Using the Diversity, Taxonomic and Functional Attributes of a Zooplankton Community to Determine Lake Environmental Typology in the Natural Southern Boreal Lakes (Québec, Canada)
Bibliographic record
Abstract
Herein, we used zooplankton as a study model for determining how biodiversity components as well as taxonomic and functional attributes reflect lake typology in the natural southern boreal lakes. We estimated the regional and local variation in zooplankton diversity and the community structure across a set of fourteen lakes within a national park. Regional diversity (γ diversity) accounted for 40 species including 20 rotifers, 10 cladocerans and 8 copepods. Local diversity (α diversity) averaged 15 species per lake. Spatial variation in β diversity was inversely related to spatial variation in α diversity. Inter-lake variation in zooplankton communities based on taxonomy, functional traits and biotic indices was explained by two major limnological gradients: namely lake trophic status and fish community. The community structure reflected a gradient of rotifer to calanoid copepod dominance in response to trophic status. Several key species of rotifers (Kellicottia longispina and Conochilus unicornis) and of small (Bosmina and Diaphanosoma birgei) or large (Daphnia catawba and Holopedium gibberum cf glacialis) cladocerans were good indicators of lake zooplankton typology, as in other boreal lakes. We distinguished two main groups of lakes: (1) oligotrophic lakes inhabited by brook trout and dominated by the calanoid copepods and (2) mesotrophic lakes inhabited by northern pike and dominated by rotifers. Overall, our study can help managers better define monitoring and conservation strategies for lake ecosystems in natural parks.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".