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Record W4404708547 · doi:10.14321/aehm.027.02.06

Preface

2024· article· en· W4404708547 on OpenAlexaffabout
Charles K. Minns

Bibliographic record

VenueAquatic Ecosystem Health & Management · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicWater Resources and Governance
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEnvironmental science

Abstract

fetched live from OpenAlex

Here in this journal, Munawar and Hartig (2020) presented a brief history of the evolution of the “Ecosystem Approach” (EA) in the Great Lakes basin stemming from the historic Canada-U.S. Great Lakes Water Quality Agreement signed in 1972, a listing of the efforts to propagate the EA in other large aquatic systems around the world, and an invitation to participate in an EA conference.Munawar and Hartig (ibid) reminded us of the history of EA in the Great Lakes Basin where from 1972 onwards our collective thinking shifted from water quality management toward ecosystem management. Key architects of that shift were people like Jack Vallentyne (“Johnny Biosphere”) and Al Beeton (Beeton and Vallentyne, 1988) who articulated a broad definition of the “Ecosystem Approach”:“‘Ecosystem Approach’ means an integrated set of policies and managerial practices that relate people to ‘ecosystems’ of which they are part-rather than to external resources or environments with which they interact.” With key characteristics: synthesis; a holistic perspective; and ecological, anticipatory, and ethical actions in respect of natural ecosystems.Brenda Lee, Henry Regier and Dave Rapport (Lee et al., 1982) documented the rapid evolution and diversification of particular approaches across the Great Lakes. The Ecosystem Approach first flourished in the many Areas of Concern (AOCs) singled out across the Great Lakes where many stressor levels were high, with further expansion via lake-wide and coastal management planning more recently. People like Richard Vollenweider and Mohiuddin Munawar helped develop the initial eutrophication metrics needed to measure progress and helped stimulate the development of benchmarks and metrics across the diverse spectrum of stressors. Guided by those people and ideas, I know personally that we strived very hard to realize the full potential of the Ecosystem Approach in the Bay of Quinte AOC (Minns et al., 2023) inspired by EA advocates like Jack Christie (Minns, 1999), and by scientists like Murray G. Johnson and Glen Murray who argued in the 1970s for the creation of a long-term ecosystem study in the Bay of Quinte to chart restoration while building understanding of the many complexities. While the Bay of Quinte AOC is now close to being delisted as beneficial use metrics improve, the science program is largely dormant and the local authorities maintain institutional and regulatory efforts to improve local land, wetland, and water management practices.In August 2022, that Ecosystem Approach conference convened at the University of Windson campus, close to the Canada-U.S. border, in honour of the 50th anniversary of the launching of EA efforts in the Great Lakes region of North America. Diversity is a significant feature of many aspects of this conference: the diversity of ecosystems, aquatic and beyond, considered; the diversity of stressors impacting ecosystems; the diversity of the organizations sponsoring the conference, the diversity of origins and backgrounds of the participants; the diversity of Ecosystem-based Approaches (EbAs) being pursued across the worlds ecosystems; the dimensions of EbAs being considered; and the diversity of the recommendations made to fuel future efforts to make all necessary progress around the world.Many organizations sponsored the conference: The Aquatic Health and Ecosystem Management Society (AEHMS), University of Windsor, The Nature Conservancy, Fisheries and Oceans Canada, American Fisheries Society-International Fisheries Section, The Joyce Foundation, the Great Lakes Fishery Commission, the International Joint Commission, U.S. Geological Survey, University of Michigan-School of Environment and Sustainability, International Association for Great Lakes Research, Canadian Consulate General, and the City of Windsor's Ojibway Nature Centre.The conference was ably steered by the following people: John Hartig and Mohiuddin Munawar (Executive Co-chairs); Catherine Febria and Bradley Cardinale (Conference Co-chairs); and Mathew Child, Marc Gaden, Scott Sowa, and Ralph Tingsley (Members) with strong support from Jennifer Lorimer and Nia Khuong for the conference Secretariat. An editorial committee consisting of C.K. Minns, J. Hartig, C. Febria, S. Ludsin and M. Munawar provided advice in the development of the special issue. Foreword by Dr. Henry Regier is gratefully acknowledged. Thanks to Susan Blunt for conducting technical editing of the manuscripts.The two- and one-half day hybrid conference took place August 22–24, 2022, with about 100 participants. The first day was open-access and a series of oral presentations and some virtual posters revealed the diversity of topics and issues to be tackled in the seven synthesis workshops: History and Origin of EbAs; Science-policy; Education, Outreach, and Knowledge Transfer; Blue Economy; Human Dimensions; Indigenous Management Systems; and Technological Advances/Uncertainty. The first day was capped by a keynote presentation from Professor Hugh Possingham (Univ. Queensland, Australia). On day two the synthesis working groups began their work with mixtures of surveys, presentations, and discussions. On the morning of day three the groups reviewed and compiled their synthesis overviews and shared their results in a final plenary session after lunch. After the conference, the working groups continued their work preparing the seven papers presented in this special issue. Finally, a group drawn from the working groups prepared a synthesis paper tackling the challenge of integrating all that occurred, and the consensus achieved at the conference.Together the papers in this special issue make it clear there is no single model for ecosystem-based approaches, success has been patchy to date but for EbAs to succeed they must share many features: broad community engagement, clear achievable objectives, sustained economic, institutional, and scientific commitments, and inevitably adaptation into the future. More commitment, attention and progress will be needed everywhere on Earth to restore and sustain the many ecosystems upon which all life on Earth depends. Hopefully the results of this conference shared here will assist in this challenge we all face.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.851
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.024
GPT teacher head0.326
Teacher spread0.302 · 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 teacher head, not a consensus.

Study designNot applicable
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".

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Citations0
Published2024
Admission routes2
Has abstractyes

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