Distribution of unionid freshwater mussels depends on the distribution of host fishes on a regional scale
Bibliographic record
Abstract
Abstract Aim The successful conservation of endangered mussel communities requires, in part, a thorough understanding of the processes that shape their distribution. Therefore, we tested the prediction that (1) the distribution of host fishes explains a significant amount of variation in mussel community composition. In addition, because mussel distribution also depends on spatial processes and environmental variables, we predicted that (2) the distribution and community composition of mussels in Ontario varies across eight contiguous watersheds, flowing into three different basins of the Great Lakes (Huron, St. Clair and Erie); and (3) environmental variables also explain part of the mussel distribution. Location Watersheds in south‐western Ontario, North America, Great Lakes Region. Methods Existing data on the distribution of mussels and fishes, and environmental and spatial information were compiled. Variation partitioning with redundancy analysis was used to examine what proportion of the variation in mussels' community composition was explained by watershed (as a spatial component), environmental differences and host fish presence. Redundancy analysis for mussel abundances was used to illustrate the similarities in the distributions of mussels and fishes, and the association of differences in community composition of mussels among watersheds with certain mussel species and environmental variables. Results Host fish presence explained 44%, watershed identity 28% and environmental factors 23% of the variation in mussel species composition. However, much of the explained variation was shared among these components, and all three components together explained 55% of the total variation in species composition. Even after statistically eliminating the other explanatory variables, host fish distribution was the most important group of predictor variables, although we used a subset of relevant environmental variables because of the scale of the study. Main conclusions Our results highlight the important role played by host fishes in shaping current distributions of freshwater mussels and underscore the necessity of incorporating these relationships in conservation efforts and management actions.
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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 | 0.000 | 0.001 |
| 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".