The effects of Common Carp (Cyprinus carpio L.) on water quality, algae and submerged vegetation in Delta Marsh, Manitoba
Bibliographic record
Abstract
Common Carp, (Cyprinus carpio), have long been associated with the degradation of wetlands worldwide. Through their feeding activities they resuspend sediments leading to reductions in the abundance and diversity of submerged macrophytes, and the alteration of water chemistry which can lead to the phytoplankton-dominated state. This study took in Delta Marsh, a freshwater coastal wetland of Lake Manitoba, in Manitoba, Canada. It was the second part of a four-year study in which baseline data were collected in 2001 from ten ponds (1-13 ha) with varying degrees of connectivity to the main marsh and carp-accessibility. I continued to monitor a subset of the control and altered ponds two and three years following their alteration (2003 and 2004); I included new ponds, including one large open bay (20.3 ha). The overall four-year study has shown that the presence of carp is at least partially responsible for the turbid, phytoplankton-dominated state that exists in Delta Marsh, and that carp abundance is an important factor. Ponds previously isolated then exposed to carp activity, particularly in the spring when they were gathered at high densities, shifted to the turbid, phytoplankton-dominated state with few macrophytes, and the removal of carp from ponds led to the clear-water state, though not necessarily an abundance of macrophytes. Due to the complexity of natural ecosystems, the effects of carp were not as predictable as smaller-scale studies would suggest. In my study, water quality, submerged vegetation biomass and algal growth varied both temporally and spatially in carp-accessible and carp-free ponds. Nutrient deficiency among periphyton assemblages was hypothesized to be alleviated by the presence of carp. Using nutrient diffusing substrata, I found that nutrient deficiencies varied from year to year among carp-free and carp-accessible ponds. In 2003 the hypothesis was supported, however, in 2004 two of the carp-free ponds exhibited no-nutrient limitations to periphyton assemblages while N and P co-limitation became prevalent in one carp-accessible pond. Parameters over which there was no control, such as the spatial and temporal distribution of carp, their density within a pond, water depth and unquantified top-down effects, including zooplankton grazing, may have contributed to the variability of the results.
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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 | 0.001 | 0.001 |
| 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".