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Record W4280501854 · doi:10.1016/j.watres.2022.118573

The role of organic nutrients in structuring freshwater phytoplankton communities in a rapidly changing world

2022· review· en· W4280501854 on OpenAlexafffund
Kaitlin L. Reinl, Ted D. Harris, Inge Elfferich, Ayooluwateso Coker, Qing Zhan, Lisette N. de Senerpont Domis, Ana M. Morales‐Williams, Ruchi Bhattacharya, Hans‐Peter Grossart, Rebecca L. North, Jon N. Sweetman

Bibliographic record

VenueWater Research · 2022
Typereview
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsUniversity of Waterloo
FundersGlobal Lake Ecological Observatory NetworkNational Science Foundation
KeywordsPhytoplanktonNutrientEutrophicationEnvironmental scienceEcologyOrganic matterPhosphorusPlanktonBiologyChemistry

Abstract

fetched live from OpenAlex

Carbon, nitrogen, and phosphorus are critical macroelements in freshwater systems. Historically, researchers and managers have focused on inorganic forms, based on the premise that the organic pool was not available for direct uptake by phytoplankton. We now know that phytoplankton can tap the organic nutrient pool through a number of mechanisms including direct uptake, enzymatic hydrolysis, mixotrophy, and through symbiotic relationships with microbial communities. In this review, we explore these mechanisms considering current and projected future anthropogenically-driven changes to freshwater systems. In particular, we focus on how naturally- and anthropogenically- derived organic nutrients can influence phytoplankton community structure. We also synthesize knowledge gaps regarding phytoplankton physiology and the potential challenges of nutrient management in an organically dynamic and anthropogenically modified world. Our review provides a basis for exploring these topics and suggests several avenues for future work on the relation between organic nutrients and eutrophication and their ecological implications in freshwater systems.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.995
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.050
GPT teacher head0.312
Teacher spread0.262 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations97
Published2022
Admission routes2
Has abstractyes

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