Asynchronous onset of eutrophication among shallow prairie lakes of the Northern Great Plains, Alberta, Canada
Bibliographic record
Abstract
Coherent timing of agricultural expansion, fertilizer application, atmospheric nutrient deposition, and accelerated global warming is expected to promote synchronous fertilization of regional surface waters and coherent development of algal blooms and lake eutrophication. While broad-scale cyanobacterial expansion is evident in global meta-analyses, little is known of whether lakes in discrete catchments within a common lake district also exhibit coherent water quality degradation through anthropogenic forcing. Consequently, the primary goal of this study was to determine whether agricultural development since ca. 1900, accelerated use of fertilizer since 1960, atmospheric deposition of reactive N, or regional climate warming has resulted in coherent patterns of eutrophication of surface waters in southern Alberta, Canada. Unexpectedly, analysis of sedimentary pigments as an index of changes in total algal abundance since ca. 1850 revealed that while total algal abundance (as β-carotene, pheophytin a) increased in nine of 10 lakes over 150 years, the onset of eutrophication varied by a century and was asynchronous across basins. Similarly, analysis of temporal sequences with least-squares regression revealed that the relative abundance of cyanobacteria (echinenone) either decreased or did not change significantly in eight of the lakes since ca. 1850, whereas purple sulfur bacteria (as okenone) increased significantly in seven study sites. These patterns are consistent with the catchment filter hypothesis, which posits that lakes exhibit unique responses to common forcing associated with the influx of mass as water, nutrients, or particles.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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 source (direct Gemma or distilled Codex), 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".