Monitoring for Resilience within the Coastal Wetland Fish Assemblages of Fathom Five National Marine Park, Lake Huron, Canada
Bibliographic record
Abstract
A resilient coastal wetland is naturally dynamic and responds to disturbances by maintaining the regimes defining structures and functions. Methods to monitor resilience have been difficult to develop, yet are essential to either prevent or actively navigate a regime shift. As others have reported, ecosystem behavior becomes more variable when resilience decreases and feedbacks begin to weaken. To advance the practice of conservation within protected areas, a resilience-based approach to monitoring was explored within Fathom Five National Marine Park, Canada. By means of a multivariate distance-based control chart, the variability of fish assemblages in eight coastal wetlands over an eight-year period (2005–2012) was monitored. The control chart identified occasions when variance in three of the park's wetlands deviated more than expected (i.e., acted “out of control”). To explain the exceedances. an ordination of fish assemblages was completed using principal components analysis (PCA) and redundancy analysis (RDA). Colonization by the invasive round goby (Neogobius melanostomus) and the prolonged period of low lake levels and stranding were discussed as possible explanations for the exceedances. In conclusion, the control chart and ordination methods provided valuable insight and understanding of wetland dynamics and were recommended as part of a long-term resilience-based approach to monitoring.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".