ASSESSMENT OF ARCTIC GRAYLING RE-INTRODUCTION POTENTIAL IN THE BIG MANISTEE RIVER, MICHIGAN.
Bibliographic record
Abstract
Arctic Grayling Thymallus arcticus were once the dominant fluvial salmonid species in Michigan’s Lower Peninsula. By the late 19th century most populations in the State had experienced drastic declines and by 1936 the species was declared extinct in Michigan. Beginning in 2011 the Little River Band of Ottawa Indians and Michigan Technological University partnered on research to determine the feasibility of re-establishing the species in the Big Manistee River watershed which was home to one of the last Arctic Grayling populations in the Lower Peninsula. The objectives of this research were to: A) assess abiotic habitat suitability for Arctic Grayling, B) identify potential biotic interactions that could impact Arctic Grayling re-introduction success, C) assess food availability and bioenergetic capacity of eight Big Manistee River tributaries, and D) model population viability and extinction sensitivities of a potential re-introduced Arctic Grayling population. Results from this study indicate that suitable biotic conditions for Arctic Grayling are available in all of the eight tributaries included in this study. Brook and Brown Trout currently occupy all of the potential re-introduction tributaries and densities of Brown Trout > 0.10/m2 should be considered a potentially limiting factor in determining overall site suitability (Chapter 2). A bioenergetic assessment indicates that 59% of the study reaches exhibit positive Net Energy Intake (NEI) for drift-feeding salmonids indicating that they are likely suitable re-introduction areas. No statistically significant relationship was found between invertebrate densities or NEI and the densities of salmonid species currently occupying these habitats indicating that food availability is not a limiting factor for salmonids in the Big Manistee River system (Chapter 3). Population viability analysis indicates that it is possible to establish a viable Arctic Grayling population in the middle portion of the Big Manistee River watershed studied. Sensitivity analyses suggest that Arctic Grayling populations in the southern portion of their range (i.e. Michigan and Montana) are most sensitive to factors influencing reproductive output while northern populations (Canada and Alaska) are most sensitive to factors affecting adult survival (Chapter 4) Overall, the combined findings from this research suggest that conditions are favorable for Arctic Grayling re-established in the Big Manistee River watershed.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".