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Record W2527945865 · doi:10.1002/aqc.2709

Wetlands: conservation's poor cousins

2016· article· en· W2527945865 on OpenAlexaff
Richard T. Kingsford, Alberto Basset, Leland J. Jackson

Bibliographic record

VenueAquatic Conservation Marine and Freshwater Ecosystems · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicCoastal wetland ecosystem dynamics
Canadian institutionsUniversity of Calgary
FundersAustralian Research CouncilHorizon 2020 Framework ProgrammeLifeWatch – Niclas Öberg Foundation
KeywordsWetlandOverexploitationHabitat destructionEcosystem servicesBiodiversityEnvironmental scienceEcosystemEcologyGeographyBiology

Abstract

fetched live from OpenAlex

Abstract About 5–10% of the world's land surface is currently wetland but possibly >70% is already destroyed or impaired. Conservation of these unique ecosystems lags progress in other realms, reflected in high rates of biodiversity loss. Wetlands provide a range of critically important ecosystem services including fresh water, nutrient cycling, food and fibre production, carbon fixation and storage, flood mitigation and water storage; water treatment and purification and habitats for biodiversity. There is increasing recognition that these services provide real economic values. Wetlands are affected by numerous threats including habitat loss and degradation, climate change, pollution, invasive species, overharvesting and disease. The most serious impact is from habitat loss and degradation caused by upstream water resource developments and conversion to agriculture, industry and transport, and urban development. The status of the distribution and extent of the world's wetlands remains poorly known, varying among countries. Wetland loss has varied internationally, with generally higher impacts in the Northern Hemisphere, with its long history of conversion to urban centres, ports and agriculture and yet there are increasing losses occurring in developing continents in the south. Wetland conservation needs to focus primarily on identification of priority areas for biodiversity conservation and legal protection, including Ramsar‐listing. Identification of wetland biodiversity hotspots for conservation should be an imperative, with associated Ramsar‐listing. There also needs to be effective protection of flow regimes. Mitigation of other deleterious processes, pollution, overharvesting, invasive species and disease, also remains particularly important. Conservation of wetlands remains especially challenging, given the importance of fresh water for human communities, industry and agriculture. Without effective conservation actions, mitigation of threats, rigorous risk assessment and acknowledgement of the value of wetland ecosystem services, wetland conservation will continue to lag behind conservation in other realms in protecting the Earth's biodiversity. Copyright © 2016 John Wiley & Sons, Ltd.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.028
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0060.006
Scholarly communication0.0040.005
Open science0.0010.006
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0280.002

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 head0.009
GPT teacher head0.193
Teacher spread0.184 · 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 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".

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Citations357
Published2016
Admission routes1
Has abstractyes

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