Climatic influences on algal populations of boreal forest lakes in the Experimental Lakes Area
Bibliographic record
Abstract
We examined long‐term phytoplankton data records for four oligotrophic boreal lakes situated in the Experimental Lakes Area (ELA), western Ontario, for responses to climatic change. ELA experienced a cyclical wet‐dry‐wet pattern from 1968 to 1998, with the early 1970s and 1990s having above‐average precipitation and the 1980s being a period of drought with a 2°C increase in air temperature. During this drought, the length of ice‐free season, duration of stratification, depth of the euphotic zone, and light extinction increased while precipitation and nutrient inputs to the lakes decreased. Phytoplankton assemblages of four study lakes were temporally coherent. During the drought, phytoplankton biomass and the number of phytoplankton species increased despite decreased nutrient inputs. There was a noticeable shift in species composition to greater abundances of dinoflagellates and large chrysophytes—mixotrophic species capable of cycling through the deeper, lower light, high‐nutrient waters, presumably to consume bacteria as an alternative to autotrophic production. These species have slow turnover times; therefore, suspended nutrients were held in the water column for a longer period of time. Phytoplankton photosynthesis was less responsive.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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 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".