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Post-fire dynamics of the forest formations in the mounts of Tlemcen (Western of Algeria): Case of the Forest of Zarifet

2023· article· en· W4324327699 on OpenAlexaff
Okkacha Hasnaoui, Farah Bessaid, Mohamed Bourouaha, Brahim Babali, Sid Ahmed Aouadj, H. Khatir

Bibliographic record

VenueBIODIVERSITY JOURNAL · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMediterranean and Iberian flora and fauna
Canadian institutionsStem Cell Network
Fundersnot available
KeywordsGeographyForestry

Abstract

fetched live from OpenAlex

A study on the post-fire dynamics of plant species in the Zarifet forest (National Park of Tlemcen, north-western Algeria) was conducted after a violent fire that destroyed more than 200 hectares in the month of October 2016.Floristic records were done at a control site and the burned area during the phenological period, which extends from 2017 to 2019.The analysis of the floristic succession indicated a continuum of population dynamics over the three years after the fire.The results showed that the number of species found in the burnt sites reached 52 species (39%) after 8 months from the initial fire and 121 of them (91%) at three years afterward.The natural regrowth of the vegetation in the Tlemcen Mountains is typical of the "tiger bush".The competitivity between the different species has been highlighted in the present study.The most competitive species in the post-fire occupation of the soil are stump-rejecting species and geophytes one, such as Quercus ilex, Chamaerops humilis, Calicotome intermedia, Asparagus acutifolius, Ulex boivinii, Drimia maritima, Cistus sp., Stipa tenacissima and Ampelodesmos mauritanicus.The analysis of the frequency indices (F.I.) seem to be in favor of an expanding tendency of these taxa.

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 score0.009
Threshold uncertainty score0.198

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 head0.030
GPT teacher head0.217
Teacher spread0.187 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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