Anthropogenic forcing leads to an abrupt shift to phytoplankton dominance in a shallow eutrophic lake
Bibliographic record
Abstract
Abstract The timing and causes of lake eutrophication are often obscured when multiple anthropogenic disturbances coincide in space and time. This issue is particularly problematic for shallow lakes in arid regions that experience strong climatic forcing which alters lake hydrology and water levels, and further conflates causal drivers. We used Utah Lake (Utah, U.S.A.) as a model system to examine how natural hydrological variability and anthropogenic forcing influence ecosystem structure of large shallow lakes in arid climates. Paleolimnological analyses of sedimentary biogeochemistry, pigments, DNA, and morphological fossils were used to identify shifts in primary production and evaluate the relative influence of regional climate‐driven hydrological variability and of humans on ecosystem structure. Sediment cores revealed that the phase prior to non‐indigenous settlement included numerous macrophyte and gastropod remains, sedimentary DNA from plants, low organic matter, and low algal production. An abrupt transition occurred in the late 19th century concomitant with agricultural and urban expansion and the introduction of common carp, which was characterised by a loss of macrophytes and an increase in phytoplankton abundance as indicated by sedimentary DNA and pigment concentrations. A further shift to increased cyanobacteria occurred c. 1950 when exponential population growth increased wastewater influx, as recorded by sedimentary δ 15 N values. Taken together, our data demonstrate that the current eutrophic state of Utah Lake is a function of anthropogenic forcing rather than natural climate‐driven hydrological fluctuations. Furthermore, large lakes in arid regions can exhibit similar patterns of abrupt ecosystem change between alternate states as those observed in northern temperate/boreal and subtropical ecosystems.
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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 | 0.000 |
| 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) | 0.001 | 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".