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Record W6989545015

Biogeochemical Cycling Across the River-Shoreline-Lake Interface of the Lake Erie Watershed

2023· dissertation· en· W6989545015 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship at UWindsor (University of Windsor) · 2023
Typedissertation
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsNutrientWatershedBiogeochemical cycleTributaryEutrophicationPhosphorusNutrient cycleNutrient pollutionHydrology (agriculture)STREAMS
DOInot available

Abstract

fetched live from OpenAlex

Management strategies have historically centred around phosphorus loading control into the Great Lakes to address anthropogenic eutrophication. These strategies have met with some successive reducing the total phosphorus (TP) concentrations since 1980s. In the past 20 years, the frequency, extent, and toxicity of harmful algal blooms (HABs), especially cyanobacterial HABs, have increased particularly in the western Lake Erie basin. Factors associated with recent HABs have been linked to increase in nutrient bioavailability from diffuse sources, internal loading, and a shift in nitrogen (N):P ratios, which potentially favours non-N fixing HABs. To address this issue, federal and provincial governments in Canada have identified a 40% reduction target in TP and soluble reactive phosphorus (SRP) to mitigate nearshore HABs. However, this is a complex issue and there is still limited information on the dynamics of nutrient transport from adjacent tributaries to the western basin of Lake Erie to provide an effective watershed nutrient management plan. Further, rivers and streams are often viewed as a conduit transporting nutrients directly into lakes. This thesis aims to investigate mechanistic changes in nutrient bioavailability, identify causal sources and sinks specifically for P and N, and investigate the interplay between in-stream sediment process and nutrient cycling along a river-lake continuum. To investigate change in P bioavailability, state-of-the-art in situ wet chemical analysers were deployed to measure three fractions of P, including TP, total dissolved phosphorus (TDP) and SRP, in the Sturgeon Creek watershed and nearshore of Lake Erie. After quantifying biofouling effects during six-month deployment in the field, the calibrated high-frequency data suggest considerable spatiotemporal variation in nutrient bioavailability. The results show approximately 40% of P entering the nearshore area is considered as bioavailable. For the first time, ratios of SRP:TP were continuously measured in real-time in the field, presenting a promising tool for in situ P monitoring beyond the shoreline of Lake Erie. Real-time observations were later correlated to sediment investigations. Sediments were identified based on the potential to sequester or release P (source vs sink) along the river-lake continuum. This information was linked to impacts from land uses within the watershed of Sturgeon Creek. Water and riverbed sediments were collected from eight sites along the transect from headwater to the nearshore of Lake Erie. Analyses for nutrient chemistry, stable nitrate isotopes and sediment equilibrium phosphorus concentration (EPC0) were performed. Typically, Sturgeon Creek sees 2- , 9- , and 18-fold higher concentrations of nitrate-nitrogen (NO3-N), TP, and SRP, respectively, compared to other agricultural watersheds in the region. Stable isotope analyses suggest the sources of NO3 are likely influenced by mixing of inorganic nitrate fertiliser and organic/manure fertiliser. Although most of the locations are net phosphorus sinks, limited phosphorus retention capacity is observed in river segments where the concentrations of P has accumulated. The evidence from this study suggests a combination of nutrient influence from both residential areas and horticulture in the region. To identify the bacterial influence in this watershed on nutrient dynamics, Sturgeon Creek riverbed sediments were collected for microbial metabarcoding and metatranscriptomic analyses. The results were paired with the observed nutrient chemistry from the water column along the transect. Water samples were analysed for NO3-N, nitrite-nitrogen (NO2-N) and ammonium-nitrogen (NH4- N). Analyses of the bacterial community structure shows no significant differences in alpha diversity of active taxa. Interestingly, nitrate reducers are abundant across all sites. Post wetland locations reveal a shift in microbial communities towards anaerobic taxa, including sulphatereducing bacteria and methanotrophs. Supporting metranscriptomics analyses indicate an active N metabolism; denitrification is the dominant pathway (32 to 55%), followed by nitrification (5 to 21%) along the transect. Collectively, this investigation provides a clear link between water column chemistry and sediment microbial metabolism. Key genes of N transformation exhibit a strong correlation with the change in concentration of NO3-N, NO2-N and/or ratio of NO2/NO3. This thesis demonstrates that nutrient bioavailability, sources, and sinks can be significantly influenced by land use change along the river-lake continuum and highlights the important role of sediment microbial processes in nutrient cycling and overlying water quality. Through incorporating multiple tools, it is likely to effectively uncouple the complexity of biogeochemical processes along the river-lake continuum that under heavily anthropogenic influence. The approaches established within this work can further contribute to nutrient management design and watershed mitigation and restoration.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.833
Threshold uncertainty score0.331

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.012
GPT teacher head0.243
Teacher spread0.230 · 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 routes1
Has abstractyes

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