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Record W2907851522 · doi:10.31251/pos.v2i1.55

Vegetation and plant material of the flat palsa peatlands

2018· article· ru· W2907851522 on OpenAlexaboutno aff
Natalia P. Kosykh, Н. П. Миронычева-токарева, Е. Н. Михайлова, Larisa G. Kolesnichenko

Bibliographic record

VenueПочвы и окружающая среда · 2018
Typearticle
Languageru
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsPermafrostPrimary productionPeatTaigaShrubEnvironmental scienceVegetation (pathology)SalicaceaeAgronomyBorealWoody plantEcosystemEcologyBiology

Abstract

fetched live from OpenAlex

The aim of the study was to reveal peculiarities and regularities in plant material stock and production as dependent on the plant cover composition, soil characteristics and microrelief of the flat palsa mires in the northern taiga zone in West Siberia. The hollow-lake complexes on permafrost peatlands were chosen as the study sites. The work was carried out in 2013-2017. Plant material structure with differentiation between living and dead belowground organs was investigated and net primary production evaluated. Net primary production was found to range 3.0-4.5 t/ha per year depending on plant species composition of the phytocenosis studied. The production averaged 4.0 t/ha per year with phytomass stock averaging 14.8 t/ha, whereas in dried lake sites the net primary production reached 8.5 t/ha per year with phytomass stock estimated as 18.0 t/ha. On flat palsa sites the ratio of the aboveground shrub production to their belowground production was 1:4, while in hollow sites the belowground organs of sedges and cotton grasses accounted for most of the production, with the ratio of the above- to the belowground production estimated as 1:6. Belowground production share in the total production was found to be maximal (70%) in mesotrophic hollows mainly due to the major sedges and cotton grasses. The total primary production was estimated as 4.1 t/ha per year on flat palsa sites, 3.0 t/ha per year in oligotrophic hollows and reached a maximum of 8.5 t/ha per year in dried lake sites. Thus the average plant material stocks, both above- and belowground, seemed to be rather constant from year to year, and their estimates agreed well with those reported for mires in Canada, Sweden and Finland. Phytomass stocks and production in flat palsa mires in the northern taiga of the West Siberia were shown to depend on soil mineral nutrition and water availability in the root-inhabited layer. Only in oligotrophic hollows mosses were found to dominate in production, while the latter on the palsa sites was dominated by lichens, displaying great species diversity, significantly exceeding that of other plants. The other factors being equal, in hollow sites phytomass stocks and yearly production increased with increased nutrient availability, being decreased on palsa sites due to the permafrost layer. Analysis of phytomass production in northern taiga mires allows concluding that soil characteristics play important role in phytomass production, which was found to be rather low overall. Phytomass stock and production on palsa sites are limited by shallow thawing depths, which effect is exacerbated by drying and warming of the upper soil layer in summer, altogether resulting in unfavourble environment for root growth and development.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.015
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.206
Teacher spread0.198 · 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 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

Citations3
Published2018
Admission routes1
Has abstractyes

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