‘Taking Fishers’ Knowledge to the Lab’: An Interdisciplinary Approach to Understand Fish Trophic Relationships in the Brazilian Amazon
Bibliographic record
Abstract
Trophic levels can be applied to describe the ecological role of organisms in food webs and assess changes in ecosystems. Stable isotopes analysis can assist in the understanding of trophic interactions and use of food resources by aquatic organisms. The local ecological knowledge (LEK) of fishers can be an alternative to advance understanding about fish trophic interactions and to construct aquatic food webs, especially in regions lacking research capacity. The objectives of this study are: to calculate the trophic levels of six fish species important to fishing by combining data from stable isotopes analysis and fishers’ LEK in two clear water rivers (Tapajós and Tocantins) in the Brazilian Amazon; to compare the trophic levels of these fish between the two methods (stable isotopes analysis and LEK) and the two rivers; and to develop diagrams representing the trophic webs of the main fish prey and predators based on fisher’s LEK. The fish species studied were Pescada (Plagioscion squamosissimus), Tucunaré (Cichla pinima), Piranha (Serrasalmus rhombeus), Aracu (Leporinus fasciatus), Charuto (Hemiodus unimaculatus), and Jaraqui (Semaprochilodus spp.). A total of 98 interviews and 63 samples for stable isotopes analysis were carried out in both rivers. The average fish trophic levels did not differ between the stable isotopes analysis and the LEK in the Tapajós, nor in the Tocantins Rivers. The overall trophic level of the studied fish species obtained through the LEK did not differ from data obtained through the stable isotopes analysis in both rivers, except for the Aracu in the Tapajós River. The main food items consumed by the fish according to fishers’ LEK did agree with fish diets as described in the biological literature. Fishers provided useful information on fish predators and feeding habits of endangered species, such as river dolphin and river otter. Collaboration with fishers through LEK studies can be a viable approach to produce reliable data on fish trophic ecology to improve fisheries management and species conservation in tropical freshwater environments and other regions with data limitations.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".