Dissolved organic matter mediates the effects of warming and inorganic nutrients on a lake planktonic food web
Bibliographic record
Abstract
Abstract Lakes are undergoing striking physicochemical changes globally, including co‐occurring increases in dissolved organic carbon and nutrient concentrations, water color, and surface temperature. Although several experimental studies of lake browning and warming have been conducted over the last decade, knowledge remains limited as to the structural and functional responses of multitrophic plankton communities, especially under environmentally relevant physicochemical conditions. Using reverse osmosis to manipulate naturally occurring dissolved organic matter (DOM), we performed an enclosure experiment to evaluate the response of a planktonic food web (zooplankton–phytoplankton–bacterioplankton) to individual and combined increases in DOM and temperature, while accounting for changes in inorganic nutrients associated with DOM enrichment. We found that concomitant increases in DOM and temperature or inorganic nutrients elicited substantially greater biotic effects, but infrequently led to interactive effects. Overall, major plankton groups responded differently to manipulated factors, with most effects observed in standing stocks, community composition, and trophic structure, while metabolic (primary production and respiration) rates appeared to be generally less responsive. DOM enrichment had a clear stimulatory effect on phytoplankton, but weakly affected zooplankton. More specifically, DOM enrichment, alone or combined with inorganic nutrient amendments, decreased zooplankton : chlorophyll a ratios, implying a reduced trophic transfer efficiency and altered trophic structure. Warming generally increased bacterial abundance and cyanobacterial dominance, especially under DOM‐enriched conditions. Collectively, these results demonstrate that increasing local DOM, even by only ~ 2 mgC L−1, can enhance plankton responses to rising temperature or inorganic nutrients in the near‐surface layer of a clearwater lake, with potential implications for ecosystems facing co‐occurring environmental changes.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".