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Record W2981659845 · doi:10.4095/305908

From single-species to biodiversity conservation? Habitat mapping and biodiversity analysis of the Eastport Marine Protected Area, Canada

2017· report· en· W2981659845 on OpenAlexaboutno aff
Emilie Novaczek, Beatrice Proudfoot, Victoria Howse, Christina Pretty, Rodolphe Devillers, EN Edinger, Alison Copeland

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal plant biology
Canadian institutionsnot available
Fundersnot available
KeywordsBiodiversityMarine biodiversityGeographyHabitatMarine protected areaBiodiversity conservationGlobal biodiversityEcologyEnvironmental resource managementEnvironmental scienceBiology

Abstract

fetched live from OpenAlex

As a signatory to the Convention on Biological Diversity, Canada has committed to protect at least 10% of its coastal and marine waters by 2020 through ecologically representative and well-connected systems of protected areas. As more nations implement additional marine conservation measures to meet international targets, understanding how existing protected areas contribute to broader conservation goals is important. Our study describes the benthic habitat mapping of a small Canadian MPA and reports on its contribution to conservation of regional benthic marine biodiversity. We also suggest methods for incorporating benthic habitat connectivity analysis into adaptive management processes. The Eastport MPA (Newfoundland, Canada) is a 2.1 square kilometre no-take reserve designated in 2005, based on a voluntary fishery closure implemented in 1997. The primary goal of the Eastport MPA is to protect and sustain the American lobster (Homarus americanus) population, which supports an important local fishery. The MPA's stated management goals also include protection of benthic biodiversity and protection of rare and endangered species. Benthic habitats within and adjacent to the MPA were characterized and mapped using multibeam echosounder data and seafloor videos. Three statistically distinct benthic habitats were identified within the boundaries of the MPA: 'shallow rocky', 'sand and cobble', and 'sand'. The distribution of species was primarily driven by depth and substrate type. The shallow rocky habitat (48% of the study area) contains complex bedrock and boulder features with high macroalgal cover, which are associated with juvenile and adult American lobster habitat. However, a previous study covering a broader area identified 10 distinct habitats in Newman Sound, the area surrounding the MPA. Species composition was also significantly different inside and outside the MPA, with much lower species richness within the protected boundaries. These results indicate that this small MPA contributes little to the conservation of the regional marine biodiversity, vulnerable habitats, or species at risk. The high resolution marine habitat maps produced provide the opportunity to apply landscape ecology concepts, such as habitat connectivity metrics, to support marine conservation and adaptive management initiatives. In Eastport, benthic habitat connectivity is currently being assessed to identify areas that could be selected for a possible MPA expansion. Preliminary results derived from applying Patch Cohesion and Connectance Indices suggest that while habitats within the MPA are highly contiguous, connectivity between corresponding habitat patches is low. Further analysis of benthic habitats outside the MPA may help to identify possible solutions that maintain continuity and enhance connectivity with new or expanded protected areas. The results of this study will support adaptive management, something rarely done for Canadian MPAs, and will contribute to the development of methods for the identification of effective and well-connected MPA networks.

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)0.000
metaresearch head score (Gemma)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.140

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.006
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.049
GPT teacher head0.192
Teacher spread0.143 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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