The relative importance of autotrophic and heterotrophic microbial communities in the planktonic food web of the Bay of Quinte, Lake Ontario 2000–2007
Bibliographic record
Abstract
The structure and function of the microbial and planktonic communities of the Bay of Quinte, Lake Ontario were studied for 8 years from 2000 to 2007. The bay has a long history of eutrophication and has undergone remediation efforts which included reductions in phosphorus loadings and the implementation of a long term research and monitoring program (1972–present) conducted by Fisheries and Oceans Canada along with other federal and provincial agencies. Microbial loop research was added in 2000 to the ongoing monitoring program which included nutrients, phytoplankton, zooplankton, benthos and fish so that a comprehensive picture of food web linkages would emerge. The structure of the microbial-planktonic food web was determined based on microscopic analysis of bacteria, autotrophic picoplankton (APP), heterotrophic nanoflagellates (HNF), ciliates, phytoplankton and zooplankton and was compared to a traditional grazing food chain consisting of phytoplankton and zooplankton. On a seasonal weighted mean basis, HNF biomass (fresh weight) of 1.7–8.4 g m−3 at Belleville and 1.1–6.3 C m−3 at Conway exceeded that of zooplankton in virtually all observations and was often greater than the combination of phytoplankton and zooplankton. Furthermore, the results showed that HNF contributed upwards to 85% of the organic carbon pool on a seasonal weighted mean basis. Various parameters in the upper bay relating trophic status to autotrophic communities were measured including: point source phosphorus loadings (>10 kg d−1); primary production (>300 g C m−2 y−1); chlorophyll a (>12 μg l−1) and phytoplankton biomass (>3 g m−3) which indicated that the upper bay remained eutrophic. This was also confirmed by the “battery of tests” strategy of ecological indicators developed in our laboratory to assess trophic status, health, and potential Beneficial Use Impairments. Based on our observations spanning 8 years, it was concluded that the microbial food web was dominated by heterotrophic communities which are still widely ignored in Great Lakes research and monitoring efforts. Our data clearly demonstrates that future studies and management strategies should include the “microbial loop” to obtain a holistic picture of the structure, function and dynamics of the lower food web.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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 | 0.001 | 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".