Spatial, Environmental, and Biotic Determinants of Zooplankton Community Composition in Subarctic Lakes and Ponds in Wapusk National Park, Canada
Bibliographic record
Abstract
Abstract Northern regions are expected to experience large environmental change over the next few decades. The response of biota will depend on changes in the local environment, regional processes that influence lake connectivity, and species interactions. In 2008, we surveyed 92 lakes and ponds across Wapusk National Park, located on the southwestern shore of Hudson Bay. At each site we assessed water chemistry and zooplankton community composition. In an effort to understand how the aquatic ecosystems will respond to future environmental change, we determined local characteristics (e.g., water chemistry), regional spatial factors (e.g., dispersal), and biotic interactions (e.g., species associations) influencing community composition. Important environmental variables included lake area, pH, ionic composition, total phosphorus, and chlorophyll a; however, spatial variables explained more variation than environmental variables, suggesting that dispersal is an important driver of zooplankton composition in this region. Additionally, species exhibited negative co-occurrence patterns, suggesting biotic interactions are important in structuring the zooplankton communities. As environmental conditions change and the distribution of habitat (i.e., coastal fen, interior peatland, and spruce forest) shifts, evidence that the park's zooplankton community is spatially structured coupled with our suspicion that zooplankton are likely to experience high dispersal levels in Wapusk leads us to suggest zooplankton may indeed be able to track changing environmental conditions within the park, although it remains unclear how species interactions will modify this expectation.
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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 | 0.002 | 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 | 0.001 |
| 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".