MétaCan
Menu
← Back to cohort
Record W4238390162 · doi:10.5194/hessd-4-3209-2007

Modelling the impacts of European emission and climate change scenarios on acid-sensitive catchments in Finland

2007· preprint· en· W4238390162 on OpenAlexafffund
Maximilian Posch, Julian Aherne, Martin Forsius, Stefan Fronzek, Noora Veijalainen

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsTrent University
FundersSuomen YmpäristökeskusNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsHelsingin Yliopisto
KeywordsEnvironmental scienceClimate changeRepresentative Concentration PathwaysEvapotranspirationSurface runoffPrecipitationWatershedDeposition (geology)Surface waterGlobal warmingDrainage basinClimate modelAtmospheric sciencesHydrology (agriculture)Environmental engineeringStructural basinMeteorologyEcology

Abstract

fetched live from OpenAlex

Abstract. The dynamic hydro-chemical Model of Acidification of Groundwater in Catchments (MAGIC) was used to predict the response of 163 Finnish lake catchments to future acidic deposition and climatic change scenarios. Future deposition was assumed to follow current European emission reduction policies and a scenario based on maximum (technologically) feasible reductions (MFR). Future climate (temperature and precipitation) was derived from the HadAM3 and ECHAM4/OPYC3 general circulation models under two global scenarios of the Intergovernmental Panel on Climate Change (IPCC: A2 and B2). The combinations resulting in the widest range of future changes were used for simulations, i.e., the A2 scenario results from ECHAM4/OPYC3 (highest predicted change) and B2 results from HadAM3 (lowest predicted change). Future scenarios for catchment runoff were obtained from the Finnish watershed simulation and forecasting system. The potential influence of future changes in surface water organic carbon concentrations was also explored using simple empirical relationships based on temperature and sulphate deposition. Surprisingly, current emission reduction policies hardly show any future recovery; however, significant chemical recovery of soil and surface water from acidification was predicted under the MFR emission scenario. The direct influence of climate change (temperate and precipitation) on recovery was negligible, as runoff hardly changed; greater precipitation is offset by increased evapotranspiration due to higher temperatures. Predicted changes in dissolved organic carbon induced by reductions in acid deposition or increases in temperature may potentially influence the recovery of surface waters from acidification and may offset the increase in pH resulting from S deposition reductions. However, many climate-induced changes in processes are generally not incorporated in current versions of acidification models. To allow more reliable forecasts, the mechanisms by which climate changes affect key biogeochemical processes need to be incorporated directly into process-oriented models such as MAGIC.

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 score0.099
Threshold uncertainty score0.197

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.030
GPT teacher head0.262
Teacher spread0.232 · 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

Citations5
Published2007
Admission routes2
Has abstractyes

Explore more

Same topicPeatlands and Wetlands Ecology→French-language works237,207→