Ecosystem monitoring in the Northwest Atlantic: Canada's Atlantic Zonal Monitoring Program (AZMP)
Bibliographic record
Abstract
No abstracts are to be cited without prior reference to the author.The Canadian Department of Fisheries and Oceans (DFO) has the mandate to provide the environmental datasets that are necessary to track and predict changes in ocean state and productivity, to respond to questions posed by end-users, to alert them to short and long-term environmental/ecosystem changes, and to provide adequate historical databases to address future issues. In that context, DFO designed and implemented an ecosystem observing program for the Northwest Atlantic in 1998 that builds upon existing monitoring activities in the region. The Atlantic Zonal Monitoring Program (AZMP) represents a minimum effort to detect and follow climate change and variability in the Northwest Atlantic while increasing Canada’s capacity to understand, describe, and forecast the state of the marine ecosystem and to quantify the changes in ocean physical, chemical and biological properties and the predator-prey relationships of marine resources. The AZMP derives its information on the state of the marine ecosystem from data collected at a network of sampling locations (fixed point stations, cross-shelf transects, groundfish surveys, satellite remote-sensing) sampled at a frequency of bi-weekly to annually. Information on the relative abundance and community structure of plankton is also collected on long survey lines from Iceland to Newfoundland and Newfoundland to the Gulf of Maine from commercial ship traffic instrumented with the Continuous Plankton Recorder (CPR). The AZMP sampling design provides basic information on variability in physical (temperature, salinity, ocean optics, sea-level), chemical (nutrients, oxygen) and biological (chlorophyll, plankton abundance and species) properties of the Canadian Atlantic continental shelf. Groundfish surveys and cross-shelf transects provide detailed regional geographic information but are limited to seasonal coverage at best. Critically placed fixed stations complement the geography-based sampling by providing more detailed information on temporal (seasonal) changes in ecosystem properties. Satellite remote-sensing of sea-surface phytoplankton biomass (chlorophyll) provides the large scale (zonal) perspective on important environmental and ecosystem variability. The CPR lines provide information on large scale (inter-regional) and long-term (yearly to decadal) variability in plankton abundance and community structure. Ongoing groundfish surveys provide distribution and abundance estimates for commercial and non-commercial finfish and invertebrates. Observations from the first three years of AZMP operation and historical data are providing a clear picture of the scales of natural ecosystem variability in the region and new evidence that links biological variability with changes in physical and chemical environmental properties. Links between indices of groundfish recruitment and environment/ecosystem variability are also being explored.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".