The effects of terrestrial dissolved organic matter on phytoplankton biomass and productivity in boreal lakes
Bibliographic record
Abstract
Abstract Allochthonous dissolved organic matter (DOM) structures many physical, chemical, and biological properties of lakes including key variables that control productivity at the base of freshwater food webs. A growing number of studies have documented increasing DOM concentrations within lakes across Europe and North America, including boreal lakes. Such increases are associated with the recovery of catchment soils from acid rain and rising precipitation linked to climate change. We examined phytoplankton biomass, productivity, and their drivers across eight pristine boreal lakes with DOM ranging from 3.5 to 9.5 mg dissolved organic carbon/L. Physical and chemical properties were assessed using standard limnological methods. Phytoplankton biomass was assessed using both chlorophyll a (Chl‐ a ) and via microscopy. Phytoplankton productivity was assessed using change in partial pressure of carbon dioxide within in vitro incubations. Increases in DOM were associated with significant increases in epilimnetic nitrogen, phosphorus and Chl‐ a concentrations suggesting that nutrients associated with DOM stimulated phytoplankton biomass and productivity. Such results were misleading; there was no significant relationship between Chl‐ a and phytoplankton biomass. Chl‐ a :biomass and Chl‐ a :carbon ratios indicated that increases in Chl‐ a with DOM were driven by photo‐acclimation to declining light availability. Further, results presented as epilimnetic concentrations would not account for concurrent declines in thermocline depth or euphotic depth driven by DOM. Increases in DOM led to large declines in thermocline ( c. 50%) and euphotic ( c. 75%) depths, and depth‐integrated phytoplankton biomass ( c. 70%) and primary production ( c. 70%). Our results indicate that DOM plays a structuring role for key physical, chemical, and biological properties of lakes, including productivity, at a landscape level. Further, practitioners should be cautious when using Chl‐ a as an indicator of phytoplankton biomass in studies using DOM or water clarity gradients, report results using depth integrated units due to changes in volumes of thermal layers induced by DOM, and incorporate estimates of sub‐epilimnetic productivity when evaluating DOM effects.
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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 | 0.000 | 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".