Warming shifts top-down and bottom-up control of pond food web structure and function
Bibliographic record
Abstract
The effects of global and local environmental changes are transmitted through networks of interacting organisms to shape the structure of communities and the dynamics of ecosystems. We tested the impact of elevated temperature on the top-down and bottom-up forces structuring experimental freshwater pond food webs in western Canada over 16 months. Experimental warming was crossed with treatments manipulating the presence of planktivorous fish and eutrophication through enhanced nutrient supply. We found that higher temperatures produced top-heavy food webs with lower biomass of benthic and pelagic producers, equivalent biomass of zooplankton, zoobenthos and pelagic bacteria, and more pelagic viruses. Eutrophication increased the biomass of all organisms studied, while fish had cascading positive effects on periphyton, phytoplankton and bacteria, and reduced biomass of invertebrates. Surprisingly, virus biomass was reduced in the presence of fish, suggesting the possibility for complex mechanisms of top-down control of the lytic cycle. Warming reduced the effects of eutrophication on periphyton, and magnified the already strong effects of fish on phytoplankton and bacteria. Warming, fish and nutrients all increased whole-system rates of net production despite their distinct impacts on the distribution of biomass between producers and consumers, plankton and benthos, and microbes and macrobes. Our results indicate that warming exerts a host of indirect effects on aquatic food webs mediated through shifts in the magnitudes of top-down and bottom-up forcing.
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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 | 0.001 |
| 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".