Darkening waters: climate-induced shifts in precipitation and DOM reduced phytoplankton but not zooplankton in dimictic boreal lakes
Bibliographic record
Abstract
This study examines the extent to which temporal (1980–2019) increases in precipitation drove dissolved organic matter (DOM) loads and lake concentrations, and evaluates implications to physical, chemical, and biological variables within dimictic boreal lakes at the IISD Experimental Lakes Area, Canada. Long-term increases in precipitation (c. +27%) were associated with increased DOM loads and lake concentrations (c. +9%). Increased DOM within dimictic lakes over time was associated with shallower thermocline depths (c. −17%) and euphotic depths (c. −13%), reduced mean light intensity in the water column (c. −20%), reduced depth-integrated phytoplankton biomass (c. −32%) but increased epilimnetic chlorophyll a concentration (c. + 27%), and we detected no significant temporal declines in crustacean zooplankton. Our results confirm earlier observations that caution should be exercised when using epilimnetic chlorophyll a as an indicator of phytoplankton responses to DOM. However, once corrected for photoadaptation depth-integrated chlorophyll a was a useful indicator of depth-integrated biomass and its response to DOM.
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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 | 0.000 |
| 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".