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Record W7025220074

Vegetation and carbon dynamics of high-latitude peatlands in a changing climate : From early Holocene to recent past

2022· other· en· W7025220074 on OpenAlexaboutno aff

Bibliographic record

VenueTyöväentutkimus Vuosikirja · 2022
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsPeatVegetation (pathology)Climate changeHoloceneCarbon cycleGlobal warmingCarbon fibersGlobal change
DOInot available

Abstract

fetched live from OpenAlex

The high-latitudes are warming at more than twice the rate of the global average. Warming and the consequent changes in hydrology affect peatland functioning, especially through changes in vegetation and carbon dynamics. The majority of the world’s peatlands are found in the Northern Hemisphere, forming a globally significant carbon storage and they are in constant interaction with the atmosphere through carbon uptake and release. The global importance of peatlands is widely recognised; however, the role played by high-latitude peatlands in changing climates is still unclear. It is not thoroughly understood how warmer future climates and hydrological changes will affect peatland vegetation and carbon processes. These uncertainties result from the complexity of peatlands and from the manifold future trajectories that are affected by different forcing factors from climate to local conditions. In this dissertation, I aim to increase our knowledge of high-latitude peatland vegetation and carbon dynamics under changing climatic conditions. My approach is palaeoecological, because I use peat records as an archive to reconstruct the response of high-latitude peatlands to known changes in climate. Peatlands function as important archives, since under anoxic and acidic conditions, peat-forming plant remains are well preserved. By identifying these plant remains, we can reconstruct past vegetation compositions. The various peat-forming plants have their own ecological niche, since they prefer and require specific hydrological or nutritional conditions and thus are good indicators for past hydrological changes and conditions. For this dissertation, I collected, in total, 47 peat records from eastern Canada, northern Sweden and Finland, the Kola Peninsula and the northeast of European Russia. I investigated how peatland habitats, carbon accumulation and cycling of our study sites have changed in response to changes in climate. For this, I used plant macrofossils, peat geochemical measurements and dating methods. In addition, I statistically inspected the change in vegetation compositions over time and used a model of carbon accumulation that considered peat decay aspects to determine whether carbon accumulation has been higher or lower than what we would otherwise predict, based on carbon accumulation models. My results show that during recent centuries, the vegetation compositions of the microhabitats examined have mostly changed from typical wet sedge fen vegetation to Sphagnum moss-dominated intermediate surfaces and dry moss- and dwarf shrub-dominated surfaces. During recent decades, these vegetation compositions have remained rather stable, with no major changes in vegetation. However, the spatiotemporal variation within and between the study sites was prominent, and thus to detect any large-scale signals from the data it was essential to use multiple samples and sampling points. Based on my data, it was plausible to consider that if high-latitude peatland vegetation changes from sedge fen vegetation to more hummocky vegetation types, high-latitude peatland carbon accumulation and sink capacity may remain significant or even increase. To better predict the role of peatlands under changing climates, it is crucial that peatland vegetation responses, carbon dynamics and their linkages with climate are more thoroughly understood. My data also support the prevailing understanding that peatlands are important carbon sinks and storages and thus preserving ecosystems that form a nature-based solution to the problem of mitigating the effects of climate warming is highly important.

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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.008
GPT teacher head0.228
Teacher spread0.220 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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