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Record W4392610897 · doi:10.1016/j.catena.2024.107918

Long-term trend and drivers of inter-annual variability of surface water dissolved organic carbon concentration in a forested watershed

2024· article· en· W4392610897 on OpenAlex
Fougère Augustin, Daniel Houle, Christian Gagnon, Martin Pilote, Erik J. S. Emilson, Jason A. Leach, Kara L. Webster

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCATENA · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil and Water Nutrient Dynamics
Canadian institutionsCanadian Forest ServiceNatural Resources CanadaEnvironment and Climate Change CanadaUniversité du Québec à Montréal
FundersMitacs
KeywordsDissolved organic carbonSTREAMSHydrology (agriculture)Environmental scienceWatershedDrainage basinSurface waterBiogeochemistryCarbon cyclePrecipitationAcid neutralizing capacityTotal organic carbonWetlandPhysical geographyEcologyEcosystemGeologyGeographyOceanographySoil scienceSoil water

Abstract

fetched live from OpenAlex

Dissolved organic carbon (DOC) concentrations have increased over the past few decades in surface waters across Europe and North America. This has drawn a lot of attention, given the key role of DOC in the global carbon cycle and in surface water biogeochemistry and ecology. While many reports have focused on DOC response to environmental changes in headwater streams and lakes taken separately, there is a lack of studies that combines streams and lakes with varying catchment characteristics in a network-scale perspective. Here, long-term (1987–2018) trends were analyzed and environmental drivers of year-to-year variations in DOC concentrations were examined in headwater streams, lakes and lake outflows at the Turkey Lakes Watershed (TLW) in Ontario, Canada. Results indicated significant increasing of DOC trends in ten out of 12 headwater streams and in four out of 12 lakes and lake outflows over the study period. In addition, piecewise regression analysis detected breakpoints in the 2000 s for DOC time series data in some stations. Multivariate analysis showed that variations in hydro-climatic conditions and the chemistry of atmospheric precipitations explained 13 % to 99 % of year-to-year variations in DOC concentrations. Air temperature emerged as the most influential factor for lakes and lake outflows while precipitation chemistry was the main driver of inter-annual DOC variation in headwater streams. For the latter, the rate of DOC increase and the proportion of explained variance were mainly dependent on catchment characteristics, notably wetland cover which was related to mean catchment slope and total relief. In the context of global change, further research is needed to better understand how changes in climate and atmospheric deposition may be modulated by catchment attributes and ecosystem types for determining future DOC fate and behaviour in surface waters.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.082
Threshold uncertainty score0.262

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)0.0000.000

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 head0.006
GPT teacher head0.204
Teacher spread0.198 · 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