Using Multiple Sources of Knowledge to Investigate Northern Environmental Change: Regional Ecological Impacts of a Storm Surge in the Outer Mackenzie Delta, N.W.T.
Bibliographic record
Abstract
Field data, remote sensing, and Inuvialuit knowledge were synthesized to document regional ecological change in the outer Mackenzie Delta and to explore the timing, causes, and implications of this phenomenon. In September 1999, a large magnitude storm surge inundated low-lying areas of the outer Mackenzie Delta. The storm was among the most intense on record and resulted in the highest water levels ever measured at the delta front. Synthesis of scientific and Inuvialuit knowledge indicates that flooding during the 1999 storm surge increased soil salinity and caused widespread vegetation death. Vegetation cover was significantly reduced in areas affected by the surge and was inversely related to soil salinity. Change detection analysis, using remotely sensed imagery bracketing the 1999 storm event, indicates severe impacts on at least 13 200 ha of terrestrial vegetation in the outer delta. Inuvialuit knowledge identifying the 1999 surge as anomalous is corroborated by geochemical profiles of permafrost and by a recently published paleo-environmental study, which indicates that storm surge impacts of this magnitude have not previously occurred during the last millennium. Almost a decade after the 1999 storm surge event, ecological recovery has been minimal. This broad-scale vegetation change is likely to have significant implications for wildlife and must be considered in regional ecosystem planning and in the assessment and monitoring of the cumulative impacts of development. Our investigations show that Inuvialuit were aware of the 1999 storm surge and the environmental impacts several years before the scientific and regulatory communities recognized their significance. This study highlights the need for multidisciplinary and locally informed approaches to identifying and understanding Arctic environmental change.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".