Distribution and regulation of urea in lakes of central North America
Bibliographic record
Abstract
Summary 1. Urea accounts for ∼50% of global nitrogen (N)‐based fertiliser; however, little is known of the factors regulating its distribution and abundance in freshwaters. Improved understanding of urea biogeochemistry is essential because its use as fertiliser is expected to double by 2050 and because pollution with urea can promote outbreaks of toxic cyanobacteria in phosphorus (P)‐rich lakes in regions with intensive agricultural or urban development. 2. Biweekly measurements of urea concentration and diverse limnological variables (water chemistry, hydrology, algae, zooplankton) were taken during two summers (2008, 2009) in a chain of seven productive lakes within a 52 000‐km 2 catchment in central Canada to quantify environmental and anthropogenic correlates of temporal and spatial patterns of urea occurrence. 3. Mean (±SD) urea concentrations varied between 29 ± 14 and 132 ± 65 μg N L −1 , generally increased from headwater to downstream sites and represented 10–50% of bioavailable N (as sum of , and urea). Principal components analysis demonstrated that urea concentrations were elevated in agriculturally impacted lakes with abundant dissolved organic and inorganic nutrients (N, P, C) and low O 2 concentrations, but were not correlated consistently with plankton abundance or community composition. Urea concentrations were more than twofold greater in lakes receiving N from cities than in agriculturally affected basins, despite low summer concentrations of urea in tertiary‐treated urban effluent ( c . 50% of lake values). Multiple regression models evaluated using Akaike Information Criterion showed that mean water‐column O 2 concentration was the single best predictor of in situ urea concentrations ( r 2 = 0.91, P = 0.002), but that urea concentrations were also correlated significantly with changes in longitudinal position and Secchi depth and with concentrations of , non‐urea dissolved organic N (DON) and dissolved inorganic carbon. 4. Additional seasonal surveys of up to 69 closed‐basin lakes within a 100 000‐km 2 region during 2004 and 2008 revealed that urea was abundant in 100% of measured sites and exhibited concentrations (81 ± 48 μg N L −1 ) similar to those observed in lakes with surface drainage (58 ± 38 μg N L −1 ). Further, non‐urea DON accounted for 50–99% of the total dissolved N pool in both open‐ and closed‐basin lakes. 5. When combined with an extensive literature review and previous mass‐budget analyses of the study lakes, these findings allowed the development of a first‐generation model of the mechanisms regulating urea content of P‐rich lakes of central North America. In this model, water‐column concentrations of urea are predicted to be regulated mainly by algal decomposition in anoxic environments (sediments, hypolimnion), followed by redistribution into surface waters. Consequently, anthropogenic activities can increase the urea content of lakes by stimulating primary production, sedimentation and deepwater anoxia and by increasing influx of undegraded urea from agricultural and urban sources.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".