Anthropogenic influences on population sizes, age and growth of naturalized rainbow trout, <i>Oncorhynchus mykiss</i>, in Kenya
Bibliographic record
Abstract
Abstract Riverine fishery in Kenya has witnessed profound changes since the 1950s, especially after independence (in 1963) when watersheds on the south‐eastern slopes of Mt Kenya were opened up for settlement. In particular, rainbow trout populations have declined essentially resulting from anthropogenic changes through over‐exploitation and/or degraded habitats. While there still are self‐sustaining rainbow trout populations in this stream among others they are in decline an indication that changes that have occurred on the watershed have altered their sizes, age and growth. The study was carried out in the Sagana, a third‐order stream, which rises at about 4000 m altitude on the south‐eastern slope of Mt Kenya, to obtain and document information on population sizes, age and growth of rainbow trout populations and to relate them with those recorded in the 1950s when trout streams were pristine (with little human influence). Stations were fished bi‐monthly from 1996 to 1998 and later for 6 months in 2002. Information on age and growth was obtained by use of annual marks, tagging fish of known age, and by validating their age using captive fish of known age. The minimum mean back‐calculated length at age for age one rainbow trout was 13.09 cm in upstream station and 15.10 cm for downstream stations. However, there was no significant difference in mean back‐calculated lengths at age for all years between fish in upstream and downstream stations ( t ‐test, t = −0.01, P = 0.99). Although female fish showed higher mean annual back‐calculated length increments than males, there was no significant difference in mean back‐calculated lengths at age between sexes ( t ‐test, t = −0.27, P = 0.80). The rate of growth in length was rapid for 1‐year‐old fish and declined in the second and third years. This study observed that most of the fish were small with only a few reaching more than 2 years of age because of overfishing. There are good reasons for optimism about the future of trout populations in this stream but concerted efforts are required to rehabilitate them. If trout populations are to increase, a management strategy is required to reduce fishing pressure and to maintain stream fishery against competing needs for resources in the catchments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".