Relative contributions of nearshore and wetland habitats to coastal food webs in the Great Lakes
Bibliographic record
Abstract
Hydrologic linkages among coastal wetland and nearshore areas allow coastal fish to move among the habitats, which has led to a variety of habitat use patterns. We determined nutritional support of coastal fishes from 12 wetland-nearshore habitat pairs using stable isotope analyses, which revealed differences among species and systems in multi-habitat use. Substantial (proportions > 0.30) nutrition often came from the habitat other than that in which fish were captured. Nearshore subsidies to coastal wetlands indicate wetlands are not exclusively exporters of energy and materials; rather, there is reciprocity in the mutual energetic support of nearshore and wetland food webs. Coastal wetland hydrogeomorphology influenced the amount of multi-habitat use by coastal fishes. Fishes from systems with relatively open interfaces between wetland and nearshore habitats exhibited less nutritional reliance on the habitat in which they were captured, and higher use of resources from the adjacent habitat. Comparisons of stable isotope analyses of nutrition with otolith analyses of occupancy indicated nutritional sources often corresponded with habitat occupancy; however, disparities among place of capture, otolith analyses, and nutritional analyses indicated differences in the types of support those analyses inform. Disparities between occupancy information and nutritional information can stem from movements for support functions other than foraging. Together, occupancy information from otolith microchemistry and nutritional information from stable isotope analyses provide complementary measures of the use of multiple habitats by mobile consumers. This work underscores the importance of protecting or restoring a diversity of coastal habitats and the hydrologic linkages among them.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".