Developing spatial management tools for offshore marine protected areas
Bibliographic record
Abstract
Canada's Exclusive Economic Zone in the Northeast Pacific encompasses a rich variety of offshore benthic habitats, from continental shelf, slope and abyssal sediments, to sponge reefs, seamounts, gas hydrates and hydrothermal vents. Knowledge of these remote areas is uneven, derived from mostly uncoordinated surveys and sampling expeditions by surface vessels, exploration with remotely operated vehicles (ROV), and streaming data from a cabled scientific observatory operated by Ocean Networks Canada (ONC). The area currently includes two Marine Protected Areas (MPAs), managed by Canada's Department of Fisheries and Oceans (DFO), at Bowie Seamount and the Endeavour Hydrothermal Vents. The great depth (2200–2400 metres) and 250 km offshore distance of the Endeavour MPA, together with the habitat heterogeneity that is typical of volcanic ridges, present challenges to effective monitoring and management. The installation of cabled observatory infrastructure within the Endeavour MPA in 2009 provided an opportunity for remote monitoring of environmental variability. In 2014, ONC partnered with DFO to develop spatial management tools for the Endeavour MPA. Combining observatory sensor data with observations made during maintenance and research expeditions can provide insight into natural variability and human disturbance, and assist in the management and preservation of the MPA. Such an approach can also provide a knowledge base for understanding stressors and support the implementation of risk-based management. The partnership between DFO and ONC was expanded in 2016 to include other offshore areas within the now established Pacific Offshore Area of Interest. Geodatabases were developed using ESRI Geographical Information System (GIS) software for the Endeavour MPA, and three other offshore locations served by ONC's cabled observatory network: the Middle Valley hydrothermal fields, the Cascadia Basin abyssal plain, and the Nootka Fault Zone. All geodatabases integrate available data from ONC's Oceans 2.0 data management system, DFO and third party cruise data, and relevant publications. Data include bathymetry, links to annotated ROV dive videos, underwater vehicle tracks, sampling activity records, and observations of biological and geographical features. The GIS also links observations to the time-correlated ROV dive videos using ONC's SeaTube video viewing tool, allowing for further more detailed analysis. Spatial statistics tools are applied to ROV tracks and sample sites to produce heat maps highlighting well-studied (and heavily-used) areas and those with little knowledge base. The end result is a geospatial database and toolkit that can integrate many data types, and support integrated management of remote and dynamic seafloor habitats.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".