Influence of fish assemblage and shallow lake productivity on waterfowl communities in the Boreal Transition Zone of western Canada
Bibliographic record
Abstract
Summary 1. Shallow lakes in the Boreal Transition Zone (BTZ) in Alberta, Canada are naturally productive systems that provide important breeding and moulting habitat for many waterfowl (Anseriformes). To examine the relative importance of biotic and abiotic factors on waterfowl population densities, species richness and community composition, we surveyed 30 shallow lakes and evaluated the relationships among fish communities, lake characteristics and waterfowl in both breeding and moulting habitat. Shallow lakes were either fishless ( n = 15), contained only small‐bodied fishes ( n = 10) or contained large‐bodied, mostly predatory, fish in addition to small‐bodied fish ( n = 5). 2. Environmental factors, including water colour, submerged aquatic vegetation, lake area and potassium, explained 24.3% of the variation in breeding waterfowl communities. Fish assemblage contributed independently to a small but significant proportion (13.4%) of the variation, while 13.8% of the explained variation was shared between environmental factors and fish assemblage. In total, 51.5% of the variation in breeding waterfowl communities was explained. 3. Overall, 55.5% of the total variation in moulting waterfowl communities was explained. Environment alone [especially total phosphorus, lake area, maximum depth and dissolved organic carbon (DOC)] and variation shared by fish and environment similarly accounted for most of the explained variation in moulting waterfowl communities (21.7% and 25.7% respectively), while fish assemblage was only one‐third as important (8.1%). 4. Both breeding and moulting waterfowl densities increased with lake productivity, even in eutrophic and hypereutrophic lakes. Breeding waterfowl density was also twice as great in fishless lakes than in lakes with fish, after accounting for lake area. 5. Certain waterfowl taxa were linked to fishless lakes, especially in the moulting season. Canvasback and moulting ring‐necked ducks were linked to small‐bodied fish lakes, whereas moulting common goldeneye were indicators of large‐bodied fish lakes. Knowledge of fish presence and species composition can therefore help guide conservation and management of waterfowl habitat in western Canada. Our results suggest that management efforts to maintain the most productive waterfowl habitat in the BTZ should focus on smaller, shallow, fishless lakes, particularly given that larger fish‐bearing systems have greater regulatory protection.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 |
| 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".