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Record W7006167341

SMILE - sustainable mariculture in northern Irish lough ecosystems: assessment of carrying capacity for environmentally sustainable shellfish culture in Carlingford Lough, Strangford Lough, Belfast Lough, Larne Lough and Lough Foyle

2007· other· en· W7006167341 on OpenAlexfundno aff

Bibliographic record

VenueNERC Open Research Archive (Natural Environment Research Council) · 2007
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and Biological Electrophysiology Studies
Canadian institutionsnot available
FundersAgri-Food and Biosciences InstituteQueen's UniversityQueen's University Belfast
KeywordsMaricultureAquacultureAgricultureCarrying capacitySustainable developmentSustainabilityShellfishContext (archaeology)
DOInot available

Abstract

fetched live from OpenAlex

The assessment of environmentally sustainable carrying capacity for aquaculture in coastal areas poses a major challenge, given the range of issues that must be taken into account, the interactions between natural and social components, and the coupling between watershed and coastal zone. 
\n
\nIn 2001, The Department of Agriculture and Rural Development published the Shellfish Aquaculture Management Plan for Northern Ireland. The Minister for Agriculture and Rural Development stated at the presentation: “There has been a significant growth in shellfish aquaculture in Northern Ireland over the past few years. It is important that this growth is structured and that the shellfish aquaculture industry develops in a sustainable manner and with minimal environmental impact.” Following this publication, Queen’s University Belfast and the Department for Agriculture and Rural Development (DARD) produced a Phase I study of Carrying Capacity in 2003. 
\n
\nIn 2004, a consortium made up of the Institute of Marine Research – IMAR (Portugal), Plymouth Marine Laboratory – PML (U.K.) and CSIR (South Africa) was awarded a two-year contract for the Sustainable Mariculture in northern Irish Lough Ecosystems (SMILE) project, with a duration of two years, with the aim of “developing dynamic ecosystem level carrying capacity models for the five northern Irish sea loughs. 
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\nIn order to provide medium-term guidelines, this work needed to be placed in the context of a set of European legislative instruments in the area of water policy, which include older generation directives such as Habitats, and new and emerging ones such as the Water Framework Directive and the proposed Marine Strategy Directive. 
\nThe SMILE contract was conceived as an application of know-how collected in many R&D projects, but the excellent collaboration with the Agri-Food and Biosciences Institute (AFBI), Queen’s University of Belfast (QUB) and the Loughs Agency, together with the interest and feedback of the Environment and Heritage Service (EHS) and other agencies on the Oversight Committee, provided several avenues for research. In SMILE, carrying capacity assessment can be summed up as a clear practical application of integrated coastal zone management, using water quality criteria, cultivated shellfish production and sustainability of native wild species as environmental metrics. 
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\nThis book provides an overview of the approach taken in SMILE, and presents the key results for the five loughs. Data were drawn from many sources, and collected into databases that form the backbone of the modelling work. Our thanks go to all who provided data and information, and especially to the people on the ground, who watched this work develop and trusted us to get on with it. We are very grateful to Anne Dorbie for her support for this work, and her faith in the team, and to Jason Holt (POL) for Irish Sea boundary conditions. We additionally wish to thank all the producers and growers who helped with growth trials and provided the use of vessels, Tom Cowan, Greg Hood and Roy Griffin from Fisheries Division, Annika Mitchell from QUB and Nuala McQuaid from CMAR. We hope managers and shellfish farmers alike in Northern Ireland will find this and the other SMILE products both useful and profitable. Europe cannot hope to compete on quantity with the emerging shellfish export markets, the added value which is required to provide growth in jobs and profits at home must come from superior product quality, branding and environmental sustainability.

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)0.012
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.340
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0030.004
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.076
GPT teacher head0.315
Teacher spread0.240 · 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".

Quick stats

Citations2
Published2007
Admission routes1
Has abstractyes

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