MétaCan
Menu
← Back to cohort

Modelling study of soil C, N and pH response to air pollution and climate change using European LTER site observations

2018· article· en· W2805385524 on OpenAlexaff
Maria Holmberg, Julian Aherne, Kari Austnes, Jelena Beloica, Alessandra De Marco, Thomas Dirnböck, Maria Francesca Fornasier, Klaus Goergen, Martyn N. Futter, Antti‐Jussi Lindroos, Pavel Krám, Johan Neirynck, Tiina M. Nieminen, Tomasz Pecka, Maximilian Posch, Gisela Pröll, E.C. Rowe, Thomas Scheuschner, Angela Schlutow, Salar Valinia, Martin Forsius

Bibliographic record

VenueThe Science of The Total Environment · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsTrent University
FundersHorizon 2020 Framework ProgrammeNaturvårdsverketNatural Environment Research CouncilSight Research UK
KeywordsEnvironmental scienceClimate changeSoil carbonMediterranean climateDeposition (geology)EcosystemSoil acidificationBorealGlobal warmingSoil pHGlobal changeSoil organic matterAtmospheric sciencesHydrology (agriculture)Soil waterSoil scienceEcologyGeology

Abstract

fetched live from OpenAlex

Current climate warming is expected to continue in coming decades, whereas high N deposition may stabilize, in contrast to the clear decrease in S deposition. These pressures have distinctive regional patterns and their resulting impact on soil conditions is modified by local site characteristics. We have applied the VSD+ soil dynamic model to study impacts of deposition and climate change on soil properties, using MetHyd and GrowUp as pre-processors to provide input to VSD+. The single-layer soil model VSD+ accounts for processes of organic C and N turnover, as well as charge and mass balances of elements, cation exchange and base cation weathering. We calibrated VSD+ at 26 ecosystem study sites throughout Europe using observed conditions, and simulated key soil properties: soil solution pH (pH), soil base saturation (BS) and soil organic carbon and nitrogen ratio (C:N) under projected deposition of N and S, and climate warming until 2100. The sites are forested, located in the Mediterranean, forested alpine, Atlantic, continental and boreal regions. They represent the long-term ecological research (LTER) Europe network, including sites of the ICP Forests and ICP Integrated Monitoring (IM) programmes under the UNECE Convention on Long-range Transboundary Air Pollution (LRTAP), providing high quality long-term data on ecosystem response. Simulated future soil conditions improved under projected decrease in deposition and current climate conditions: higher pH, BS and C:N at 21, 16 and 12 of the sites, respectively. When climate change was included in the scenario analysis, the variability of the results increased. Climate warming resulted in higher simulated pH in most cases, and higher BS and C:N in roughly half of the cases. Especially the increase in C:N was more marked with climate warming. The study illustrates the value of LTER sites for applying models to predict soil responses to multiple environmental changes.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score0.151

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.054
GPT teacher head0.227
Teacher spread0.173 · 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 designSimulation or modeling
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

Citations29
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueThe Science of The Total Environment→Same topicSoil Carbon and Nitrogen Dynamics→French-language works237,207→