Community concordance between the fish and aquatic birds of lakes in northern Alberta, Canada: the relative importance of environmental and biotic factors
Bibliographic record
Abstract
1. Community concordance measures the degree to which patterns in community structure in a set of sites are similar between two different taxonomic groups. Although seldom incorporated into studies of lake ecosystems, aquatic birds can be influenced by the same environmental features of lakes which affect fish and invertebrates, and can interact with these organisms directly as predators, competitors or prey. We surveyed lakes in north‐central Alberta, Canada, to determine if co‐occurring fish and aquatic bird assemblages displayed concordance, and assessed the relative importance of environmental and biotic factors in contributing to observed concordance. 2. In 41 lakes (3–305 ha), we encountered seven species of fish and thirty‐one avian taxa which subsequently were used in multivariate analyses. Fish assemblages dominated by large piscivores were in large deep lakes, whereas fishless lakes and lakes with only small‐bodied fish were small and shallow, and thus, prone to winter hypoxia. Bird assemblages displayed three general patterns: (a) small shallow lakes supported a ‘core’ of widespread species (between three and eight species per lake); (b) large, deep lakes supported more species (between 11 and 16), including large, aerially foraging piscivores; and (c) large, shallow lakes supported the most species (between 15 and 23), including many ducks. 3. Randomization tests of matrix concordance and Mantel tests both showed that fish and bird assemblages were significantly concordant. Concordance reflected the fact that both groups were strongly affected by the same key environmental factors, principally lake size and maximum depth, and to a lesser extent, productivity and geographic isolation. Direct interactions between birds and fish, such as predation and competition, appeared to play much smaller roles in shaping the two 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".