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Record W2735754912 · doi:10.4038/sljas.v7i1.7496

Tilapias and Indigenous Fish Biodiversity in Sri Lanka

2006· article· en· W2735754912 on OpenAlexaff
C. H. Fernando, R.R.A.R. Sriantha, M.J.S. Wijeyaratne, R.R.T. Cumaranatunga

Bibliographic record

VenueSri Lanka Journal of Aquatic Sciences · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFish Biology and Ecology Studies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsTropicsBiodiversityOverexploitationHabitatIndigenousFisherySri lankaTilapiaHabitat destructionSubtropicsGeographyAquaculture of tilapiaBiologyFreshwater fishEcologyFish <Actinopterygii>AgroforestryEnvironmental planning

Abstract

fetched live from OpenAlex

Some species of tilapias are now found worldwide in natural and artificial habitats in the tropics and sub tropics. Claims have been made from time to time that tilapias have displaced indigenous fishes and damaged fish culture. In this paper an attempt is made to examine some of these statements and evaluate whether there is a basis for such claims. In Sri Lanka, introduced tilapias are found mainly in manmade reservoirs and still there are no records of established populations of exotic tilapias in-the river systems in the country where indigenous and endemic freshwater fish species are found. The major threats to freshwater fish biodiversity include habitat degradation and overexploitation for the ornamental fish trade. In Sri Lanka, introduction of tilapias to lacustrine waters has been beneficial in terms of contributing to fish production. Tilapias have been in natural and artificial habitats throughout the tropics and the sub-tropics for over 50 years. Considering the immense number of introductions of tilapias into individual habitats in many parts of the tropics and subtropics, surprisingly few substantiated cases of their damaging indigenous fish communities have so far been recorded. Some of these claims of cases of presumed or real damage to local fish stocks are ambiguous or ware unsubstantiated speculations. To expect absolutely no negative effects at all on the indigenous fishes by tilapias is unrealistic. On the other hand substantial quantities of tilapias are now harvested from reservoirs or raised in culture where no such enterprises existed earlier.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.513

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.019
GPT teacher head0.206
Teacher spread0.187 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2006
Admission routes1
Has abstractyes

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