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Record W3043249414 · doi:10.1029/2019gb006495

Delineating the Continuum of Dissolved Organic Matter in Temperate River Networks

2020· article· en· W3043249414 on OpenAlexaff
Joan Pere Casas‐Ruiz, Robert G. M. Spencer, François Guillemette, Daniel von Schiller, Biel Obrador, David C. Podgorski, Anne M. Kellerman, Jens Hartmann, Lluís Gómez‐Gener, Sergi Sabater, Rafael Marcé

Bibliographic record

VenueGlobal Biogeochemical Cycles · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsUniversité du Québec à Trois-Rivières
FundersDeutsche ForschungsgemeinschaftNational Science Foundation
KeywordsDissolved organic carbonBiogeochemical cycleEnvironmental scienceHydrology (agriculture)Aquatic ecosystemTemperate climateEcologyDrainage basinEcosystemGeologyGeographyBiology

Abstract

fetched live from OpenAlex

Abstract The origin and reactivity of dissolved organic matter (DOM) have received attention for decades due to the key role DOM plays in global carbon cycling and the ecology of aquatic systems. However, DOM dynamics in river networks remain unresolved, hampered by the lack of data integrating the spatial and temporal dimensions inherent to riverine ecosystems. Here we examine the longitudinal patterns of dissolved organic carbon (DOC) concentration and DOM chemical diversity along a temperate river network under different hydrological conditions, encompassing small headwater streams to the river mouth and base flow to storm events. We show that, during nonstorm conditions, the concentration of DOC and the chemical diversity of DOM exhibit their maxima in the middle section of the network, depicting a bell‐shaped pattern along the river continuum. In contrast, DOM shows a homogeneous longitudinal pattern during storm events, with highly concentrated and diverse DOM along the river network. We posit that these emerging patterns result from changes in the relative influence of catchment versus in‐stream biogeochemical processes along the river continuum and that the degree of influence is modulated by river network hydrology. Based on these findings we put forward the “Bending DOM Concept,” a new conceptual framework around which testable hypotheses on the spatiotemporal dynamics of DOM and the functioning of temperate river networks may be formulated.

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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score1.000

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)0.0010.000

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 head0.009
GPT teacher head0.194
Teacher spread0.185 · 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 teacher head, not a consensus.

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

Citations61
Published2020
Admission routes1
Has abstractyes

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