MétaCan
Menu
Back to cohort

Using Biogeography to Help Set Priorities in Marine Conservation

2004· article· en· W2073208520 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueConservation Biology · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicCoral and Marine Ecosystems Studies
Canadian institutionsUniversity of British Columbia
FundersWWF International
KeywordsBiogeographyScope (computer science)Context (archaeology)Environmental resource managementGeographyMarine conservationMarine protected areaStakeholderEcologyHabitatComputer scienceBiologyEnvironmental sciencePolitical science

Abstract

fetched live from OpenAlex

Abstract: Biogeographic information has great potential to enhance systematic conservation planning, although it has yet to be routinely incorporated in marine situations. Fundamental differences between marine and terrestrial environments (physical, biological, and sociopolitical) mean that biogeographic data are harder to obtain for marine systems, biogeographic boundaries more difficult to define, and the outcomes of similar conservation approaches may differ. Despite these challenges, an understanding of spatial context, connections, and scales of processes is needed to set conservation priorities that ensure the representation and continued persistence of species and habitats within functioning ecosystems. As we discovered in our review, scientific knowledge of marine systems is increasing rapidly thanks to recent advances in genetics, remote sensing, and geographical information systems. Such knowledge and tools have important implications for marine planning. We also reviewed the degree to which biogeography is incorporated into current marine conservation projects at spatial scales ranging from global to local. Overall, initiatives are becoming more regional in scope and incorporating biogeographic data in an increasingly rigorous manner. However, initiatives that use few or no data are also on the rise and need to be treated with due caution. We recommend undertaking global and regional reviews within biogeographic frameworks; combining analytical approaches to determine biogeographic classifications and to define a range of potential conservation areas with stakeholder involvement to set priorities; understanding contemporary processes that maintain species distributions; and acquiring knowledge of historical distributions to provide appropriate baselines for current conservation. The urgent need for marine conservation, however, means that planning should proceed with the best currently available biogeographic information even while biogeographic research continues.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.023
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.044
GPT teacher head0.275
Teacher spread0.230 · 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