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Record W2883415616 · doi:10.1002/ecy.2462

A peatland productivity and decomposition parameter database

2018· article· en· W2883415616 on OpenAlexaffabout
Kelly Ann Bona, A. B. Hilger, M. S. Burgess, Nicole Wozney, Cindy Shaw

Bibliographic record

VenueEcology · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsCanadian Forest Service
Fundersnot available
KeywordsShrubBiomass (ecology)PeatEnvironmental sciencePrimary productionEvergreenCarexVegetation (pathology)ProductivityBogLitterVegetation typeEcologyForestryEcosystemBiologyGeography

Abstract

fetched live from OpenAlex

Abstract A peatland productivity and decomposition parameter database was compiled to estimate parameters for the Canadian Model for Peatlands (Ca MP ); a module developed by the Canadian Forest Service to address the need for national‐scale greenhouse gas emission estimates from peatlands present in the forested area of Canada. Data were compiled for 186 peatland sites from 69 sources. The SITES table contains wetland classification, tree classification, province or state, country, latitude, longitude, and an indication of coordinate accuracy. The NPP ALL table contains annual net primary productivity ( NPP ; g·m −2 ·yr −1 ) data for cases where one estimate for NPP was reported for all aboveground vegetation. The NPP SHRUB , NPP MOSS , and NPP HERB SEDGE tables each contain a classification of species (if available) or vegetation layer and their NPP (g·m −2 ·yr −1 ). The BIOMASS TREE , BIOMASS SHRUB , BIOMASS HERB SEDGE , and BIOMASS MOSS tables each contain a classification of species (if available) or vegetation layer and their standing aboveground biomass (g/m 2 ). Shrubs in the NPP SHRUB and BIOMASS SHRUB tables were further classified into low or tall shrubs, and plants in the NPP HERB and BIOMASS HERB tables into herbs or sedges. The DECAY LITTER table contains decomposition parameters for different litter types and contains a classification of the type of decomposition study, study duration, information on experimental treatments, classification of above‐ or belowground plant parts, plant species, litter classification, root litter diameter, indication of hardwood or softwood, indication of evergreen or non‐evergreen, litter bag depth classification, classes for bag placement relative to the water table and relative to the peat surface, water table depth, decay rate ( k exponent), and mass loss values for years 1, 2, 3, 6, 7, 12, and 23 of a decomposition study. The REFERENCES table contains complete citation information and provides links to the source reference pdf file. This data set is vital to the national Canadian peatland modeling effort and should be useful to other peatland scientists and ecosystem modelers. © Her Majesty the Queen in Right of Canada, 2018. Information contained in this publication or product may be reproduced, in part or in whole, and by any means, for personal or public non‐commercial purposes, without charge or further permission, unless otherwise specified. You are asked to exercise due diligence in ensuring the accuracy of the materials reproduced; indicate the complete title of the materials reproduced, and the name of the author organization; and indicate that the reproduction is a copy of an official work that is published by Natural Resources Canada ( NRC an) and that the reproduction has not been produced in affiliation with, or with the endorsement of, NRC an. Commercial reproduction and distribution are prohibited except with written permission from NRC an. For more information, contact NRC an at copyright.droitdauteur@nrcan-rncan.gc.ca .

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.999

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)0.0020.000

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 head0.010
GPT teacher head0.253
Teacher spread0.242 · 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.

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

Citations22
Published2018
Admission routes2
Has abstractyes

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