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Record W6995740260

Phosphorus cycling by stream biofilms exposed to continuous and episodic loading patterns

2023· dissertation· en· W6995740260 on OpenAlexafffund

Bibliographic record

VenueUWSpace (University of Waterloo) · 2023
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant tissue culture and regeneration
Canadian institutionsUniversity of Waterloo
FundersEnvironment and Climate Change Canada
KeywordsEutrophicationCyclingNutrientWatershedPhosphorusContext (archaeology)Urban streamNutrient cycle
DOInot available

Abstract

fetched live from OpenAlex

Anthropogenic activities have led to nutrient enrichment of streams, causing eutrophication of water bodies on a global scale. Eutrophication is frequently tied to an excessive influx of phosphorus (P); a crucial nutrient that often limits productivity in freshwater ecosystems. Strategies for tackling eutrophication increasingly rely on watershed models, which predict when and how much P is carried from land to water bodies. However, some watershed models overlook the in-stream cycling of P, potentially hindering eutrophication management by miscalculating P loads to waterbodies. Stream biofilms may play an important role in P cycling through P retention and transformation. However, understanding of these processes within biofilms is limited, particularly in the context of continuous (i.e., point source) and episodic (i.e., non-point source) P delivery patterns to streams. \nTo address the knowledge gap in P cycling by stream biofilms, I investigated the potential of stream biofilms to act as P sinks and reactors under continuous and episodic loading patterns. This was achieved through a 25-day experiment in artificial streams using three treatment levels of soluble reactive phosphorus (SRP) loading: 1) unenriched – a constant 10 μg P/L concentration; 2) episodically enriched – a constant 10 μg P/L concentration with a 48-hour pulse of 400 μg P/L; and 3) continuously enriched – a constant 40 μg P/L concentration. The study aimed to compare patterns of P transformation, retention, and uptake amongst these loading patterns. \nResults showed that approximately 15% of the SRP load was retained within the biofilm across all loading patterns. 75% of the SRP load was transformed into different P forms under unenriched and continuously enriched patterns. In contrast, the episodically enriched biofilms transformed 60% of the SRP load. The biofilms’ ability to transform and uptake P decreased during the second day of the pulse, suggesting that the extended duration and high concentration of the pulse overwhelmed the biofilms in the episodic loading pattern. \nStream biofilms demonstrated potential to act as both P reactors and P sinks and may help to delay P loads and reduce P bioavailability in downstream ecosystems. However, the ability of stream biofilms to transform P delivered in an episodic loading pattern may be reduced compared to continuous loading patterns, depending on the concentration and duration of the pulse. Maximizing P transformation by stream biofilms could involve delivering P in a continuous rather than an episodic loading pattern where feasible. Integrating biofilm P cycling into watershed models could prove beneficial, but its impact might vary depending on modeled time scales and P species. This research highlights the influence of biofilms on nutrient dynamics in stream ecosystems and emphasizes the need for their inclusion in ecosystem management strategies.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.008
GPT teacher head0.202
Teacher spread0.194 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2023
Admission routes2
Has abstractyes

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