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Record W1561151435

Environmental changes in the lower Peel River watershed, Northwest Territories, Canada: Scientific and Gwich'in perpectives

2013· dissertation· en· W1561151435 on OpenAlexaboutno aff
Harneet K. Gill

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsWatershedGeographyHydrology (agriculture)Environmental scienceWater resource managementArchaeologyEnvironmental protectionGeology
DOInot available

Abstract

fetched live from OpenAlex

The circumpolar Arctic is experiencing dramatic environmental changes that are already impacting tundra ecosystems and northern communities that are intimately linked to the land. Increasing permafrost degradation, shrub encroachment, larger and more frequent fires, and increasing human development have significant effects on biotic and abiotic conditions in the lower Peel River watershed, NT. To understand and respond to rapid environmental changes, diverse knowledge perspectives are needed, so my M.Sc. research uses scientific and social scientific approaches to investigate environmental change in the lower Peel River watershed. I investigated the impacts of the Dempster highway on plants, soils and permafrost in the Peel Plateau by conducting field surveys at sites dominated either by tall alder (Alnus crispa) shrubs or by dwarf shrubs, at 30 m and 500 m from the highway. At each site I measured vegetation composition, alder growth, soil nutrients, litter and organic layer thickness, active layer thickness, and snow depth. We found that alder growth and recruitment were enhanced adjacent to the Dempster Highway, and dramatic alterations to plant community composition, soil properties and ground temperatures were observed where alder shrubs had formed closed canopies. Tall shrub sites adjacent to the road exhibited lower abundance of understory vegetation including mosses, greater litter and organic soil thickness, higher nutrient availability, and deeper snowpack. Biotic and abiotic changes associated with road effects feedback with alder canopy development, and have important implications for permafrost conditions adjacent to the roadbed, and potentially on road bed performance. This research contributes to our understanding of environmental changes caused by the highway and their consequences for infrastructure stability and pan-Arctic changes in vegetation cover. In a separate but complementary effort, I worked with Teetl’it Gwich’in land users and youth from Fort McPherson, NT to map observations of environmental conditions and changes. In the pilot year of a community-based environmental monitoring program, we employed participatory multimedia mapping with Teetl’it Gwich’in land users and youth from Fort McPherson, NT. I accompanied Gwich’in monitors on trips on the land to document environmental conditions and changes. Observations made by land users were documented using photos, videos and audio taken by youth, and land users provided detailed information about each observation in follow-up interviews. I compiled observations (photo/video, GPS location, and interview audio and transcript) into a web-based map where the public will be able to see changes on the land in the images and words of Gwich’in land users. The online map will provide a medium for local residents to communicate their knowledge and concerns about the environment, and will be useful for land management and planning, environmental monitoring, and adaptation.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.031
Threshold uncertainty score0.223

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.006
Science and technology studies0.0030.002
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.005
GPT teacher head0.185
Teacher spread0.179 · 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

Citations1
Published2013
Admission routes1
Has abstractno

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