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Multiple stressors cause rapid ecosystem change in Lake Victoria

2010· article· en· W2094779119 on OpenAlexaff
Robert E. Hecky, Rose Mugidde, Patricia Ramlal, Michael R. Talbot, George W. Kling

Bibliographic record

VenueFreshwater Biology · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Biodiversity
Canadian institutionsFisheries and Oceans Canada
Fundersnot available
KeywordsEutrophicationEnvironmental scienceClimate changeTrophic levelDeposition (geology)EcologyLimnologyProductivityEcosystemEnvironmental changeLake ecosystemGlobal changeGlobal warmingTrophic cascadePopulationFishingOceanographyFisheryGeographyNutrientFood webSedimentBiologyGeology

Abstract

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Summary 1. Lake Victoria endured multiple stresses over the past century including population growth, increased cultivation of land, meteorological variability, resource extraction, intensive fishing, introduction of exotic species and more recently climate warming. These stressors became manifest through a fundamental and rapid change in the fish community and fishery in the early 1980s and visible eutrophication. However, the relation of these two phenomena and the possible interaction of the multiple stressors have been difficult to establish because of the temporally fragmented nature of the environmental data. 2. Comprehensive limnological observations from the 1960s were repeated in the 1990s and established the eutrophication of the lake, but these do not provide insight to the time course of when changes in trophic state occurred. Comprehensive fishery catch data from 1965 to the present provide a time course of the change in community composition and yield but cannot be correlated in time with discontinuous and sparse limnological data to determine possible cause–effect relationships. 3. Palaeolimnologic studies were conducted on three cores, two offshore and one nearshore, to establish a time course for the eutrophication of the lake that can be related to time‐based data on the fishery. In the 1920s, the cores recorded an increase in nitrogen content of the sediments, but there was no significant response in the paleo‐productivity indicators of biogenic Si deposition and change δ13C of deposited organic matter. Phosphorus deposition began to increase in the 1940s in all three cores after which biogenic Si deposition increased steadily over time. Responses in δ13C of organic matter begin in the 1960s at the coring sites. In the 1970s, the δ13C of organic matter at the nearshore site increased nearly 3‰ in a 10‐year period likely as a response to a dramatic increase in internal P loading caused by spreading anoxia. 4. Nile perch, the large predatory fish introduced in 1954, had become established through much of the lake at low abundances by the 1970s. In 1980, the catch of this fish began to increase, and by the end of the decade, the Lake Victoria fishery was the largest lake fishery in the world; and Nile perch dominated the catch. While catches of some other fishes also increased, the endemic haplochromines suffered a catastrophic decline in abundance and loss of biodiversity. 5. The detailed chronostratigraphies for these sediment cores established that the major changes in the trophic condition of the lake were accomplished prior to the change in the fish community and that the increased primary productivity of the lake likely contributed to the increased fish catches after 1980. The increased algal abundance also would have greatly reduced visibility and facilitated the emergence of Nile perch as the dominant top predator. 6. Thematic implications: multiple stresses were present in Lake Victoria over several decades, but transition to a new ecosystem state with a transformed food web and highly productive algal community may have been triggered by a period of low wind stress and then generally warming climate since the 1970s. Unless phosphorus loading is stabilised or reduced, the ecosystem’s diversity and balanced productivity will not recover, and other state transitions may occur to the detriment of the lake and its riparian populations.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.254
Threshold uncertainty score0.506

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.226
Teacher spread0.205 · 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 source (direct Gemma or distilled Codex), 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

Citations351
Published2010
Admission routes1
Has abstractyes

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