ARTICLE Beaver-Created Habitat Heterogeneity Influences Aquatic Invertebrate Assemblages in Boreal Canada
Bibliographic record
Abstract
Abstract Habitat heterogeneity and wetland area play impor-tant roles in aquatic biodiversity; however, other factors are equally important in the composition and distribution of eco-logical communities. Over a 3-year period, including a year of drought, we demonstrate how beavers physically altered iso-lated shallow-water wetlands in Miquelon Lake Provincial Park, Canada, which then influenced aquatic invertebrates diversity and abundance of functional feeding groups and taxa. Digging channels by beavers extended aquatic habitats over 200 m into the upland zone and created unique aquatic habitats, which became hot-spots for predaceous aquatic in-vertebrates. Some taxa (e.g., Gerridae and Gyrinidae) were found exclusively in beaver ponds, while Culicidae were primarily in wetlands without beavers. Amphipoda were strongly associated with beaver ponds in drought and post-drought years. During extreme drought in 2009, species rich-ness, diversity and abundance declined dramatically, but re-covered quickly in 2010. Although species richness was as-sociated with wetland area, increased niche availability through active maintenance of wetlands by beavers played an important role in aquatic invertebrate diversity and distri-bution. Understanding the role of common, but seldom sur-veyed within-wetland habitats in boreal wetlands expands our ability to understand aquatic biodiversity, the importance of habitat heterogeneity and the role of other taxa in species assemblages.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".