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Record W4406334960 · doi:10.3390/f16010126

Restoration of Coniferous Forest and Myodes gapperi: Responses to Thinning, Fertilization, and Succession over a 45-Year Period

2025· article· en· W4406334960 on OpenAlexafffundabout
Thomas P. Sullivan, Druscilla S. Sullivan

Bibliographic record

VenueForests · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicForest Ecology and Biodiversity Studies
Canadian institutionsUniversity of British Columbia
FundersHabitat Conservation Trust Foundation
KeywordsClearcuttingUnderstoryPinus contortaEcological successionThinningCanopyPrescribed burnAbundance (ecology)Coarse woody debrisEcologyBiologyForestryEnvironmental scienceGeographyHabitat

Abstract

fetched live from OpenAlex

Research Highlights: We report a 45-year time-line of forest restoration after harvesting and responses of red-backed voles (Myodes gapperi), an indicator species of closed-canopy forests. Background and Objectives: We have a unique long-term window to test four hypotheses that evaluated the relationship of M. gapperi with old forest structural attributes. Materials and Methods: The study began in old-growth lodgepole pine (Pinus contorta var. latifolia) through clearcutting, regeneration, stand thinning, fertilization, and growth to mature forest (1979 to 2024) in southern BC, Canada. Populations of red-backed voles were monitored in all phases of forest restoration. Results: Clearcutting resulted in the extirpation of M. gapperi followed by small (≤2 voles/ha) populations in young (13–23 years) thinned and fertilized stands. At age 33, the mean annual abundance of M. gapperi (6.5 to 8.7/ha) was highest in the heavily thinned and old-growth stands. At age 43, mean numbers of M. gapperi ranged from 2.7 to 4.2/ha in these same stands. Heavily thinned stands had large trees, multi-layered canopies of conifers, and understory patchiness. Conclusions: This is the first report of long-term responses of M. gapperi to the restoration of mature forest. M. gapperi is a suitable species for monitoring the recovery of some old forest structural features.

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 score0.011
Threshold uncertainty score0.608

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 head0.014
GPT teacher head0.243
Teacher spread0.229 · 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
Published2025
Admission routes3
Has abstractyes

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