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Record W4220957301 · doi:10.5194/egusphere-egu22-9369

Biogeochemical responses of plants, soils and microbes to permafrost degradation in a subarctic peatland

2022· preprint· en· W4220957301 on OpenAlexaff
Oriol Grau, Olga Margalef, Joosten Hans, Andreas Richter, Alberto Canarini, Ellen Dorrepaal, Frida Keuper, Sardans Jordi, Josep Peñuelas, Janssens Ivan

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsImpact
Fundersnot available
KeywordsPermafrostPeatSubarctic climateSoil waterNutrientEnvironmental chemistryPhosphorusBiogeochemical cycleEcosystemCyclingProductivityEnvironmental scienceMireOrganic matterNitrogenChemistryEcologySoil scienceBiologyForestry

Abstract

fetched live from OpenAlex

Permafrost peatlands are particularly sensitive to climate warming. The thawing of permafrost in these ecosystems accelerates the decomposition of old organic matter in deep soil layers and re-activates the cycling of carbon (C) and nutrients. Several studies showed that the thawing of permafrost in subarctic peatlands increases nitrogen (N) availability, ecosystem productivity as well as methane (CH4) and C dioxide (CO2) emissions. The mobilisation of other nutrients like phosphorus (P) or potassium (K) and the stoichiometric changes occurring in plants, soils and microbes in these fragile ecosystems are nevertheless poorly understood. In June 2018 we collected plant and soil samples across several permafrost thaw gradients in a palsa mire complex at Stordalen (Abisko, 68°N, Sweden). We selected three contrasting situations across the gradients: a) peat mounds with an intact permafrost core (‘palsa’ areas), b) semi-degraded palsas (‘transition’ area), and c) completely degraded palsas with no permafrost (‘collapsed’ area). For each situation we collected samples of the aboveground vegetation and soil samples at 5-10, 40-45, 70-75 and 95-100 cm (layers A-D), encompassing peat (A and B) and mineral soil layers (C and D). We determined total C, N, P and K, extractable organic C (EOC), total extractable N (TEN), extractable organic N (EON), ammonium (NH4+), nitrate (NO3-), extractable organic and inorganic P (EOP and EIP), microbial enzymatic activity, microbial C, N and P and pH in soil samples at each of the four depths across the gradient. We also determined total C, N, P and K in aboveground vegetation samples. The uppermost soil layer A showed the most statistically significant changes across the gradient of permafrost thaw, namely a 2-fold increase of total N and total P, 3- fold increase of EIP, 4-fold increase of EOP and 5-fold increase of NH4+, along with an increase of potential extracellular enzymatic activity. The fraction of total P immobilised by microbes was highest in the uppermost soil layer of palsas, where microbial P reached 33% of total P. In layer B, there were also several significant changes, such as a 4-fold increase of EOC and TEN and 12-fold increase of NH4+ in transition areas, and a 4-fold increase of EOP in collapsed areas. In addition, foliar chemistry changed significatively across the gradient of permafrost thaw, with a generalised increase of N, P and K, and a decrease of the CN and NP ratios. Along with these changes in foliar chemistry there was an increase of the stocks of N, P and K in biomass across the gradient. The biogeochemical and stoichiometric changes observed in plants, soil and microbes at different soil layers and across the gradient of permafrost thaw evidence that ongoing and future environmental changes will have a major impact on the functioning of these fragile ecosystems in the Subarctic.

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 score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
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 head0.042
GPT teacher head0.266
Teacher spread0.224 · 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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