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Hot Spots and Hot Moments in Riparian Zones: Potential for Improved Water Quality Management<sup>1</sup>

2010· article· en· W2055571001 on OpenAlex

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.

Bibliographic record

VenueJAWRA Journal of the American Water Resources Association · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil and Water Nutrient Dynamics
Canadian institutionsMcMaster University
FundersNational Science Foundation
KeywordsRiparian zoneBiogeochemical cycleEnvironmental scienceWater qualityHydrology (agriculture)WatershedEcologyGeologyChemistryEnvironmental chemistryHabitat

Abstract

fetched live from OpenAlex

Vidon, Philippe, Craig Allan, Douglas Burns, Tim P. Duval, Noel Gurwick, Shreeram Inamdar, Richard Lowrance, Judy Okay, Durelle Scott, and Steve Sebestyen, 2010. Hot Spots and Hot Moments in Riparian Zones: Potential for Improved Water Quality Management. Journal of the American Water Resources Association (JAWRA) 46(2):278‐298. DOI: 10.1111/j.1752‐1688.2010.00420.x Abstract: Biogeochemical and hydrological processes in riparian zones regulate contaminant movement to receiving waters and often mitigate the impact of upland sources of contaminants on water quality. These heterogeneous processes have recently been conceptualized as “hot spots and moments” of retention, degradation, or production. Nevertheless, studies investigating the importance of hot phenomena (spots and moments) in riparian zones have thus far largely focused on nitrogen (N) despite compelling evidence that a variety of elements, chemicals, and particulate contaminant cycles are subject to the influence of both biogeochemical and transport hot spots and moments. In addition to N, this review summarizes current knowledge for phosphorus, organic matter, pesticides, and mercury across riparian zones, identifies variables controlling the occurrence and magnitude of hot phenomena in riparian zones for these contaminants, and discusses the implications for riparian zone management of recognizing the importance of hot phenomena in annual solute budgets at the watershed scale. Examples are presented to show that biogeochemical process‐driven hot spots and moments occur along the stream/riparian zone/upland interface for a wide variety of constituents. A basic understanding of the possible co‐occurrence of hot spots and moments for a variety of contaminants in riparian systems will increase our understanding of the influence of riparian zones on water quality and guide management strategies to enhance nutrient or pollutant removal at the landscape scale.

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)0.001
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 score0.011
Threshold uncertainty score0.360

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.004
GPT teacher head0.219
Teacher spread0.215 · 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