Benthic carbon is inefficiently transferred in the food webs of two eutrophic shallow lakes
Bibliographic record
Abstract
Abstract The sum of benthic autotrophic and bacterial production often exceeds the sum of pelagic autotrophic and bacterial production, and hence may contribute substantially to whole‐lake carbon fluxes, especially in shallow lakes. Furthermore, both benthic and pelagic autotrophic and bacterial production are highly edible and of sufficient nutritional quality for animal consumers. We thus hypothesised that pelagic and benthic transfer efficiencies (ratios of production at adjacent trophic levels) in shallow lakes should be similar. We performed whole ecosystem studies in two shallow lakes (3.5 ha, mean depth 2 m), one with and one without submerged macrophytes, and quantified pelagic and benthic biomass, production and transfer efficiencies for bacteria, phytoplankton, epipelon, epiphyton, macrophytes, zooplankton, macrozoobenthos and fish. We expected higher transfer efficiencies in the lake with macrophytes, because these provide shelter and food for macrozoobenthos and may thus enable a more efficient conversion of basal production to consumer production. In both lakes, the majority of the whole‐lake autotrophic and bacterial production was provided by benthic organisms, but whole‐lake primary consumer production mostly relied on pelagic autotrophic and bacterial production. Consequently, transfer efficiency of benthic autotrophic and bacterial production to macrozoobenthos production was an order of magnitude lower than the transfer efficiency of pelagic autotrophic and bacterial production to rotifer and crustacean production. Between‐lake differences in transfer efficiencies were minor. We discuss several aspects potentially causing the unexpectedly low benthic transfer efficiencies, such as the food quality of producers, pelagic–benthic links, oxygen concentrations in the deeper lake areas and additional unaccounted consumer production by pelagic and benthic protozoa and meiobenthos at intermediate or top trophic levels. None of these processes convincingly explain the large differences between benthic and pelagic transfer efficiencies. Our data indicate that shallow eutrophic lakes, even with a major share of autotrophic and bacterial production in the benthic zone, can function as pelagic systems with respect to primary consumer production. We suggest that the benthic autotrophic production was mostly transferred to benthic bacterial production, which remained in the sediments, potentially cycling internally in a similar way to what has previously been described for the microbial loop in pelagic habitats. Understanding the energetics of whole‐lake food webs, including the fate of the substantial benthic bacterial production, which is either mineralised at the sediment surface or permanently buried, has important implications for regional and global carbon cycling.
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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 | 0.001 | 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".