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Record W4253052525 · doi:10.1080/14634980008656995

Exotic species in large lakes of the world

2000· article· en· W4253052525 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAquatic Ecosystem Health & Management · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Biodiversity
Canadian institutionsnot available
Fundersnot available
KeywordsEcologyIntroduced speciesTrophic levelLake ecosystemPredationHabitatGeographyFisheryFood webEcosystemInvasive speciesPerchInvertebrateBiologyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Abstract Many of the large lakes of the world have been exposed to the introduction of exotic species. We have reviewed here the introduction of aquatic species in 18 large lakes on five continents (Laurentian Great Lakes, African Great Lakes, several Canadian lakes, Lake Titicaca, Lake Baikal, Lake Ladoga, Gatun Lake, and Lake Biwa). We found that human activities, social preferences, and policy decisions are often associated with the spread of species in these large lakes. However, the spread and resulting ecological effects of introduced species varied among the case studies reviewed (ranging from the failure of brown trout introduction in Lake Titicaca to successful introduction of Nile Perch in Lake Victoria). Those species that did establish successful populations often had major impacts upon the ecosystems of these lakes via a variety of processes, including predation, disturbance, habitat modification and competition. Although introduction of predators often negatively impacted native species (e.g. Nile perch in Lake Victoria, peacock bass in Lake Gatun), species introduced to lower trophic levels (e.g. sardine in Lakes Kariba and Kivu, rainbow smelt in Canadian Lakes) affected fisheries and altered food web structure as well. Exotic species in large lakes of the world were not limited to fish species: plants (e.g. in Lakes Baikal and Biwa), invertebrates (e.g. in Lake Ladoga), and parasites and pathogens (e.g. in Lake Titicaca) have been introduced, but it was often difficult to discern the food web and ecosystem effects of these organisms. Exotic species also impacted socio-economic systems, having both positive (e.g. Lakes Victoria, Titicaca, Kivu, and Kariba, and the Laurentian Great Lakes) and negative (e.g. Lakes Victoria and Titicaca, and the Laurentian Great Lakes) repercussions for humans who depended upon these lakes for food and income. Unfortunately, our understanding of the impacts and extent of introductions on large lake ecosystems often remains speculative at best. The introduction and spread of exotic species will continue to threaten large lakes of the world into the twenty-first century. Exotic species introductions are a global problem that deserves global attention and understanding.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.113
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.002

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 head0.018
GPT teacher head0.219
Teacher spread0.201 · 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