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Record W2984614166 · doi:10.1139/cjb-2019-0076

Sphagnum outcompetes feathermosses in their photosynthetic adaptation to postharvest black spruce forests

2019· article· en· W2984614166 on OpenAlexaffvenue
Xinbiao Zhu, Victoria Nimmo, Jianghua Wu, Raymond Thomas

Bibliographic record

VenueBotany · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsNatural Resources CanadaMemorial University of NewfoundlandCanadian Forest Service
Fundersnot available
KeywordsSphagnumBiologyUnderstoryBlack spruceBotanyMossPhotosynthesisPeatEcologyTaigaCanopy

Abstract

fetched live from OpenAlex

Mosses dominate the understory of black spruce forest, and changes in moss community composition and functional traits may influence many important ecosystem processes, particularly paludification due to accumulation of peat (mainly Sphagnum). To understand performance and fitness of ground-cover mosses in early forest succession following clearcutting, we investigated photosynthetic traits in Sphagnum and three feathermoss species (i.e., Hylocomium, Ptilium, and Pleurozium) coexisting in mature stands and decade-old black spruce harvest blocks. The results showed that all of these mosses have a significantly higher light saturation point at the harvested plots than the forested plots. Feathermosses at the harvested plots all underwent a reduction in quantum efficiency, chlorophyll b content, and chlorophylls:carotenoids ratio related to photoinhibition, particularly Pleurozium, which experienced a significant decrease in maximum net photosynthesis. In contrast, Sphagnum showed a significant increase in maximum gross photosynthesis, dark respiration, and the ratio of chlorophyll a:b at the harvested plots compared with the forested plots. The distinctive responses of moss photosynthetic traits indicate the potential proliferation of Sphagnum and decrease of feathermosses, and thus consequent peat accumulation. Our results emphasize the importance of the photosynthetic traits of moss as indicators of postharvest conditions for enhancing understory vegetation management to maintain and improve productivity of black spruce.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
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)0.0020.003

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 head0.219
Teacher spread0.209 · 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; both teacher heads agree on what is shown here.

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

Citations10
Published2019
Admission routes2
Has abstractyes

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