Biomass and productivity responses of zooplankton communities to experimental thermocline deepening
Bibliographic record
Abstract
Lake thermocline depth is likely to be altered with climate change. We assessed the response of crustacean zooplankton biomass and productivity to an experimental whole‐lake manipulation of thermocline depth. Weekly sampling occurred in Experimental and Reference years and responses were assessed with a before—after‐control—impact design. While one of three lake basins remained un‐manipulated (control), two others experienced thermocline deepening via: active mixing simulating increased wind‐stress (‘mixing with thermocline deepening’); and increased overall heat content, simulating greater water clarity (‘thermocline deepening’). Thus, we simultaneously identified seasonal responses to three treatments: mixing with thermocline deepening, thermocline deepening alone, and an isolated mixing effect. Total crustacean zooplankton biomass was enhanced by all treatment effects, owing to positive responses to thermocline deepening in Bosmina and Daphnia and a positive cyclopoid copepod response to mixing. Enhancement of biomass production rates (BP) occurred only with thermocline deepening, with no effect of mixing alone. The lack of BP response to active mixing was likely due to compositional shifts from fast growing Daphnia to slower growing cylopoids. BP variation was explained by positive and negative relationships with mean water‐column temperature and hypolimnetic temperature, respectively. Hypolimnetic warming, occurring naturally with the seasonal thermocline descent was more dramatic for the active mixing manipulation. This loss of hypolimnetic refuge for Daphnia appears to have had a negative effect on the community daily production to biomass ratio (P : Bdaily). Our study indicates a greater likelihood for reduced food‐web transfer efficiency under scenarios when mixing and hypolimnetic warming accompany thermocline deepening.
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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) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".