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Record W3092087253 · doi:10.19189/001c.128517

Peatlands of the Peruvian Puna Ecoregion: Types, Characteristics and Disturbance

2014· article· en· W3092087253 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

VenueMires and Peat · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsUniversité du Québec à MontréalCenter for Northern StudiesUniversité Laval
FundersInter-American Institute for Global Change Research
KeywordsEcoregionPeatDisturbance (geology)Environmental scienceEricaceaeEcologyPhysical geographyGeographyHydrology (agriculture)ForestryGeologyGeomorphologyBiologyGeotechnical engineering

Abstract

fetched live from OpenAlex

Peatlands represent one of the most important water resources in the Puna grassland ecoregion, but this fact is not yet widely recognised. Puna peatlands also provide key environmental services such as increasing the regional biodiversity of the Andean Altiplano plateau and contributing to the wellbeing of high-altitude human populations by providing grazing land and cooking fuel. We conducted a study in the Peruvian Puna ecoregion to describe the current condition of peatlands in terms of their vegetation, physical and chemical characteristics and disturbance status. Our results suggest that peat thickness, organic matter and degree of humification are good indicators for identifying peatlands in the Puna ecoregion. In general, the peatland sites that we sampled were dominated by mixtures of cushion and acaulescent rosette forming plants such as Distichia muscoides Nees & Meyen and Plantago tubulosa Decne. These Distichia and Plantago peatland sites were characterised by a mean surface water pH of 6.3, corrected electrical conductivity (K corr.) in the range 300–1814 μS cm-1 and presented the following mean exchangeable cation values: Ca2+ 48 mg L-1, Mg2+ 9.6 mg L-1, Na+ 8.2 mg L-1 and K+ 2.1 mg L-1. The most common causes of disturbance we encountered were grazing, peat extraction and roads. Disturbance was most severe in mining sites, where peatlands are especially vulnerable because they are not under legal protection.

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 score0.109
Threshold uncertainty score0.178

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 head0.005
GPT teacher head0.183
Teacher spread0.178 · 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