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Record W2788447539 · doi:10.1071/wr17065

Green-tree retention and recovery of an old-forest specialist, the southern red-backed vole (Myodes gapperi), 20 years after harvest

2018· article· en· W2788447539 on OpenAlexafffundabout
Thomas P. Sullivan, Druscilla S. Sullivan

Bibliographic record

VenueWildlife Research · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPinus contortaClearcuttingBasal areaBiologyAbundance (ecology)EcologySpecies richnessContext (archaeology)BiodiversityOld-growth forestSnagSpecies diversityHabitatAgroforestry

Abstract

fetched live from OpenAlex

Context Populations of many mammalian species are reduced as a result of clearcutting, despite the concurrent objectives of wood production and conservation of mammal diversity on cutover forest land. To help ameliorate this decline, green-tree retention (GTR) leaves large live trees after harvest to provide mature forest habitat and increase structural diversity of the regenerating stand. Aims To test the hypotheses (H) that, at 20 years after harvest, (H1) abundance, reproduction and survival of the southern red-backed vole (Myodes gapperi), as well as (H2) abundance and species diversity of the forest-floor small mammal community, would increase with the basal area (BA) and density of residual trees after harvest. Methods Small mammals were live-trapped in 2015–16 in replicated clearcut, dispersed retention, aggregated retention, patch cut and uncut forest sites in mixed forests of Douglas fir (Pseudotsuga menziesii var. glauca) and lodgepole pine (Pinus contorta Dougl. var. latifolia) in southern British Columbia, Canada. Key results Mean BA and density of overstory coniferous trees were significantly different at 20 years post-harvest, being higher on patch cut and uncut forest sites than on the clearcut and GTR sites. M. gapperi populations were significantly greater in aggregated retention and uncut forest sites than in the other sites, but demographic parameters were similar among sites, and therefore H1 was partly supported. Mean total abundance of small mammals differed significantly among sites, with the highest overall numbers occurring in the aggregated retention (16.2), clearcut (13.6) and uncut forest sites (11.9). Mean species richness and diversity were highest in the GTR and clearcut sites. Thus, H2 was not supported. Conclusions Recovery of M. gapperi in aggregated retention sites with 10 m2 ha–1 BA of residual trees, as a group, occurred at 20 years post-harvest. Implications Aggregated retention of residual trees should help provide some habitat to conserve forest mammals on harvest openings, but successional development up to 20 years post-harvest may be required.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.040
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.292
Teacher spread0.261 · 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 source (direct Gemma or distilled Codex), 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

Citations35
Published2018
Admission routes3
Has abstractyes

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