Accumulated state assessment of the Yukon River watershed: Part II quantitative effects-based analysis integrating western science and traditional ecological knowledge
Bibliographic record
Abstract
This article is the second in a 2-part series assessing the accumulated state of the transboundary Yukon River (YR) basin in northern Canada and the United States. The determination of accumulated state based on available long-term (LT) discharge and water quality data is the first step in watershed cumulative effect assessment in the absence of sufficient biological monitoring data. Long-term trends in water quantity and quality were determined and a benchmark against which to measure change was defined for 5 major reaches along the YR for nitrate, total and dissolved organic carbon (TOC and DOC, respectively), total phosphate (TP), orthophosphate, pH, and specific conductivity. Deviations from the reference condition were identified as "hot moments" in time, nested within a reach. Significant increasing LT trends in discharge were found on the Canadian portion of the YR. There were significant LT decreases in nitrate, TOC, and TP at the Headwater reach, and significant increases in nitrate and specific conductivity at the Lower reach. Deviations from reference condition were found in all water quality variables but most notably during the ice-free period of the YR (May-Sept) and in the Lower reach. The greatest magnitudes of outliers were found during the spring freshet. This study also incorporated traditional ecological knowledge (TEK) into its assessment of accumulated state. In the summer of 2007 the YR Inter Tribal Watershed Council organized a team of people to paddle down the length of the YR as part of a "Healing Journey," where both Western Science and TEK paradigms were used. Water quality data were continuously collected and stories were shared between the team and communities along the YR. Healing Journey data were compared to the LT reference conditions and showed the summer of 2007 was abnormal compared to the LT water quality. This study showed the importance of establishing a reference condition by reach and season for key indicators of water health to measure change, and the importance of placing synoptic surveys into context of LT accumulated state assessments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 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 teacher head, 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".