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Freshwater Protected Areas: Strategies for Conservation

2002· review· en· W2030777294 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueConservation Biology · 2002
Typereview
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsMcGill UniversityNature Conservancy of Canada
FundersMcGill University
KeywordsThreatened speciesWetlandHabitatDrainage basinGeographyEcologyEnvironmental scienceBiologyCartography

Abstract

fetched live from OpenAlex

Freshwater species and habitats are among the most threatened in the world. One way in which this growing conservation concern can be addressed is the creation of freshwater protected areas. Here, we present three strategies for freshwater protected-area design and management: whole-catchment management, natural-flow maintenance, and exclusion of non-native species. These strategies are based on the three primary threats to fresh waters: land-use disturbances, altered hydrologies, and introduction of non-native species. Each strategy draws from research in limnology and river and wetland ecology. Ideally, freshwater protected areas should be located in intact catchments, should have natural hydrological regimes, and should contain no non-native species. Because optimal conservation conditions are often difficult to attain, we also suggest alternative management strategies, including multiple-use modules, use of the river continuum concept, vegetated buffer strips, partial water discharges, and eradication of exotic species. Under some circumstances it may be possible to focus freshwater conservation efforts on two key zones: adjacent terrestrial areas and headwaters.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.218
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0020.001

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 head0.070
GPT teacher head0.299
Teacher spread0.229 · 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