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Record W2621369378 · doi:10.3390/f8060194

Preserving Ecosystem Services on Indigenous Territory through Restoration and Management of a Cultural Keystone Species

2017· article· en· W2621369378 on OpenAlexaffabout
Yadav Uprety, Hugo Asselin, Yves Bergeron

Bibliographic record

VenueForests · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsNatural Sciences and Engineering Research Council of CanadaUniversité du Québec à MontréalUniversité du Québec en Abitibi-Témiscamingue
Fundersnot available
KeywordsWildlifeKeystone speciesGeographyBiodiversityHabitatAgroforestryOverexploitationEcosystem servicesEcologyEcosystemForest managementRegeneration (biology)Forest ecologyForestryBiology

Abstract

fetched live from OpenAlex

Eastern white pine (Pinus strobus L.) is a cultural keystone tree species in the forests of eastern North America, providing numerous ecosystem services to Indigenous people. White pine abundance in the landscape has considerably decreased over the last few centuries due to overharvesting, suppression of surface fires, extensive management, and plantation failure. The Kitcisakik Algonquin community of western Quebec is calling for restoration and sustainable management of white pine on its ancestral territory, to ensure provision of associated ecosystem services. We present five white pine restoration and management scenarios taking into account community needs and ecological types: (1) natural regeneration of scattered white pines to produce individuals of different sizes and ages used as medicinal plants; (2) protection of supercanopy white pines used as landmarks and for providing habitat for flagship wildlife species, and younger individuals left as regeneration and future canopy trees; (3) the uniform shelterwood system to create white pine-dominated stands that provide habitat for flagship wildlife species and support cultural activities; (4) under-canopy plantations to yield mature white pine stands for timber production; (5) mixed plantations to produce forests with aesthetic qualities that provide wildlife habitat and protect biodiversity.

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 score0.034
Threshold uncertainty score0.980

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 communication0.0000.001
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 head0.014
GPT teacher head0.248
Teacher spread0.233 · 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

Citations31
Published2017
Admission routes2
Has abstractyes

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