Food Habits and Growth Patterns of Native and Invasive Fish in Lake Aneuk Laot Sabang, Indonesia
Bibliographic record
Abstract
Feeding habits and growth patterns of fish in lake ecosystems are influenced by food availability, competition, predation, and environmental conditions.This study aimed to analyze the feeding habits and length-weight relationships of native and invasive fish species in Aneuk Laot Lake, Sabang, Indonesia.Fish were sampled using traps and gill nets with mesh sizes of 0.5, 0.75, and 1 inch.A total of 483 fish were collected: 98 Rasbora sp., 104 Barbodes sp., and 218 Amphilophus trimaculatus.Feeding habits were examined using the digestive tract dissection method, and the data were analyzed based on the volumetric index, frequency of occurrence, index of preponderance, niche breadth, and niche overlap.Growth patterns were assessed through length-weight relationship analysis using linear regression and t-test analysis.Results indicated that Rasbora sp. is herbivorous, primarily consuming Cosmarium sp.(84.4%), whereas Barbodes sp.preferred Daphnia sp.(45.1%). A. trimaculatus primarily preys on small fish (62.5%).Both Barbodes sp. and A. trimaculatus are omnivorous.There was a high dietary overlap (0.96) between Rasbora sp. and Barbodes sp., indicating strong interspecific competition.A. trimaculatus preys on Rasbora sp., demonstrating its impact as an invasive predator.All species exhibited negative allometric growth (b < 3), suggesting environmental stress or food limitations.These findings highlight the need for managing invasive species to conserve native fish populations and maintain ecological balance.
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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 | 0.000 | 0.000 |
| 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".