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Record W2039061740 · doi:10.1080/03632415.2011.633464

Ocean Tracking Network Canada: A Network Approach to Addressing Critical Issues in Fisheries and Resource Management with Implications for Ocean Governance

2011· article· en· W2039061740 on OpenAlexafffundabout
Steven J. Cooke, Sara J. Iverson, Michael J. W. Stokesbury, Scott G. Hinch, Aaron T. Fisk, David VanderZwaag, Richard Apostle, Frederick G. Whoriskey

Bibliographic record

VenueFisheries · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsUniversity of WindsorUniversity of British ColumbiaDalhousie UniversityOcean Tracking NetworkAcadia UniversityCarleton University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFisheryMarine ecosystemMarine conservationResource (disambiguation)Environmental resource managementEcosystem-based managementOceanographyEcologyGeographyEcosystemEnvironmental scienceBiologyComputer science

Abstract

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Abstract The Ocean Tracking Network (OTN) Canada is an integrative seven-year research program initiated in 2010 with academic, government, and industry partners. The team makes use of novel biotelemetry (primarily acoustic telemetry curtains), biologging, and oceanographic technologies to better understand changing ocean dynamics and their impact on ocean ecosystems, animal movements, and ecology and the dynamics of marine animal populations, many of which are commercially important. The network is organized around three ocean arenas (i.e., the Atlantic, Arctic, and Pacific) where specific research projects will occur. However, all projects will contribute toward addressing a single unifying nationalscale question—what are the movements of continental shelf marine animals, how do these movements affect species interactions, and what are the consequences of environmental variability/change and human activities on these species’ distributions and abundance? Taxa that will be tracked include diadromous (e.g., salmon, eels, sturgeon) and marine (e.g., sharks, capelin, cod) fishes and a variety of marine mammals (e.g., grey seals, killer whales). Some of the common activities that occur in all arenas include measurements of oceanographic characteristics and variability at various spatial and temporal scales, movements of key species at several trophic levels, and use of key acoustic “bioprobes” (animals that carry tags that record locations visited, ocean conditions, and interactions with other tagged animals) and “roboprobes” (remotely controlled autonomous vehicles such as gliders that measure physical, biological, and chemical conditions) to complement measurements from fixed OTN acoustic telemetry curtains. Ultimately, scientific information generated will inform resource management, help formulate new socioeconomic policies, and provide some impetus to the reformulation of governance practices and legal standards. RESUMEN La Red de Monitoreo Oceánico (RMO) en Canada, es un programa integral de investigación que inició en 2010 con la participación del sector académico, industrial y de gobierno. El equipo hace uso de tecnología de punta en cuanto a bio-telemetría (cortinas primarias de telemetría acústica), bio-marcado y oceanografía con el fin de comprender la dinámica del océano y su impacto sobre los ecosistemas marinos, el movimiento de los organismos y su ecología así como también la dinámica de las poblaciones de animales marinos, muchos de ellos de importancia comercial. La red se encuentra organizada en torno a tres dominios oceánicos (i.e. Atlántico, Ártico y Pacífico) donde se desarrollarán proyectos específicos de investigación. No obstante, todos estos proyectos abordarán un problema común de escala nacional /Cuáles son los movimientos de los animales marinos en la plataforma continental?, ¿Como estos movimientos afectan las relaciones entre especies?, ¿Cuáles son las consecuencias de la variabilidad/cambio ambiental y las actividades humanas en la distribución y abundancia de dichas especies? Los taxa que serán monitoreados incluyen peces diádromos (e.g. salmon, anguilas, esturión) y marinos (e.g. tiburón, capelines, bacalao) y una variedad de mamíferos marinos (e.g. focas, orcas). Algunas de las actividades comunes a los tres dominios incluyen la medición de características oceanográficas y su variabilidad en distintas escalas de tiempo y espacio, el movimiento de especies clave de distintos niveles tróficos así como también el uso de “biosondas” (animales que portan marcas que registran las localidades visitadas, las condiciones oceánicas y la interacción con otros animales marcados) y “robosondas” (vehículos a control remoto que miden las condiciones físicas, biológicas y químicas del océano) con el objetivo de complementar la información proveniente de RMO fijas, como las cortinas acústicas telemétricas. En ultima instancia, los datos generados se utilizarán para informar a los manej adores, para asistir en la formulación de nuevas políticas socioeconómicas y a brindar ímpetu a la reformas de prácticas de gobernanza y estándares legales.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.027
metaresearch head score (Gemma)0.046
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.094
Threshold uncertainty score0.684

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.046
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0120.023
Science and technology studies0.0110.004
Scholarly communication0.0130.005
Open science0.0040.009
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0100.001

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.

Opus teacher head0.051
GPT teacher head0.239
Teacher spread0.188 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations102
Published2011
Admission routes3
Has abstractyes

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