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Record W2766516516 · doi:10.1038/s41598-017-13924-w

Spatiotemporal Variability in Phosphorus Species in the Pearl River Estuary: Influence of the River Discharge

2017· article· en· W2766516516 on OpenAlexaff
Ruihuan Li, Jie Xu, Xiangfu Li, Zhen Shi, Paul J. Harrison

Bibliographic record

VenueScientific Reports · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsUniversity of British Columbia
FundersNational Key Research and Development Program of ChinaChinese Academy of SciencesNational Natural Science Foundation of China
KeywordsEstuaryPhosphorusParticulatesEnvironmental sciencePhytoplanktonStratification (seeds)Environmental chemistryPhosphateNutrientWater columnHydrology (agriculture)OceanographyChemistryEcologyGeologyBiologyAgronomy

Abstract

fetched live from OpenAlex

Phosphorus was the stoichiometrically limiting nutrient in the Pearl River Estuary (PRE). In order to examine how the river discharge regulates phosphorus dynamics in the PRE, the concentrations of dissolved inorganic phosphorus (DIP) and organic phosphorus (DOP), particulate inorganic phosphorus (PIP) and organic phosphorus (POP) in the water column were determined in May 2015 (spring), August 2015 (summer) and January 2016 (winter). Our results showed that all types of phosphorus were significantly lower in spring and summer than in winter. The Pearl River discharge input played an important role in regulating phosphorus dynamics. Strong vertical mixing in winter resulted in high levels of total particulate phosphorus (1.50 ± 0.97 μM) and dissolved phosphate (DIP: 1.44 ± 0.57 μM, DOP: 0.58 ± 0.42 μM) at the surface. On the other hand, the river discharge input created stratification in spring and summer, favoring the settlement of suspended particulate matter and enhancing light levels. This promoted phytoplankton growth, which was responsible for a DIP drawdown of 0.43 ± 0.37 μM in May and 0.56 ± 0.42 μM in August at the surface. Additionally, stratification restricted the bottom phosphorus replenishment. Our findings provided an insight into processes causing stoichiometric P limitation in the PRE.

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)0.004
metaresearch head score (Gemma)0.001
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 score0.021
Threshold uncertainty score0.978

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.012
GPT teacher head0.208
Teacher spread0.195 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations88
Published2017
Admission routes1
Has abstractyes

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