Macrophytes moderate the taxonomic and functional composition of phytoplankton assemblages during a nutrient loading experiment
Bibliographic record
Abstract
Abstract Ponds and shallow lakes are sensitive to eutrophication, which often increases turbidity and produces toxic algal blooms. Previous research has found that the presence of macrophytes in shallow water bodies can mitigate the effects of nutrient loading by promoting water clarity and inhibiting phytoplankton growth. However, there is still little known about how macrophyte abundance modifies the response of phytoplankton taxonomic assemblages, particularly their functional composition, to nutrient loading. We investigated how macrophyte abundance altered phytoplankton assemblages using experimental ponds that were treated with a nutrient press. Natural communities of phytoplankton, zooplankton, and fish were seeded in ponds with one of three levels of macrophyte abundance that received weekly nutrient additions. A total of nine ponds (each treatment in triplicate) were monitored for 76 days. Analyses of Shannon's diversity and functional dispersion revealed significant variation in phytoplankton assemblage composition among macrophyte treatments and through time. Phytoplankton biovolume, community metrics, and the dominant traits were generally more stable in the high macrophyte treatment ponds. Although nutrient loading did not induce a regime change to a turbid, phytoplankton‐dominated state, phytoplankton assemblages did shift to a dominance of larger, inedible taxa and metaphyton became more abundant in ponds with macrophytes and zooplankton assemblages shifted to smaller species. Our study demonstrates how functional traits and functional diversity metrics can provide richer insights into the dynamics and causes of shifts in shallow freshwater ecosystems. Macrophyte densities clearly played a significant role in shaping phytoplankton assemblages. Based on the functional traits of phytoplankton distinguished among treatments, we inferred that competition for light, grazing, and, probably, allelochemicals were mechanisms through which macrophytes mediated changes in phytoplankton assemblages.
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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) | 0.001 | 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 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".