Comparative Analysis of Distribution of Intertidal Fish Assemblages in Different Estuarine Systems on Northern Coast of Brazil
Bibliographic record
Abstract
The northern coast of Brazil has more than 30 estuaries distributed along 650 km of coastline. These conditions favor the presence of relatively large fish communities in estuarine environments, but published information on the fish fauna in tidal creeks in northern Brazil is only available for some mangrove systems, and comparative studies between fish estuarine communities in different tidal creeks are less common. The choice of the study area was based on the fact that it has been poorly investigated with regard to estuarine fish fauna in comparison in mangrove tidal creeks using the same fishing gear. The objective of the present study was to compare the composition of the relative biomass of taxonomic, functional and ecological guilds of fish assemblages occurring in estuarine systems along the northern coast of Brazil. The study area of the present comparative analysis extended from the southeastern edge of the Marajoara Gulf to the western edge of the Maranhense Gulf. A comparative analysis among different estuarine systems was performed using data from other studies. The abundance of juveniles was greater in the Caeté, Curuçá and Cururuca estuaries than other estuaries. Cluster analysis separated the estuaries into two distinct groups and significant differences between these groups only exist in relation to geographical proximity. The present investigation indicates that the coastal region between the states of Pará and Maranhão is characterized by high dynamics and environmental heterogeneity, particularly with regard to changes in river discharge and tidal fluctuations. The present results underscore the importance of ecological information on ichthyofauna in tropical estuaries in order to include appropriate descriptors in conservation or restoration processes of marine communities and habitats.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".