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Record W4251048193 · doi:10.32920/ryerson.14643888

Recreational Trail Impacts and their Spatial Influence on Species Diversity and Composition

2021· preprint· en· W4251048193 on OpenAlexaffabout
Nicholas Alexander Pankiw

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicBotany and Plant Ecology Studies
Canadian institutionsToronto Metropolitan UniversityYork University
Fundersnot available
KeywordsRecreationSpecies richnessTransectGeographyDeciduousDisturbance (geology)Vegetation (pathology)EcologyTemperate rainforestTemperate climateEcosystemBiology

Abstract

fetched live from OpenAlex

This thesis quantifies the differences observed in floral communities exposed to varying degrees of long-term recreational trail use. The study was undertaken in a temperate deciduous forest located in Uxbridge, ON, Canada, which permits hiking, mountain biking and equestrian trail users. Vegetation exposed to trail impacts was sampled using transects which extended from the trail edge to 25m into the forest interior. The results demonstrated that trail-influenced environments experienced significant shifts in composition and reductions in species richness at distances beyond the influence of an edge effect. It was also established that types of recreational trail use do not disproportionately cause greater disturbance or result in greater exotic and invasive species coverage. Multiple regression analysis revealed that when choosing new trail routes, managers can mitigate changes to species composition by selecting areas with steep side-slopes and by avoiding areas with a south facing aspect.

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)0.001
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 score0.023
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.034
GPT teacher head0.200
Teacher spread0.166 · 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

Citations0
Published2021
Admission routes2
Has abstractyes

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