed release in riparian <scp><i>Salicaceae</i></scp> coincide with high atmospheric temperature

2019· article· en· W2968502596 on OpenAlexaff
Bérenger Bourgeois, Eduardo González

Bibliographic record

VenueRiver Research and Applications · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsEnvironmental scienceRiparian zoneSalicaceaeGerminationRelative humidityRiparian forestSeed dispersalPrecipitationSeedlingWoody plantAtmospheric sciencesHorticultureEcologyBiologyGeographyHabitatBiological dispersalGeology

Abstract

fetched live from OpenAlex

Abstract Riparian shrubs and trees in the Salicaceae family release their seeds when floods that create nursery sites for germination are more frequent, but little is known about the factors controlling temporal variations in seed release within the seed release period. The seed release of three riparian tree species dominating European floodplain forests ( Populus alba L., Populus nigra L., and Salix alba L.) was monitored in spring 2007 and 2008 using seed traps placed along the Middle Ebro River, NE Spain. Correlations relating biweekly seed rain intensity (seeds trapped per square meter) to meteorological (atmospheric temperature, cumulative precipitation, relative humidity, solar radiation, mean wind speed) and hydrological (river discharge) variables were investigated. The best combination of environmental variables explaining seed rain intensity was identified using an Akaike information selection criterion‐based backward selection, after accounting for temporal autocorrelation both in seed rain intensity and environmental variables. Seed rain correlated positively with temperature for P. alba , P. nigra , and S. alba , though its effect decreased with relative humidity for P. nigra . Our results can help fine‐tune the design of environmental flows to promote sexual recruitment of Salicaceae trees: Planning water releases during the hottest days of the seed dispersal period, when seed rain peaks, should maximize seed germination density and thus increase the potential for successful seedling establishment.

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 score0.056
Threshold uncertainty score0.270

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.007
GPT teacher head0.227
Teacher spread0.221 · 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

Citations10
Published2019
Admission routes1
Has abstractyes

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