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Record W4401365338 · doi:10.1080/15230430.2024.2375176

An analysis of McMurdo Dry Valleys’ lotic habitats within Antarctica’s protected area network and addressing gaps in biodiversity protection

2024· article· en· W4401365338 on OpenAlexaff
Anna Wright, Cassandra M. Brooks, M. N. Gooseff, Adrian Howkins, Stephen M. Chignell

Bibliographic record

VenueArctic Antarctic and Alpine Research · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicPolar Research and Ecology
Canadian institutionsUniversity of British Columbia
FundersNational Science Foundation
KeywordsBiodiversityRiver ecosystemEcosystemHabitatAquatic ecosystemEnvironmental scienceEcologyEnvironmental resource managementGeographyBiology

Abstract

fetched live from OpenAlex

The McMurdo Dry Valleys (MDV), Antarctica’s largest ice-free region, hosts unique terrestrial ecosystems, with biodiversity concentrated in the aquatic environments and surrounding soils. Despite being a scientific hub, the creation of the MDV Antarctic Specially Managed Area (ASMA) made significant steps toward protecting the environment from degradation from human usage. However, with sustained human presence within the MDV, increasing human activity across Antarctica, and aquatic ecosystems subject to environmental change, the effectiveness of current protections for biodiversity conservation requires evaluation. This study employs spatial analysis of MDV protected areas, streams, lakes, research camps, and tourist sites to assess the robustness of current protections, identify underprotected areas, and outline steps for future protection. Within the MDV ASMA, five smaller Antarctic Specially Protected Areas (ASPAs) exist. Only two ASPAs contain streams, and only one with a full hydrologic catchment. With roughly 6% of the lotic habitat area protected by ASPAs, the MDV fall short of global goals for freshwater protection. Past successful management of the MDV shows the effectiveness of collaboration and early action, and amongst calls for ASPA network expansion and restructuring, the MDV has the opportunity to be at the forefront again and increase the protection of Antarctic aquatic ecosystems.

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)0.003
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 score0.143
Threshold uncertainty score0.972

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.060
GPT teacher head0.326
Teacher spread0.266 · 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.

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

Citations4
Published2024
Admission routes1
Has abstractyes

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