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Record W2605532620

Effects of Disturbance and Landscape Position on Vegetation Structure and Productivity in Ontario Boreal Forests: Implications for Woodland Caribou (Rangifer tarandus caribou) Forage

2014· dissertation· en· W2605532620 on OpenAlexaboutno aff
Erin E. Mallon

Bibliographic record

VenueThe Atrium (University of Guelph) · 2014
Typedissertation
Languageen
FieldEnvironmental Science
TopicRangeland and Wildlife Management
Canadian institutionsnot available
Fundersnot available
KeywordsWoodland caribouDisturbance (geology)TaigaVegetation (pathology)EcologyBorealGeographyProductivityWoodlandForageForestryEnvironmental scienceBiologyPredation
DOInot available

Abstract

fetched live from OpenAlex

Hypotheses explaining recent declines in the abundance of woodland caribou in boreal Ontario include increased disturbances and predation. Caribou may select peatlands to avoid predation. Peatlands are regarded as low productivity, nutrient-limited systems, caribou may face a trade-off between predation risk and nutrient intake through foraging. I quantified differences in plant community and plant foliar quality in boreal stands across drainage class, disturbance type and time-following-disturbance. I found that understory productivity was influenced more by drainage and time-following-disturbance than by disturbance type. I also quantified variation among stand characteristics and plant functional types using measures of plant foliar quality. Foliar quality varied mostly by plant functional type. Overall, this thesis does not support the hypothesis that caribou face a trade-off between forage quality and predation risk by selecting peatlands, as peatlands had greater levels of understory productivity and foliar quality relative to uplands.

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 score0.370
Threshold uncertainty score0.975

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 head0.004
GPT teacher head0.186
Teacher spread0.182 · 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

Citations3
Published2014
Admission routes1
Has abstractyes

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