A Spatial Analysis of Fish Habitats in Coastal Wetlands of the Laurentian Great Lakes
Bibliographic record
Abstract
The overall objective of this study was to provide a spatial pattern analysis offish distribution in the Great Lakes and to relate these patterns to shoreline features such as coastal wetlands, tributaries and substrate type. Very little is known regarding the distribution patterns of fish in the Great Lakes at the geographical scale of each lake basin. I first explored whether there were systematic patterns in distribution offish and coastal wetlands by looking at density maps of each and calculating nearest neighbor distances. I used three different classification schemes to sort the 139 fish taxa into functional categories to produce ecologically meaningful distribution maps. There were striking differences in the overall distribution pattern of nursery and spawning habitat in the five Great Lakes when data were compared for Jude and Pappas' classification taxocenes: open-water, intermediate and coastal. Overall, open-water species were the most abundant, and were also widely distributed throughout all five lakes. Coastal species were the least abundant and appeared to be restricted to the two lower lakes. The distribution pattern of coastal and intermediate taxa overlapped a great deal; both taxocenes made extensive use of the two lower lakes for spawning and nursery habitat during this synoptic survey, especially in western Lake Erie and eastern Lake Ontario. Fish distribution patterns sorted by thermal preference and by reproductive guild were compared with those sorted by taxocene. Results from a chi-square analysis indicated a high degree of overlap between thermal classes and taxocenes. There were also positive associations between many reproductive guilds and the three taxocenes, although these were not as strong as the previous comparison. I then examined spatial association between distributions of fish and coastal wetlands and other geomorphic features by testing the distribution offish along the shore of the Great Lakes and calculating the correlation between fish and coastal wetlands of Lake Ontario. A chi-square goodness-of-fit test indicated strong associations between the distribution offish and three shoreline classes: (wetland, sandy beach/dunes and bluff) and fish used coast~cl wetlands preferentially for spawning and nursery habitat at a basin-wide scale. Bivariate pattern analysis indicated that occurrences offish in L. Ontario were positively associated with both coastal wetlands and tributaries, although the relationship was considerably weaker for tributaries than for wetlands. Results from this study indicated that 1) Fish have an aggregated distribution pattern along the shores of Great Lakes and L. Ontario; 2) Coastal wetlands have an aggregated distribution pattern along the shores of Great Lakes and L. Ontario; 3) Spatial distribution offish and wetlands is positively associated; 4) The preferred utilization of coastal wetlands by majority of the Great Lakes fishes is consistent across geographic scales, from the site level to that of the entire Great Lakes basin.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".